STUDY OF WOMEN’S EMPOWERMENT

IN THE DISTRICT OF BANKURA

SUBMITTED BY

PAPITA DUTTA

TO

THE UNIVERSITY OF BURDWAN

FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN

ECONOMICS

2014

UNDER THE GUIDANCE AND SUPERVISION OF

DR. MANIKLAL ADHIKARY

PROFESSOR OF ECONOMICS

BURDWAN UNIVERSITY

Dr. Maniklal Adhikary

Professor

Department of Economics

The University of Burdwan

Golapbag, Burdwan-713104

West Bengal (INDIA)

Dial (0342)-2558-554, Extn. 438 (O)

+91-9476-233029

+91-9434-660220

Date:

Certified, that Smt. Papita Dutta, a registered scholar in Economics, Burdwan

University, Golapbag, Burdwan, West Bengal, has duly completed her research work

under my supervision. She is keen on submitting her thesis entitled “Study of Women’s

Empowerment in the District of Bankura”. I have approved her thesis and permitted her

to submit it to the University of Burdwan for Ph. D. degree in Economics. Further,

certified that neither this dissertation nor any part thereof was submitted to this or any

other university in the country or abroad for Ph. D. or any other degree. However, it may

also be noted that Smt. Dutta has delivered two seminar lectures on her research work in

partial fulfillment of the requirement for the submission of the Ph. D. thesis and compiled

with all relevant conditions specified in the resolutions of the University of Burdwan.

Maniklal Adhikary

i

Preface

The importance of human capital juxtaposed with physical capital has been emerging

since the end of the Second World War to pace economic development in the developing

countries. Empowerment is no doubt the pivotal component of human capital.

Empowerment of women has emerged as a developmental issue after the inception of the

concept of ‘capability approach’ for development. Before that, women’s empowerment

was the subject of the feminists and viewed as a socio-political issue. The feminists look

women’s empowerment entirely as an instinct matter. After 1980s economists have

recognized women’s empowerment as an instrument for human development. In addition

to the feminist goals the instrumental idea of women’s empowerment have some

important policy pay-offs. Advocates of instrumentalists have tried to define women’s

empowerment with a broader vision compared to the vision of feminists. However,

women’s empowerment has still not been clearly defined and segregated from other

closely related concepts like gender inequality. Women’s empowerment is viewed as

mechanism of improving the qualitative aspects of women. In this dissertation we have

studied women’s empowerment as means and ends of forming human capital.

Nowadays women’s empowerment is a multidimensional and multi-level concept. The

study of women’s empowerment is also context specific. We have premeditated

empowerment at the household level and at the community level for the women of

Bankura district. For this purpose we have considered five dimensions of women’s

empowerment for each level. These are economic dimension, familial dimension,

political dimension, social dimension and legal dimension. Further, each dimension has

been covered by some suitable indicators in the context of Bankura district. Combining

all the dimensions we have computed empowerment index for each sample woman at the

household level and at the community level. This empirical study is based on a set a

primary data collected from 580 women of Bankura district. An attempt has been taken

to estimate the impact of women’s empowerment at the household level and at the

community level on family planning decision, on the incidence of domestic violence

against women, and on spending for children’s education in Bankura district. The study

ii

has also analysed the nature and causes of the low level empowerment of the women in

Bankura district.

The corpus of this dissertation has been structured into six chapters. In chapter one, we

present the relevance and the objectives of this study. The second chapter deals with the

review of relevant literatures. Chapter three has explained the theoretical framework for

the estimation of the impact of women’s empowerment on the issues of household

welfare and for investigation of the factors affecting women’s empowerment. Empirical

models and hypotheses for empirical testing have also been formulated in this chapter.

Chapters four has analysed the components of empowerment of the women in Bankura

district, West Bengal. We have found that empowerment of the sample woman at the

household level and at the community level have not reached at the creditable level. We

have explained the empirical impact of empowerment variables along with other factors

on household and child welfare in chapter five. In this chapter the empirical estimates of

the women’s empowerment have also been explained. Our empirical findings shows that

women’s empowerment is instrumental in improving the probability of taking family

planning decision, in alleviating the incidence of domestic violence and in increasing the

share of household income spend for children’s education. Finally, we find age, personal

occupation, personal income, financial inclusion, household’s landholding, SHG-

membership, educational background of the female household members as crucial factor

for enhancing empowerment at the household level and at the community level. On the

basis of the empirical findings, we draw the policy prescription in chapter six for

improving household welfare and empowerment of the women in a better way.

I want to extend my thanks and gratitude to all of those who have supported me in the

process of preparing this dissertation. It is an output of collective efforts of many

individuals.

I particularly honour and thank Dr. Maniklal Adhikary, Professor of Economics,

Burdwan University, for his unwavering support and constant inspiration for preparing

this dissertation. He enriches this dissertation with his valuable advices and precious

commands. I am fortunate enough to have him as my teacher and supervisor. Without his

iii

guidance and support, it was quite impossible for me to proceed towards my dream of

preparing this Ph. D. dissertation.

My parents, Rina Dutta and Sisir Dutta need no gratitude for their unconditional love,

affection, patience and support that they have shown throughout my life. Actually, it is

their meticulous efforts that help me prepare this thesis. I am thankful to God for giving

me such loving and caring parents.

I am thankful to my beloved husband, Dr. Supravat Bagli, for encouraging me and

particularly for his support and cooperation during the course of data collection. He has

helped me enrich this dissertation with his valuable commands and suggestions. I am

thankful to my only son, Arya (Reetobrato Bagli) because he tolerates my all absence

with patience. Though he has been deprived of my love and affection during the period of

preparing this thesis, he understands me in his own little ways. I remain indebted to him for

this sacrifice in rest of my life.

I want to express my earnest thanks to my loving sister, Sangita Dutta, for her absolute

support. She accompanied my son during my hard time in preparing my thesis.

I am thankful to Dr. Madhuri Adhikary for providing me home like ambience. I would

like to thank Sri Ajoy Kumar Majhi and Smt. Chitra Sadhu, who sincerely supported me

during my fieldwork.

I am grateful to Professor Arup Kumar Chattopadhyay, Professor Soumeyendra Kishore

Dutta, Dr Atanu Sengupta, Dr. Pravat Kuri, Dr. Rajarshi Majumdar, Dr. Anindita Sen

and all other teachers of the Department of Economics, Burdwan University, who have

provided valuable suggestions and comments for enriching this dissertation.

I am thankful to the authorities of Burdwan University for giving me the opportunity to

execute my research works. I extend my heartfelt thanks to the staff members of the

department of Economics, for their invariable support. I extend my sincere appreciation

to the staff members of Indian Statistical Institute, Kolkata, and the staff members of

iv

Guskara Mahavidyalaya, Guskara who have supplied valuable documents, information

and reading materials related to my dissertation.

.

Last but not the least; I am ever thankful to all respondents and personalities who spend

time and effort for me during the time of household survey. There are too numerous

friends and relatives who remain unnamed here to receive my heartfelt appreciations.

I am humble to state that I have prepared this dissertation with the best of my knowledge

and efforts. Despite my sincere efforts in the preparation of this dissertation there may

have some mistakes for which I am solely responsible.

28th

May, 2014 PAPITA DUTTA

Burdwan

v

CONTENTS

List of Tables x

List of Figures xii

Chapter One 1-30

WOMEN’S EMPOWERMENT

AN INSTRUMENT FOR HUMAN DEVELOPMENT

1.1. Introduction 1

1.2. Idea of Women’s Empowerment 4

1.3. Women in India and in the District under Study: A Fact Sheet 9

1.4. Relevance of the Study 14

1.5. Justifications of the District Selection 16

1.6. Socio-Economic-Demographic Characteristics of Bankura District 17

1.6.1. Geographic and Administrative Profile 18

1.6.2. Demographic Characteristics 19

1.6.3. Socio-Economic Characteristics 21

1.6.4. Educational Status 22

1.6.5. Empowerment Statistics 24

1.7. Objectives of this Study 25

1.8. Conclusion 30

vi

Chapter Two 31-72

REVIEW OF LITERATURES ON WOMEN’S EMPOWERMENT

2.1. Introduction 31

2.2. Women’s Empowerment: Issues and the Conceptions 32

2.3. Women’s Empowerment and Welfare: The Impact Studies 41

2.4. Studies relating to Determinants of Women’s Empowerment 51

2.4.1. Studies on Women’s Empowerment: The Indian Scenario 51

2.4.2. Studies on Women’s Empowerment: The Global Scenario 61

2.5. Conclusion 72

Chapter Three 73-120

MODEL, METHODOLOGY AND DATA

3.1. Introduction 73

3.2. Measures of Women’s Empowerment 74

3.2.1. Selected Dimensions and Indicators of Women’s Empowerment 76

3.2.1A. Dimensions and Indicators of Women’s Empowerment at

Individual or Household level 76

3.2.1B.Dimensions and Indicators of Women’s Empowerment at Community level 78

3.2.2. Degree of Women’s Empowerment 79

3.2.3. Analytical Framework for Computing Composite Index of

Women’s Empowerment 80

3.3. Research Design for Studying the Impact of

Women’s empowerment on Household Welfare 82

3.3.1. Analytical Framework for Studying Impact of

Women’s Empowerment on Family Planning Decision 82

3.3.2 Analytical Framework for Impact of Empowerment on

Domestic Violence against Women 85

vii

3.3.3. Analytical Framework for Impact of Women’s Empowerment on

Children’s Educational Expenditure 87

3.4. Analytical Framework for Studying Women’s Empowerment 90

3.5. Regression Specification of the Analytical Models relating to

Women’s Empowerment 92

3.5.1. Probit Models for Decision regarding Family Planning 92

3.5.2. Logit Models for Incidence of Domestic Violence 93

3.5.3. Log-Lin Models for Children’s Education Expenditure as

Proportion to Household Income 93

3.5.4. Linear Regression Models for Women’s Empowerment at

the Household Level and at the Community Level 94

3.6. Definition and Measurement of the Variables included in

the Regression Models 96

3.7. Specification of Hypothesis 105

3.7.1. Hypotheses relating to the Model for Decision regarding Family Planning 105

3.7.2. Hypotheses relating to the Model for Incidence of Domestic Violence 108

3.7.3. Hypotheses in Connection with the Child Education Expenditure 111

3.7.4. Hypotheses relating to the Models of Women’s Empowerment 113

3.8. Methodology of Data Collection 115

3.8.1. Sampling Design 116

3.8.2. Profile of the Sample Areas 117

3.8.3. Nature and Scope of Data 118

3.8.4. Diagnostic Check for the Sample Size 119

3.9. Conclusion 120

Chapter Four 121-156

COMPONENT ANALYSIS OF WOMEN’S EMPOWERMENT

4.1. Introduction 121

4.2. Descriptive Statistics of the Surveyed Households 122

4.2.1. Categorical Characteristics of the Sample Households/Individuals 122

viii

4.2.2. Socio-Economic and Demographic Characteristics

of the Surveyed Population 127

4.3. Frequency Distribution of the Indicators of Women’s Empowerment

at Household Level and at Community Level 130

4.4. Analysis of Women’s Empowerment Indices 137

4.4.1. Outcomes of Principal Component Analysis

of the Household Level Empowerment of Women 137

4.4.2. Outcomes of Principal Component Analysis

of the Community Level Empowerment of Women 141

4.4.3. Descriptive Statistics of the Empowerment Indices 144

4.5. Bivariate Correlation among Selected Variables 147

4.6. Conclusion 155

Chapter Five 157-198

EMPIRICAL ESTIMATES AND ANALYSIS

5.1. Introduction 157

5.2. Impact of Women’s Empowerment on Decision regarding Family Planning 157

5.2.1. Model-1A: Probit Model with Simple Empowerment Indices 158

5.2.2. Model-1B: Probit Model with Composite Empowerment Indices 164

5.3. Impact of Women’s Empowerment on Domestic Violence against Women 167

5.3.1. Model 2A: Logit Model with Simple Empowerment Indices 168

5.3.2. Model-2B: Logit Model with Composite Empowerment Indices 174

5.4. Impact of Women’s empowerment on Expenditure for Child Education 176

5.5. Determinants of Women’s Empowerment in Bankura District 182

5.5.1. Determinants of Women’s Empowerment at the Household Level 183

5.5.2. Determinants of Women’s Empowerment at the Community Level 190

5.6. Conclusion 198

ix

Chapter Six 199-221

POLICY PRESCRIPTIONS

6.1. Introduction 199

6.2. Major Findings 199

6.3. Existing Policies and Programs towards Empowering Women 203

6.3.1. National Policy and Legislation for Women in India 203

6.3.2 Governmental Programmes for Enhancing Women’s Empowerment in India 206

6.4. Policy Prescriptions and Implications 210

6.4.1. Suggestions for Empowering Women in Bankura District 211

6.4.2. Suggestions for Improving the Likelihood towards Family Planning 214

6.4.3. Suggestions for Alleviating Domestic Violence against Women 216

6.4.4. Suggestions for Improving Child Education Expenditure 218

6.5. Conclusion 220

Bibliography 222-234

x

Tables

Table- 1.3.1 Sex Ratio: Number of Female per Thousand Male 10

Table-1.6.1 Geographical Area (Square Kilometres) 18

Table-1.6.2 Administrative Profile of Bankura District 19

Table-1.6.3 Population and Decadal Growth rate by residence 20

Table-1.6.4 Percentage Distribution of Rural Urban Population 20

Table-1.6.5 Sex Ratio in West Bengal and Bankura District 21

Table-1.6.6 Caste Wise Population (Percentage) with Reference to 2001 Census 21

Table –1.6.7 Human Development Index of Bankura District 21

Table-1.6.8 Percentage of Population According to Occupational Status in 2001 22

Table 1.6.9 Gender Wise Distribution of Literates 23

Table-1.6.10 Sex Wise Literacy Rate among Scheduled Caste, Scheduled Tribe 23

Table 3.8.1 Area Specific Distribution of the Sample Households 117

Table-4.2.1 Distribution of the Categorical Variables of the Sample Households 124

Table-4.2.2 Percentage Distribution of the Individual Categorical Variables 126

Table-4.2.3 Relevant Demographic Profile of the Sample Households 127

Table-4.2.4A Socio-economic Characteristics of the Sample Households 128

Table-4.2.4B Socio-economic Characteristics of the Sample Households 129

Table-4.3.1A Percentage Distribution of the Indicators of

Women’s Empowerment at Household Level 131

Table-4.3.1B Percentage Distribution of the Indicators of

Women’s Empowerment at Household Level 133

Table-4.3.2A Percentage Distribution of the Indicators of

Women’s Empowerment at the Community Level 135

Table-4.3.2B Percentage Distribution of the Indicators of

Women’s Empowerment at the Community Level 136

Table 4.4.1 Results of KMO and Bartlett’s Test for Sample Adequacy for

Factor Analysis of Women’s Empowerment at the Household Level 137

xi

Table-4.4.2 Total Variance in the Indicators of Women’s Empowerment

Explained by the Components at the Household Level 139

Table-4.4.3 Rotated Component Matrix of Women’s Empowerment

at Household Level 140

Table-4.4.4 Results of KMO and Bartlett’s Test for Sample Adequacy for

Factor Analysis of Women’s Empowerment at the Community Level 141

Table-4.4.5 Total Variance in the Indicators of Women’s Empowerment

Explained by the Components at the Community Level 142

Table-4.4.6 Rotated Component Matrix of Women’s Empowerment

at the Community Level 143

Table-4.4.7 Descriptive Statistics of the Women’s Empowerment 145

Table-4.4.8 Percentage Distribution of Women’s Empowerment in Bankura District 145

Table-4.5.1 Bivariate Correlation Matrix 148

Table-4.5.2 Bivariate Correlation Matrix 149

Table-4.5.3 Bivariate Correlation Matrix 151

Table-4.5.4 Bivariate Correlation Matrix 152

Table-4.5.5 Bivariate Correlation Matrix 154

Table-5.2.1 Results of the Probit Model for the Decision regarding Family Planning

When Women’s Empowerment is the Simple Average of the Indicators 160

Table-5.2.2 Marginal Probability of the Decision regarding Family Planning

When Women’s Empowerment is the Simple Average of the Indicators 161

Table-5.2.3 Results of the Probit Model for the Decision regarding Family Planning

When Women’s Empowerment is Composite Index of the Indicators 165

Table-5.2.4 Marginal Probability of the Decision regarding Family Planning

When Women’s Empowerment is measured by Composite Index 166

Table-5.3.1 Results of the Logit Model for the Incidence of Domestic Violence

When Women’s Empowerment is Simple Average of the Indicators 169

Table-5.3.2 Marginal Probability for the Incidence of Domestic Violence

When Women’s Empowerment is Simple Average of the Indicators 170

Table-5.3.3 Results of the Logit Model for the Incidence of Domestic Violence

When Women’s Empowerment is Composite Index of the Indicators 174

Table-5.3.4 Marginal Probability of the Incidence of Domestic Violence

When Women’s Empowerment is Composite Index of the Indicators 175

xii

Table-5.4.1 Results of the Log-Linear Model for Child Education

When Women’s Empowerment is Simple Average of the Indicators 178

Table-5.4.2 Results of the Log-Linear Model for Child Education

When Women’s Empowerment is Composite Index of the Indicators 179

Table-5.5.1 Estimates of degree of Women’s Empowerment at Household Level 187

Table-5.5.2 Estimates of Composite Women’s Empowerment Index at

Household Level 189

Table-5.5.3 Estimates of degree of Women’s Empowerment at Community Level 193

Table-5.5.4 Estimates of Composite Women’s Empowerment Index at

Community Level 194

Figures

Figure1.2.1 Dynamics of Women’s Empowerment 9

Figure-4.4.1 Percentage Distribution of Women’s Empowerment at

Household Level 146

Figure-4.4.2 Percentage Distribution of Women’s Empowerment at

Community Level 146

Figure-5.3.1 Age-Group Wise Prevalence of Domestic Violence against Women in

Bankura District 167

1

Chapter One _____________________________________________

Women’s empoWerment

An Instrument for Human Development

1.1. Introduction

In the present era, the concept of development has been broadened. In addition to its

quantitative aspects, like increase in real income, consumption, wealth etc. and their

equal distribution, it includes some other qualitative aspects of human livelihood like

capabilities of person, reduction of vulnerabilities, freedom to choose alternative

opportunities etc. Professor A.K. Sen (1999) has explained development in terms of the

expansion of real freedom that the citizens enjoy to pursue the objectives they have and

in this sense, economic development is the expansion of human capabilities. This is

known as capability approach of development. Capability is one kind of freedom, the

range of options that a person has in deciding what kind of life she / he wants to lead. So

a person should have capacity to choose best life that she/he likes from the constraint

opportunities available to her/him. Sen (1999) has also emphasized on the process of

expanding freedom equally for all people. In this view, the meaningful development

includes gender equality in enjoying freedom in addition to less poverty or better access

to basic amenities and opportunities. Following this view in the recent years the

capability approach of development is widely accepted in most of the developing

countries for accelerating the developmental process.

In September 2000, in the Millennium Summit held under the auspices of UNDP, the

member countries promised to fulfill a series of time-bound targets related to human

development with a deadline of 2015. These are known as the Millennium Development

Goals (MDGs). The MDGs have been regarded as the global agreement to combat

2

human deprivation through collective and multilateral actions. The agenda of the MDGs

have been noted below.

Millennium Development Goals (MDGs)

1) Alleviation of extreme poverty and hunger

2) Achievement of universal primary education

3) Eradication of gender inequality and improvement of women’s empowerment

4) Reduction of child mortality

5) Improvement of maternal health

6) Prevention of severe diseases (AIDS, malaria, tuberculosis etc.)

7) Ensuring environmental sustainability

8) Development of global partnership

In Millennium Development Goals (MDGs) summit, 2010, the international

development community recognized gender equality and women’s empowerment as the

major development goal in their own right (MDG 3 and 5) and as critical channels for

achieving the other MDGs and reducing income and non-income poverty. Being a

signatory to the Millennium declarations India has paid due emphasis on inclusive

development in the recent five year plans to articulate policies with view to achieving

MDGs. Several public policies and initiatives in our country reflect that our country is

also committed to develop capabilities equally among human beings.

No doubt the process of capability development approach has changed many things

towards human development during the last one and half decade across the globe. Our

country is also approaching this goal. Despite having some recognised instrumental

power of women’s empowerment, average women in our country like in most of the

countries still have status far behind that of men, particularly in terms of right,

opportunity and endowment. Women constitute almost half of world population. In India

Women constitute 48.46% of the total population (Census, 2011). Like men, women take

the responsibility of human capital formation in the family and hence in building nation

and its destiny; but the status of women in our common society is far below the expected

level. There is a sharp distinction between male and female in our society in terms of sex

ratio, child infanticide, literacy rates, health and nutrition indicators, wage differentials,

3

access to finance, ownership of land and property and in power and culture. Comparing

to their male counterpart, women have lower access for resource, education and health

facility, medical care and lower percentage in earned income, lower power, and lower

percentage even in food. Not only that they are dependent of others, like father, husband

or sons. A common woman does almost all types of works e.g., cooking, tailoring,

sweeping, washing, nurturing, taking care of family members, housekeeping, working as

laundry person, nursing etc in the home and sometimes they do drudgery. She gets very

little time or no time at all to think about herself and her likings which adversely affect

her health and mind also. But the tragedy is that these works do not get any recognition

in our society. Instead of getting the respect they deserve for their roles in the society,

they become vulnerable, marginalised and oppressed population in the society. This

gender inequality can be vanished by enhancing opportunities and capabilities of women

i.e., by promoting empowerment among women. Against this end enhancing women’s

empowerment is recognised as a social movement. Simply women’s empowerment is the

generation of decision-making power among women and providing opportunities to

them so that women can precisely decide about themselves and about the world

surrounding them.

The convention in our patriarchal society is that male persons enjoy the freedom of

taking decisions about all types of household matter and social matter and women only

obey the decisions. Although this convention has been changing recurrently, but it does

not happen at that rate as we need. We shouldn’t forget that nearly half of world

population is women and a major proportion of poor is women. Women are poor not for

the lack of their ability to participate in the production process but for the lack of

opportunity to participate in the production process or for non-recognition of their

housekeeping activities as productive. Globally the gender gap in economic activity is

very prominent. Women are, generally, unemployed or underemployed and when

employed, in most of the cases, they are under paid and employed in informal sectors.

Though working hour of women is very high within house, it is not counted as most of

the time women are involved in household’s jobs. These household’s jobs are not

included in economic activity of a country.

4

Different indicators of human development show that women have lesser access to

property, resource, education, health facilities, medical care and lower percentage in

earned income and finally lower participation in job market, if not least, in decision

making power also, (World Bank, 2001). Moreover, they are the victims of domestic

violence. The basic cause behind this poor condition of women is the bypassing of

women population by the most mainstream development activities. A nation with

slightly less than half of women population can never step on the pave of development

by bypassing its women population. Without developing women population,

developmental procedure will become farce. Swami Vivekananda realised this more than

hundred years ago. He said that “There is no chance for the welfare of the world unless

the condition of women is improved. It is not possible for a bird to fly on one wing”. We,

therefore, should not think of true and total development leaving women aside. Further,

women become marginalised and vulnerable section of the society as social customs and

political system deprived them from their right under the guise of cultural and religious

traditions. Women are, also, victimized by the ethnic tradition. The solution to these

problems requires the building of the capabilities among women. For the betterment of

the condition of women it is necessary to empower women. This urgently, needs the

creation of an environment in which the distribution of power and resources, the

opportunity to engage in productive work, opportunities to access education, medical

care and public services can move in favour of women population.

The remaining part of this chapter has been divided as follows. In section 1.2, we have

presented the theoretical idea of women’s empowerment. Section 1.3 shows the existing

status of women. Relevancy of the study has been discussed in section 1.4. Section 1.5

deals the justification of the selection of the district of Bankura for studying the

empowerment of women. In section 1.6 along with its sub-sections we have presented

the socio-economic and demographic characteristics of the population, particularly

women, in the district of Bankura. The objectives of our research work have been

specified in section 1.7. Finally, section 1.8 concludes this chapter.

1.2. Idea of Women’s Empowerment

The term ‘Women’s Empowerment’ becomes a catchphrase in most of the

developmental studies during the era of globalization. The World Bank and many other

5

development agencies have emphasised the concept of empowerment, specifically,

women’s empowerment, in theoretical discussions and policy perspectives. Exercise of

the concept of empowerment has a long history. During the mid-seventeenth century, it

was used as a legalistic meaning ‘to invest with authority’. Thereafter it began to appear

as a more general word with meaning "to enable or permit". The present generation

meaning of empowerment has been coined in the civil rights movement, which sought

‘political empowerment’ for its followers (Tripathi, 2011). The concept of women’s

empowerment has been broadly used in feminist movement across the globe. But we did

not get any particular definition of women’s empowerment from the feminist form of

advocacy. Advocates of feminist movement think women’s empowerment as a synonym of

gender equality and it is an end in itself. They viewed the empowerment of women as a set

of rights towards equality with men (Kabeer, 2001). According to feminist approach

empowerment is entirely a subjective matter. The idea of empowerment as an instrument

of human development came into discussion after 1980s. The new paradigm concept of

women’s empowerment was closely related with feminist discourse. In addition to the

feminist goals the new idea of women’s empowerment had some important policy pay-

offs (Alsop, et al., 2005). It was known as instrumentalist form of advocacy towards

women’s empowerment. Advocates of instrumentalists tried to define women’s

empowerment with a broader vision compared to the vision of feminists. They had tried

to quantify the concept of empowerment. However, this concept has still not been clearly

defined and segregated from other closely related concepts. Sometimes empowerment is

a process of improving the qualitative aspects of women; sometimes it is a state or the

expected effect of empowering process. Different studies have looked into the concept of

empowerment from different angles according to the need of their studies and different

social contexts.

Many studies have used the term empowerment as the process of empowering groups or

individuals (Rowlands, 1995; Molhotra, et al., 2002, Samanta, 2009, Verma 2009). In

our study we concentrate on women’s empowerment at the individual level and at the

community level. Like many other countries, women’s empowerment is considered as a

social movement in India. First of all, we would, vividly, analyze what the empowerment

is. There is an interpersonal variation in meaning and connotation of empowerment

depending on the economic, socio-cultural and on many other conditions of the society.

6

The meaning and the process of empowerment, particularly, women’s empowerment

varies from time to time, region to region, culture to culture. Let us we present some

definition and ideas of empowerment, given by various previous studies.

Literally, empowerment means giving authority or power to powerless in a particular

situation. In UNDP Human Development Report, 1995, women’s empowerment has

been defined as the expansion of choices for women and an increase in the women’s

ability to exercise choices. Empowerment is the power of decision making i.e. autonomy

(Jejeebhoy, 1995). In a working paper of World Bank, Alsop, et al. (2005) state that

empowerment is the enhancing an individual’s or group’s capacity to make choices and

transform those choices into desired actions and outcomes. It is the ability of some

people to control their own destinies even when, their interests are opposed by others

with whom they interact. Women’s Empowerment is a process whereby women become

able to organize themselves to increase their self reliance, to assert their independent

rights to make choices and to control resources which will assist in challenging and

eliminating their own subordination (Keller and Mbwewe, 1991 cited in Rowlands,

1995). Singha Roy (1995) has considered empowerment as a process of creation of

social environment where women can take decision and make choices of their own,

either individually or collectively, for social betterment. Mehra (1997) has defined

empowerment as a process that enables girls and women to challenge current norms and

change conditions. Panda, et al. (2003) have argued that self-perception is the reflection

of empowerment. The process of empowerment refers to power that controls one’s own

life. The study of Khan, et al. (2006) has also explained empowerment as a process for

establishing control over resources and for acquiring ability and opportunity to decision

making process and its implementation.

In the study of Kabeer (2001) we have found a useful definition of empowerment, which

can be applied across the range of contexts. She states that empowerment means “the

expansion in people’s ability to make strategic life choices in a context where this ability

was previously denied to them”. Reddy (2002) defines empowerment as directing one’s

life in such a way that she/he can reach the stage where she/he is more likely to be

successful in whatever she/he attempts to do. According to him, the processes involved

in empowering are increase in people’s awareness and confidence, ability to articulate

7

problems, gaining access to resources and public facilities and negotiating over relations

between different social groups.

According to Lillykutty (2003), empowerment of women develops them as more aware

individuals, who are politically active, economically productive and independent and are

able to make intelligent decision in matters that affect them and their nations. For

empowering women she suggests five hierarchical steps of equality, namely, welfare

(fulfillment of basic needs of women), access (control over power resources such as

personal wealth, land, skill, education, social status, leadership etc.), conscienisation

(eliminating all forms of discrimination against women i.e., taking actions to fill up

gender gap), participation (organizing themselves for being a direct partner of

developmental works.) and control (creating an environment where they can enjoy all

human rights which, are enjoyed by men and ability of women to take decision over their

life and their children). Sen (1998) has argued that poverty led to denial of rights and

opportunities to poor for full participation in society and to arrest this kind of social

exclusion, there is need for improving their capabilities and entitlements, which is

nothing but empowerment.

From the definitions mentioned above the concept of women’s empowerment may be

summed up as follows. The empowerment of women leads to

the generation of decision making power of women in economic, political

and societal issues

increasing access to education; health care; and other public services within

a geographical and social context

eliminating all forms of discrimination against women

creating the sense of dignity among women.

Therefore, women’s empowerment is a dynamic process and is a multidimensional

concept. It is context specific. There are many indicators of women’s empowerment

which may vary from context to context.

8

Quantification of empowerment is relatively a new phenomenon in literature of women

studies. We have seen that different studies have measured women’s empowerment in

different ways. Some studies (Sen, 1999, Molhotra et al. 2002, Handy, 2004, Sridevi,

2005, Adhikary and Dutta, 2011,) have attempted to measure the degree of

empowerment considering several dimensions of women’s empowerment in several

fields. It means that these studies have measured the width of women’s empowerment.

On the other hand a few studies (Kishor, 1997, Becker, 1997, Kabeer, 2001, Alsop, et al,

2005) have proposed to measure empowerment considering the dimensions which

incorporate process of empowerment as well as its effectiveness. Actually these studies

have tried to measure the intensity of empowerment level. According to instrumentalists,

(Sen, 1999, Kabeer, 2001, Jejeebhoy, 2002, Malhotra, 2002, Alsop, et al, 2005) women’s

empowerment primarily depends on two interrelated sets of factors, (1) Agency and (2)

Opportunity Structure. Agency is the person’s ability to make meaningful choices. In

other words, agency is the attribute of the person by which she visualises the alternative

possibilities of action and makes choices. Opportunity structure includes the existing

formal and informal framework within which agents operate. Working simultaneously,

these two factors generate different degrees of empowerment. The degree of

empowerment definitely makes some personal and social welfare which in turn enhances

empowerment. Alsop, et al. (2005) have recommended that the degree of women’s

empowerment can be quantified by assessing the following issues.

(a) Whether a person has the opportunity to make a choice.

(b) Whether a person actually uses the opportunity to choose.

(c) Once the choice is made, whether it brings the desired outcomes.

There is a reciprocal relation between agency & opportunity structure and degree of

empowerment. Further, women’s empowerment has some impacts on development

outcomes. We have represented the dynamic relations in chain diagram 1.2.1 as

developed by Alsop, et al., 2005. It shows that the extent of the agency and opportunity

structure are both the causes and consequences of the degree of empowerment. The

empowerment is an effective instrument of household and social welfare. The

identification of the linkage between women’s empowerment and welfare or

9

development outcomes is the main contribution of the instrumentalists’ advocacy of

women’s empowerment. They have recognized women as the agent of change.

Figure1.2.1 Dynamics of Women’s Empowerment

Source: Alsop, et al. (2005)

However, this explained association, is a theoretical one. There is not any systematic

statistical analysis which confirms this theoretical illustration. Alsop, et al. (2005) have

rightly pointed out that due to paucity of suitable data on direct indicators of

empowerment, the relationship between empowerment and development outcomes still

remains a hypothesis. One of the central objectives of this dissertation is to test this

hypothesis empirically.

1.3. Women in India and in the District under Study: A Fact Sheet

All over the world women remain beyond the reach of development project. In all

components of human development, women’s position is lower than men’s. The census

reports reveal that number of females per thousand males in India has increased from

933 in 2001 to 940 in 2011. Therefore, female population has grown at a rate faster than

that of male population during 2001-2011. It is no doubt a good indicator of gender

equality. This ratio for child under six years is, however, 914 as per census report, 2011

which was 927 in 2001.

Agency

Opportunity

Structure

Degree of

Empowerment

Development

Outcomes

10

Table- 1.3.1 Sex Ratio: Number of Female per Thousand Male

Census 2001 2011

Area Total Rural Urban Total Rural Urban

India 933 946 900 940 947 926

West Bengal 934 950 893 947 950 939

Bankura District 952 952 951 954 954 958

Source: Census Report, 2001 and 2011

In the state of West Bengal sex-ratio is 947 which is record figure of sex ratio in this

state during the last century. However, child sex ratio in West Bengal has reduced from

960 to 950 during 2001-2011. The picture is more or less same in the district of Bankura,

West Bengal. According to census report, 2001over all sex ratio in the district of

Bankura was 952 which increased to 954 in 2011. But it is interesting to note that in the

district, the sex ratios for general castes, scheduled castes and scheduled tribes were 937,

966 and 984 respectively. The figures indicate that general caste community has more

gender discrimination compared to that for the others communities and the scheduled

tribes have positive attitudes towards gender equality. Therefore, in terms of number,

females are closely equal with their male counterpart. The recent trend of sex ratio is no

doubt a good sign; but many other statistical figures frustrate us.

Illiteracy is a social curse on human beings. It adds impetus in the feminization of

poverty and in deterioration in the status of women. India is not free from the curse of

illiteracy. In 2001, the adult women literacy rate of India was only 42.2% whereas the

adult male literacy rate was 67%. In term of enrollments in the educational institutions

they are far below their male counterpart. The combined primary, secondary and tertiary

enrollment ratio among female population in 2001 was only 49% whereas for male

population it was 62%. The literacy gender parity index in India in 1995-1996 was only

0.8. At present 82% of male population aged seven year and above are literate, while

65% of the female are literate (Census, 2011). It is evident that male female gap in

literacy has been declining during the era of globalization. In 2011, 71% of female 7+

aged are literate in West Bengal whereas 60% of female 7+ aged are literate in the

district of Bankura. Women’s education level is lower compared to that of men

population in the state of West Bengal and in Bankura district. It is reported that 60%

women are literate whereas 81% men population are literate in Bankura district (Census

2011). The access to education among women in the area under study is not satisfactory

11

compared to men. In this district 937 girls per thousand boys enrol in the primary

section. Moreover, dropout among girls is higher than that among boys within the

primary section.

Violence against women is a serious social problem across the countries. Violence

against women is now daily news in our country and in our state. Women face violence

not only outside home, but also within home. In accordance with the report of National

Crime Record Bureau (2013) 106527 women in 2012 have reported the experience of

domestic violence from husband and/or in-laws. This number has increased by 7.5%

compared to the figure in 2011. In the state of West Bengal, domestic violence has been

reported to increase by 18% during 2011-12. In terms of this rising rate West Bengal

stands first. The number of dowry death has not been included in this figure. Normally

women in our society do not want to confess the experience of domestic violence. Only a

small section has reported their experience of domestic violence. Moreover, a number of

females are suffering from violence in their natal house. Therefore, the actual prevalence

of domestic violence against women is very high in India.

The survey report of UNIFEM (2011) tells us that one fourth of the Indian women faced

physical violence at home in 2010 and 37.2% of sample women reported that they have

faced domestic violence at least once in their life. In most of the cases violence came

from husband or from close relatives. National Health and Family Survey 2005-06 has

revealed that 26% of Indian women have faced the incident of physical violence in home

within two years of their married life.

West Bengal has got some defamation in this respect. According to National Crime

Record Bureau (2011) West Bengal ranks first in term of percentage of share of crime

committed against women in India. In this state the rate of rape, kidnapping and

abduction, dowry death, cruelty by husband and relatives are 2.6%, 4.1%, 0.6% and

21.6% respectively. Based on 2008 statistics of the National Crime Records Bureau,

West Bengal has the highest number of battered wives among the Indian states. In

dowry-related deaths, it comes fifth among the states. In the district of Bankura reported

number violence against women in 2001 was 210 that increased to 326 in 2005.

12

So far, in India the protection of women from domestic violence Act has been passed in

2005 which has come into force on October, 2006. But due to improper utilization and

implementation of this act and due to our social immoral value a large section of women

in India and in our study state and district are suffering from domestic violence. There

are several forms of domestic violence. It scratches the root of self-confidence and self-

esteem of the woman. Reduction of self-confidence and self-esteem increases the

dependency of the woman on husband or father which is main pillar of patriarchal and

feudalistic nature of our society. Therefore, the root cause of domestic violence lies in

the framework of the patriarchal and feudalistic nature of the society.

However, women are not dependent of men in real sense. Most of them work hard for

their family particularly housekeeping. Household jobs are treated as household duties

not as economic activities. According to the report of NSSO (2009-10) 347 women per

thousand in rural area and 465 women per thousand in urban area are completely

engaged in household duties. On the other hand, only 5 men per thousand in rural area

and 4 men per thousand in urban are engaged in household duties. The majority of the

homemaker women earn some money from outsources working at home. But it is

omitted from the mainstream labour force because these women offer these earning to

their family heads or husbands and earning is looked as family income. It is a fact that

women work more time than men but they earned a very low percentage of income. The

female work time as a percentage of male work time for the year 2000 was 117. But

male population spends 61% of total work time on marketed activities whereas women

population spends only 35% of their work time. Actually women spend most of their

work time in unpaid household works. Their activities are not accounted in the National

Income statistics. As a result women has lower share in earned income. In India the

estimated earned income by women population was only $1531 in 2001 whereas it was

$4070 by Indian male. Economic dependence of women resists them to become a part of

the building of nation.

Further, in India, women are far below their male counterpart in term of access to and

control over resources, participation in work force and remuneration. The discrimination

of the dignity of work of men and women has been focused in their wage differentials.

The daily wage of women labour is Rs 119.76 in rural area, which is Rs 297.35 for men

13

labour (NSSO, 2009-10). Although the participation of women in unorganised sector is

noticeable, their participation in organized service sector is negligible. Census report

2001 reveals that in Bankura district 32.04% women participates in the work force.

However, women’s participation in the manufacturing and service sector in this district

is not commendable. Women of the district are mainly engaged in the primary sector.

But their share in landholding is insignificant (Bankura District HDR 2007).

In 2001, 39.44% of total seats in Panchayet Bodies were reserved for women. Though

women physically filled up the seats, in most of the cases the male leader influences

their activities. In our country, state and sample district the incidence of child marriage is

rampant. In West Bengal 53% of women marry before reaching the legal minimum age

at marriage (NFHS-3). In our country average age of marriage is 22.2 years while in

West Bengal it is 20.3 years. It is evident that average age of marriage for women in

Bankura lies in 15-18 years. Bankura District HDR, 2007 has reported that there is social

discrimination among women either on the issue of ‘caste’ and untouchability or on the

basis of ‘haves and have not’s in rural Bankura.

Further, the access to health care facilities by women is not satisfactory in India. The

pregnant women receiving prenatal care in India was 62% in 1996 while it was 70% for

the whole world. It is reported that 63.2% of women are suffering from anemia. NFHS-3

has reported that 22% of men think that contraception is women’s business and a man

should not have to worry about it. It has been reported that 37% of women have used

sterilization as a method of family planning while it is only 1.2% of men.

In the light of the above information we can conclude that number of women is

increasing but the status of women in our society is far below the expected level. A large

part of them could not enjoy the minimum facilities which are necessary for their health

and dignity. Women in contrast to men have low access to property, community

resources and services, education, health facilities, medical care. They have lower

percentage in earned income. They are vulnerable and marginalized group compared to

men in society. A large number of women face domestic violence. Therefore, it is

essential to abolish the gender inequality against women for inclusive development of a

country.

14

1.4. Relevance of the Study

Observing the present status of the women in India and in the district of Bankura we find

that globalization fails to develop the status of women population to the expected

standard. Women population, particularly in India, has been excluded from the

favourable impact of globalization. In the Millennium declaration, 2000, the member

states of United Nations declare that for true sustainable development it is necessary to

abolish poverty, hunger, disease etc. and announce the empowerment of women as one

of the Millennium Development Goals. Literally, empowerment means to give some

power in the hands of powerless. It enriches person with power. Many developmental

projects have been undertaken by the governments of various countries. But the fact is

that most of these mainstream developmental projects, latently or actively, bypass

women population. Even when mainstream development projects include women by

increasing investment on women’s health and education, it is for lowering birth rate and

to improve the well being of children. These are the policies not for women’s own well

being so that they can expand their ability to exercise choices (Mehra, 1997). As a result,

women population remain far below the male population not only in terms of numbers,

but also in terms of various development indices such as literacy rate, employment,

access to medical facilities, enrollment in educational institution etc.

Time has, now, come to take special policies, exclusively, for the development of

women. Enhanced women’s empowerment can serve as one of the strongest weapons to

fight against such obnoxious reality. Empowerment is now considered as a component of

human development. United Nations declared the year, 2001, as the year of women’s

empowerment. Women can achieve better familial, societal and economic status and can

fight against the various atrocities if some policies are taken to empower them. This

requires the creation of an environment in which the distribution of power and resources,

the opportunity to engage in productive work, opportunity of access to education,

employment, medical care and health services etc. can move in favour of women

population. To quest for the suitable policies for empowering women it is necessary to

find out the responsible factors of women empowerment and their importance to

improve empowerment. Increased level of empowerment among women increases the

importance of women in their family and in the society. This may be the panacea of the

two dangerous diseases in our society namely the gender inequality and poverty.

15

Therefore, understanding the concept of empowerment and the study of the determinants

of women’s empowerment are very much relevant in present context.

In the existing literature still now women’s empowerment is a fuzzy concept. In recent

times, the instrumentalist form of advocacy has been translating the feminist views into

the mechanists’ discourse of policy (Kabeer, 2001). There have no universally accepted

indicators of women’s empowerment in literatures. We find different set of indicators of

women’s empowerment in different studies depending on the context of the study. These

may be helpful to construct the empowerment index. Yet a major portion of the existing

studies are anecdotal, informative and descriptive. They have tried to present a

theoretical explanation of the relation among intermediary indicators of empowerment,

agency and opportunity structure and development outcomes. Several studies have

quantified women’s empowerment in several contexts. But the study of the impact of

women’s empowerment on development outcomes is not very much common in the

existing literature. In a working paper of World Bank Alsop, et al. (2005) has rightly

mentioned that

“while we currently have much anecdotal and case study evidence to

suggest an instrumental purpose in empowering people, robust data

demonstrating a clear association between empowerment and development

outcomes are hard to find”.

This argument justifies the concrete relevance of our study which deals with the

estimation of the impact of women’s empowerment on development outcomes.

Quantification of the concept of women’s empowerment is the main contribution of the

instrumentalists. But there is not any unanimously accepted measure of women’s

empowerment at the individual level. It is not a surprising fact that the nature of

individual’s empowerment absolutely depends on existing infrastructure that the

individual may get access. In other words, the nature of women’s empowerment is

context and area specific. It indicates the difficulty of the proposition of universal

measure of empowerment at the individual level. So, for an area specific study one

should be conscious regarding the measure of empowerment. This fact raises the

16

relevance of our study. In our dissertation we have attempted to develop a measure of

individual empowerment for the women in the district of Bankura, West Bengal. We

have planned to measure the women’s empowerment at the household level and at the

community level.

The instrumental advocacy of women’s empowerment argued that women’s

empowerment have some positive impact on household and child welfare. But the

impact study of empowerment on development outcomes is not common in the existing

literature. World Bank (2005) has explained the theoretical relation between

empowerment and development indicators. Theory at best can give the nature and

direction of the relation among the factors. However, without an empirical estimation of

the relationship, theory can be of little use in policy. Therefore, empirical study relating

to the impact of women’s empowerment on household and child welfare is immense

important in India. It makes our study a relevant one.

The importance of family planning has got attention in our country since the early 1950s.

But how the attitude of rural couples towards family planning is related with

empowerment of women is not well established. In recent times the problem of domestic

violence against women has also received deep attention of the governments. It is

expected that women’s empowerment is an important determinant of the incidence of

domestic violence. Therefore, in the present era, examinations of the impact of

empowerment on family planning decision and on incidence of domestic violence

against women are important issues which are the central objectives of our dissertation.

Recently, in addition to women’s welfare the issue of child welfare has come forward as

an aspect of inclusive development. Towards this end, our study regarding the impact of

women’s empowerment on child education is most relevant. Hence, in order to

understand the level of empowerment of the rural women level and its impacts on

household and family welfare, our study is no doubt important.

1.5. Justifications of the District Selection

In order to study the nature of empowerment of women and its impact on household

well-being we have considered the district of Bankura in West Bengal. The justifications

behind the selection of the district are stated as follows.

17

Bankura district is one of the poor and backward districts in India. In this district all the

components of human development index is lower than the all India average. It means

that people of this district are lagging in position relative to average Indians and average

people of West Bengal. The condition of women is worse than that of men. In section-

1.3 we have presented the required information for showing that the women of Bankura

district are in the lower position than men in all dimensions of human development. To

get a vivid picture of the position of women in this district we need to study about their

empowerment at the household level and at the community level.

From many primary and secondary sources we know that more than half of the

households in the district of Bankura belong to lower social castes. Conventionally

women of these lower social castes work outside home for earning their livelihood.

However, most of them participate in unorganized sector like agriculture and animal

husbandry. So far, our primary observations indicate that although these women support

their respective household economically, a large section of them suffers from domestic

violence. It is observed that women get less importance in taking decisions on various

issues of family welfare, like family planning decision and spending for their children’s

education. These observations are odd enough and motivate us to study the attitudes of

women towards family planning, incidence of domestic violence against women and

spending towards education for households in the district of Bankura.

Moreover, in spite of the economic contribution of these women a part of them fails to

enjoy the decision making power in different economic and non-economic fields within

and outside household. During the course of this study it would be possible to find out

the causes of the powerlessness of women and the different factors responsible for this

powerlessness. These help the policy makers, the government, the non government

organizations take appropriate projects and policies for improving the situation of

women in our study area. All these justify the selection of the district under study.

1.6. Socio-Economic-Demographic Characteristics of Bankura District

In order to study the issues regarding empowerment of the rural women we have selected

the district of Bankura in West Bengal. With this end in view, first we need to

understand the socio-economic-demographic profile of the district, which are relevant to

18

carry out the research work. These statistics will provide us a clear picture about the

relevance of the study and consideration of the district and thereby induce us to

empirically estimate the impact of women’s empowerment and thereby determining

factors of it. In the following sub-sections we would introduce the district under study.

1.6.1. Geographic and Administrative Profile

Geographically, the district of Bankura is fourth largest district in West Bengal. In terms

population as per census 2011, it ranks thirteenth. It is located in the western zone of

West Bengal, which is called ‘Rarhanchal’. A major part of ‘Rarhanchal’ is known as

‘Jangalmahal’. The district of our study belongs to the zone of ‘Jangalmahal’. Once

upon a time, a part of the district was kingdom of the Malla Raj. Present administrative

area of Bankura District took its shape on 1881 under the Burdwan Division of West

Bengal. The geographical area of the district is 6882 square kilometres out of which

6820.51 square kilometres are rural. The geographical statistics of Bankura district have

been depicted in table-1.6.1.

Table-1.6.1 Geographical Area (Square Kilometres)

West Bengal Bankura District

Rural 85427.26 6820.51

Urban 3324.74 61.49

Total 88752 6882 Source: Director of Census Operation, West Bengal, 2005.

This district is bounded by Burdwan district in the north, Hooghly district and Burdwan

in the east. The west line of Bankura district is bordered by the district of Purulia. South

line of this district is a border line with the district of Paschim Medinipur. Major part of

this district particularly western part is mainly undulating terrain. ‘Susunia’ and

‘Biharinath’ are remarkable hill of this district. Land of the eastern part is relatively plain

and fertile. In the district of Bankura major portion of the land area is structured by

laterite soil and light forestry, which is not suitable for intensive agriculture. Basically,

the district is draught prone, only Damodar and Kangsabati river projects provide

irrigation to a very small part of the land area of the district. Mundeswari, Dwarakeswar

and Damodar rivers also create some fertile valley in the district. Dwarakeswar river

flows through the middle of the district and Damodar river separates the district from

19

Burdwan district. Yet, 82% of total population has engaged themselves in cultivation

because there is no better opportunity in the other sectors. Not only that, in the course of

our pilot survey we have experienced that the means of transportation and condition of

the roads in this district are too bad and remote. These prime features no doubt influence

the socio-economic-cultural status of the people of the district.

Table-1.6.2 Administrative Profile of Bankura District

Sub-division 3 (Bankura Sadar, Bishnupur, Khatra)

Community Development Block 22

Police Station 22

Municipality 3 (Bankura, Bishnupur, Sonamukhi)

Gram-Panchayat 190

Village 5178

Inhabited Mouza 3543

Uninhabited Mouza 385 Source: Human Development Report, Bankura District, 2007

We have depicted the administrative system of the district of Bankura at a glance in

table-1.6.2. Administrative headquarter of the district is situated at Bankura town.

Bankura district is divided into three sub-divisions namely – Bankura, Khatra and

Bishnupur. Bishnupur was the capital of the kingdom of the Mallaraj and it has a cultural

heritage. There are twenty-two Community Development Blocks and twenty-two Police

Stations in the district. The three-tier panchayet system of the district constitutes of 190

Gram Panchayets with 03 Municipalities, 22 Panchayet Samities and one Zilla Parishad.

There are 5187 villages and 05 towns in this district.

1.6.2. Demographic Characteristics

In 2011, total population of the district of Bankura stood at 35, 96,292, which is 3.93%

of the total population of West Bengal. Out of them 91.64% live in rural area (Census

Report, 2011). This figure confirms that most of the people of this district remain far

away from urban amenities. Census Report, 2011 shows that 1608635 females live in

rural Bankura, whereas 147153 females live in urban Bankura. Based on the census

report, 2011, we find that in the district of Bankura the decadal growth rate of population

in between year 2001 and 2011 has been 12.64 percent, which is slower than that of our

state and nation. Perhaps, it may happen due to the continuous emigration of the people

20

from the district. In 2001, rural population in Bankura district was 92.63 percent of total

population, which has marginally decreased to 91.64 percent in 2011. The figure

establishes that almost all people of the district are residents of rural areas. It is

interesting to note that decadal growth of urban population in Bankura population

increased to 8.36% in 2011 from 7.37% in 2001. It means that the rapid urbanization

take place during the last decade. The rural urban population distribution is shown in

tables 1.6.3 and in 1.6.4.

Table-1.6.3 Population and Decadal Growth rate by Residence

Total Rural Urban

Person 3596292 3265613 330679

Male 1840504 1686978 153526

Female 1755788 1608635 147153

Decadal Growth rate (person) (per cent) 12.64 11.43 27.8

Source: Provisional Census Report, 2011

Table-1.6.4 Percentage Distribution of Rural Urban Population

State/District 2001 2011

Rural Urban Rural Urban

West Bengal 72.03 27.97 68.11 31.89

Bankura 92.63 7.37 91.64 8.36

Source: Census 2011, Provisional population totals, Director of Census Operation, W.B, 2005

Table-1.6.4 shows that in between 2001 and 2011 percentage of rural population has

declined in West Bengal as well as in the district of Bankura. However, all the urban

areas in the district are dependent on agriculture and its allied activities. One distinct

feature of the district population is that a good number of rural families are seasonal

migrant and move as agricultural labourer to the neighboring districts at the time of

cultivation (Our field survey).

Table-1.6.5 reveals that sex ratio in the district of Bankura is better than that in the state

as a whole. Sex ratio in the district has slightly improved from 952 females per thousand

males in 2001 to 954 females per thousand males in 2011. In the state as a whole this

improvement is good enough during the last decade. It is a positive sign towards gender

equality. However, the rate in district is much slower than the rate of our state where

sex-ratio increases to 947 in 2011 from 934 in 2001.

21

Table-1.6.5 Sex Ratio in West Bengal and Bankura District

State/District 2001 2011

West Bengal 934 947

Bankura District 952 954

Source: Census Report 2011, Government of India.

Table-1.6.6 Caste Wise Population (Percentage) with Reference to 2001 Census

State/District

Scheduled Caste Scheduled Tribe General & Backward Classes

West Bengal 23.01

5.49 71.5

Bankura District 31.25 10.36 58.39

Source: Director of Census Operation, W.B.2005.

This sex ratio of the district is different for different caste categories as shown in table-

1.6.6. It is 937, 966 and 984 for general, SC and ST population respectively (Census,

2001). This shows that the higher the caste in social status the higher is the gender

discrimination. In the district of Bankura 31.25% of total population belongs to

Scheduled caste category and 10.36% belongs to Scheduled tribe category (Census,

2001). This confirms the rampant presence of backward classes in this district. These

figures are relatively high compared to the figures of our state West Bengal. Thus the

district of Bankura is the residence of a large number of Scheduled Caste and Scheduled

Tribe people of West Bengal.

1.6.3. Socio-Economic Characteristics

According to West Bengal Human Development Report (2004) Bankura district ranks

eleventh in human development among seventeen districts in West Bengal (ignoring the

breakup of Dinajpur and Midnapore districts). The values of human development indices

have been depicted in table 1.6.7.

Table –1.6.7 Human Development Index of Bankura District

State/District Health Index Income Index Educational Index HDI

West Bengal 0.70 0.43 0.69 0.61

Bankura District 0.67 0.26 0.62 0.52

Source: West Bengal Human Development Report, 2004.

22

It is seen that values of health index and educational index for the district under

consideration are slightly lower than that for West Bengal but in terms of income index

our district lies far behind the state. Therefore, income poverty is more serious than the

poverty in terms of health and education in Bankura district relative to that in the state of

West Bengal as a whole. According to NSSO (1999-00) 59.62% of rural households and

52.38% of urban households in Bankura district were below the poverty line, determined

by planning commission (West Bengal HRD, 2004). Per capita monthly consumption

expenditure is an important indicator of the economic condition of people. National

Sample Survey (1999-00) has reported that in Bankura district per capita monthly

consumption expenditure was Rs. 350.28 for rural people and for urban people it was Rs.

500.40. Therefore, the district of Bankura is a poor district in West Bengal.

Table-1.6.8 Percentage of Population According to Occupational Status in 2001

Year Farmers Agricultural Labourers Non-farm Occupation

1991 43.2 36.5 20.3

2001 32.6 37.1 30.3

Source: West Bengal Human Development Report, 2004.

From the table 1.6.8 it is clear that most of the people in Bankura are engaged in farm

activity. It is an indicator of underdevelopment. The table indicates that during the period

1991-2001 a good percentage of population has shifted themselves from farm to off-farm

occupation. It is a good indication for development. So the district under study is a

developing district of West Bengal. However, the percentage of agricultural labourers

remained more or less same during the period 1991-2001. This means that the

agricultural labourers could not change their occupational status. Only some farmers are

shifted to off farm occupation. Therefore, agriculture is the main occupation of the

people of this district. We find that 32.6% of total population works as farmer, 37.1% as

agricultural labourer and only 30.3% engage in off-farm jobs. Hence, nearly 70% people

directly depend on agriculture for their livelihood.

1.6.4. Educational Status

Table-1.6.9 has shown the gender-wise education of the people in West Bengal and in

the district of Bankura. Though universal human right declaration treat education as one

23

of the basic right of every individual, the light of education does not reach to a large

proportion of population in Bankura district. On the basis of final census data 2011, the

overall literacy rate in India is 74.4%, where as it is 77.08% in West Bengal and 70.95%

in Bankura district. Female literacy rate in Bankura district is also lower than that at the

state and national level. The table reveals that literacy rate of Bankura district has

increased during the decade 2001-11 by nine percentage point in respect to total

population. Yet, after the twenty years of total illiteracy drive program we have seen that

in the district of Bankura 29 % of total population aged not below six year could not read

and write. According to Bankura Human Development Report, 2007, female literacy rate

is less than 50% in more than 16 out of 22 blocks of this district. This implies that major

proportion of rural women is illiterate. This report reveals that the girls’ enrolment per

thousand boys is 937 in this district in primary and upper primary level and with higher

classes, girls’ enrolment decreases and thereby, dropout increases.

Table 1.6.9 Gender Wise Distribution of Literates

State/district 2001 2011

Total Male Female Total Male Female

India 65.4 75.8 53.67 74.4 82.14 65.46

West Bengal 68.2 77.02

60.2 77.08 82.68 71.16

Bankura District 63.44 76.76 49.43 70.95 81.00 60.44

Source: Census 2011, Provisional population totals, Director of Census Operation, W.B, 2005

The table-1.6.10 indicates that there is inequality in literacy rate among scheduled castes

and scheduled tribes people. According to census data 2001, the literacy rate is 58.22%,

27.11% and 42.92% in respect of male, female and total scheduled castes population

respectively. These percentages are lower than the corresponding percentages for West

Bengal as a whole. The literacy rates are 67.84%, 31.13% and 49.60% in respect of

male, female and total scheduled tribe population respectively in Bankura district.

Table-1.6.10 Sex Wise Literacy Rate among Scheduled Caste Scheduled Tribe

State/District Scheduled Caste Scheduled Tribe

Male Female Person Male Female Person

West Bengal 70.54 46.90 59.04 57.38 29.15 43.40

Bankura District 58.22 27.11 42.92 67.84 31.13 49.60

Source: Director of Census Operation, W.B.2005.

24

Based on the statistics we can say that the scheduled tribe communities of Bankura

district are educationally advanced compared to other part the state. The percentage of

literate persons among tribal people is higher than those among scheduled castes people.

Both male and female people of scheduled tribes are better in formal education than

those in scheduled caste community. But females in both categories have low access to

education in contrast to their male counterpart. This information reveals that the SC and

ST women in this district are disadvantageous group in contrast to the men population.

It leads to lower productivity and lower social and professional status of the women of

Bankura district.

1.6.5. Empowerment Statistics

According to census 2001, the female work participation in India is 25.7 percent against

the male participation rate of 51.9 percent. In Bankura district female work participation

is 32.04 percent, which is higher than national level. Among the female workers, 21.66

percent work as cultivators, 48.74 percent work as agricultural labourers, 9.72 percent

work in household industry and 19.88 percent are engaged in other activities. This

occupational pattern of women of Bankura district indicates that most of the women

work in fields as agricultural labourers and women’s participation in tertiary sector is

very negligible. This is an indicator of rural poor economy. We have collected all these

information from Bankura HRD, 2007. Women’s work participation has been considered

as one of the determinants of women’s empowerment.

Though Indian constitution does not have any provision of gender bias, there is no

significant presence of women in the field of politics. According to UNDP, 1995,

women’s political participation is considered as one of the major components of gender

empowerment measure (GEM). According to the 73rd

amendment Act in 1972 one-third

of total seats in panchayats and municipalities are reserved for women. Bankura HRD,

2007, tells that 39.44 percent seats of panchayet bodies were reserved for women in

Bankura district in 2001 and it is 6.10 percent more than minimum reservation. In most

of the cases women’s political decisions are influenced by their husband, father, son or

other male family members; women are silent spectators in the field of politics. Actually

they are not active participants of politics; women’s presence in politics is symbolic,

ineffective and latent.

25

Bankura district Human Development Report, 2007, shows that women in this district

suffer from protein deficiency and malnutrition and from anemia and tuberculosis. Most

of the women do not get antenatal care. In deed women are deprived of their basic right

of health. HDP, 2007 of Bankura district has reported that the average age of marriage

for women lies below18 years. However, it is above 18 years for general caste women.

Dowry system where bride’s parents pay dowry to groom’s family, is very much

common among the general and scheduled castes marriage. It is reported that the dowry

for general caste ranges from Rs. 50000 to Rs. 400000 in 2005. It is important to note

that tribal community has no such dowry system. In tribal community groom’s family

give some jewellery to the bride as gift. Like any part of the world the women in the

district of Bankura are not free from violence. In 2005, police stations in Bankura district

have reported 326 cases of domestic violence against women.

1.7. Objectives of this Study

Prior to implementation of any development project, it is essential to measure how much

it would be effective to improve the situation of poor, women, lower-caste and

vulnerable and non-empowered population. After complementation of project, it is

equally important to study the impact of the project on the people whom it was

implemented for. So it needs to develop an index of empowerment, which would include

most of the indicators of empowerment. Empowerment is not only qualitative in nature;

it has a number of definitions also depending on the context of the study. Meaning of

empowerment varies from person to person and region to region, caste to caste, ethnicity

to ethnicity. So it is not very easy to propose a common measure for empowerment or

quantify it. We want to divide our whole study into three steps. First, we have tried to

quantify women’s empowerment. Second, we assess the impact of women’s

empowerment on household welfare and third step is the exploration of the determining

factors of women’s empowerment in the district of Bankura, West Bengal.

In the quantification of women’s empowerment we are interested to measure it at the

household level as well as at community level. There are several dimensions of women’s

empowerment at the household level as well as at the community level. We, therefore,

have to select the indicators and dimensions of the women’s empowerment and explain

the logic behind the selection. With the use of the indicators of the women’s

26

empowerment we form an index by which we can measure empowerment, women’s

empowerment in particular at the individual level. We have planned to formulate

empowerment index for both at the household level and at the community level. The

detailed methodology has been explained in chapter three. It would be helpful to

evaluate the impact of women’s empowerment on household and child welfare that has

been considered as a result of empowerment.

In order to assess the impact of women’s empowerment on household and child welfare

in the district of Bankura we have considered three issues – attitudes towards family

planning, incidence of domestic violence and spending for child education. No doubt all

the three aspects of household and child welfares are closely related with women’s

empowerment. But the question that will be naturally asked is that to what extent or

magnitude the issues mentioned above are in reality properly executed or materialised

through women’s empowerment.

Although India has taken several steps towards family planning since 1952, still now

more than 40% women did not use family planning measures. This picture appears better

in West Bengal in contrast to that in major states of India. But still here 29% of women

in reproductive age did not take decision regarding family planning. More surprisingly,

in our country seven percent women do not adopt any short of family planning measure

just in order to have maximum number of children. Fifteen percent of women reported

their unwillingness to adopt family planning measure either due to the disapproval of the

decision making family members or their religion, and another ten percent reported

concerns about health or the fear of side effects (NFHS-3). Some women are reluctant to

adopt family planning measures until they get male child. This information we have got

in our field survey in the process of personal interview. These reasons behind the

unwillingness to adopt using family planning measures are directly linked with the

unawareness, unconsciousness and lack of empowerment on the part of women.

Therefore, women’s empowerment at the household level and at the community level is

expected to affect the decision towards family planning. With this end in view, we have

planned to examine the impact of women’s empowerment at the household level and at

the community level along with other household and community characteristics on

decision regarding family planning for the women in Bankura district, WB.

27

Our second aspect regarding household welfare is domestic violence against women.

Violence against women is common irrespective of social customs, economic status,

caste, creed, religion and other cultural backgrounds. The issue of domestic violence has

been emerged as a research agendum in the field of social science as well as in medical

science. Actually, the manifestation of patriarchal power results in violence against

women. In a patriarchal country like India the male enjoys dominance, privileges and

freedom in all aspects of life, where as women are deprived of basic human rights and

therefore are the victims of social customs. The definition of violence against women

(VAW) cannot be singled out. UN General Assembly, in its resolution 48/104 of 20

December 1993 defined VAW as “Any act of gender based violence that results in or is

likely to result in physical, sexual, psychological harm or suffering to women including

threat of such act, coercion or arbitrary deprivation of liberty whether occurring in public

or private life”. Any untoward action that adversely affects security, freedom and

welfare of women, is considered as violence against women. It gets the women deprived

of enjoying their basic human rights.

The victims of domestic violence range from the killing aged woman to killing of female

foetal. Domestic violence is present everywhere irrespective of time and space, region,

religion, class, caste, status and position, economic condition, age etc. The tragedy

becomes aggravated because this crime does occur not only in external atmosphere but

also within the family at home. When violence occurs within the family, this is

commonly known as Domestic Violence (DV). World Health Organization (WHO) has

defined DV as “the range of sexually, psychologically and physically coercive acts used

against adult and adolescent women by current or former male intimate partners”.

Beating, kicking, slapping, harmful restrictions to regular ordinary behaviour, normal

activities and freedom of movement, threats to demolish from property, denial of access

to resources and control over assets, threat of murder, hurting the feelings of wife by

using the putrid idiom, sexual assault, rape, provocation to commit suicide or deliberate

self-harm etc. are some examples of domestic violence. It affects not only the woman

concerned but also affects the family as well as society.

We have already mentioned that a large section of women suffers from domestic

violence in spite of the existence of the Act for the protection of women from domestic

28

violence. It shows that laws and order are not sufficient to combat the incidence of

domestic violence against women. In order to find an alternative way we would like to

investigate the association between the incidence of domestic violence and women’s

empowerment. We actually like to assess the impact of women’s empowerment at the

household level and at the community level along with other socio-economic factors on

the probability of the incidence of domestic violence against women.

The issue of child welfare is equally important in the goal of inclusive and sustainable

development. In our patriarchal society, no one would deny the role of mother in child

welfare like in child education, health, nutrition and his/her all round development.

Women’s empowerment is, therefore, a crucial factor for child welfare. In order to

examine the role of women’s empowerment in child education we consider the issue of

spending on education of the children of the sample women in the district of Bankura.

Particularly, we are interested to explore the impact of women’s empowerment at the

household level and at the community level along with some selected household

characteristics on spending for her child.

Once we find that empowerment has an instrumental effect on household and child

welfare, we need to search for the determinants of the women’s empowerment and need

to develop a theoretical relation between the women’s empowerment and its

determinants. Once we establish the theoretical relations between women’s

empowerment and its determinants we should test the empirical validity of these

relations. It can also be used for policy making about how much and what kind of

incentive is necessary to improve the empowerment level of women of a particular

region.

In this part of our study we have intended to estimate, empirically, the empowerment

level of women of Bankura District. Using a set of primary data, we want to explore the

significant determinants of the women’s empowerment. In this study, we examine the

effects of several individual and community characteristics like age, education,

occupation, income, financial inclusion, membership in SHGS, caste etc. on women’s

empowerment. This study tells us what kind of other incentives or policies are required

29

in the particular region under study to improve the index of empowerment. We have

designed the study with the particular objectives as follows.

First, we would like to study the possible dimensions and indicators of the women’s

empowerment at the household level as well as at the community level for the

women in the district of Bankura. With reference to the selected dimensions and

indicators we have developed the index of women’s empowerment at the household

level as well as at the community level for each sample woman.

Second, once we have the women’s empowerment as quantitative variable we can

estimate the impact of women’s empowerment on household and child welfare. In

this step we have considered three aspects of household and child welfare – decision

regarding family planning, incidence of domestic violence against women and

spending for child education.

a) We, therefore, investigate the effect of women’s empowerment at the

household and at the community level along with the other socio-

economic and demographic traits on the decision regarding family

planning for the sample women in the district of Bankura.

b) This study assesses the impact of women’s empowerment along with

some selected factors on the incidence of domestic violence against

women in the district of Bankura.

c) We also seek to examine the impact of the women’s empowerment along

with other household and community characteristics on proportion of

household income spending for children’s education for the households

in the district of Bankura.

Third and finally, we intend to trace out and examine the responsible and

significant factors in the determination of the women’s empowerment at the

household level as well as community level. It will help us develop an empirical

relation between the index of empowerment and its determinants.

30

1.8. Conclusion

Discussion of this chapter clears that empowerment of women and abolishing of gender

inequality is essential for inclusive and sustainable economic development. In UNDP

Human Development Report, 1995, the main slogan was “Human Development if not

Engendered is Endangered.” To empower women many steps, policies and projects have

been taken by various international agencies and governments of many countries, but

these were inadequate. Under this backdrop, it is necessary to suggest and implement

appropriate policies for empowering women. What kind of policy should be effective for

empowering women depends on social, economic, demographic characteristics and

cultural norms of the region where the women live. Policies of empowerment are region

specific and culture specific. We would like to investigate the nature, the dimensions and

determinants of women empowerment in the district of Bankura, West Bengal. We have

also planned to investigate the impact of empowerment on household and child welfare

indicating the decision regarding family planning, incidence of domestic violence against

women and proportion of household income spending for child education. In this chapter

we, mainly, chalk out the concept of empowerment, the relevancy and objectives of our

study and social-economic-demographic characteristics of our study area. The detailed

review of the literature for the dissertation has been presented in the second chapter.

Later on, in the third chapter, we present the various dimensions of women’s and a

proposed measurement of the women’s empowerment. The third chapter deals with the

methodology of estimation and hypotheses for our study. We have interpreted and

discussed the empirical findings of this study in chapter four and five. On the basis of

this empirical study, finally, in chapter six we suggest some alternative policies for

improving women’s empowerment and family welfare of the rural households in the

district of Bankura.

31

Chapter two

Review of Literatures on Women’s

Empowerment

2.1. Introduction

Review of the existing literature is the basement of any research. At the initial stage of a

fundamental research, a researcher should go through the relevant literatures. This

chapter presents a review of the existing literature relating to women’s empowerment

which is the central theme of our dissertation. We have planned to develop a measure of

women’s empowerment. So we need to review the existing definitions and measures of

women’s empowerment. We have to know what kinds of difficulties the previous studies

have faced in measuring women’s empowerment; what the different indicators of

women’s empowerment are; what the existing policies are to accelerate women’s

empowerment, how much they are effective to change women’s empowerment etc.

Understanding the impacts of women’s empowerment on different developmental

outcomes is another objective of our study. We need also to understand the possible

determinants of women’s empowerment. In order to gather the existing knowledge

regarding the above mentioned facts we need an extensive literature survey. Keeping this

view in mind, we have reviewed various literatures relating to our study.

The remaining part of this chapter has been structured as follows. In section 2.2 we have

presented the studies, which deals with the conceptual framework of women’s

empowerment. The studies relating to the impact of women’s empowerment on

household welfare have been reviewed in section 2.3. Section 2.4 cities the empirical

studies on women’s empowerment. This section is divided into two sub-sections where

we present the review of empirical studies conducted in different parts of India and

32

studies conducted in abroad respectively. Finally, in section 2.5 we conclude the chapter

of literature review.

2.2. Women’s Empowerment: Issues and the Conceptions

It is widely accepted that empowerment is a quality of human beings and a multi-

dimensional phenomenon. It helps the individual persons or groups to participate and to

get benefit from political or development process in households, communities and

countries. Many researchers and bodies have reported that empowerment is directly

associated with many developmental outcomes. We go to this discussion in details in

section 2.4. Understanding this nexus many developing countries like Nepal, Chile, etc.

have emphasized on empowerment with innovative measures in their Human

Development Reports. However, there is not any universally accepted measure of

empowerment. Nobody would deny that it is difficult to quantify the level of

empowerment. Different studies conducted in different regions have attempted to explain

and quantify empowerment in different ways. As the nature of empowerment is

absolutely influenced by regional culture, different studies have considered different

dimensions and indicators for measuring it. This section has reviewed some important

studies relating to the conceptual framework of women’s empowerment.

The United Nations states that enhancing empowerment means an increase in people’s

ability to bring about change (Human Development Report, 2010). In order to analyse

the components of women’s empowerment UNICEF (1993) has proposed a framework.

These are listed below as cited in Verma (2009).

Welfare: It addresses only the basic needs of women. Women are passive

beneficiaries of the various programmes launched for improvement of their

‘conditions’.

Access: It involves equality of access to resources and opportunities. Women start

recognizing barriers to the accessibility of resources for themselves.

Conscientization: Women are made aware and conscious of gender inequalities as

well as structural and institutional discrimination inherent in the system.

33

Participation: By organizing themselves and working collectively, women get

empowered to gain increased participation and representation in decision making

alongside men equally.

Control: The ultimate level of equality and empowerment, where women are able

to take decision over the various aspects of their lives and play an active role in the

development process. Their contributions are fully recognized and rewarded.

These are actually the stem of the capability approach of development proposed by

Professor Amartya Sen. Thus the expansion of real freedom that the citizens enjoy to

pursue the objectives they have. Obviously, it is a qualitative approach for development.

In different studies women’s empowerment has been defined in different manners.

Keller and Mbwewe (1991, cited in Rowlands, 1995) state that women’s empowerment

is a process which enables the women to organize themselves to increase their self-

reliance, to assert their independent right to make choices and to have control over

resources which will assist in challenging and eliminating their own subordination. The

study of Rowlands (1995) has explored the meaning of empowerment, in the context of

its root-concept: power. According to her empowerment is more than simply opening up

of the access to decision making; it includes the processes that lead people to perceive

themselves as able and entitled to occupy that decision making space, and so overlaps

with the other categories of ‘power to’ and ‘power from within’. She has opined that

empowerment has three dimensions such as Personal, Close relationships and

Collective. The concept of empowerment has been used in different contexts, but it has

been most usefully applied in development context. An empowerment approach centered

on economic activity must pay attention to more than the activity itself. Common view is

that power comes automatically through economic strength. But, she has argued that it

may do, but often it does not, depending on specific relations determined by gender,

culture, class or caste. She has also illustrated that empowerment is a process which

cannot be imposed by outsiders. Although she agrees with the view that appropriate

external support and intervention can expedite and encourage empowerment. In the

context of development Rowlands (1995) has pointed out the importance of individual as

well as collective empowerment. As empowerment is a process where each individual

has to do at her or his own pace, we should take necessary steps for raising level of

34

confidence and self-esteem among poor and marginalized people in such a way that will

enhance their ability to take charge of their own needs. Further, individual empowerment

is one element in achieving empowerment at the collective levels. But concentration on

individuals alone is not enough. She has thought that changes are needed in the

collective abilities of individuals to take charge of their own needs – as households,

communities, organizations, institutions and societies.

Dreze and Sen (1995) have described women empowerment as ability to define self-

interest and choice, and consider woman as not only able but also entitled to make

choices. In order to improve the level of women’s empowerment they have proposed to

reduce gender biasness in mortality rate and natality rates, in access to education and

professional training, in employment, in the ownership of property and in household

work and decision making. Analysing the data from India they have illustrated that

female literacy reduces child mortality rate while both female labour force participation

as well as female literacy reduced female child mortality rate. They have interpreted

these results as evidence of the fact that women’s access to education and employment

had enhanced their ability to exercise agency, i.e., the process of empowerment.

Kishor (1997) has conceptualized empowerment in terms of ‘control’ by which women

would be able to access information, take decision and act in their own interest or for

their dependents. She has considered three categories of composite indicators to measure

women’s empowerment. These are ‘direct evidence of empowerment’, ‘source of

empowerment’ and ‘the settings for empowerment. She has grouped the indicators of

behavioural and attitudinal factors into ten dimensions. We have listed these indicators

including the variables.

Direct Evidence of Empowerment

a) Devaluation of Women: reports of domestic violence; dowry paid at marriage

b) Women’s Emancipation: belief in daughters’ education; freedom of

movement

c) Reported Sharing of Roles and Decision Making: egalitarian gender role;

egalitarian decision-making

35

d) Equality in Marriage: fewer grounds reported for justified divorce by

husband; equality of grounds reported for justified divorce by husband or

wife

e) Financial Autonomy: currently controls her earnings; her earnings as share

household income.

Source of Empowerment

a) Participation in the Modern Sector: index of assets owned; female education

b) Lifetime Exposure to Employment: worked before marriage; controlled

earnings before marriage

Setting Indicators

a) Family Structure Amenable to Empowerment: does not now or previously

live with in-laws

b) Marital Advantage: small age difference between spouses; chose husband

c) Traditional Marriage: large educational difference with husband; did not

choose husband

Mayoux (2000) has clarified basic views regarding the inter-linkage between

microfinance and women’s empowerment. This paper is based basically on secondary

source materials. Following Kabeer (1999) the study has outlined the process of

women’s empowerment considering the analysis of power relation. The power relations

are as follows.

Power within: enabling women to articulate their own aspirations and

strategies for change

Power to: enabling women to develop the necessary skills and access the

necessary resources to achieve their aspirations

Power with: enabling women to examine and articulate their collective

interests, to organize to achieve them and to link with other women’s and

men’s organizations for change

Power over: changing the underlying inequalities in power and resources,

which constrain women’s aspirations and their ability to achieve them

36

These power relations function in socio-economic and political spheres of life at

different levels like individual, household, community, market and institutional.

Reviewing the existing views regarding the impact of microfinance on women’s

empowerment the study has concluded that cost effective ways integrating microfinance

with other empowerment interventions and complementary services are still lacking. In

order to maximize the contribution of microfinance to women’s empowerment Mayoux

(2001) has proposed a strategy, namely, ‘Gender Mainstreaming for Empowerment’ for

donors or Governmental agencies. The core element of this strategy is that gender policy

should integrate productive and reproductive work, welfare concerns and measures to

address power inequalities in strategies for both women and men. Particularly, equality

in access to all microfinance services and an adequate and non-discriminatory regulatory

framework is required for empowering women through microfinance.

According to Kabeer (2001) empowerment refers to the expansion in people’s ability to

make strategic life choices in a context where this ability was previously denied to them.

She has analyzed the concept of women empowerment based on three dimensions

namely, Resources, Agency and Achievements. Resources occupied by the individual

can be materials, social or human which have been treated as conditions of

empowerment. The second dimension of empowerment relates to Agency which acts as

the process of empowerment. According to her agency encompasses a wider range of

purposive actions, including bargaining, negotiation, deception, manipulation, resistance

and cognitive processes of reflection and analysis. Resources and agency together which

Kabeer (2001) refers to as outcome of empowerment, constitutes the potential that

people have for livings the life they want. The ability to choose has been considered as

the central theme of the concept of power. Power may have a negative sense like threat

but empowerment changes the negative senses to a positive one. Empowerment can

reflect change at different levels. At the immediate level empowerment is recognized by

individual resources, agency and achievement. It occurs at the intermediate level, in the

rules and relationship which prevail in the personal and socio-political spheres of life. It

can also occur in the ‘Deeper’ level which changes the distribution of resources and

power in the society and reproduces it over time. She has critically assessed the measures

of women’s empowerment used in different studies. Usually, indicators of the resource

dimension are measured by the access to some specific assets or services. She has rightly

pointed out that many studies fail to consider the differential prior possibility of having

37

access to a particular resource. One should be alert in this line when resource-based

measure of empowerment will come on hand. In order to measure the agency

dimension, she proposes some decision making power of person towards the betterment

of the lives. According to her, in India typical measures of agency dimension include the

decision to purchase of food, purchase of major household goods, purchase of small item

of jewellery, course of action if child falls ill, disciplining the children, children’s

education. To measure the achievement dimension of women’s empowerment, Kabeer

(2001) has agreed with the measures considered in the study of Dreze and Sen (1995),

Kishor (1997) and Becker (1997). But she has pointed out that one needs to segregate

between gender-differentiated achievements which signal differences in values and

preferences and those which draw attention to inequalities in the ability to make choices.

However, she has argued that there is no unique linear model by which one can identify

the causes for women’s disempowerment and alter to create the desired effect. Besides,

she has explained that many of the resources, form of agency and achievements of

women’s empowerment are integral to the broader development goals. With this end in

view, she did not specify causal relationship between resources, agency and

achievements. However, for modelling empowerment we need at least a theoretical

causal consequence among these components, which identifies the directional

relationship. This study has insisted us to study the women’s empowerment in two ways.

On the one way we study the resource and agency dimensions of empowerment by

which we shall construct the empowerment index. On the other hand to realize the

achievement dimension which assesses the impact of empowerment index on some

selected indicators of family welfare.

Viswanathan (2001) has critically assessed the implication of the components of Human

Development Index and Gender development Index in Indian context with special

reference to the state of Karnataka. She has explained that most of the indicators of these

measures underestimated the women’s work and its value in the context of India. This

study has highlighted a set of alternative indicators (asset ownership, access to credit and

environmental degradation) for gender development in India. Application of the Gender

Empowerment Measure (GEM) in India has also been criticized. GEM proposed by

UNDP in Human Development Report 1995 considers the indicators such as earned

income share in professional and managerial jobs and share in parliamentary seats.

Viswanathan (2001) agrees that income confers power, but in many cases in India

38

income earning women enjoy less control over their earnings. Besides, poor women in

India are compelled to earn; it is not a matter of their choice. So a higher workforce

participation rate may imply less instead of more empowerment for women. She has

argued that a large share for women in professional and managerial jobs is hardly reflect

the autonomy and self-reliance of women in India where acute gender biased

differentials in wages and nature of work are the norm of employment. To explain this

argument she has cited the example of Karnataka, where female workforce for the state

has been growing at a faster rate than the male workforce. But disaggregated data

between urban and rural areas indicates that male workforce has shifted from low

income and less skilled jobs in villages to better paying skilled jobs in cities. Greater

participation of women in the workforce seems to be due to vacancies of the shifted male

workforce to the cities. As a result, women are remaining subordinate in terms of the

nature of work and wages. This study also suggests that for assessing the political

participation share of women in local body level is a better norm than that in

parliamentary seats in India. She has pointed out that the pervasive presence of domestic

violence is common in India. Income and apparent status hardly manage to reduce it. So

in order to understand the level of women’s empowerment in developing countries like

India we need to take into account the magnitude of domestic violence against women.

Based on the data of unnatural death of women she has explored that the magnitude of

domestic violence in Karnataka is a serious social problem. She has noticed that despite

the existence of administrative and judicial system, National Human Rights

Commission, the National and State Women’s Commission, a large part of the Indian

women is suffering from the problem of domestic violence. They observed that

‘conspiracy of silence’ that operates in all societies is one of the reasons of domestic

violence and the sufferers treat it as an acceptable adjunct to harmony within the homes.

Another reason is, however, the non availability of the data to disclose the enormity and

prevalence of such violence. Often women in India do not report the problem of violence

to police based on the belief that an outsider should not interfere in marital issue.

However, this study did not explore the nature of relation between empowerment and

violence in India.

Based on the existing theoretical studies regarding the women’s empowerment,

Molhotra, et al. (2002) have come to the conclusion that women’s empowerment is a

complex development concept but not broader than the concept of social inclusion.

39

“Process” and “agency” are two essential elements of women’s empowerment. Women’s

empowerment encompasses a progression, where women act as agent, from one state to

another. For example, it may be an improvement from gender inequality to gender

equality for a specific set of families. The study has reported that major number of

reviewed studies fails to capture the process element of empowerment. According to this

study, empowerment of women may vary from her home to other broad area. So it has

suggested to measure empowerment separately at household level, community level and

at broader arenas. Molhotra, et al. (2002) has proposed six dimensions for each level.

These are Economic Dimensions, Socio-Cultural Dimensions, Familial/ Interpersonal

Dimensions, Political dimensions, Legal Dimensions and Psychological Dimensions.

Different indicators for measuring empowerment have been considered for different

dimensions of each level.

Molhotra, et al. (2002) have reviewed two types empirical studies, namely, studies

considering empowerment as outcome of interest and studies considering impact of

empowerment on other developmental variables. Reviewing a large number of studies

they have concluded that factors such as education, employment, positive marriage

condition and microcredit are influential for women’s empowerment. On the other hand,

a handful of studies show that empowerment has some favourable impact on

contraceptive use, spending on nutrition, child wellbeing and reduced fertility rates. For

measuring women’s empowerment Molhotra, et al. (2002), have some suggestions for

the future researchers. First, we should consider context-specific measures, which reduce

the dependence on proxy measures. Second, in order to capture the process element of

empowerment we should collect data across time dimensions. Third, at a minimum,

quasi-experimental evaluation designs and collection of baseline and end line data must

be considered in implementing programs aimed at empowering women. Fourth, more

interdisciplinary interaction is necessary to develop indicators and approaches that

capture the key elements of women’s empowerment.

The study of Agarwal (2003) has suggested a technological model for empowering rural

women. Women’s employments through technological improvement and participatory

approach are needed to improve their lives. This would ensure a sustainable future for

rural India. Technology model described how scientific and technical interventions could

40

improve the quality of life of women in rural areas. This also shows that the following

factors are crucial for women’s empowerment in rural area.

Proper reorganization of the productive and domestic roles of women

Improvement of women’s empowerment needs facilities like drinking water,

health, sanitation, nutrition, family planning, education and security

Gender integrated participatory technology development is required

Improvement of local women motivator as active “change agent” of technology

through talks and audiovisuals, awareness build up through demonstration and

hands on the job training in relevant field

This study has explained that technological development model along with education,

employment, reduction of socially traditional attitudes i.e. religion, family structures etc.

are responsible factors of women empowerment.

Lillykutty (2003) has explained the relation of education and empowerment of women

with the quality of life. She states that empowerment of women is developing them as

more aware individuals who are politically active, economically productive and

independent and are able to make intelligent decision in matters that affect them and

their nations. A woman is said to be empowered if she has command over wealth,

education, social status, skill etc. and has access to formal financial services. This can be

done by creating an environment in which the distribution of power and resources, the

opportunity to engage in productive work, opportunities to access education, medical

care, and health services can move in favour of women population. If we look into the

definitions of women’s empowerment we find that empowerment is a concept of human

agency- self-efficacy on the one hand and on the other hand it is a process. It indicates

that women’s empowerment has at least three dimensions. She has attempted to establish

a strong positive relation between education and empowerment of women. Education

enhances women’s status in the society and leads to greater input into family and

community decision-making. It provides girls with a basic knowledge of their rights as

individuals and citizens. Knowledge and decision making power can place the women on

a more equal footing with male. Education also provides knowledge and skill especially

in the areas of health, nutrition, sanitation and the environment. Education not only

emancipates women from ignorance, ill treatment and dependence etc, but also

41

empowers them to claim their right to quality of life. Finally, education can serve as a

powerful instrument for individuals to achieve power and status in the society. It is a

source of mobility, equality, and empowerment both at the individual and social level.

Verma (2009) has tried to conceptualise the concepts, needs and context of whole issue

of empowerment and has reviewed the various approaches of empowerment of women.

He has defined empowerment as a process of gaining or accessing control over self and

the resources as well as the ideology which determine power relationships. The process

of empowerment tries to change the existing balance of power in a given context.

Analysing the earlier literature he argued that empowerment is a process of capacity

building and skill development. According to author, empowerment may help the

women to participate more effectively at different socio-political forum. With this end in

view, Verma (2009) has set twin goals of women’s empowerment (a) to challenge

subordination and subjugation; and (b) to transform all the structures, systems and

institutions which in any way, may cause or support gender discrimination and

inequality. In order to achieve these goals she has opined that women need to be

empowered in the contexts of individual, social, economic, physical and psychological

aspects. To suggest the suitable strategy for empowering women in true sense, this study

has presented a critical assessment of the existing alternative approaches and strategies

for women’s development, emancipation and empowerment. It is revealed that most of

the approaches are over-lapping in concept and practice. The discussion of this paper has

come to the conclusion that for empowering women we need the full participation of the

people who are already empowered in the formulation, implementation and evaluation of

the action strategies. Verma (2009) has found that social work approach to women’s

empowerment is suitable in this respect.

2.3. Women’s Empowerment and Welfare: The Impact Studies

The concept of empowerment has been recognized as an instrument of human

development since the inception of the UNDP’s Human Development Report in 1990.

In this section we have planned to review the studies, which have investigated the impact

of women’s empowerment on family as well as social welfare. The studies under this

category have tried to explain the contribution of women’s empowerment in investment

and income generation, in women and child health, in child education and awareness and

social capital, broadly, in family well-being as well as social well-being.

42

Jejeebhoy (1995) has considered five dimensions of empowerment for studying nexus

between reproductive behaviour and women’s empowerment in the developing

countries. These are knowledge autonomy, decision-making autonomy, physical

autonomy, emotional autonomy and economic and social autonomy and self-reliance.

Reviewing many studies conducted across the globe she has established that kinship

structure in the family, education of the women and women’s autonomy, which are the

indicators of empowerment, reduce the fertility rate.

The empirical study of Becker (1997) conducted in Zimbabwe has explored the

implications of women’s empowerment on different set of functioning which Kabeer

(2001) refers to as achievements dimension of empowerment. The functioning that have

been considered in this case are the use of contraception and take-up of pre-natal health

care. In this study women’s empowerment has been measured by an index of women’s

role in decision-making in three important issues. These include the purchase of

household items, the decision to work outside and the number of children to have. In

order to separate the effect of women’s empowerment he has carried out a regression

analysis in two steps based on the primary data. In the first step he has estimated the

effects of some likely determinants of these achievement variables. He has found that

household possessions, the number of survival children, the wife’s employment and

husband’s education have some favourable impact on the use of contraception. Aged

women, rural women and who had polygamous husbands were less likely to use

contraception. The likelihood of receiving pre-natal health care was directly related to

the household possessions index, rural residence, women’s age, education and

employment and husband’s education. In the second step, Becker (1997) incorporated

the women’s empowerment index as an extra explanatory variable to his equations to see

what difference it made. Incorporating the empowerment index he has found that the

goodness fit has improved little for the equation in relation to contraceptive use but

improved significantly for the equation of receiving pre-natal health care. In Zimbabwe

Government has committed to ensure the availability of contraceptives through

community based distribution system for family planning. It makes the ‘contraceptive

use’ a routine behaviour of the women of Zimbabwe. That is why, women’s

empowerment has not significant and separate effect on their contraceptive use. By

contrast, women’s take-up of pre-natal health visit is significantly determined by their

43

role in intra-household decision-making as well as by their education and their

employment status.

In Indonesia Beegle, et al. (1998) have examined the impact of women’s characteristics

on pre-natal care and on the incidence of delivery at hospital. They analysed the data on

about 2000 couples from the 1997-98 Indonesia Family Life Survey. Individual assets,

education and social status of the women have been considered as indicator of her

empowerment. This empirical study has revealed that volume of individual assets, level

of education and social status of the women increases the probability of getting pre-natal

and delivery care of the women in Indonesia.

In an exhaustive study Murthi, et al. (1998) have explored the determinants of three

demographic outcomes such as child mortality rate, the total fertility rate, and the

relative survival chances of male and female in India. For empirical analysis they took

the cross-section data of 296 districts from the census data of 1981. It is found that

female literacy has a negative and statistically significant impact on child mortality and

on male child bias. Male literacy has also a negative effect on child mortality but the

effect of male literacy is smaller than that of female illiteracy and statistically

insignificant. Higher labour force participation exudes the extent of gender bias.

Urbanization and medical facilities have reduces the child mortality and accelerates

gender bias. Poverty in India is positively associated with higher level of child mortality.

However, poverty is not the cause of female disadvantages. A higher proportion of ST

population in district reduces the extent of anti female bias in child survival. This study

has also compared the southern and northern part of India regarding the same three

issues of demography. In southern part child mortality rate is higher and a girl child has a

survival advantages over boys. The empirical analysis reveals that female literacy and

labour force participation are crucial for total fertility. This study has admitted the role of

women agency in mortality, fertility, and gender inequality. The direct proportion of

child health, female literacy, and female labour force participation are likely to be more

conducive to reduce fertility than the indirect intervention based on promising the

general level of economic development.

Pitt, et al. (1998) have estimated the impact of male and female participation in group

based credit programs namely, the Grameen Bank (GB), Bangladesh Rural

44

Advancement Committee (BRAC) and Bangladesh Rural Development Board’s (BRDB)

Rural Development RD-12 microfinance programs in Bangladesh on household

expenditure, on women’s non-land asset, on women’s and men’s labour supply and on

boys’ and girls’ schooling, paying close attention to the issue of endogeneity. They have

used a quasi-experimental survey design and village level fixed-effect method to identify

the effects of credit programs in a limited information likelihood framework. For

estimation they have used a primary data collected from eighty-seven rural Bangladeshi

villages during 1991-92. The participation in group-based credit programs is measured

by the quantity of household’s cumulative borrowing. No doubt this is an indicator of

empowerment in rural Bangladesh. Correcting the problem of endogeneity they have

shown that credit received by women and men have strong positive impact on total

annual household expenditure for each program. The estimated effects of female’s credit

on expenditure, for three programs, are near about two times of the same of male’s

credit. Irrespective of the programs only the effects of female’s credit are statistically

significant. In addition to the expenditure effect, the study has shown that women’s

participation in credit program increases their non-land assets value, whereas men’s

participation does not. Another result indicates that the women’s participation in the

Grameen Bank has a positive significant effect on the women’s labour supply. On the

other hand credit goes to the male and goes to the female significantly reduce the men’s

labour supply. Only the Grameen Bank female’s credit has positive and significant

impact on girls’ school enrolment (see also in Pitt, et al. 1996). Both the male’s and

female’s credit from Grameen Bank and Bangladesh Rural Development Board’s

(BRDB) Rural Development RD-12 have also positive and significant impact on the

boys’ school enrolment. Moreover, these estimated impacts of program participation on

women’s labour supply, on schooling of children and on value of non-land asset holding

are free from endogeneity problem relating to program participation.

Analysing the IFPRI survey data collected from 826 households in Bangladesh, 114

households in Indonesia, 1500 households from the Ethiopia Rural Household survey

(1997) and data on 500 households from the Project for Statistics on Living standards

and Development in South Africa (1998) Quisumbing, et al. (1999) have studied the

impact of women’s empowerment on expenditure shares of food, education, health,

children’s clothing, alcohol/tobacco use and child schooling. They have considered the

value of women’s own assets at the time of marriage as indicator of women’s

45

empowerment. This study has reported that more the resource controlled by women

increases the share of expenditure on child education, but not equally for boys’ and girls’

across the surveyed countries.

Quisumbing, et al. (2000) have also conducted a case study in Bangladesh exclusively

to estimate the impact of wife’s and husband’s empowerment captured by assets at

marriage and current assets on expenditure shares of food, clothing and children’s

education. This study is based on the survey of 826 households residing in 47 villages in

three sites in Bangladesh. The empirical findings show that wife’s assets have some

positive effect on the share of expenditure on children’s clothing and education. Current

assets have a positive effect of on food expenditure share.

We have seen that Kishor (1997) has offered three categories of indicators of women’s

empowerment (refers to section 2.2). Kishor (2000) has investigated the effects of these

indicators on child welfare outcomes, particularly, on infant survival rates and on infant

immunization. This investigation is relied on the data of 3783 women in Egypt who had

a birth in the last five years from the Egypt Demographic Health Survey, 1995-96. The

findings of the multivariate analysis of this study have revealed that the source/setting

indicators of women’s empowerment are more important than the direct evidence of

empowerment in the determination of the outcome variables – infant survival rates and

infant immunization in Egypt. She has found that infant survival rate was lower in the

households where women lived or previously had lived with their in-laws and in the

households where there was a large age and educational difference between spouses.

Women’s employment before her marriage increases the survival rate of her children. It

has been found that mother’s employment and education significantly increase the rate

of child immunization in Egypt. However, children were less likely to have immunized

in the households where mother were under the authority of their parents in-laws.

Besides, among the direct measure of empowerment ‘belief in equality in marriage’ has

a positive and significant effect on children’s survival chance and on the likelihood of

child immunization.

In an empirical study Koenig, et al. (2003) have estimated the impact of women’s

autonomy along with some individual, household and community level variables on the

incidence of domestic violence in Bangladesh. They have illustrated a conceptual

46

framework for the determinants of domestic violence. This study is based on the data set

collected in 1993 under the Family Health Research Project of the ICDDR from two

areas of rural Bangladesh. A total of 9620 sample women aged 15-49 year, has been

considered in this study. Of them 3785 reside at Sirajgonj area and others reside at

Jessore. This study has taken the wife’s report of current physical violence as measure of

domestic violence. It is the dependent and binary variable. Individual and household

socio-economic characteristics includes the wife’s age, religion, landholdings, education

of both the husband and wife, number of living sons and family structure. This study has

included two important individual status namely membership in group lending program

and women’s autonomy. The authors have used the five manifest variables reflecting

three dimensions of women’s autonomy drawing on the work of Jejeebhoy (2000). They

have constructed the women’s autonomy index following the methodology of latent class

analysis. This study also included three community-level variables, constructed through

the aggregation of individual responses at the ‘mouza’ level, a civil administrative unit

corresponding closely to the community level. In order to examine the impact of

community level variables they have considered 179 mouzas through cluster sampling

strategy. These are community-level women's education, community-level savings and

the community-level women's autonomy index. As the domestic violence for each

individual is binary, logistic regression has been used for multivariate analysis. Initially,

they have fitted the logit regression for all observation then they have repeated the model

for each area. This study has revealed that 42% of the sample women have currently

faced domestic violence. A somewhat higher percentage of women in Sirajgonj than in

Jessore reported physical violence. Regression analysis has shown that increased

education, higher socio-economic status, non-Muslim religion, and extended family

residence reduce the incidence of violence. The effects of women’s status on violence

were found to be highly context-specific. In the more culturally conservative area,

Sirajgonj, higher individual-level women’s autonomy and membership in group lending

program increase the risks of violence, and community-level variables were unrelated to

violence. In the less culturally conservative area, Jessore, in contrast, individual-level

women’s status indicators were unrelated to the risk of violence, and community-level

measures of women’s status were associated with significantly lower risks of violence.

However, this study has considered only one indicator of domestic violence. So, it fails

to measure the extent of domestic violence.

47

Thus, we find that the issue of domestic violence has become an issue of concern for all

the Government, policy makers and health workers. There is a perhaps very few studies

which discuss the relation between domestic violence and economic empowerment of

women, particularly, in our study area. In this context, the present study sets three

objectives. First, we study the nature of economic empowerment of the rural women in

the district of Bankura. Second, this study explores the determinants of domestic

violence in the district of Bankura. Third, we would like to examine the impact of

economic empowerment along with other determinants on marginal change in the

incidence of domestic violence. The findings of this study would help the policy makers

to frame appropriate policy for the betterment of women so that they can live safe and

sound lives at home.

Maldonado, et al. (2003), in a study, have explained the role of microfinance program

along with women’s empowerment and other individual and household characteristics on

the child education decision of rural households in Bolivia. They have formulated a

theoretical model of utility and apply the count model to estimate the education gap

(expected education – actual education) of rural child. The women’s empowerment

measures the proportion of the accumulated human capital held by the worker women of

the household. Human capital has been measured by the numbers of years of schooling

accumulated by the workers of the household divided by the number of workers. The

estimation is based on two sets of data one is at municipality level and other is at

national level. This study reveals that microfinance program and women’s empowerment

significantly reduce the education gap of the children in rural Bolivia. However, age, the

position of child compared to siblings, household land holdings and poverty index have

positive and significant impact on education gap.

Ahmed, et al. (2006) have examined the effect of physical violence during pregnancy on

prenatal and early-childhood mortality. For this purpose they have collected data from

2199 women in Uttar Pradesh, India and have used proportions, Logistic Regression

model, Hazards Model to examine the risks for prenatal, neonatal, post-neonatal, and

early-childhood (aged 1–3 years) mortality by mother’s exposure to domestic violence.

They found that 18% of sample women experienced domestic violence during their last

pregnancy. After adjusting other risk factors, they found that mothers who had

experienced domestic violence had higher risks for prenatal and neonatal mortality than

48

the mothers who had not experienced violence. They found no significant associations

between domestic violence and either post-neonatal or early-childhood mortality.

Koenig, et al. (2006) have examined individual and community level influences on

domestic violence in Uttar Pradesh, North India. To conduct this study they have used

the multilevel modelling to explore domestic violence outcomes among a sample of

4520 married men. They found that the individual-level variables like childlessness,

economic pressure, and intergenerational transmission of violence increase the risk of

physical and sexual domestic violence, where as higher socioeconomic position of

households lowers it. They also have shown that a community environment of violent

crime and Community-level norms concerning wife beating were associated with more

risks of both physical and sexual violence and were significantly related only to physical

violence.

Schaedel, et al. (2007) have discussed the role of mother’s empowerment in advancing

the education of their children under the School Family Partnership program (SFP) in

Israel. This study has reported that women’s empowerment indicating the involvement

and familiarity with the SFP program is suitable for student’s achievement. However, the

education of mother is not so important for her ward’s achievement.

The article of Rocca, et al. (2008) have studied the empirical relationships between

women’s empowerment and physical domestic violence among young married women

residing at the slums area of the city of Bangalore. In order to explore the determinants

of domestic violence against women this study has applied the unadjusted and adjusted

multivariable logit regression model. They have found that women in love marriages

contrasted with the women in arranged marriages have more experience of domestic

violence. Women whose families were asked for additional dowry had higher level of

violence. Women who worked before or after marriage were more likely to report

spousal violence. This study has revealed that dowry given at marriage and stable-

occupation of husband reduces the risk of marital violence. It proves that the practice of

dowry is a deep reflection of the many form of gender inequality that women experience.

They have opined that as the practice of dowry is pervasive and routine in many

communities in India, the effectiveness of anti dowry and anti violence laws is limited.

Moreover, this study has shown that participation in SHG increases the probability of

49

having domestic violence. This result indicates that unspoken norm of restricted mobility

of the young women is still pertaining in the Indian society. In addition to the anti dowry

and anti violence laws they have suggested some strategies that mobilize women,

families and communities, to challenge the pervasive acceptance of dowry and to

promote gender equality.

Chowdhury, et. al. (2009) have evaluated pattern of domestic violence pattern in non-

fatal deliberate self-harm (DSH) attempters by analyzing 89 DSH cases admitted at three

Sundarban BPHCs. The authors found that most of DSH attempters were young, female,

low-educated and married. They also found that 69.6% of DSH attempters experienced

more than one form of domestic violence and among female DSH attempters; husband

was responsible for 48.48% cases followed by in-laws for 16.67% cases.

Sarkar (2010) has reported the prevalence, characteristics and reasons of domestic

violence, if any, for adult and adolescent females residing in Singur block of Hooghly

district, West Bengal. The study has found that 23.4% of sample women were exposed to

domestic violence in the past year. Maximum prevalence of domestic violence was

observed among 30-39 years age group, illiterate and unmarried females. This study has

explored that the prevalence of domestic violence was found to be higher among the

Muslims than the Hindus. Prevalence of domestic violence was rampant among the

females who were unmarried or who did not give birth to a child. Majority of the

respondents opined that opportunity of education, being economically productive and

better family income would help them to overcome the problem of domestic violence.

In an empirical study, Janssens (2010) has systematically investigated the quantitative

impact of empowerment program namely, the Mahila Samakhya Program in Bihar, India

on social capital. He has assumed that activities of Mahila Samakhya Program have

increased the nature of agency and empowerment of women. In this study, social capital

refers to the behaviour regarding trust, cooperation and assistance of the households.

Trust has been divided it into two levels, viz. trust in community members and trust in

strangers. The study has constructed the normalized index following factor analysis

based on the arguments against statements relating to trust in community level. Trust in

strangers is quantified putting value one if the respondent disagrees to the statement: “if

you meet a new person from outside the village, you should be very careful to trust this

50

person” and zero otherwise. On the other hand, the issue of cooperation has been

measured by assistance among households and joint action to improve community

infrastructure. The assistance variable is measured as the normalized index constructed

from a factor analysis of the five indicators of assistance. The empirical analysis has

covered three districts in Bihar, namely, Sitamari, Muzaffarpur and Darbhanga. It has

used a set of quasi-experimental data collected from 1991 households. The empirical

findings of this study suggest that Mahila Samakhya increases the level of trust in

community members and in strangers. It substantially increases the level of participation

in collective action, either in school projects or infrastructure for the member

households. The impact of the program is especially large among its target group: the

lower castes and the poorest and least educated households. But it has limited influence

in social assistance among households. This study has also reported that the Mahila

Samakhya program has a bandwagon effects and induce others to join in the activity as

well in the area under study. However, this study did not give any explanation of the

measure of women’s empowerment.

Based on secondary data source Kumar (2011) has investigated the inter-state

disparities in India in the status of women and economic development and its changes

over time. The composite indices for women’s status and for economic development

have been prepared using Principal Component Analysis. This study has reported a high

level of dispersion among the Indian states with respect to the various indicator variables

of women’s status. During the period 1980-90 the disparities have declined for most of

the educational and health status variables. The disparities have declined for most of the

educational and economic status variables over the period 1990-2000. The PCA shows

that educational variables are more important relative to the other variables to influence

the status of women irrespective of the periods under consideration. On the other hand,

urbanization rate, per capita income and the number of factories per lakh of population

have been found to be the dominant factors to explain the nature of economic

development of the states. It has found that Kerala, which occupies tenth/eleventh rank

in accordance to economic development, tops the ranking for women status for each year

under study. This decadal analysis has shown that the states of Uttar Pradesh, Orrisa and

Madhya Pradesh have improved their position among the states over time in the rank of

women’s status. On the other hand, West Bengal, Andhra Pradesh and Gujrat have

shown deterioration in their rankings. Moreover, average ranks of the states for the three

51

years in women’s status and economic development have shown that economically least

developed states are also lower in the ladder of women’s status and vice-versa.

Ray, et al. (2012) have recorded the prevalence of different types of ‘life time’ violence

against the women (VAW) under reproductive age in two urban wards in Siliguri

Municipal Corporation. They have found that more than fifty percent of sample women

had ever faced physical violence. As a consequence of VAW, 54.5% of victims suffers

from mental problem followed by 39.2% were experienced to physical injury. Only 4.9%

has consulted physician and 3.6% have reported to police.

From the literature it is thus clear that women’s empowerment affects a wide range of

household welfare indicators. So, we need to review the literatures that help us

understand the determinants of women’s empowerment. In following section we have

reviewed the studies relating to determinants of women’s empowerment.

2.4. Studies relating to Determinants of Women’s Empowerment

In this section we have discussed the impacts of different socio-economic and

demographic characteristics of women on her empowerment. First, we proceed with the

review of existing empirical literature carried out in different parts in India.

Subsequently, we have presented the studies conducted in abroad relating to the

determinants of women empowerment.

2.4.1. Studies on Women’s Empowerment: The Indian Scenario

Conducting an empirical study in the state of Andhra Pradesh Narasimham (1999) has

assessed the role of awareness generation strategy developed by an NGO, AWARE

(Acronyms for action for Welfare and Awaking in Rural Environment) on women’s

empowerment. The findings generated through participatory observation and interviews,

show that in every area of empowerment such as earnings, education, healthcare status,

access to and ownership of resources including land, decision making power, autonomy

and assertiveness, women, who have been exposed to the awareness generation strategy,

do better than the women of the villages where no awareness had been created. This

study reveals earning of women, degree of consciousness, awareness, education,

confidences, ownership of land and membership of any organization as responsible

factor for women empowerment. However, Narasimham (1999) has described just how

52

to improve empowerment but how much empowerment would be improved is not

answered in her study.

Jejeebhoy (2000) has compared the effect of a range of women’s and household

characteristics on women’s autonomy between the two regionally and culturally different

Indian states, namely, Tamil Nadu and Utter Pradesh. In this study, measures of

women’s autonomy have included four dimensions: (a) role in economic decision-

making, (b) mobility, (c) incidence of domestic violence and (d) access to economic

resources and control over economic resources. For empirical analysis she has conducted

a primary survey and collected data from 1842 women in four districts based on focus

groups analysis. The districts of Coimbatore and Ramnathpuram have been selected

from Tamil Nadu and Meerut and Pratapgarh from Uttar Pradesh. First, this study has

attached a score for each dimension in accordance with the extent of autonomy of the

woman. Finally, she has computed a summary index of women’s autonomy taking mean

of the score indices of each dimension. In order to measure the impact of individual and

household traits on the autonomy index, a linear regression model has been fitted for

each state. This study has revealed that the women in Tamil Nadu are far better in terms

of autonomy than the women in Utter Pradesh. However, determinants of women’s

autonomy varied in the two states. She has found that traditional characteristics – the

number of sons they bore, dowry size and nuclear family type – were directly related

with the autonomy indicators in restrictive culture of Utter Pradesh than they were in the

more egalitarian culture of Tamil Nadu. In Utter Pradesh female employment has also a

positive and significant effect on most of the autonomy indicators but female education

has insignificant effect. However, in Tamil Nadu female employment and education

have strong positive impact on their autonomy.

Jejeebhoy, et al. (2001) have extended the previous study of Jejeebhoy(2000). In order

to examine the influence of religion and region on the women’s autonomy they have

covered ten districts of the state of Punjab in Pakistan in addition to the study area of

Uttar Pradesh and Tamil Nadu in India. In this study initially they present a regression

analysis of the summary index of women’s autonomy for Pakistan, Tamil Nadu and

Uttar Pradesh separately. In this step they have found that the traditional factors such that

co residence with mother-in-law, size of dowry, and age are significant determinants of

women’s autonomy in Uttar Pradesh and Pakistan. In Tamil Nadu, by contrast the only

53

traditional factor, age, plays important role in the determination of women’s autonomy.

Education and wage work status are also significant determinants of autonomy index, but

their impacts are stronger in Tamil Nadu. This study has shown that religion has not any

consistent impact on autonomy index in the two states in India. In the second step

Jejeebhoy, et al. (2001) have pooled the data from the three sites and exclusively

estimated the impact of contextual factors, namely, religion (Hindu/Muslim), country

(Pakistan/India) and region (Northern/southern subcontinent) on autonomy index. This

regression analysis has revealed that only the region i.e. sub continental trait is important

in the determination of women’s autonomy. Religion and nationality are immaterial in

shaping women’s autonomy in the South Asian zone.

Reddy (2002) has examined the process of empowering rural disadvantaged women in

Ranga Reddy district of Andhra Pradesh through self-help efforts, micro-credit, income

generating activities and a range of community infrastructure development activities

undertaken by the NIRD action research project. He has argued that possession of

various power resources, such as, personal assets, wealth, lands, skills, educations,

capabilities, information, knowledge, social status and position held, leadership traits and

maneuverability etc. determine the degree of decision making power; that is called the

empowerment of an individual. Under this research project, SHGs meet the capital

investment need of the women which help them to achieve self-sufficiency. It improves

the decision making power and the leadership power of the members; help in the family

planning attitude; improve the health of the children and mother; protect against the sex

discrimination; prevent atrocities on women etc. Finally, the important component of the

SHG is the micro credit package that is designed by District Rural Development Agency

to benefit the disadvantaged women. The interaction of the women with external

agencies develops the confidence and approachability. It improves the professional and

social skills of the women. Reddy (2002) suggests that participation in SHG, which

enhances their institutional and managerial capacity, is an imperative element in the

empowerment process of the rural women. This research study has also shown that the

women, who have significant control over credit provided to them, influence the degree

of empowerment.

According to Varadarajan, et al. (2002) women empowerment is not a question of

giving or providing some provisions, but it is a question of all women being able to use

54

those provisions without hesitation. Women’s empowerment includes two components,

namely, attitudinal empowerment and material advancement. The key area in the

empowerment of women is the economic area. They suggested that the development of

micro enterprises in general and particularly by the women would be appropriate

approach to fight against poverty at the grassroots level and generate income at the

household level. They have explained that self-employment and entrepreneurship create

economic independence and better social status and sometimes it is necessary for

improving their position not only in their family but also in the society where people

treat them with respect. In fact the best non-controversial way to empower women is the

spirit of entrepreneurship.

Evaluating the first phase impact of Maharashtra Rural Credit Program (MRCP), Bhide

(2003) observes that the SHGs have been able to bring a large section of village

populations, who were deprived of the banking service, under the shelter of banking

service. This study has looked at the various financial and social issues related to SHGs.

In order to evaluate the impact of SHGs, Bhide (2003) has considered a sample of 358

SHG members drawn across 147 SHGs in four districts of Maharashtra. This empirical

study has found that SHGs catalyze the savings rate and increase the ability to absorb

credit to create new assets by rural poor and open opportunities for rural poor. The

investigation reveals that SHG as a social organization conducts a meeting per month. In

these meetings the members of the group discuss several social issues like importance of

education, decision-making power within family and in society, family planning,

involvement of the group in village affairs and gender awareness etc. The meetings and

activities of the members of SHGs help build new leaders and new way of collective

functioning in rural area. The participants of MRCP have reported that the formation of

SHGs through MRCP increases the number of credit resource, slightly increases the

income of the members as well as expenditure on education, health etc. and help poor

people to shift towards self-employment. They have also reported that SHG programme

could not change the power of mobility or household decision-making power of women.

It helps the rural poor women to enhance the confidence level.

Jain, et al. (2003) have statistically analyzed the impact of membership of SHG on

various dimension of women empowerment. To estimate the impact they have used a

primary data collected from Kunpur Dehat district of Uttar Pradesh. They have found

55

that the membership of SHG enhance the quality of status of women as participants,

decision makers and beneficiaries in the democratic, economic, social and cultural

spheres of life. Their statistical result shows that the number of total SHGs members had

increased their level of education than those of non-member of SHGs. The SHGs

members had higher housing facilities than non-members. The number of total SHGs

members had increased their exposure of mass media, extension orientation,

occupational level, size of holding material possession, annual income, membership of

the organization are significantly higher than those of non-members of SHG. This study

confirms the effectiveness of membership of SHG to improve women’s empowerment.

In a micro study conducted in the foothills of Himalayas, Handy, et al. (2004) have

explained the role of NGOs in empowering woman in rural India. They have constructed

an empowerment index including four dimensions of empowerment, namely, personal

autonomy power, family decision making power, economic and domestic consultation

power and political autonomy power. To do this they first measured an index for each

dimension; then aggregating these indices they constructed the empowerment index

which they have called E-index (empowerment index). To document the level of

empowerment among women who participated in NGOs, they have collected data from

the different employee groups. At the leadership group they have interviewed

supervisors of various programmes. At the follower level they have interviewed

fieldworkers who went into the village and worked directly with village women. They

also choose to interview some local woman living in the area that the NGO served.

These women are called recipients. Measuring the E-index for each group they have

found that empowerment levels of different groups are significantly different.

Particularly the E-index of supervisors is higher compared to that of field workers and

recipients. To account for this difference they search the impact of various socio-

economic-demographic factors on the E-index. Because they observed that socio-

economic-demographic status of different group are different. From the literature survey

and their personal observation they have expected that the E-index is a function of age,

family structure, income class, education and tenures at NGO. In order to understand the

combine effects of all conceptualized variables they did not include the recipient group,

as they all had zero years at the NGO. They have found that the years of participation in

the NGO and education level of woman are significant explanatory variables of women’s

empowerment but income class and family structure are not.

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Sridevi (2005) has studied the empowerment of lady teacher of the schools in the city

Chennai, India. She has analyzed the empowerment in two ways, one is qualitative

analysis and other is quantitative analysis. For two parts she has considered ten

determinant of women empowerment. These are family type, age, educational

qualification, household time spend, freedom of mobility, spouse age differences,

educational differences with spouse, number of children, control over personal salary

and supporting the natal home. In both types of analysis these factors are taken as

independent variables. She has derived the empowerment of women in the form of a

qualitative variable. This is obtained from the respondents’ perception about whether

they feel empowered or not. If a respondent feels empowered then the value is 1 and 0

otherwise by this manner the dependent variable was derived in the form of binary

variable. Then applying logit model she has analyzed the significant impact of the above

independent variable on the log odds ratio of women’s empowerment.

In the next part for quantitative analysis, she has constructed empowerment index of

women using a weighted average. To calculate the empowerment index she has used

various proxy variables. These are (a) control over personal salary, (b) maintenance of

family income, (c) supporting the natal home (d) financial decision on own health care

and (e) expenditure on the education of children. In this step she has taken empowerment

index as the dependent variable. Then, by using a multiple regression analysis, she has

found the direction and the magnitude of each factor’s influence on the empowerment of

women. For both type of analysis she has used a personal stratified random sample of

eighty women, postgraduate school teacher, collected from the city of Chennai in India.

From the both types of analysis she has found more or less same result. The study

reveals that age, household time spend on household work, freedom of mobility, spousal

age differences, educational differences with spouse, control over personal salary and

supporting the natal home are significant determinants of women’s empowerment in

both type of analysis. However, educational qualification is significant only in

quantitative analysis.

The study of Vasimalai, et al. (2007) have attempted to focus on the principles and

socio-economic impact of the Kalanjiam model of group based microfinance. This

program is based on the principles of self-help, mutuality and ownership by poor

women. On the basis of a random sample of 300 respondents, of which 240 belong to

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Kalanjiam model, Vasimalai, et al. (2007) has assessed the impact of model on economic

development of the family and on empowering the marginalized group of women. The

study has shown that the family income of the members has increased at an increasing

rate with the age of groups. Comparing the empowerment of women member of

Kalanjiam model and control grouped women the study has established that women’s

empowerment of the Kalanjiam member is greater than that of the non-members. To

make this comparison authors have considered domestic violence, sharing the household

works by the husband, assets owned by the women, decision making ability, personal

skills, women’s share in household income, exposure to outside of the family, interaction

with the community, leadership ability and women’s space in the public sector as

criteria.

Meher (2007) has assessed the impact of SHG based microfinance on income poverty

and empowerment in KBK region of Orissa collecting information from 77 members of

selected five women SHGs. The study reveals that SHG based microfinance is successful

to reduce income poverty. He has considered the variables like importance in family,

awareness regarding education and health care as indicators of the social domain of

women’s empowerment. Economic domain is explained through the indicators like

economic self-sufficiency, consumption of nutritious food, purchase of consumer

durables and awareness regarding the use of utensils. Participations in gram sabha and

political awareness have been taken as indicators of political domain of women’s

empowerment. The positive change of a particular indicator indicates the incremental

improvement of the corresponding domain and women’s empowerment as a whole.

According to Meher (2007) positive change of an indicator up to 40% due to

participation in SHG indicates low impact on empowerment. Above 60% positive

change of the indicator implies high impact and 40-60% positive change implies

moderate impact of the participation in SHG on empowerment. Based on this research

design the study has informed that members of four SHGs have scored moderate impact

and members of remaining one group have scored low impact with respect to social

empowerment. In terms of economic domain of women’s empowerment the members of

all the groups under consideration fall in the low impact category. Sample SHGs have

moderate impact on the political empowerment level of the members. The study has

reported that all the SHGs, except one, have low impact on women’s empowerment

considering the average impact of the three domains. The exception one has shown a

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moderate impact of empowerment. Indeed, the study has shown a gloomy picture of the

performances of SHGs in the process of empowerment generation among the group

members.

Chattarjee (2008) has examined the impacts of SHGs on income, employment and

empowerment status of women in Khejuri block of Purba Midnapur district, West

Bengal. This study has shown that SHGs generate income and employment of women

members at an admirable level. In order to assess the role of SHGs in empowering

women he has considered six elements of empowerment, namely, importance in family,

role in deciding the number of children, decision making power in family matters,

increase in self dependence, securing the respect of husband and in-laws and decrease in

domestic violence. The findings of the study are as follows. As the women earn more

through SHG, the importance of them in family increases compared to unemployed.

Self-employed women have more freedom in deciding the number of children. SHGs

members play a dominant role in taking decision on different matters such as saving and

expenditure in family; education of children; pattern of consumption. Members having

higher income enjoy higher level of self-dependence in family. Economic emancipation

and engagement in broader social system have reduced domestic violence against

women. SHGs have inculcated conscious in women regarding health and education for

their children. Almost all the respondents have completed the immunization package or

been continuing this in due course.

Nayak, et al. (2009) have analyzed the status of women empowerment in India using the

data of NFHS-3 (Government of India, 2005-06). In this study decision making power of

woman in household, freedom of movement, acceptance of unequal gender role, access

to education, access to employment, exposure to media, experience of domestic violence

and political participation have been considered as indicators of women’s empowerment.

This study reveals that the decision-making power of woman in household varies

directly with their age, education, and husband’s education level. Employed women are

likely to have more decision-making power in household than the unemployed women.

In urban area and in nuclear type of family women enjoy more autonomy in household

decision-making. It is found that mobility of widow or divorcee is more than ever

married women. More than half of the sample women believe and accept intra household

unequal gender norm against women. This attitude does not vary significantly with age

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or structure of family but declines sharply with education and for urban region of

residence. The study has shown that participation of girls at all stages of education has

been increasing overtime. Not only women lag behind men in terms of access to

employment, but also a major portion of employed women does not have full control

over their cash earnings. However, control over their cash earnings is positively related

with age and place of residence and education, but not varies significantly with

household structure. In terms of exposed to media women are disempowered relative to

men in India. Extent of domestic violence is lower in urban areas as compared to rural

areas. Experience of domestic violence of ever-married women is higher than that for

never married women. Aged women are more victimized of domestic violence compared

to younger. Women are also less empowered in terms of casting votes and representation

in general elections overtime. Nayak et al. (2009) has also identified several constraints

in achieving desired level of women’s empowerment. These are poverty, social norms

and family structure, lack of awareness about legal and constitutional provision etc.

Samanta (2009) has examined the effectiveness of SGSY-centric microfinance

programme on women’s empowerment in Burdwan district, West Bengal. She has

considered the six indicators of empowerment, namely, mobility, confidence and

capacity building, entitlement, perception of empowerment, decision making, and

autonomy and authority. The study has revealed that the women have improved their

capacity of financial management and can participate in financial decision of the family

after joining SHGs. Although in most cases income of the women are spend for

maintenances of family, husband or other family members, hardly allow them to keep

the money with themselves. In this study, 72% of the women have reported that they

have been empowered after joining SHGs, but almost half of them could not clarify why

they feel empowered. A section of the sample women have felt that they have achieved

the power of bargaining for their own well being. Samanta (2009) has reported that

sample SHG member women enjoy significant authority regarding voting in election and

children’s education and very little independent authority in family planning, family

expenditure, going outside and medical treatment.

In an empirical study conducted in Burdwan district in West Bengal Adhikary, et al.

(2011) have computed the degree of women’s empowerment considering five

dimensions, namely, economic, socio-cultural, familial, political and legal dimensions.

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This study has revealed participation in Self-Help group, education level of the women,

time spent on unpaid household job, type of family, nature of residential region and caste

as important factors affecting the degree of women’s empowerment.

A study of Adhikary, et al. (2011) based on 964 households’ data has shown that

compared to men, women are likely to have less access to formal credit. However, the

participation in SHG ensures the accessibility to formal credit for the rural women and

increases the household expenditure on food and nutrition, on fuel and energy, on health

care and on education for the rural poor households in the district of Bankura, West

Bengal.

Conducting a field survey in Hosakote in Bangalore (Rural) District, Karnataka

Anuradha (2012) has analysed the changes of women’s empowerment after joining self-

help groups. This study has applied PCA to construct empowerment index and observed

socially viable, personality outlook, economically strong, living standard and

accessibility as important component of women’s empowerment. Reorganizations in

community, literacy level, access to credit and health, voicing concern have been taken

under socially viable variable. It is reported that SHG membership facilitate the women

various opportunities to involve in various activities which empower them by enhancing

their role in the society. This study has grouped nutrition awareness, decision making

related to child centred and money centered, participation in development programme

and increase in confidence level under personality outlook. It has found that there has

been a positive transformation in personality outlook after joining SHGs. The author has

named ownership of house and land and improved relation with husband as

economically strong. This study shows that economic position of women has improved

significantly after joining SHGs. The variables, change in personal financial position,

change in share in family income and reorganization in family have been grouped under

the living standard. This study shows that SHGs have improved the living standard of

women. Better interactions with outsider, access to credit and asset building have been

levelled as accessibility. The association among the SHG members and officials of

different offices help the SHG members have connection with outsiders. Participation in

SHG has also ensured access to credit and other financial products.

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2.4.2. Studies on Women’s Empowerment: The Global Scenario

In the new millennium enhancement of women’s empowerment has got importance

across the globe as process of economic development. Many theoretical and empirical

studies have been conducted in different parts of world outside India under the discipline

of Development Economics. In this section we are going to review some selected

studies, conducted outside India.

Malhotra, et al. (1997) have empirically analyzed how education and employment

status of women, other life course and household factors affect women’s empowerment

in Kalutara district of Sri Lanka. They have considered whether the woman has most

control over the money matters and other social and institutional matters in the family as

measure of empowerment. In order to measure the impact of education, employment and

other factors on empowerment the logistic regression analysis has been used. The study

has revealed that years of schooling and current employment status of women have

positive and significant impact on the financial decision making power of women in the

family. But, after a certain level, additional schooling does not contribute to increased

control of financial matters. However, education and employment are immaterial to have

power on social and organizational issues. Past work experience is an important

determinant of the financial decision and of the social/organizational decision-making

power of the currently married women. The study has shown that poor women lay

behind the women from middle-income group families in terms of enjoying the power of

financial and social/organizational control in the family. The empirical study has

reported that the women from Moor families are less likely to have control over financial

and social/organizational decisions than the women from Sinhalese families. It is also

found that the motherhood status of women increases her social and organizational

power but not her financial power. Women of large families and those residing with their

parents are better in position to have input in social and organizational matters. However,

husband’s characteristics don’t have significant effect on woman’s decision-making

power in the family in Sri Lanka.

Amin, et al. (1998) have explored the relationship between poor women’s participation

in NGO based microcredit programme and their empowerment using empirical data from

rural Bangladesh. In order to quantify women’s empowerment this study has constructed

three indices, namely, inter-spouse consultation index, individual autonomy index and

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authority index. It has been found that NGO credit member enjoys higher level of

empowerment than the non-member, irrespective of non-member’s residence in

programme area or non-programme area. The non-member in programme area shows a

higher level of empowerment on the autonomy and authority index than do the non-

member of non-programme area. Education, house type, yearly income, duration of

NGO credit membership and non-agricultural occupation are positively related with

autonomy and authority index. Both the indices vary with age and region. The level of

empowerment for theses indices vary directly with age. The regions having traditional

restrictions on women and less coverage of the NGOs have lower empowerment level of

women. Membership of NGO and residence in an NGO programme area are

significantly and positively related to autonomy and authority index. Income has positive

relation with consultation index. Concrete or corrugated buildings, areas of residence

outside the southern and eastern region, non-agricultural occupation, respondent’s

education and respondent’s age have significant and positive relation with either

autonomy index or authority index. NGO credit membership has strongest effect in

explaining the variation in women’s empowerment. Focus group discussion reflects that

the relation between NGO credit membership and indices of women’s empowerment is

due to increased contribution to the economic survival of their families, due to their

credit related movement outside their home and due to their participation of NGO

consciousness raising activities.

Arends-Kuenning, et al. (2001) have examined the rural Bangladeshi people’s view

about the benefits of education of women. For this purpose they have used data from in-

depth interview conducted in 1996 and 2000 in two villages located in the Rajshahi

district of Bangladesh. From the in-depth interview, the authors have realized that

parents think that daughter’s well-being is best secured through marriage and education

is very much valuable in marriage market because it is an input in children’s education.

From the in-depth interview the authors have observed that education helps women to

produce human capital, to enhance women’s income earning power and to increase

women’s bargaining power and to catch respect within the family. With the spread of

micro-credit, targeting the poor women, people have recognized the importance of

education for managing micro enterprises. All these are different dimensions of women’s

empowerment. Hence from this study it is obvious that education accelerates the

empowerment level of women. Thus, we can conclude that education is a determining

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factor of women’s empowerment. This study does not provide any statistical analysis

and does not directly say anything about the impact of education on empowerment.

Mason, et al. (2003) have viewed women’s empowerment as a part of sociological and

anthropological conception. They have defined domestic empowerment of women as

their freedom from being controlled by other family member and their ability to affect

desired outcome within the household. They have considered four aspects of domestic

empowerment namely economic decision-making power, family size decision-making

power, physical freedom of movement, husband control on them via intimidation and

force. Using a household level data collected from 56 communities in Pakistan, India,

Malaysia, Thailand, Philippines in 1993 and 1994 they have shown that community

differences are significant in measuring women’s empowerment. This study has

established the fact that community and country as opposed to individual and household

characteristics are able to explain more variation in empowerment i.e., a women’s

community can better explain her score in particular empowerment measure than can her

own age, education, age at first union or economic experience.

Ghuman, et al. (2004) have illustrated the nature of gender relations and difficulties in

its measurement using data collected from 23 communities in five Asian countries,

namely, India, Pakistan, Malaysia, Philippines and Thailand. They have asked the same

questions to the married women ages 15-39 years and to their husbands at different times

regarding the women’s autonomy. For measuring women’s autonomy they have focused

on the Freedom of Movement, Decision-Making regarding Children, Household Tasks

and Decisions as domains of women’s autonomy. Applying an item response model the

study reveals that wives and husbands have significantly different assessment on

women’s autonomy in various domains. They are also different in terms of cognitive

understanding of the responses regarding the focused domains. The nature of these

differences also varies across the contexts and across the communities. The study has

found that husbands in South Asian communities ascribe higher autonomy of their wives

than wives do for themselves. Finally, Ghuman, et al. (2004) have estimated a logit

model in order to measure the impact of differing perspectives of wives and husbands

regarding the women’s autonomy on the experience of infant mortality. It has been

found that women’s autonomy has negative impact on the child mortality if the woman

reports on her own decision making power on what to do when the child falls sick. On

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the other hand, if the husband reports that his wife takes decision regarding the matter; it

has positive impact on child mortality in the sample countries except Pakistan. However,

Ghuman, et al. (2004) have opined that these survey questions are of limited utility for

understanding differences in gender stratification across different contexts.

Conducting an empirical study in rural Vietnam Santilan, et al. (2004) have assessed

nature of women’s empowerment in the socio-economic sphere as well as in

reproductive health. For this study they have interviewed 57 married women between the

age of 22 and 52 years and 13 of the women’s husband. They have conducted a

qualitative analysis of the case study material assembled from the in-depth interviews.

This study has developed two sets of domains along with their indicators for women’s

empowerment. One set is related to socio-economic sphere and other is related to

reproductive health. The domain of socio-economic empowerment includes production,

housework, family expenditure, relation with natal relatives, community participation

and right of husband and wife in the family. The reproductive health domain includes

decision making about childbearing, contraception, sexual communication and

negotiation, pregnancy, appraisal of health services reproduction tract infection,

reproductive health role and right. Each indicator has been attached a score ‘one’ for the

responses that has little or no evidence for empowerment, ‘two’ for moderate evidence

and ‘three’ for considerably empowered respectively. Each woman receives a score for

each indicator and an overall score for each domain. They have pointed out the

methodological challenges that they faced in analyzing women’s empowerment. They

have faced challenges in conceptualization of empowerment. They have had conscious

regarding the overlapping concepts. To avoid the ‘politically correct’ response they have

made a cross-checking of the response from community leaders. In order to collect the

responses in a better way and for collecting the appropriate answer of the sensitive issues

they have deployed systematic analytical framework to open ended data and competent

surveyors. Based on the field survey, they have reported that the women exert a

significant degree of control in daily decision making about productive activities.

Regarding the family expenditures usually women take decision jointly with their

husbands, but in case of disagreement husband enjoys more power. A major portion of

the sample women participates in community occasions. Many respondents agree with

the one or two child policy. However this study is too small to draw definite conclusion

65

regarding the nature of women’s empowerment in Vietnam. But it provides an

invaluable application in further study of women’s empowerment.

Parveen, et al. (2004) have measured and estimated the empowerment of the women

resided at three villages of Mymensingh district of Bangladesh. They have constructed

cumulative empowerment index taking six empowerment indicators, namely,

contribution to household income, ownership of assets, access to resources, participation

in household decision-making, perception on gender awareness, coping capacity to

household shocks. They have considered seven influential factors - two at individual

level, two at household level and three at social level as determinants of women’s

empowerment. These are formal education, non-formal education, sexes of children,

spousal relationship, media exposure, spatial mobility and traditional socio-cultural

norms. The regression analysis has revealed that formal and non-formal education, sexes

of children, spousal relationship, exposure to media and spatial mobility have positive

and highly significant effects on cumulative empowerment index. On the other hand,

traditional socio-cultural norms have a significant and negative impact on cumulative

empowerment index.

Parvin, et al. (2004) have examined the performance of income generating activities

supported by Rural Women Employment Creation Project (RWECP) on empowerment

of poor women in Dumuria Thana of Khulna district in Bangladesh. The study is based

on a set of primary data collected from a random sample of eighty women who are

members of RWECP. In the study they have considered three indicators of women’s

empowerment, namely, participation in household decision-making, control over income

and access to assets. In order to analyze the impact of income generating activities under

RWECP on women’s empowerment the study has used descriptive statistics and

Weighted Mean Index (WMI) method. The study reveals that engagement of women in

income generating activities under RWECP has enhanced their capability to express their

opinion and make decision to meet personal needs, to contribute to buy households

assets, availing treatment and recreational facilities independently. However, in most of

the cases income of women are controlled by their husbands. Findings show that widows

and abandoned women are in better position to control their earnings than the women

living with husbands. Low level of control over income does not allow them to have

significant access to assets of their own. The constructed WMI of empowerment has

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shown that the level of empowerment is noticeably high for the women engaging in cattle

rearing and low for the women engaging leather goods making. The study has concluded

that marital status and religion are influential factors of women empowerment in rural

Bangladesh.

Williams (2005) has defined women’s empowerment as relative level of adherence to

current and context specific gendered norms. He has identified six dimensions of

women’s empowerment, namely, sense of self and vision of the future, mobility and

visibility, economic security, decision-making power in the households, participation in

non-family group, interact effectively in public sphere. This study has formulated a

conceptual model of women’s empowerment. In this model he has shown that economic

and gender components of empowerment influence each other and both have interactive

effect on exercise of power that effect health, fertility, mortality etc. He has further

shown that economic resources available to women have independent influences on

these demographic achievements. He has used confirmatory factor analysis to test the

hypothesis, women’s empowerment is multi-dimensional and whether the indicators

chosen conform to theoretical model. Calculating the goodness of fit index, Tucker-

Liews index, Comparative fit index he has found that six dimensions model fits

significantly better than one dimension model. He has estimated correlation and variance

between two components of latent dimensions. Some of these correlations are

statistically significant. Thus he has shown that empowerment is multidimensional in

nature and theses dimensions are interrelated.

Moser, et al. (2005) have explored the success and limitations of gender-mainstreaming

policies of international development institution. The common policies include six

components- a dual strategy of mainstreaming gender combined with targeted actions

gender equality, gender analysis, a combined access to responsibility, gender training,

support to women’s decision-making and empowerment, monitoring and evaluation.

Besides, work with other organization, budget, and knowledge resources have been

considered by some of the organizations. However, they have observed that the

implementations of the gender mainstreaming policies are inconsistent and involving in

few activities, rather than coherent and integrated process. The implementation of

policies consists of institutional and operational inputs, which are closely interrelated.

The most of gender mainstreaming evaluations focus on institutional inputs rather than

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the process of operational and programming implementation. They have identified a

range of constraints regarding implementation. First, the lack of responsibility,

commitments and skill of gender specialist are primary constraint regarding program

implementation. Second one is the male leadership which discriminates female staffing

in term of attitudes, recruitment, working conditions, structure and procedures.

Sometimes it excludes women by scarcity of high level of job shares, extensive travel

requirements and long work hours that are difficult to do for women with dependent

children. Third constraint is the voluntary accountability. Gender training is another

constraint in implementing gender policies. Constraints may also come from operational

aspects of gender mainstreaming. The common operational constraints are the lack of

effective, consistent and systematic monitoring and mainstreaming outcomes and

impacts. Terms of women’s participation in economic activity have been identified as

another operational constraint.

Conducting an empirical study in Sylhet district of Bangladesh Hossain, et al. (2006)

have argued that change approach is most suitable for empowerment of women in

Bangladesh. The ‘change approach’ includes integrated development, economic

empowerment and consciousness raising approach and the changing of the attitude of

male towards female. In this study empowerment means women’s authority to make

choices and decision that facilitates the development of knowledge and control over

resources to exercise the right. This study explores that women in Bangladesh have to

rely on their male guardian’s opinion in taking decision. In this study 79% of women

reports that they are not usually congratulate any income generating activities in case of

husband disagreement. Though nearly 62% women of this study have self-income but

more than 65% says that their participation in decision-making remains unchanged in

spite of increasing their income. To increase the consciousness of the women,

development workers have taken several awareness campaigning. However, 52% can’t

go outside their home conniving at their husband opinion. Their participation would be

ensured at the meeting if their husband allows them for it. Most of the sample women

have identified the male dominance attitude as a major hindrance to empower women.

They have expressed their opinion in support of changing the attitude of male. About

two-third of the sample women think that ‘change approach’ which covers all the

changes in the society related to women’s empowerment, i.e., changes in values and

attitudes, income, employment, education, access to property and resources, participation

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in taking decision in the family, is most important and most effective for women’s

empowerment.

Bhuiyan, et al. (2007) have defined empowerment as a mechanism of awareness and

capacity building leading to greater participation in decision-making and greater access

to and control over physical resources as well as power structure. This study says that

empowerment includes women’s participation in work place. The authors narrate that the

entrepreneur development focuses on women’s empowerment in general and their

participation in income generating activities in particular. Women’s entrepreneur help

women increase the courage to talk with people associated with business and trade. They

say that entrepreneur increases women’s participation in decision making in family and

social matter; removes social seculation and religious sanction against women. It

decreases social discrimination against women and increases the income of the women.

The authors have argued that women’s entrepreneur changes the social-psychophysical

quality of individual women, which is most effective for empowerment. Working as an

entrepreneur improves the woman’s social and economic status. Trade and generation of

income increase the self-confidence of women. Finally we can conclude from the study

that working as entrepreneur increases the empowerment of women. But, working as

entrepreneur is not the only determinants of women’s empowerment, there are many

other determinants of women’s empowerment. This study remains silent about the other

determinants of women’s empowerment.

Mostafa, et al. (2008) have tried to measure the women’s empowerment index (WEI)

score for Bangladeshi women using Bangladesh demographic and health survey

(BDHS), 2004, data. They measured WEI in domestic sphere using three dimensions-

women’s economic decision-making power, household decision-making power, and

physical freedom of movement. Each dimension has some relevant indicators and on the

basis of this indictors score was given to each dimension. They have concluded that

though the level of women’s empowerment is not satisfactory for any age group, older

women have more independence and empowerment than younger.

Chowdhury, et al. (2009) have explored the key determinants of women’s

empowerment in a remote area of Pakistan. In order to carry out this study the authors

collected the primary data from southern Punjab from 200 respondents using stratified

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random sampling techniques. All the respondents are female of age group 14-65 years.

For measuring women’s empowerment they constructed cumulative women’s

empowerment index (CWEI). CWEI is a composite index of four separate indices,

namely, personal autonomy index, family decision-making index, economic domestic

consultation index and political autonomy index. They have considered independent

variables like education of women, years of women’s schooling, doing any paid work,

having bank account, access to media, opportunities for outing, per capita income of the

households, participation rate dependency ratio, education index of households, age of

women, marital status of women, asset ownership by respondent, knowledge of Islamic

women’s empowerment, joint family structure, living in community, not believing on

typical out-dated socio-cultural norms, number of household member, fear of violence

from father/husband and distance of health unit from respondent’s home. For analyzing

data, they used descriptive analysis and ordinary least square. They have considered four

regressions analysis- one for total sample, one for urban area, one for rural area and one

for tribal area. The regression analysis based on total sample shows that woman doing

paid work, having bank account, access to media, opportunities for outing, age of

women, married women and knowledge of Islamic view point of women’s

empowerment have significant and positive impact on women’s empowerment. Women

doing paid work, participation rates and age of the woman have positive impact on

women empowerment in rural area. Married women and doing paid work have

significant positive impact on empowerment of the women belonging in tribal

community.

Ashraf, et al. (2010) have explored the impact of a commitment savings product on

female empowerment in Philippines. They have considered the special savings product,

called SEED (Save, Earn and Enjoy Deposits) account with the Green bank of Caraga, a

small rural bank in Mindanaano, Philippines. It is a term deposit and individual savings

account. Female empowerment has been quantified in this study by constructing two

decision making indices from nine decision making situations. The nine situations refer

to decisions on what to buy at the market, expensive purchases, giving assistance to

family members, family purchases, recreational use of the money, personal use of the

money, number of children, schooling of children and use of family planning. For each

decision it assigned value two if the respondent exclusively takes the decision, zero if the

spouse takes the decision and one if both take it. The first empowerment index is

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constructed taking equally weighted mean of each response of the nine decisions. The

second index is the linear combination, determine through a factor analysis, of the

individual responses to each questions. For empirical analysis they have randomly

chosen 3125 adult clients of the Green Bank. They have also made a randomization to

divide the total sample in to three groups. The first one is the commitment treatment

group, who were counselled regarding the importance of savings and offered SEED

product, second one is the marketing treatment group who were counselled but not

offered SEED product and the third is control group who were neither counselled nor

offered SEED product. This study reveals that assignment to the treatment group

strongly increases the both decision making indices for married women but not for

married men. Not only that, the average effect is largely driven by increases in decision

making ability for women who were below the baseline median. The marketing has a

smaller effect on changes in decision making indices. This study has also examined the

effect of the SEED product on household expenditure pattern on durables and savings

attitudes. It is found that SEED product increases the purchase of consumer’s durables

associated with female use. Ashraf et al. (2009) has argued that it is happened due to

empowerment effect of the SEED product. Indeed, the opening of SEED account has

improved the savings practices of the treatment assigned bank clients.

Varghese (2011) has conducted an empirical study on women’s empowerment in Sohar

region, Sultanate of Oman. This empirical study is based on a set of primary data

collected from 150 women. This study has measured the women’s empowerment by

identifying the household decision making ability, assessing economic decision making

capability and evaluating the freedom of mobility of the women. According to the author

there are the three dimensions of women’s empowerment, namely, economic,

households and social. For each dimension, an index of women’s empowerment has

been computed following the methodology of UNDP used in the calculation Human

Development Index. Finally by taking the simple average of these dimensional indices

the author computed the Women Empowerment Index (WEI). The computed

dimensional index has shown that women of Oman are forward in terms of household

and economic empowerment but they are backward in position in terms of social

empowerment. In order to quest the responsible factors affecting women’s empowerment

this study has considered five socio-economic statuses of women. These are income,

education, employment, acquisition of assets and media exposure. For statistical analysis

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she has applied ANOVA and regression technique. This study has found that income,

education, employment, acquisition of assets have positive and significant impact on

women’s empowerment whereas the media exposure is insignificant in the determination

of women’s empowerment. Finally, this study has taken women’s perception on their

empowerment. For this purpose, this study has considered three issues (the right to

protection against harms, the right to set up association and the right to get own land)

relating to legal rights and one issue (the right to involve in country’s politics) relating to

political right. The primary survey of this study reveals that majority of the sample

women are aware about the right to protection against harms. Only 29 percent of the

sample women have strongly reported that they have the right to set up association.

Nearly 20 per cent are disagree or neutral regarding their right to get own land. However,

almost half of the sample women have opined that they do not have right to involve in

country’s politics. So far, this study has considered only the women’s perception

regarding their empowerment. For perception analysis one should consider the

perception of the person concerned as well as other persons within the family.

Zaman, et al. (2012) find out the level of empowerment of women in household

decision making process in some purposively selected rural and urban areas of

Bangladesh. It has considered 18 variables in household domain, namely, freedom of

purchase saris, freedom of purchasing cosmetics, opinion for children’s admission in

school, opinion seeks for child birth, opinion for family planning, freedom of purchase

children’s clothing, treatment autonomy for children, treatment autonomy for own,

freedom for expenditure, knowledge about inheritance law, freedom of expenditure for

own, freedom of saving money, freedom of purchasing ornaments, free to move outside,

opinion for land dispute, freedom to travel, freedom to purchase of properties for own,

whether microcredit holder. Using these variables, a composite level of women’s

empowerment was assessed by Principle Component Analysis. After getting the score

they categorized empowerment as poor with score 1-82, fair with score 83-122 and good

with score above 123. The authors showed that 40% had poor, 19% had fair and 41%

had good level of women’s empowerment. Using bivariate analysis this study has

revealed that level of women’s empowerment is high among the respondents living in

the urban areas, having less number of children, religion in Islam, having higher level of

education of both husband and wife, engaged in jobs, having higher monthly income

contributed to family and living in pacca house (p<0.05). It also shows that there are no

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significant association with current age of both husband and wife, age at marriage and

spousal age difference (p>0.05). This study does not clarify how the scores were given to

assess empowerment and it considers only individual factors at household level.

Reviewing the studies related to women’s empowerment we can easily select the major

dimensions and their indicators of the women’s empowerment those help us quantify the

women’s empowerment. We are also enlightened with the several socio economic and

demographic outcomes of women’s empowerment. Besides, the detailed review of

literature helps us recognise the important determinants of women’s empowerment in the

district of Bankura, West Bengal.

2.5 Conclusion

The literature review in this chapter has covered the wide range of vantage points for

investigating women‘s empowerment like, autonomy (Dyson & Moore 1983; Kabeer,

2001; Jeejebhoy & Sathar 2001), agency and status (Jain et al. 2003, Kumar, 2011),

women‘s land rights (Quisumbing et al., 1999), process of gaining control over self and

resources (Verma, 2009, Samanta, 2009), domestic economic power (Handy, et al.

2004), bargaining power (Beegle et al., 1998; Quisumbing & de la Briere 2000), power

(Agarwal, 1997; Beegle et al., 1998), patriarchy (Malhotra et al., 1997), gender equality

(World Bank, 2001 & 2012). Often there is not any clear demarcation in the meanings of

these terms for women’s empowerment. A few studies have attempted to develop the

index for women’s empowerment. Many studies examined the impact of different socio-

economic-demographic factors on women’s empowerment. A wing of studies has tried

to examine the impact of empowerment on several dimensions of family and child

welfare. In this dissertation applying a sophisticated econometric tool we develop the

index for women’s empowerment at the individual level as well as community level.

Then we examine the impact of empowerment on three important aspects of family and

child welfare and explore the important determinants of women’s empowerment in

Bankura district. This type of thorough study on women’s empowerment is still

uncommon in existing literature. In the coming chapter we come to the details of models,

methodology and data source of our study.

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Chapter Three __________________________________________________

Model, METHODOLOGY AND DATA

3.1. Introduction

In the second chapter we have reviewed the literature on the studies related to women’s

empowerment. In the course of the literature review, we have seen that many studies

deal only with the concept of women’s empowerment. Majority of the theoretical studies

suggest that women’s empowerment is multidimensional and context specific. A number

of studies have tried to quantify the qualitative idea, empowerment, particularly

women’s empowerment. Some of the empirical studies have tried to find out the

important determinants of women’s empowerment. The impacts of women’s

empowerment on human well-being have been assessed in a few studies. Different

studies have taken different indicators or measure of women’s empowerment in

accordance with their context and objectives. They have applied different methodologies

for estimating the impact of women’s empowerment on household and child welfare. In

order to capture the concrete idea of women’s empowerment in Bankura District of West

Bengal we specify the suitable econometric models and methodologies in this chapter.

We have planned to divide our study in three parts. In the first part of this study we want

to measure the level of empowerment for the rural women in the district of Bankura.

Second, we are interested to find out impact of empowerment on the household welfare

as well as on human wellbeing. In this part we have planned to emphasize on the three

issues of household welfare, viz. issue of family planning, issue of domestic violence

and issue of child education. In the third part of our dissertation the various influential

factors of women’s empowerment in the district of Bankura are dealt with. In order to

carry out our study with the issues mentioned above we need to find out a suitable

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approach to quantify empowerment and relevant methodology for estimating the

different models related to the issues of our study. With this end in view, we have

arranged the current chapter in the following manner.

In section 3.2 we have developed two systematic approaches for quantifying women’s

empowerment along with its different dimensions. Sub-section 3.2.1 deals with the

selected dimensions and corresponding indicators of women’s empowerment at the

individual/household level as well as at the community level. We explain the details for

measuring the degree of empowerment in sub-section 3.2.2. In sub-section 3.2.3 we have

explained the framework for developing a composite index for women’s empowerment.

This section will help us show the empowerment status of women in the district of

Bankura. Section 3.3 deals with the research design for studying the impact of women’s

empowerment on household welfare. This section has been decomposed into three sub-

sections. In sub-section 3.3.1 we have explained the methodology for studying the

impact of women’s empowerment on family planning. We have addressed the issue of

domestic violence which is expected to be connected with empowerment. Analytical

framework for studying the nature of domestic violence against women in the district of

Bankura has been presented in sub-section 3.3.2. Sub-section 3.3.3 has presented the

analytical framework for the study of empowerment on child education. The analytical

framework for finding out different influential factors of women’s empowerment has

been explained in section 3.4. Regression specifications for each of the selected issues of

women’s empowerment have been presented in section 3.5 along with its subsections.

The definitions and measurements of the dependent and independent variables of the

specified models specified have been explained in Section 3.6. In section 3.7 we have

logically developed the hypotheses relating to the specific econometric models. The

methodology of data collection and the diagnostic check for the sample size have been

discussed in Section 3.8 and in its different sub-sections. Finally, we have come to the

conclusion of this chapter in section 3.9. Now we are going to present the detailed

analytical frameworks one by one.

3.2. Measures of Women’s Empowerment

In this section we want to quantify the idea of women’s empowerment. We have already

discussed that women’s empowerment is a buzzword now-a-days in developmental

policies. It is qualitative and multidimensional in nature. However, there is not any

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universally accepted definition of women’s empowerment in the existing literature; its

definition is very much context specific. One may consider women’s empowerment in

the individual/household context or in the community/locality context or in the

national/international context. Consequently different studies have tried to measure it in

different ways depending on different contexts. Our study area, the district of Bankura, is

mainly a rural as well as poor district in the state of West Bengal. In this district the

major development indices of women are standing below the expected level. Due to the

geographical as well as social backwardness it is not surprising that women of this

district have very little power and voice in the broader area of life. In other words, the

empowerment of women in the national or international level in the area under study is

almost zero and invariant in the broader area of life. However, owing to the different

local and social customs of different communities, women of different regions and

religions and communities have enjoyed different levels of empowerment at the

household level as well as at the community level. Against this situation if one attempts

to focus empowerment from a single window, it will give the wrong impression about

the actual empowerment of a particular woman. In order to address the possibility of this

wrong impression in the measure of empowerment we have sketched to study

empowerment at the household level and at the community level separately. Therefore,

we would like to measure empowerment of women in two levels.

Women’s Empowerment at the Household Level

Women’s Empowerment at the Community Level

In the course of literature review we have found two wings of studies of quantifying

women’s empowerment. One wing has considered the value of a specific indicator or

simple average of the values of the selected indicators/dimensions of empowerment

(Ghuman, et al. 2004, Srivedi, 2005, Adhikary and Dutta, 2011, Varghese, 2011). Other

wing has tried to cover a wide range of the indicators and considered the weighted

average of the values of the indicators of empowerment as a measure (Kishor, 1997,

Jejeebhoy, 2000, Koenig, et al. 2003, Handy et al. 2004, Parveen et al. 2004, Chowdhury

et al. 2009). However, no one of the studies takes into account both the types

simultaneously and compares the pros and cons of these two types of measures. With

this end in view, we have planned to measure women’s empowerment at household as

well as at community levels by two different ways – simple average method and

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weighted average method. In this study Principal Component Analysis has been used to

derive the weights of the indicators of women’s empowerment. Before going to the

detailed specification of the methodology for measuring women’s empowerment we

discuss the dimensions and selected indicators of women’s empowerment at the

household level and at the community level.

3.2.1. Selected Dimensions and Indicators of Women’s Empowerment

We have found several dimensions and indicators of women’s empowerment in the

existing literature. A section of existing literature only proposed the dimensions and

indicators for measuring empowerment. Different studies reviewed in chapter two have

tried to measure empowerment empirically considering different dimensions and

indictors which are fitted in their context. In an exhaustive analytical study, Molhotra et

al. (2002) has proposed several indicators for measuring empowerment at household

level, at community level and at broader arenas. She has also proposed six dimensions of

women’s empowerment for each level. These are economic, socio-cultural,

familial/interpersonal, legal, political, and psychological. However, she did not quantify

women’s empowerment in practice. Actually these dimensions are extremely broad in

scope and not very much easy to capture at a time. In our dissertation we have planned to

quantify women’s empowerment at the household level as well as at the community

level. We have tried to follow the dimensions as proposed by Molhotra, et al. (2002). In

order to cover the dimensions we have selected some relevant criteria as indicators in the

context of our study. The selected indicators for respective dimensions are as follows.

3.2.1A. Dimensions and Indicators of Women’s Empowerment at Individual or

Household level

Indicators of Economic Dimension

Whether she has control over her personal income or asset.

Whether she can have access to household resources.

Proportion of household expenditure that she bears. (>50% | < 50% | None)

Who decide the use of saving/ loan? (Own / with spouse/ with other family

member/other members)

Does she take part in the decision for selling or buying asset for household?

Does she enjoy freedom in choosing her occupation? (Yes/No)

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Indicators of Political Dimension

Did she cast her vote in the last election?

Does other influence her to cast her vote?

Does she know the name of local leader? (panchayat pradhan / councilor/ MP/

MLA)

Whether she know the candidate of opposition party in the last election.

Does she get domestic support for her political engagement?

Indicators of Socio-Cultural Dimension

Whether she is free to move outside her home.

Does she regularly enjoy Radio, telephone, TV and Newspaper?

Whether or not she participates in local cultural programs.

Does she want to educate her girl or other girls in her household?

Does she arrange the marriage of the girls before their eighteen years old or

support it?

Whether she want to send her child for earning.

Indicators of Personal / Familial Dimension

Whether her marriage is arranged or self selection.

Can she articulate her personal problem to other family members?

Whether or not she can independently decide about her child education, health,

food etc.

Whether she has decision making power regarding her personal health, body.

Whether anybody interfere when she talks to strangers.

Indicators of Legal Dimension

Whether she knows the mechanisms of justice used in the locality.

Does she think women/men get (better, equal or worse) treatment from this

system?

Whether she knows the laws and legislation available in favour of women.

Whether she knows about the various kinds of public services available in the

locality.

Whether her marriage is registered or not.

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3.2.1B.Dimensions and Indicators of Women’s Empowerment at Community level

Indicators of Economic Dimension

Whether she is employed/earner or not.

Whether she has ownership of land or property or not.

Whether she has access to formal savings, insurance or loan etc.

Whether she has access education or training service when she needs it.

Whether anybody threats her to evict from property.

Whether her present occupation is secured or not.

Indicators of Political Dimension

How much does she involve in political process? (Very involved / slightly

involved / not at all)

Whether she attends any political gathering or not.

Whether she is a member of any political party.

Did she ever contest vote as a representative?

Is she leader of any organization?

Indicators of Socio-Cultural Dimension

Does she participate in community activity?

Whether she is a member of any social organization or group.

Whether she can influence the election/ selection of the leader of organization or

group.

Whether or not she knows the location of the nearest post-office, school, hospital,

club, vegetable market, other social/ cultural organization.

Does she feel exclusion from participation in any community activity organized

by local government, religious organization, school, the local development

association etc.?

Does she oppose the social curses like a) Dowry system, b) Inter-caste marriage,

c) preference of male child?

Indicators of Personal / Familial Dimension

Did she ever campaign against social curse like dowry, violence?

Whether she has professional training or not.

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Has she voluntarily changed her occupation after marriage?

Did she sacrifice employment or membership of any organization due to familial

ground?

Whether she has immunised her children in due time.

Indicators of Legal Dimension

Whether she ever used the mechanism to seek redress or access justices.

Whether she complains about the deficiency of public services in her locality.

Is she active in complaining about any problem to the system of justice? (Very

active, a little bit active, fairly active, and not active at all)

Does she think that authorities are more, less or equal effective about other

people’s need/concern compared to her? - (More equal, less).

3.2.2. Degree of Women’s Empowerment

Let us now quantify women’s empowerment based on the above indicators. We intend to

measure empowerment index by two methods. First, we would like to compute the

degree of women’s empowerment for each woman at household level and at community

level using simple average method. Therefore, the simple indices adopted in the study

for measuring the empowerment of women at the household level and at the community

level are given as follows.

100level household at the criteria selected ofnumber total

womanby the fulfilled level household at the criteria selected ofnumber DOWEH

100level community at the criteria selected ofnumber total

womanby the fulfilled levelcommunity at the criteria selected ofnumber DOWEC

where, iDOWEH and iDOWEC are the degree of women’s empowerment at the

household level and at the community level for ith woman.

Using this formula we can easily measure the empowerment of women at the household

level and at the community level, which are now quantitative in nature. In accordance

with the specification of the quantification of the degree of empowerment we can say

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that the values of women’s empowerment vary from zero to hundred. The higher the

value of empowerment index the higher is the empowerment of women i.e. the higher is

the status of women in household and in society.

3.2.3. Analytical Framework for Computing Composite Index of Women’s

Empowerment

In order to study the empowerment level of the women at the household level and at the

community level we have considered a large number of indicators which are usually

correlated because they are measuring the same issue. So to make the analysis concrete

we need to reduce the large number of indicators to lesser number of factors that are

being measured by the indicators. Besides, we have put same weight for each

dimension/indicator in our first measure; but in reality different dimension/indicator

should have different weight in contributing to women’s empowerment. The weights of

the indicators may be derived in a number of ways. Factor analysis is the common

statistical tool for the derivation of relative weights and is applied to deduce a set of

latent factors that account for the patterns of collinearity among multiple metric

variables. In literature we have found a variety of methods that extract factors from an

inter-correlation matrix of the variables. Principal Component Analysis (PCA) is

probably the most common method used in the extraction of factors. In order to study

and understand the level of empowerment extracting a small number of

orthogonal/uncorrelated variables called Principal Components from the set of indicators

under consideration and to derive relative weights of the selected indicators we would

like to use the technique of Principal Component Analysis. Each Principal Component is

a linear combination of all the variables/indicators under studied having unit variance.

In PCA, the linear model accounts for large proportion of the variation of the data set. If

the PCA becomes unrotated, the eigenvectors may not align close to the data clusters and

thus may not represent the actual physical states as well. The rotated PCA methods rotate

the PC eigenvectors so that they become closer to the cluster of data point. There are

several strategies for rotation in the literature of Econometrics. Orthogonal rotation

strategy is applied if no relationship is found between the principal components. In order

to determine whether the extracted components are related or not, a simple correlation

has been applied on the component scores. If the results show no correlation one can

apply orthogonal rotation strategy on the indicators. In the present study Varimax

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rotation strategy, which is the most popular form of orthogonal rotation schemes, has

been applied. Varimax rotation maximizes the variance of the rotated squared PCs. It

means that the squared loadings are made as large as possible or as close to zero as

possible means that many of the loadings are essentially set to zero, yielding loading

patterns which have more localized features than the unrotated patterns. In view of the

above, PCA has been re-run/rotated (Varimax) specifying the fixed number of

components (whose Eigen value is greater than one) to be retained. The respective

rotated component scores have been obtained by regression method. In order to develop

a composite index of women’s empowerment we derive the component scores also

(Antony et al. 2007). The weighted sum of the component scores may be considered as

the composite index of women’s empowerment.

Finally, in order to arrive at the composite index of women’s empowerment (CIWE), the

rotated component scores and the corresponding per cent of variances (rotation sums of

squared loadings) accounted by the principal components are used. Principal

Components are extracted in decreasing order of their variances. This indicates that

variances explained different principal component are different, thus the weight of

different principal components are different. To address this, we have constructed the

CIWE as the weighted sum of the component scores – the weights being percentage of

variations explained by the respective Principal Components after rotation. Thus, CIWE

is to be calculated taking the sum of product of Component score ( ikC ) and

corresponding percent of variance kV explained by the principal component (Antony et

al, 2007)

ikki CVCIWE (3.2.1)

where, iCIWE stands for the composite index of empowerment for ith woman, kV

denotes the percentage of variation explained by kth principal component after rotation

and ikC is the component score of ith woman with respect to kth

principal component

after rotation.

Applying PCA tool for the indicators of women’s empowerment at the household level

we derive this formula and compute the CIWEH for the sample women at the household

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level. Similarly for the indicators of women’s empowerment at the community level we

compute the CIWEC for the sample women at the community level. It should be noted

that the values of these indices vary from to and follows standard normal

distribution. So it has some good properties for inference analysis.

3.3. Research Design for Studying the Impact of Women’s empowerment on

Household Welfare

In the new millennium women’s empowerment has been recognized as an instrument for

improving household welfare. A large section of the literature regarding women’s

empowerment has put their attention on quantification and on measurement of women’s

empowerment from several view points. A group of studies has tried to identify the

responsible factors for empowering women. A very few studied have examined the

impact of women’s empowerment on several dimension of household welfare. Again

among these studies a section has theoretically analyzed the expected gain of women’s

empowerment on household welfare. Systematic empirical estimation of the impact of

women’s empowerment on household welfare is very much limited. Against this

situation, we are interested to estimate the impact of women’s empowerment on three

specific issues of household welfare. These three issues are the family planning,

domestic violence and child education expenditure. In the subsequent sub-sections we

deal with the research design for studying the impact of women’s empowerment along

with some other selected variables on decision towards family planning, on incidence of

domestic violence and on child education expenditure in the context to our sample

women in Bankura district.

3.3.1. Analytical Framework for Studying Impact of Women’s Empowerment on

Family Planning Decision

We like to study how the decision regarding family planning is affected by women’s

empowerment. In order to estimate the impact of women’s empowerment along with

other explanatory variables on the family planning decision we formulate probit model.

The decision regarding family planning is the dependent variable in this particular case.

The decision towards family planning is specified by the information whether or not the

woman is an ideal family planner. If the woman has only one or two children and there is

no possibility of further child adaptation, or if the woman has strong decision that she

will not have more than two children, the woman is identified as an ideal family planner.

83

The couples who have more than two children or have not taken any decision about

family planning are considered as non-family planner. In this view, each woman has

only two possible responses, ‘yes’ and ‘no’ regarding family planning decision.

Therefore, the variable, decision regarding family planning can take only two values for

two responses. We attach value ‘1’ for the woman who has taken family planning

decision and ‘0’ otherwise. The decision regarding family planning ( iY ), which is the

dependent variable, is a dichotomous variable taking values ‘1’ and ‘0’.

The family planning decision definitely depends on some socio-economic and

demographic traits of the woman and her household and on some community traits. It is

expected that empowerment of the particular women have a crucial role for taking family

planning decision. This means that women’s empowerment along with several socio-

economic and demographic traits of the woman/household determine the decision

towards family planning. Let iP stands for the conditional probability of taking decision

regarding family planning. In the present framework, in terms of a typical binary

response model we like to assess iP conditional on certain information set, , which

consists of socio-economic and demographic traits of individual/household along with

women’s empowerment at the household level and at the community level. These traits

are apparently exogenous and predetermined variables that have been considered as

determinants of the conditional probability of taking family planning. Already we have

expressed iY , as dichotomous variable and iP is the probability that 1iY Therefore, by

definition of mathematical expectation we can say iii XYEP , where iX stands

for socio-economic and demographic traits of the thi individual/household along with

women’s empowerment belonging to the information set, . Hence, the decision

regarding family planning for the sample women is a function of the information set, .

Factors affecting the Decision towards Family Planning

We have classified the socio-economic and demographic traits affecting the decision

regarding family planning into two categories, namely, the individual and household

characteristics and the community characteristics of the woman. Examination of the

impact of women’s empowerment at the household level and at the community level on

the family planning decision is one of our prime objectives. So, women’s empowerment

84

at the household level is the main explanatory variable under the individual/household

characteristics. In addition to women’s empowerment at the household level, we

consider some other variables as determinants of the decision regarding family planning.

In the category of individual and household characteristics we have incorporated male

child bias, education level, age at marriage, spousal age gap, spousal education, family

composition, household’s land holding, household occupation, per capita family income,

dependency ratio. We expect that women’s empowerment at the household level should

have a positive impact on the decision regarding family planning for the sample women.

In order to check the empirical validity of the claim we include women’s empowerment

at the household level and at the community level as chief exogenous variables in the

model for the decision regarding family planning. In the rural society we see that

education level of the woman as well as other family members affect the outlook to

family planning. Age at the time of marriage of the woman is crucial for taking any

fruitful decision regarding family planning. Dependency ratio is another determinant of

the family planning decision. Besides, we cannot ignore the variables like household’s

landholding, per capita family income and occupational status of the family as important

determinants of the decision regarding family planning.

There are several community characteristics like caste, race, religion, region, social

customs that affect the family planning decision of the couples. But in our dissertation

we have planned to study the attitudes of rural couples regarding family planning in the

district of Bankura. In the area under study the variation of region, race, religion, social

custom are very much limited. With this end in view, women’ empowerment at the

community level, participation in SHG-centric microfinance program and caste, three

community characteristics, have been considered as important exogenous variables

affecting the decision regarding family planning in this study. In order to analyze the

impact of caste we have categorized the persons in four groups like Scheduled Caste,

Scheduled Tribe, Other Backward Classes and General Caste as per government

regulation. Against this backdrop, we can write

Decision regarding Family Planning= f (Women’s Empowerment at the household

level and at the community level, Individual/Household Characteristics, Community

Characteristics, and Random Disturbances)

85

On the basis of such specification, we finally pay our attention in Probit Model. The

cumulative distribution function for Probit model is given by

dx22x

1exp

2Π

1F(x)

(3.3.1)

where x is a standard normal variable and xF is a cumulative distribution function.

3.3.2 Analytical Framework for Impact of Empowerment on Domestic Violence

against Women

In order to assess the impact of women’s empowerment on household welfare, we would

like to examine the impact of women’s empowerment at the household level and at the

community level along with other determinants on the probability of the incidence of

domestic violence that she faces. The incidence of domestic violence is

multidimensional in nature. So, to study the extent of domestic violence we need to

specify the several indicators for measuring the intensity of domestic violence. But in the

course of our field survey we have observed that most of the rural women are not willing

to disclose the intensity of violence from that they suffer. That is why; we are reluctant

to form a composite index for domestic violence for our sample women. We have

collected information from the woman or from her neighbour whether or not the

particular woman faces frequent physical violence from her husband or from other

household members. If a woman suffered from physical assault by her husband or other

family member at least in two episodes during the last six months, we have identified

that the particular woman faces domestic violence. With reference to our criteria,

therefore, domestic violence is a binary variable. Let us now discuss the several socio-

economic-demographic and community traits that may affect domestic violence against

women.

Factors Affecting Domestic Violence against Women

We can divide the determinants of domestic violence against women into two categories,

namely, individual/household characteristics and community characteristics. In the

course of our literature review we have noticed that individual/household’s socio-

economic-political factors such as nature of marriage, duration of marriage, dowry,

women’s education, age, occupation of woman, childlessness, economic pressure, and

86

intergenerational transmission of violence, financial condition of family, husband’s

education, average education level of the family, family type, household occupation are

important determinants of the incidence of domestic violence against women. On the

other hand, different studies have reported that caste, region, religion, environment of

violent crime and community-level norms concerning wife beating, culture and customs

of the society are the major community level factors that influence the incidence of

domestic violence against women.

In addition to women’s empowerment at the household level and at the community level

in the spectrum of individual/household characteristics we have taken duration of

married life, spousal age gap, family type, highest male education, husband education,

household occupation, husband’s drug addiction, annual per capita income, land holding,

dependency ratio, dowry demand at and post marriage as determinants of the incidence

of domestic violence against women in the category of individual/household

characteristics. Among the community characteristics we have considered women’s

empowerment at the community level, duration of self-help group membership and

caste. Note that caste of the sample member has been divided into four categories as we

have mentioned in the last sub-section. Hence, we can write:

Domestic Violence against Women = f (Women’s Empowerment at the household level

and at the community level, Individual/Household Characteristics, Community

Characteristics, Random Disturbances)

The incidence of domestic violence is a dichotomous variable (iY ) that takes the value

‘1’ for the woman who is victims of domestic violence and value ‘0’ for others. So, in

order to estimate the probability of facing domestic violence for a woman in the district

of Bankura we formulate a Logit model. The logistic function for the logit model is as

follows

)exp(1

)exp()exp(1)(

1

X

XXX

(3.3.2)

where )(X expresses the cumulative distribution function of X which follows logistic

distribution.

87

3.3.3. Analytical Framework for Impact of Women’s Empowerment on Children’s

Educational Expenditure

The third issue that we have selected for studying the impact of women’s empowerment

on household welfare is the nature of educational expenditure for children. It is true that

the women/households, who have no children in the age of studying in educational

institutions, don’t have this expenditure at all. On the other hand, the women/households,

who have children in the age of studying in educational institutions, have two options:

either send their children school/colleges for education or not. The women/households

who send their children for education must have some expenditure towards children

education. But expenditure for children education is also zero for the women/households

who do not send the children in educational institutions. Actually, this part of our study

is restricted among those sample women who have children in the age of attending

school and colleges. A very large portion of our sample women have children in the age

of attending school and colleges. So this part of our study does not lose generality. The

educational expenditure for children in a family is one of the major indicators of a family

wellbeing. It is expected that development of the family increases the expenditure for

children’s education. This study has planned to investigate the impact of women’s

empowerment at the household level and at the community level on education

expenditure for her children. Education, particularly, primary education is most

important for economic development. In India, as well as in our state of West Bengal,

primary education is the four years of schooling from the age of six. The duration of

education up to the class of eighth standard is termed as elementary education. Education

up to tenth class is known as secondary education. Education after secondary level is

viewed as higher education. Education up to elementary level has been made compulsory

and free for all the children by the government of India. But we have the experience that

a large section of the guardians of the students at any level cannot depend completely on

the government and government aided schools for education of their children. Most of

them arrange private tuition for their children. In urban area a section of guardians send

their children in private school. However, in rural area, like our study area this

opportunity is completely absent. A major part of the guardians, who like to educate

their children, in rural area also send their children to private tutors. However, during the

course of field survey we have observed that most of the people in our study area are

living in a poor economic condition. A considerable number of children have to engage

in job to collect their livelihood. In our study area many potential students could not

88

complete their primary education. Here dropout rate is high. As a result, educational

expenditure varies widely across the sample households. Like any other part of India

here primary and secondary education are provided by the government, forming a free

education system. In spite of these, a major number of households have to spend money

for education of the children.

The expenditure relating to education of the children is viewed as children’s educational

expenditure. Expenditure for purchasing educational kits like books, papers, pens,

pencils school dresses etc., are the essential expenditure for children’s education. The

fact is that most of the students at primary level as well as secondary level even at the

college level take the shelter of private tuition. The major part of expenditure for

children’s education is the fees for private tuition. Almost all villages in our country

have at least one primary school. So traveling cost for attending primary school is zero

for almost all households. However, women/households have to bear some travelling

cost for their children who attend secondary or higher secondary school and college.

This cost proportionally amplifies with the number of the tuition trips. Therefore, cost

for commuting school/colleges and tuition is a significant part of children’s educational

expenditure. Another head of educational expenditure is for school (private school) and

college tuition fees. The students, who study at residential institution or study in the

institution far away from their residential addresses, need some accommodation cost.

Besides, women/households give some money to their children for refreshment during

travelling for education. In addition to these, actual costs for children’s education there

may have some opportunity costs. It is common that during the time of education parents

or other family members have to spend some times every day for preparing and or

escorting the children for school and for coaching. Sometimes guardians have to attend

the school/colleges for admission and examination of the children, meetings or for

functions. These factors give rise to some opportunity cost relating to children’s

education. Other part of the opportunity costs of children’s education arise when the

children have some opportunity to earn during the period of education. Sometimes,

guardians want to send their child for earning. This fact also adds some opportunity cost

for children’s education to the guardians. In order to explain the analytical framework

for modeling the child education expenditure first note down the probable heads of the

educational expenditure for children.

89

Probable Heads of the Educational Expenditure for Children

Expenditure for purchasing educational kits including school uniform if any

The cost for private tuition fees

Commuting expenditure for attending tuition and school

Fees for education (for higher education/private school)

Accommodation costs if any

Tiffin cost/ pocket money

Opportunity cost ( for the guardians themselves and for the guardians who wants

to send their child for earnings)

We did not consider the opportunity cost for children’s education due to lack of reliable

information and calculating hazards. In estimation we have considered annual child

education expenditure as proportion to annual household income. To compute

expenditure for children’s education first we calculate the expenditure for each head for

month or for year as we have been informed from the respondent and add them. Then we

average the expenditure for the last year. We have finally divided the annual child

education expenditure by annual household income to get the proportion of household

income spend for child education. It is a quantitative variable and expressed as

percentage.

Factors affecting Children’s Educational Expenditure

No doubt the educational expenditure varies from household to households depending on

the number children and their educational level. It is also directly related with income of

the households. In addition to these two factors, children’s educational expenditure

depends on mother’s/household characteristics and community characteristics.

Educational expenditure depends on certain information set, which consists of socio-

economic and demographic traits of women along with her empowerment status. These

traits are exogenous and predetermined variables that have been considered as

determinants of the educational expenditure for children.

We have classified the socio-economic and demographic traits affecting the child

education expenditure into two categories, namely, the individual/household

characteristics and the community characteristics of the woman. As per our specific

90

objective in the range of individual/household characteristics we have considered

women’s/mother’s empowerment at the household level as the primary explanatory

variable determining children’s educational expenditure. Generally, empowered woman

at the household level as well as the community level are more conscious about the

effectiveness of education. Against this backdrop, we can write

Children’s Education Expenditure as Proportion to Household Income = f (Mother’s

Empowerment at the household level and at the community level, Mother’s/Household

Characteristics, Community Characteristics, Random Disturbances).

In order to estimate the impact empowerment status along with other explanatory

variables on the children educational expenditure as proportion to household income we

formulate a multiple log linear regression model as

iii UβXY ln (3.3.3)

where iY stands for the educational expenditure for children, iX denotes the set of

explanatory variables, which includes all the individual/household and community

characteristics along with the empowerment variables, k captures the marginal impact

of the particular explanatory variable on (ln iY ) child educational expenditure as

proportion to household income and iU are the random disturbances.

The estimation of this model will help up capture the rate of change of the expenditure

for children’s education for change in empowerment at the household level and at the

community level.

3.4. Analytical Framework for Studying Women’s Empowerment

We expect that women’s empowerment is an instrument for improving household and

child welfare. Particularly we have already formulated the framework for assessing the

impact of women’s empowerment on family planning decision, on incidence of domestic

violence against women and on child education expenditure. In this connection it is

rational to quest the factors affecting household level and community level of

empowerment. With this end in view, in the present section, an attempt has been taken to

describe the strategy to estimate the women’s empowerment at the household level and

91

at the community level so that we can find out the probable determinants of it in the

context of our study objectives and study area.

Factors affecting Women’s Empowerment

Several studies reviewed in chapter two have examined the impact of several socio-

economic and demographic traits on women’s empowerment. Similarly in the context of

our study we have selected some factors affecting women’s empowerment at the

household level and at the community level. In the range of individual/household

characteristics we have considered age, education, personal occupation and income, per

capita household income, household occupation, landholding, family type, educational

background of the household and access to formal credit. We have considered SHG

membership and caste in the range of community characteristics.

Therefore, the general functions for studying empowerment at the household level and at

the community level can be written as follows.

Women’s Empowerment at the Household Level = f (Individual/Household

Characteristics, Community Characteristics, Random Disturbances).

Women’s Empowerment at the Community Level = f (Individual/Household

Characteristics, Community Characteristics, Random Disturbances).

In order to estimate the empowerment status as a function of some individual/household

characteristics and community characteristics we have planned to formulate multiple

linear regression models. In this analytical framework the indices of women’s

empowerment are the dependent variables which are quantitative by construction. Now,

we can write the function for each index of women’s empowerment in terms of general

linear regression model as

iii UβXY (3.4.1)

where iY stands for the index of women’s empowerment of the ith

woman, iX denotes

the set of explanatory variables, which includes all the individual/household and

community characteristics affecting the empowerment status, k captures the marginal

92

impact of the particular explanatory variable on empowerment index and iU are random

disturbances.

3.5. Regression Specification of the Analytical Models relating to Women’s

Empowerment

Once we have the theoretical framework of the models corresponding to the issues of the

women’s empowerment, we need to specify the empirical models for estimation. Now

we specify the econometric models serially in accordance with the analytical

frameworks.

3.5.1. Probit Models for Decision regarding Family Planning

In order to specify the probit model for the decision regarding family planning we follow

the framework analyzed in section 3.3.1. In this context we have considered two models,

Model-1A and Model-1B. In Model-1A we have taken the degrees of women’s

empowerment as explanatory variables and in Model-1B the composite indices of

women’s empowerment have been considered as explanatory variable along with some

other explanatory variables. The specific models are as follows.

Model-1A Probit Model when Empowerments Quantified by Simple Average

USTSCOBCDSHGMDOWECAPCHINDRATIO

HLANDNONFARMCULTITYFAMIHEDUEDU

SAGEGAGAMFFSFFFSMFMSFDOWEHDRFP

19181716151413

121110987

6543210

(3.5.1)

Model-1B Probit Model when Empowerments Indexed by PCA

USTSCOBCDSHGMDOWECAPCHINDRATIO

HLANDNONFARMCULTITYFAMIHEDUEDU

SAGEGAGAMFFSFFFSMFMSFDOWEHDRFP

C

C

19181716151413

121110987

6543210

(3.5.2)

93

3.5.2. Logit Models for Incidence of Domestic Violence

As the incidence of domestic violence against women is a dummy variable in accordance

with our specification, we formulate a Logit model. We have measured women’s

empowerment levels following two methodologies. Keeping this view in mind, here we

also estimate two models. Degrees of women’s empowerment have been considered as

determinant of domestic violence against women in Model-2A whereas Model-2B

includes composite indices of women’s empowerment.

Model-2A Logit Model when Empowerments Quantified by Simple Average

USTSCOBCDSHGMDOWECADDICPMDOW

DOWAPCHINDRATIOHLANDNONFARMCULTI

TYFAMIHIMEDUHEDUSAGEGDURMDOWEHDVIO

19181716151413

121110987

6543210

(3.5.3)

Model-2B Logit Model when Empowerments Indexed by PCA

USTSCOBCDSHGMCIWECADDICPMDOW

DOWAPCHINDRATIOHLANDNONFARMCULTI

TYFAMIHIMEDUHEDUSAGEGDURMCIWEHDVIO

C

C

19181716151413

121110987

6543210

(3.5.4)

3.5.3. Log-Lin Models for Children’s Education Expenditure as Proportion to

Household Income

In the section of analytical framework we have explained the justification of log-lin

model for examining the impact of women’s/mother’s empowerment on household’s

expenditure for children’s education. In this sub-section we express the explicit form of

the regression models. Like another issues in this case we also set two models - one is

based on the degrees of women’s empowerment and other on the composite indices of

women’s empowerment.

94

Model-3A Log-Lin Model when Empowerments Indexed by Simple Average

USTSCOBCDSHGMDOWEC

APCHINLOGDRATIOHLANDNONFARMCULTI

TYFAMIHIFEDUHIMEDUHEDUDOWEHLEDEX

1514131211

109876

543210

)(

(3.5.5)

Model-3B Log-Lin Model when Empowerments Indexed by PCA

USTSCOBCDSHGMCIWEC

APCHINLOGDRATIOHLANDNONFARMCULTI

TYFAMIHIFEDUHIMEDUHEDUCIWEHLEDEX

C

C

1514131211

109876

543210

)(

(3.5.6)

3.5.4. Linear Regression Models for Women’s Empowerment at the Household

Level and at the Community Level

By definition and conception the empowerment of women is a qualitative attribute of the

women. So far we have quantified it at two levels, namely at individual/household level

and at community level. Further, to measure the women’s empowerment for each level

we have considered two methodologies. Applying simple average method we have

computed degrees of women’s empowerment at the individual/household level and

women’s empowerment at the community level. We have also computed composite

index of women’s empowerment at the individual/household level and at the community

level applying Principal Component Analysis. In the previous section we have explained

the analytical framework for studying women’s empowerment at household level and

community level. Therefore, we have four measures for women’s empowerment. To this

end in view, we formulate four linear regression models to identify the major

determinants of women’s empowerment in the district of Bankura. First two are related

with household level empowerment and last two with community level empowerment.

These have been specified as follows.

95

Model-4A Linear Model for Household Level Empowerment Indexed by Simple

Average

USTSCOBCDSHGMHIFEDUHIMEDU

HLANDNONFARMCULTIAPCHINDRATIOTYFAMI

AFCTPINCSELFLABEDUAGEAGEAGEDOWEH

201918171615

14131211109

876543210 321

(3.5.7)

Model-4B Linear Model for Household Level Empowerment Indexed by Principal

Component Analysis

USTSCOBCDSHGMHIFEDUHIMEDU

HLANDNONFARMCULTIAPCHINDRATIOTYFAMI

AFCTPINCSELFLABEDUAGEAGEAGECIWEH

201918171615

14131211109

876543210 321

(3.5.8)

Model-4C Linear Model for Community Level Empowerment Indexed by Simple

Average

USTSCOBCDSHGMHIFEDUHIMEDU

HLANDNONFARMCULTIAPCHINDRATIOTYFAMI

AFCTPINCSELFLABEDUAGEAGEAGEDOWEC

201918171615

14131211109

876543210 321

(3.5.9)

Model-4D Linear Model for Community Level Empowerment Indexed by Principal

Component Analysis

USTSCOBCDSHGMHIFEDUHIMEDU

HLANDNONFARMCULTIAPCHINDRATIOTYFAMI

AFCTPINCSELFLABEDUAGEAGEAGECIWEC

201918171615

14131211109

876543210 321

(3.5.10)

96

In order to estimate Model-1A and Model-1B, we apply Binary Probit Maximum

Likelihood method. Model-2A and Model-2B have been estimated by Binary Logit

Maximum Likelihood method. The remaining models would be estimated using

Ordinary Least Squares method.

3.6. Definition and Measurement of the Variables included in the Regression

Models

We have specified the empirical models in the last section. In this section we define and

specify the measurement of the variables that have been considered in these models. We

would like to define and measure the variables considered in the whole study serially.

Note that a few variables are common in more than one model. To avoid the repetition,

we only refer the variables those have already been defined and explained.

Variables in Models for Family Planning Decision

In this model, we look into the determinants of the family planning decision for the rural

women. The dependent variable in the model is the decision towards family planning,

which we explain first and then explanatory variables of this model.

DRFP (Decision regarding family planning by the woman under study): It is the

dependent variable in Model-1A and Model-1B. If the woman strongly inform that she

has or will have utmost two children, we consider her as ideal family planner. Therefore,

decision regarding family planning is a dichotomous variable such that

DRFP = 1, if the woman’s family planning decision is positive

0, otherwise

Women’s Empowerment Variables

In Model-1A and Model-1B the main explanatory variables are the women’s

empowerment variables. These are constructed variables. In this study we have measured

women’s empowerment at two levels- household level and community level. Detailed

methods of construction of women’s empowerment variables have been explained in

sub-sections 3.2.2 and 3.2.3. Four measures of women’s empowerment have been

specified below.

97

A] DOWEH (Degree of Women’s Empowerment at Household Level): It is simply a

ratio of the number of criteria fulfilled by the woman to the total number of criteria set

for women’s empowerment at the household level. It has been expressed as percentage.

So it ranges from zero to hundred.

B] DOWEC (Degree of Women’s Empowerment at Community Level): Like DOWEH, it

is a ratio of the number of criteria fulfilled by the woman to the total number of criteria

for women’s empowerment at the community level. It is also expressed as percentage

form and thereby ranges from zero to hundred.

C] CIWEH (Composite Index of Women’s Empowerment at Household Level): It is the

weighted sum of the component scores – the weights being percentage of variations

explained by the respective Principal Components after rotation. By principles of

Principal Component Analysis these composite Index of women’s empowerment are unit

free but the values of this index varies from to .

D] CIWEC (Composite Index of Women’s Empowerment at Community Level): It is the

weighted sum of the component scores – the weights being percentage of variations

explained by the respective Principal Components after rotation. It is also unit free but

the values of this index varies from to .

The first two measures have been considered as primary explanatory variables in Model-

1A and the last two are the main explanatory variables in Model-1B. In addition to the

empowerment variables we have considered some other explanatory variables which are

common in both the models for decision regarding family planning.

Male Child Bias: In order to measure the male child bias we have divided the women in

accordance with the sequence of their children up to second issue into five groups,

namely, a) women having one child only (ONEC), b) women having first and second

children male, (FMSM), c) women having first child male and second child female,

(FMSF), d) women having first child female and second child male, (FFSM) and e)

women having first and second children female, (FFSF). Now if we find women having

at least one female child are less likely to adopt family planning we say that they are

male child biased.

98

Thus, male child bias is a categorical variable and the women, who have only one child

or who have male child in first and second issue, have been considered as reference

category for analyzing the impact of other groups. Therefore, the included dummy

variables are as follows.

FMSF =1, for the woman having first child male and second child female

0, otherwise

FFSM = 1, for the woman having first child female and second children male

0, otherwise

FFSF = 1, for the woman having first and second children female

0, otherwise

AGAM (Age of the Woman at the Time of Marriage): It is the chronological age,

measured in years, of the woman at the date of her marriage.

SAGEG (Spousal Age Gap): Spouse Age Gap, measured in years, is the difference

between the physical age of husband and wife.

EDU (Educational Qualification of the Woman): It is the number of years the woman

attended the formal educational institutions.

HEDU (Educational Qualification of the Husband): It is the number of years the

husband attended the formal educational institutions.

TYFAMI (Type of Family): We consider two types of family – nuclear and joint.

Nuclear family is a family where the woman (wife) lives with her husband and their

children. On the other hand, joint family is one where husband, wife and their children

live with other members of family like mother-in-law, uncle, aunt etc. It is a dummy

variable as

TYFAMI = 1, if the woman belongs to nuclear family.

0, otherwise

99

Household Occupation: Household occupation means the economic activity in which

the workers of the family are involved in to earn their livelihood over years. We have

divided the households into three categories in terms of their main occupation as follows.

CULTI (Cultivation): Households mainly engaged in cultivation are considered in this

category.

NONFARM (Non-Farm Self-employment): If major portion of the family income comes

from the self-employed non-agricultural activities, the family is considered in this

category.

Wage Labour: Households, in which earning members are wage labours or earning from

the source other than cultivation or self-employment, are considered in this category.

In our study we have considered wage labour as the reference category for analyzing the

impact of other categories i.e., Cultivation (CULTI) and Non-farm Self-Employment

(NONFARM). Specifically,

CULTI =1, if the household is mainly engaged in cultivation.

0, otherwise

NONFARM = 1, if the household is mainly engaged in nonfarm self-employment.

0, otherwise

HLAND (Household’s Landholding): Household’s land is defined as the total size of

land owned by the household for cultivation or residence. We have taken landholding as

a quantitative variable, the unit of measurement of agricultural landholding being bigha

(1 bigha = 0.4 acre).

DRATIO (Dependency Ratio): Dependency ratio is defined as the proportion of

dependents or non-working members to the total members of the family. The

dependency ratio in the family is expressed as percentage.

APCHIN (Annual Per Capita Household Income): Household income is the sum total of

the incomes of all the earning members in the household. We have taken the total

monthly expenditure as proxy for the household’s monthly income and convert it into

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annual income. Dividing it by household size we get per capita annual household

income. The unit of measurement of this variable is rupee.

Explanatory Variables Reflecting the Community Characteristics

The main community level variable in our study is women’s empowerment at the

community level. We have taken DOWEC and CIWEC as main explanatory variables

reflecting community characteristics in Model-1A and in Model-1B respectively. We

have already specified DOWEC and CIWEC. Now we define the other community level

variables affecting the decision regarding family planning, which are common in Model-

1A and in Model-1B.

DSHGM (Duration of SHG Membership): The duration of the SHG (self help group)

membership is measured by the period for which the woman acts as a member of the

SHG. We have taken month as measuring unit of the duration of SHG-membership.

Caste: Caste of a person is a categorical variable indicating the person belonging to a

specific caste, namely, General Castes (GEN), Other Backward Classes (OBC),

Scheduled Caste (SC) and Scheduled Tribe (ST) with GEN as reference category.

Therefore, we have three dummy explanatory variables in connection with caste.

OBC = 1, if the person belongs to the Other Backward Classes.

0, otherwise

SC = 1, if the person belongs to the Scheduled Caste

0, otherwise

ST = 1, if the person belongs to the Scheduled Tribe

0, otherwise

Variables in Models for Incidence of Domestic Violence against Women

In order to study the incidence of domestic violence against women in the district of

Bankura we have formulated two econometric models depending on the measures of

women’s empowerment. Except the empowerment variables, the variables in the models

are same. In the models for domestic violence against women, the incidence of Domestic

Violence is the dependent variable. It has been denoted by DVIO.

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DVIO (domestic violence against women): We have measured this variable by

considering whether the woman experienced at least any two episodes of hit, kick, slap,

beat etc. by her husband or other family member in the last six months or not. The

incidence of domestic violence is a binary variable as specified below.

DVIO = 1, if the woman is victim of domestic violence during the last six months.

0, otherwise

Explanatory Variables

First, we list those explanatory variables which have already been specified in the

models for the decision regarding family planning. These are the DOWEH (Degree of

Women’s Empowerment at Household Level), CIWEH (Composite Index of Women’s

Empowerment at Household Level), SAGEG(Spousal Age Gap), HEDU (Educational

Qualification of the Husband), TYFAMI (Type of Family), Household Occupation,

CULTI (1= Cultivation), Household Occupation, NONFARM (1= Non-farm self-

employment), HLAND (Household’s Landholding), DRATIO (Dependency Ratio) and

APCHIN (Annual Per Capita Household Income). The explanatory variables indicating

the community traits are DOWEC (Degree of Women’s Empowerment at Community

Level), CIWEC (Composite Index of Women’s Empowerment at Community Level),

DSHGM (Duration of SHG Membership) and the dummies for Caste. In addition to

these variables, we have included some other variables in the individual/household

characteristics as specified below.

DURM (Duration of the Married Life): It is the chronological age of the woman after

her marriage and is measured in years.

HIMEDU (Highest Education among Male Household Members): It is the education

level of that male member of the family who attended the formal educational institution

for maximum period. The number of years that male member attended the educational

institution has been considered for measuring this variable.

DOW (Dowry Given at Marriage): It is captured the fact that whether the natal family of

the woman has given any kind of dowry (financial or physical assets) to her in-laws at or

before marriage It is a binary response variable as specified below.

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DOW = 1, if the natal family of woman have given dowry.

0, otherwise

PMDOW (Post Marriage Dowry Demand): It is also a response variable stating whether

or not the in-laws of the woman has claimed for assets after marriage from her natal

house. Therefore,

PMDOW = 1, if the natal family of woman have given dowry after marriage.

0, otherwise

ADDIC (Addiction of the Husband): By addiction of the husband of the representative

woman we mean whether or not the husband is addicted to any kind of tobacco or

alcohol or both.

ADDIC = 1, if the husband is addicted to any kind of tobacco or alcohol or both.

0, otherwise

Variables in Models for Child Education Expenditure

Based on the different measures of empowerment we have formulated two separate

econometric models. These have been specified as Model-3A and Model-3B. In both the

models log of child education expenditure as proportion to household income in the last

year has been considered as the dependent variable. Except the empowerment variables,

the variables in Model-3A and in Model-3B are same.

LEDEX (Ln of Child Education Expenditure as Proportion to Annual Household

Income): It is the logarithmic value of the percentage of child education expenditure to

annual household income. We have already explained its measurement in section 3.3.3.

This is the dependent variable in the models for child education expenditure for the

women in Bankura district. No doubt it is a metric variable.

Explanatory Variables

First, we pass on the list of explanatory variables affecting child education expenditure,

which have already been specified in the previous models. These are the DOWEH

(Degree of Women’s Empowerment at Household Level), CIWEH (Composite Index of

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Women’s Empowerment at Household Level), HEDU (Educational Qualification of the

Husband), HIMEDU (Highest Education among Male Household Members), TYFAMI

(Type of Family), Household Occupation, CULTI (1=Cultivation), Household

Occupation, NONFARM (1=Non-farm self-employment), HLAND (Household’s

Landholding), DRATIO (Dependency Ratio) and APCHIN (Annual Per Capita

Household Income). The explanatory variables indicating the community traits are

DOWEC (Degree of Women’s Empowerment at Community Level), CIWEC

(Composite Index of Women’s Empowerment at Community Level), DSHGM (Duration

of SHG Membership) and the Caste dummies. In addition to these variables we have

included one more variable in the individual/ household characteristics namely Highest

Education among Female Household Members (HIFEDU)

HIFEDU (Highest Education among Female Household Members): The highest number

of years in the educational institution, attended by any female member of the family, has

been considered as the highest education among female household members. So,

HIFEDU is a quantitative variable measured in year.

Variables in Models for Women’s Empowerment

In accordance with the two alternative measures of empowerment we have specified two

models for empowerment at the household level and two for empowerment at the

community level. We have defined four empowerment variables. For each of these

empowerment variables a regression model has been formulated. We have inserted the

same independent variables in each model for studying women’s empowerment at the

households and at the community level. We now specify them as follows.

Explanatory variables reflecting Individual/household level Characteristics

First, we mention the explanatory variables which have already been specified in the

previous models. These are EDU (education level of the woman), TYFAMI (Type of

Family), Household Occupation, CULTI (1=Cultivation), Household Occupation,

NONFARM (1=Non-farm self-employment), HLAND (Household’s Landholding),

DRATIO (Dependency Ratio), APCHIN (Annual Per Capita Household Income),

HIMEDU (Highest Education among Male Household Members) and HIFEDU (Highest

Education among Female Household Members). The explanatory variables indicating

the community traits are DSHGM (Duration of SHG Membership) and the Caste

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dummies. In addition to these variables we have included some more variables as

follows.

Age (AGE): Age means simple the physical age of the person, counted by years.

However, in different stages of life, women play different roles and duties in their

households and in community. To gage the impact of age of women at different phases

of life on her empowerment at the household level and at the community level we have

divided them into four age groups: AGE1, AGE2, AGE3 and AGE4. Age of women in

our study is a categorical variable with AGE4 as the reference category. Therefore,

AGE1 = 1, if age of the woman is below 25 years

0, otherwise

AGE2 = 1, if age of the woman is into the range 25-35 years

0, otherwise

AGE3 = 1, if age of the woman lies in the range 36-45 years

0, otherwise

Occupational Status of the Woman: Occupation of a woman means the work that the

individual do on the most of the time of a day in general. We divide the occupation of

the women into three categories such that Homemaker, (HM) Wage labour (LAB) and

self-employed or service holder (SELF) with home maker category as reference

category. The women, who basically are engaged in household job or in field agricultural

activity without payment, belong to the category of home maker. The women who work

for wages or crop share in the agricultural sector or do household job for wage belong to

wage labour group. Women, who are mainly involved in business, manufacturing

activity, provide services in organized sector, work for wages or commission in the non-

agricultural unorganized sector belong to self-employed category. Thus we have

LAB = 1, if the woman belongs to wage labour group

0, otherwise

SELF = 1, if the woman earns from self-employment or from service

0, otherwise

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PINC (personal income of the woman): It is amount of the money, measured in rupee

which the woman earns from her personal activity per month in average.

AFCT (Access to Formal Credit): It is a qualitative dichotomous variable indicating

whether or not the woman has access to formal credit. Therefore,

AFCT = 1, if the woman has access to formal credit.

0, otherwise

3.7. Specification of Hypothesis

In order to study the empowerment and related issues of rural women in the district of

Bankura we have already specified some models that to be estimated empirically. In this

section, we propose the relevant hypotheses respective to those models.

3.7.1. Hypotheses relating to the Model for Decision regarding Family Planning

In the model for decision regarding family planning, our purpose is to explain how the

household and community level empowerment of women along with other socio-

economic factors affect the probability of taking family planning decision. The probit

models that we have specified will enable us to test how the several explanatory

variables affect the probability of taking family planning decision. The relevant models

in this particular context are Model-1A and Model-1B and relevant hypotheses related to

these models are set below.

Hypothesis-1

The empowerment of women has some positive effect on the decision regarding family

planning. That is, 0β1

and 0β1C (refer to equation 3.5.1 and 3.5.2). As the women

become more and more empowered they can realise the benefits of having small family.

Empowered women do not take their children as their livelihood security of old age.

Rather they become more conscious about their children health and education. So, we

can say that the level of household empowerment is positively related with the

probability of taking decision regarding family planning.

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Hypothesis-2

Women having two children with at least one female child are less likely to adopt family

planning. That means, 00,0β 432 and (refer to equation 3.5.1 and 3.5.2). It

is expected that if the household prefers male child compared to female, then the couple

under the household will not adopt family planning.

Hypothesis-3

Decisions regarding family planning are positively related with the age of the women at

marriage. Age of the women at marriage positively affects the probability of taking

family planning decision. That is, 0β5 (refer to equation 3.5.1 and 3.5.2).

Hypothesis-4

It is convention in Indian culture that a husband should be older than his wife. The

greater the difference of age between husband and wife the lower will be the women’s

say about family planning decision. The probability of taking family planning decision

by women is expected to be lower for larger age gap of spouses. That is, 0β6 (refer to

equation 3.5.1 and 3.5.2).

Hypothesis-5

Education of the women has positive impact on the decision regarding family planning.

That is, 07 (refer to the Model-1A and Model-1B).

Hypothesis-6

Education of the husband has a positive impact on the decision towards family planning

by woman. The probability of taking family planning decision by woman is directly

related with the age of the person. That means, 08 (refer to equation 3.5.1 and 3.5.2).

Hypothesis-7

Type of family, which the woman belongs to, affects the decision towards family

planning by women. The probability of taking family planning decision by women is

expected to be higher for the women of the nuclear family compared to those of the joint

family. That means, we expect 0β9 (refer to equation 3.5.1 and 3.5.2).

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Hypothesis-8

The main occupation of the household is likely to influence the probability of taking

family planning decision by woman. The probability of taking family planning decision

is higher for the women of cultivator family and non-farm family than other. If the

family shifts from the wage labour class to the cultivator class or to the non-farm self-

employed family, the probability of taking family planning decision will increase.

Specifically, we like to test 0β10 and

0β11 (refer to equation 3.5.1 and 3.5.2).

Hypothesis-9

We can expect that the larger the size of landholding the larger will be the probability of

taking family planning decision. That is, 0β12 (refer to equation 3.5.1 and 3.5.2).

Hypothesis-10

Dependency ratio is expected to be negatively related with the probability of taking

family planning decision by women. That is, 0β13 (refer to equation 3.5.1 and 3.5.2).

Hypothesis-11

Annual per capita family income has a positive impact on the family planning decision

by women. That means that we like to test 0β14 for Model-1A and for Model-1B.

Hypothesis-12

Like the household level empowerment of women the community level empowerment of

women has some positive effect on the decision towards family planning. That is,

0β15 and 0β15C (refer to equation 3.5.1 and 3.5.2). Higher community

empowerment means women have larger mobility in the society. They can easily

identify the benefits of small family and troubles of having large family. So the women

having higher community level empowerment want to have a small family.

Hypothesis-13

The duration of SHG-membership increases the probability of taking family planning

decision. That is, 0β16 in equation 3.5.1 and 3.5.2. Being the member of SHG, a

woman becomes more conscious and gets in touch with other people. They understand

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the importance and advantages of family planning. So the probability of taking family

planning decision increases with the increase of the duration of SHG-membership.

Hypothesis-14

The probability of taking family planning decision by woman is expected to be lower for

the people of OBC, SC and ST compared to that for the people of general caste. That is,

0 and 0,0β 191817 ββ (refer to equation 3.5.1 and 3.5.2).

3.7.2. Hypotheses relating to the Model for Incidence of Domestic Violence

In the model for the incidence of domestic violence, our purpose is to explain how the

empowerments of women along with other explanatory variables affect the probability of

suffering from domestic violence. This section presents the hypotheses logically. The

relevant models in the particular context are Model-2A (equation-3.5.3) and Model-2B

(equation-3.5.4) and relevant hypotheses related to these models are stated below.

Hypothesis-1

The probability of sufferings of women from the incidence of domestic violence is

negatively related with the household level empowerment and with the community level

empowerment. It means that we like to test 01 and 015 (refer to equation 3.5.3)

and we test 01 C and 015 C (refer to equation 3.5.4).

Hypothesis-2

Duration of married life of the woman is negatively related with the incidence of

domestic violence against her. That is, 02 (refer equations 3.5.3 and 3.5.4).

Normally, with the increase in age women become more experienced and their

influences in the family increase. Therefore, the duration of married life of the woman

inversely affects the probability of sufferings from the incidence of domestic violence.

Hypothesis-3

Spousal age gap is directly related with the occurrence of domestic violence against

women. The higher the age gap the higher will be the occurrence of domestic violence

against women. That is, 03 (refer to equations 3.5.3 and 3.5.4).

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Hypothesis-4

Husband education has a negative impact on the occurrence of domestic violence. With

the increase in the level of education of husband, the probability of occurrence of

domestic violence against his wife decreases. That is, 04 (refer to equation 3.5.3

and 3.5.4). This is self-explanatory.

Hypothesis-5

Higher education of the male family member is likely to reduce the occurrence of

domestic violence. That is, higher education among the male person in family reduces

the probability of occurrence of domestic violence against women. That is, 05 (refer

to equation 3.5.3 and 3.5.4).

Hypothesis-6

The probability of occurring violence against women within family is expected to be

lower for the women of the nuclear family compared to those of the joint family. That

means, we expect 06 (refer to equation 3.5.3 and 3.5.4).

Hypothesis-7

It is very difficult to say whether the women of wage labour family suffer more from

domestic violence in contrast to the women of cultivator family or the non-farm self-

employed family. That is why, we want to test the hypothesis, 00 87 and (refer

to equations 3.5.3 and 3.5.4).

Hypothesis-8

There is no reason to expect any particular relation between the size of the household’s

landholding and the occurrence of violence against women. Therefore, we frame the

alternative hypothesis 09 (refer to equations 3.5.3 and 3.5.4).

Hypothesis-9

There is no confirmed relation between the dependency ratio and the probability of

occurrence of violence in the family against women. Therefore, we would like to test

010 (refer to the Models-2A and Model-2B).

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Hypothesis-10

Higher the annual per capita family income lower will be the probability of the

occurrence of domestic violence against women. That means that we like to test

011 for equations 3.5.3 and 3.5.4. Higher per capita family income ensures higher

living and social standard of the family. So we expect that with the increase in the annual

per capita income, the probability of the occurrence of domestic violence against women

will decrease and vice-versa.

Hypothesis-11

We like to test whether the dowry system causes domestic violence in the area under

study. With this end in view, we make hypothesis that the women who have given any

kind of dowry suffer more from domestic violence from her in-laws. Not only that, we

expect the sufferings of women to increase if the post marriage dowry demand arises.

That is, we have set the hypotheses 012 and 013 (refer to the equations 3.5.3

and 3.5.4).

Hypothesis-12

The frequency of the sufferings of women from domestic violence and drug addition of

their husbands are directly related. That is why, we are interested to test 014 (refer to

the equations 3.5.3 and 3.5.4).

Hypothesis-13

There is a negative relation between the occurrence of domestic violence against women

and the duration of SHG-membership. That is, 016 (refer to the equation 3.5.3 and

3.5.4). In fact being the member of self-help group a woman becomes more conscious

about their rights and about their own wellbeing along with the wellbeing of the family

and the society.

Hypothesis-14

The women who come from the OBC, SC and ST family are more likely to suffer from

domestic violence compared to the women of the general caste. That is,

0 and 0,0 191817 (refer to the equation 3.5.3 and 3.5.4).

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3.7.3. Hypotheses in Connection with the Child Education Expenditure

In this sub-section we would formulate a set of hypotheses stating the relation between

children’s education expenditure and women’s empowerment along with several other

determinants.

Hypothesis-1

Household as well as community level empowerment of a woman has a positive impact

on her children’s education expenditure. Therefore, the higher the empowerment of

women the higher will be the expenditure as proportion to household income for their

children’s education. So, we expect 01 and 011 in equation 3.5.5 and 01 C

and 011 C in equation 3.5.6.

Hypothesis-2

The higher the education level of the father, the higher will be the share of educational

expenditure in household income for children in the family. That is, 02 α (refer to

Models-3A and Model-3B).

Hypothesis-3

The educational expenditure out of family income is directly related with the highest

male education and highest female education in the family. That is, 0 and 0 43

(refer to Model-3A and Model-3B). Like many other decisions, the decision of how

much to spend in children education depends on the education level of the other family

members. An educated person better understand how much and for which stream of

education they would spend. It is natural to expect that the highest male education and

highest female education have favourable effect on the educational expenditure of the

family.

Hypothesis-4

Women who belong to the nuclear family spend more on the education of their children

than the women who belong to the joint or extended family. Thus we say that if a

woman moves from the joint family to nuclear family, she will spend more. That is,

05 (refer to equations 3.5.5 and 3.5.6).

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Hypothesis-5

A mother of cultivator family or non-farm self employed family spends more on their

children education compared to a mother of wage labour family. That is,

00 76 and (refer to equations 3.5.5 and 3.5.6). In wage labour family more heads

means more income. Moreover, most of these families suffer from poverty. So they

concentrate more on their bread rather the education of their children. That is why, in

wage labour family children are also occupied as wage labour.

Hypothesis-6

Household’s landholding has positive effect on the children’s education expenditure. The

income share in children’s education expenditure increases as the size of the household

agricultural land holding increases. That is, 08 (refer to equations 3.5.5 and 3.5.6).

This is self-explanatory.

Hypothesis-7

Dependency ratio in the family affects negatively the educational expenditure.

Therefore, the expenditure for education of children and dependency ratio in the family

varies inversely. That is, 09 (refer to equations 3.5.5 and 3.5.6).

Hypothesis-8

As annual per capita family income increases share of child educational expenditure in

income increases. That means that we like to test 010 (refer to equations 3.5.5 and

3.5.6).

Hypothesis-9

The duration of membership of a woman in a SHG are expected to affect the expenditure

for their children education positively. As the number of years engaged in SHG

increases, the education expenditure for their children also increases. It implies

that 012 in equation 3.5.5 and 3.5.6.

Hypothesis-10

Women belonging to the general caste are more likely to spend on children’s education

compared to the women belonging to the Other Backward Classes, Scheduled Caste and

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Scheduled Tribe. Therefore, the spending for children education as proportion to family

income will be higher in the general caste families contrasted with the non-general caste

families. That is, 000 151413 and , (refer to equations 3.5.5 and 3.5.6).

3.7.4. Hypotheses relating to the Models of Women’s Empowerment

In order to assess the impact of several socio-economic-demographic factors on

women’s empowerment at the household level and at the community level we have

specified four regression models in accordance with the measure of empowerment. In

this sub-section we propose the hypotheses relating to the empirical models.

Hypothesis 1:

It is very difficult to assign any particular relation between the age of the woman and the

empowerment level of women. We expect that the women’s empowerment at the

household level and at the community level of age group below 25 years is lower than

that of the reference group. Again we can assume that age groups 25-35 years and age

group 35-45 years enjoy more empower compared to reference group (above 45 years).

It means that 0,0,0 321 and (refer to equations 3.5.7 and 3.5.8) and

0,0,0 321 and (refer to equations 3.5.9 and 3.5.10).

Hypothesis 2:

Education of women directly affects women’s empowerment at the household level and

at the community level. Here our hypothesis is 04 referring to equation 3.5.7, 3.5.8

and 04 in equations 3.5.9 and 3.5.10. Education makes a woman more conscious in

all phases and all aspects of life. It increases her political and legal understanding. It

improves the decision making power of woman at home and outside home. From all

these observations we expect that education enhance both the household and societal

empowerment of woman.

Hypothesis 3:

The occupation of a woman is likely to influence her empowerment. Therefore, the

empowerment is higher for wage labour and self employed women compared to home

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makers. Specifically, we like to test 05 and 06 (refer to equation 3.5.7 and

3.5.8). We also like to test 00 65 and in equation 3.5.9 and 3.5.10.

Hypothesis-4

Average Monthly Personal Income of the woman affects her empowerment level

positively. That is, 07 refer to equation 3.5.7, 3.5.8 and 07 in 3.5.9 and 3.5.10.

Hypothesis-5

There is a positive relation between the access to formal credit and the empowerment of

women. That is, we test 08 referred to equation 3.5.7 and 3.5.8 and 08 in and

3.5.9 and 3.5.10.

Hypothesis-6

Women belonging to nuclear family enjoy more empowerment compared to the women

belonging to joint family. This means 09 and 09 (refer to equations 3.5.7, 3.5.8,

3.5.9 and 3.5.10).

Hypothesis-7

Dependency ratio in the family is negatively related with the empowerment of woman.

We like to test 010 (refer to equations 3.5.7 and 3.5.8). We set alternative

hypothesis 010 in equations 3.5.9 and 3.5.10.

Hypothesis-8

We cannot confine to any definite relation between the annual per capita family income

and the empowerment of a woman of that family. In this case we test the hypothesis

011 (refer to equations 3.5.7 and 3.5.8) and 011 (refer to equations 3.5.9 and

3.5.10).

Hypothesis 9

Women who belong to the cultivator family or non-farm self-employed family has more

empowerment in compare to the women of wage labour family. That is,

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00 1312 and in equations 3.5.7, 3.5.8 and 00 1312 and in equations 3.5.9

and 3.5.10.

Hypothesis-10

It is very difficult to identify the direction in which the empowerment of women move

when the size of the household’s landholding increase or decrease. In this case we test

the hypothesis 014 and 014 (refer to equations 3.5.7, 3.5.8, 3.5.9 and 3.5.10).

Hypothesis-11

Highest male education and highest female education in the household other than the

respondent is likely to accelerate the empowerment level of the woman in the household

as well as in the society. Therefore, the household and societal empowerment of women

varies directly with the highest male education and highest female education in the

household. Specifically, we like to test 015 , 016 and 015 , 016 (refer to

equations 3.5.7, 3.5.8, 3.5.9 and 3.5.10).

Hypothesis-12

The duration of SHG membership has positive impact on the empowerment of woman.

The higher the number of years of involvement of a woman in a SHG the higher will be

her empowerment at the home and at the society. This means 017 and 017 (refer

to equations 3.5.7, 3.5.8, 3.5.9 and 3.5.10).

Hypothesis-13

The empowerment of general caste women is expected to be higher for the women of

OBC, SC and ST, i.e. 0 and 0,0 201918 (refer to equation 3.5.7 and 3.5.8). We

also examine 0 and 0,0 201918 in equations 3.5.9 and 3.5.10.

3.8. Methodology of Data Collection

An adequate and reliable source of data is the primary ingredient of an empirical study.

Without an adequate and reliable data set, any type of empirical analysis and its results

would be falsified and will convey a wrong message to the future researchers and policy

makers and thereby the purpose of the empirical study will be lost. That is why, before

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going to the any type of empirical analysis we need to have a set of adequate and reliable

data, which are collected following a scientific methodology. Keeping this point in

mind, we have collected a set of primary data from the district of Bankura in West

Bengal during 2012-2013. In this section we like to explain the methodology of data

collection and present the nature and scope of the data and finally present the procedure

of the diagnostic check for the sample size that would be used to factor analysis and

estimate the econometric models as specified in the above sections.

3.8.1. Sampling Design

In order to carry out the study of women’s empowerment we have considered the case

study of the district of Bankura in West Bengal. This district belongs to the Jangalmahal

(West Midnapore, Bankura and Purulia) in West Bengal. It has some distinct history and

cultural norms as mentioned in the chapter one. We have selected Bankura district

purposively as our study area. It is already known that the district has three sub-divisions

and twenty-two blocks. For conducting the sample survey we have followed four stages

stratified mixed sampling procedure. First of all, two blocks, namely Kotulpur and

Chhatna have been selected purposively. Of which Kotulpur block is relatively

developed and Chhatna block is relatively underdeveloped area in the district of

Bankura. This constitutes the first stage of our sampling. In the second stage of the

sampling we have randomly selected two Gram panchayets from Chhatna block and

three from Kotulpur block. Later on, we have chosen two (four villages from Dhaban

Gram panchayet) villages from each of the sample Gram panchayet. In total twelve

villages have been selected for our empirical study. Finally, after making a pilot survey

for each village, sample households are selected randomly from the sample villages. This

completes the fourth stage of the sampling design. It should be noted that number of

households chosen from each village are not equal. It depends on the total number of

households and other socio economic characteristics of the villages. Therefore, we have

designed a multi-stage sampling procedure which is also a combination of both

purposive and random sampling to take the advantages of the both. It may be looked as a

multi-stage stratified random sampling. Primarily, we have surveyed more or less six

hundred households and interviewed at least 611 persons; of them we have recorded the

relevant information of 580 households/persons in our data sheet. Data of some

households are rejected due to incomplete, insufficient, or absurd information and for

117

maintaining standard sample size suitable for factor analysis and econometric

estimations.

3.8.2. Profile of the Sample Areas

It has been already mentioned that our sample is constituted by 580 households residing

at villages belonging to two blocks in the district of Bankura. In this sub-section we

present an overview of the characteristics of the sample villages. Almost all the sample

villages are remote in terms of the access to well transport facility, health facility,

banking facility, job opportunity etc. In our sample we have selected three villages

namely Gopalpur, Sidabari and Meghkata, where scheduled tribe community forms the

major segment of population. In table-3.8.1 numbers and distribution of sample

households corresponding to each village have been presented. A large number of

Muslim households reside at Sarisadighi and Hati villages. Majority of the households at

Ghatdighi, Dhaban and Tegharia belongs to scheduled castes community. There is no

one village with any type of Bank branch.

Table 3.8.1. Area Specific Distribution of the Sample Households

Blocks GramPanchayets Villages Total

Households

Scheduled

Caste

Households

Scheduled

Tribe

Households

Sample

Households

Kotulpur

Madan

Mohan Pur

Hati 200 100 0 50

Sundarchack 200 80 0 49

Sihar Masinapur 260 80 20 60

Sihar 750 150 90 50

Kotulpur Ghatdighi 750 350 0 60

Sarishadighi 110 60 0 40

Chhatna

Dhaban

Dhaban 550 265 0 70

Tegharia 250 50 30 25

Sidabari 175 25 30 27

Gopalpur 265 55 130 44

Jamtora

Meghkata 120 0 90 60

Chitora 195 40 40 45

Total 580

Source: Author’s own field survey area during 2012-2013

118

There is a primary agricultural credit Samabay Samity at few sample villages. We have

taken different size of villages in terms of the number of total households residing at the

villages. In this sense, Sihar is the largest village and Sarisadighi is the smallest one

among the sample villages. But sample households selected from Sihar is not highest

among the number of households selected from other sample villages because a large

section of the households in this village lies in a homogeneous group. In almost all the

villages, the SHG based micro financing has been functioning but their tenure and

outreach of activities differ from village to village. Most of the groups have been formed

by women. This program includes the village women in the main stream development

process making their financial inclusion and inculcates empowerment. In few villages

women have participated in the NREGA program for supporting their families.

3.8.3. Nature and Scope of Data

We had prepared a structured questionnaire based on the objectives and necessity of our

empirical study. For each village first we have conducted a pilot survey regarding the

village level information. Then, the required data have been collected directly from the

representative women from households. The purposive information has been collected

through personal interview method. A woman from each sample household has been

interviewed personally in a face-to-face contact to collect relevant information. The

conversation was conducted in the local language. Therefore, we can claim that our data

set is purely primary in nature.

In order to study the nature causes and consequences of women empowerment we have

conducted exhaustive household survey and gathered the information regarding the

different indicators of empowerment at the household level and at the community level

as mentioned in section 3.2. Information regarding different household welfare has been

collected to assess to impact of empowerment. Particularly data for several issues on

domestic violence and on decision regarding family planning have also been collected.

We have covered household income and expenditure pattern on food nutrition, on fuel

and energy, on health care and on child education. We have also collected information

regarding some selected socio economic and demographic characteristics of the

respondent women, households and village like social status, age, educational

background of the woman and other household members, occupation of the woman and

occupational structure of the family, landholding, annual family income, dependency

119

ratio, SHG-membership status, caste, religion, distance of household from bank, school,

hospital etc. We have divided categorically all the relevant information into individual,

household and community characteristics. The respondents are not always smart enough

to inform actual figure of the required data. So, we have logically tried to make a

generalization. It is natural that in any type of data collection there may be some sort of

discrepancy or personal bias. In our case we have tried to minimize this problem through

cross checking.

3.8.4. Diagnostic Check for the Sample Size

In order to study women’s empowerment at the household level and at the community

level we have planned to apply factor analysis. So, we should check the factorability of

our data set. The primary condition for applying the factor analysis is that the variables

under consideration, indictors of women’s empowerment in our case, are significantly

correlated with each other. There are two popular tests for diagnostic check of the data

set to be used in factor analysis. One is Bartlett’s test of sphericity and other is the

Kaiser-Meyer-Olkin measure of sampling adequacy.

In order to test the null hypothesis that the correlation matrix of the variable under

consideration is an identity matrix we have used Bartlett's Test of Sphericity based on

the test statistic

2

)1(2

1

2 ~])/1ln()][ln/212(6

1)1[(

kkjIkkDkkn where, k stands for

number of variables, jI denotes jth eigenvalue of D.

Kaiser-Meyer-Olkin measure of sampling adequacy has been used to compare the

magnitudes of the observed correlation coefficients in relation to the magnitudes of the

partial correlation coefficients of the variables with the help of the formula

22

2

ijij

ij

r

rKMO

where, kijr ,....2,1.ij

The range 0.8 to 1.0 of KMO statistic indicates a commendable degree of common

variance. If KMO statistic lies in the range 0.6 to 0.8 we can say that the degree of

120

common variance is mediocre. The value of KMO statistic below 0.6 reveals a miserable

degree of common variance and the researchers should not use the factor analysis. This

methodology suggests that before going to Principal Component Analysis for

empowerment indicators we have to conduct the KMO test of the data set of the

indicators of women’s empowerment. If we find KMO value greater or equal to 0.6 we

apply PCA and otherwise not. We should, therefore, obey this rule in our study of

women’s empowerment.

Once our data set of the indicators of women’s empowerment passes this diagnostic test

we can apply Principal Component Analysis for extracting the factors of women’s

empowerment and their respective weight. It will help us measure a composite index for

women’s empowerment at the household level and at the community level.

3.9. Conclusion

In this chapter we have explained the women’s empowerment conceptually and

quantitatively. We have proposed two alternative methodologies for quantifying the

women’s empowerment at household level and at the community level for the sample

women. The frameworks for studying the impact of women’s empowerment, on

household welfare denoted by the attitudes regarding family planning, domestic violence

against women and children education expenditure have been presented. We have

presented the regression specification of our analytical framework of the issues of

women’s empowerment in the district of Bankura followed by the underlying hypotheses

in the respective models. Given the model, methodology and data, we present and

discuss the empirical findings of the issues relating to women’s empowerment in the

district of Bankura in chapter four and chapter five.

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Chapter Four __________________________________________________

Component Analysis of women’s empowerment

4.1. Introduction

In chapter one we have chalked out some specific research issues related to women’s

empowerment in the district of Bankura that are to be addressed in this dissertation.

Chapter two has exposed the motivation and backdrop of our empirical investigation.

Against this backdrop, in chapter three we have formulated the relevant working models

and set our hypotheses related to the study of women’s empowerment. In this chapter we

are going to discuss the descriptive statistics of our sample women. We analyse the

components of empowerment of the sample women and inter correlations among several

variables in this chapter. For this purpose we have conducted a self-designed household

survey during the period 2012-13.

The route of journey of this chapter has been designed as follows. In section 4.2 we have

presented the descriptive statistics of surveyed households along with its three sub-

sections. In sub-section 4.2.1 we have explained the categorical characteristics of the

sample households followed by the discussion on the categorical characteristics of the

respondents. We have presented the socio-economic variables and demographic

quantitative features of the surveyed population in sub-section 4.2.2. Section 4.3 deals

with the discussion on the relevant indicators of women’s empowerment at the

household level and at the community level. Section 4.4 elucidates findings related to

women’s empowerment indices. It has three sub-sections. Sub-section 4.4.1 deals with

the outcomes of Principal Component Analysis of the household level empowerment of

the women. In sub-section 4.4.2 we have presented the results of the Principal

Component Analysis of the community level empowerment of the women. We have

122

presented the descriptive statistics of the empowerment indices in section 4.4.3. Section

4.5 has explained the profile of inter-correlation among different socio-economic-

demographic and empowerment variables of the sample women/households. We have

concluded this chapter in section 4.6.

4.2. Descriptive Statistics of the Surveyed Households

Nobody would deny that in an empirical study it is very much important to look into the

nature of the socio-economic and demographic characteristics of the surveyed

households and respondents. In order to carry out this empirical analysis we have

conducted a primary level household survey in selected regions of Bankura district, West

Bengal. From this survey and field observations we have collected information about

socio-economic and demographic characteristics of households of our study region. This

empirical study is based on the information of 580 women/households in the district of

Bankura surveyed during the period 2012-13. During the course of our household survey

we have observed that the households surveyed for our study are of different categories

with respect to their family composition, their main source of livelihood, with respect to

their caste and religion. There is also some heterogeneity among the sample

women/households in terms of household income, landholding, family size, number of

child, dependency ratio, household expenditure pattern, social caste and community etc.

With this end in view, we have classified the socio-economic and demographic

characteristics of the surveyed households and women into two types of variables – one

is the categorical variable and other is the quantitative variable. In this section with its

two sub-sections we are going to present the descriptive statistics of the surveyed women

and their households.

4.2.1Categorical Characteristics of the Sample Households/Individuals

In this sub-section we present the categorical characteristics of the sample households

and that of the sample women. Table-4.2.1 depicts the frequency and percentage

distribution of the categorical variables related to households and table-4.2.2 depicts the

percentage distribution of the categorical variables related to the sample women.

The table-4.2.1 shows that out of 580 sample women 475 (81.90 %) women belong to

nuclear family, whereas, only 105 (18.10%) women belong to extended family. It

indicates that most of the sample women in rural Bankura live with their own and next

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generations. In term of household occupation we find that 44.31% of sample households

are engaged in cultivation in their own land. Our study covers two community blocks,

namely, Kotulpur which has cannel and tube well based irrigation facility and Chhatna

which has no developed irrigation facility for cultivation. As a result we find that farmers

of Kotulpur block can engage themselves in agricultural works throughout the year while

most of the farmers of Chhatna block stay unemployed seasonally. The main occupation

of one third of the surveyed households is wage labour. A major section of this wage

labour is engaged in agriculture. Like the farmers, agricultural labourers in Chhatna

block remain unemployed seasonally and agricultural labourers in Kotulpur get job

almost whole year. We have observed that the wage rate of agricultural labourer in

Chhatna is lower than that of the agricultural labourers in Kotulpur block. A large

number of respondents have reported that the program of NREGA recently reduces the

length of seasonal unemployment and makes a wage hike for the agricultural labourers in

the area under study. However, farmer households have reported that NREGA program

sometimes creates the shortage of labour at the sowing and harvesting time and as a

result it makes the cultivation costly. Moreover, a good number of the wage labourers in

our surveyed area works at brick field, sand lifting field, stone crashing and

constructional activity. Of the sample households 14.31% earns their livelihood mainly

from self-employment. Our field observations show that most of the self-employment

activities of our sample households are either grocery shop or some traditional ancestry

occupations like, worshipping, barbering, pottery, cobbler, carpentry, etc. Only seven

percent of the sample households belong to service sector by occupation. It is pointed out

that majority of the service holders in the area under study are engaged in education

sector or in defense sectors.

Our study covers four categories of castes. We find from the table that 31.21% of sample

households belong to general caste, 23.28% to other backward classes, 33.62% to

scheduled caste and 11.90% to scheduled tribes. As majority of the households in the

district of Bankura are under Hindu religion the sample survey has covered most of

Hindu households. This table shows that 97.07% of households belong to Hindu religion

and the remaining households belong to Muslim (2.93%). In accordance with the

notified poverty line (BPL card holders) our study observed that nearly 41.90% of

sample households live above poverty line whereas 58.10% below the poverty line.

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Table-4.2.1 Distribution of the Categorical Variables of the Sample Households

Variable Category Frequency Percent Cumulative

Percent

Family Composition Extended 105 18.10 18.10

Nuclear 475 81.90 100.00

Household Occupation

Cultivation 257 44.31 44.31

Self-employment 83 14.31 58.62

Wage labour 198 34.14 92.76

Service 42 7.24 100.00

Social Caste of the

Sample Households

General Caste 181 31.21 31.21

Other Backward Classes 135 23.28 54.48

Scheduled Caste 195 33.62 88.10

Scheduled Tribe 69 11.90 100.00

Religion Muslim 17 2.93 2.93

Hinduism 563 97.07 100.00

Economic Status Above Poverty Line 243 41.90 41.90

Below Poverty Line 337 58.10 100.00

Accessibility to Adequate

Sanitation

No 398 68.62 68.62

Yes 182 31.38 100.00

Access to Safe Drinking Water No 405 69.83 69.83

Yes 175 30.17 100.00

Access to Advanced Cooking

Fuel

No 435 75.00 75.00

Yes 145 25.00 100.00

Whether any household

member is addicted in drug

(like smoking, tobacco, liquor,

etc.)

No 280 48.28 48.28

Yes 300 51.72 100.00

Access to Affordable housing No 203 35.00 35.00

Yes 377 65.00 100.00

Prevalence of Child death

before completing five Years

of Age

No 514 88.62 88.62

Yes 66 11.38 100.00

Source: Author’s computation based on primary data, 2012-13

Although several governmental and non-governmental sanitation programs have been

functioning for last one and half decades in the area under study, we observe that only

31.38 % of our sample households have accessibility to adequate sanitation. We find that

only 30.17% of sample households have accessibility to safe drinking water. A large

number of households have reported that they collect drinking water from their own or

neighboring house’s well or tube well where water is contaminated with huge iron and

other unhygienic minerals. Most of the women have not access to advanced cooking

fuel. Only 25% have accessibility to it. Our study shows that at least one member of

51.72% sample households is addicted to smoking, tobacco, liquor etc. However, we

find that most of the sample women are not addicted to any kind of drug. Only a few are

addicted to tobacco (gurakoo) and a handful of women smoke. In terms of affordable

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housing defined as the per capita number of rooms in the house being greater or equal to

one, 377 households have accessibility to affordable house. They are 65% of our total

sample households and the remaining 35% have not accessibility to it. We find that there

is prevalence of child death before completing five years of age in 11.38% of sample

households in the area under study. It is greater than the rate of child death prevalence in

our country as a whole (Economic Survey, 2012-13).

Table 4.2.2 gives the percentage distribution of the individual categorical variables of

sample women. All sample women are of age eighteen or above eighteen years. We find

that out of 580 sample women 64 (11.03%) women are of age below twenty five years,

207 (35.69%) women belong to age group 25-35 years, 199 (34.32%) women belong to

age group 36-45 years and 110 (18.96%) women are of age above 45years. The age

distribution of the sample women shows that our study has covered all age groups of

women. It will help us study the nature and consequences of empowerment in different

age groups of women in Bankura district, W.B. In our sample most of the women are

married (92.93%). A very few proportion of the sample women are separated with

husband (0.52%). Our sample consists of 6.55% widow.

We find that nearly half of the sample women (49.7%) are exclusively homemaker. Our

field survey finds that 15.3% of sample women work in their family land together with

other family members. We have got 7.10% of our sample respondents as self employed.

One fourth of the sample women works as wage labours. Among the wage labourers

most of the women work in agricultural sector. In this sample only 3.6% of the women

are engaged in service sector. Note that among the service holders majority are serving

the education sector. One or two are engaged in health sectors. No one woman in our

sample is serving as administrator.

This table shows that 61.38% of the sample women have savings account in a bank,

whereas only 38.62% do not have bank account. It means that a large part of the rural

women in the district of Bankura are financially excluded. We find that 43.97% are

member of self-help group and 56.03% are not member of any self-help group.

Therefore, the SHG-centric microfinance program has covered a broads section of the

rural women in the inclusive development process. In our sample 40.69% of women

have their own mobile phone.

126

Table-4.2.2 Percentage Distribution of the Individual Categorical Variables

Variable Category Frequency Percent Cumulative

Percent

Age

<25 Year 64 11.03 11.03

25-35Year 207 35.69 46.72

36-45Year 199 34.32 81.04

45< Year 110 18.96 100.00

Marital Status

Divorce 3 0.52 0.52

Married 539 92.93 93.45

Widow 38 6.55 100.00

Personal Occupation

Homemaker 288 49.7 49.7

Farming 89 15.3 65.0

Self-employed 41 7.10 72.1

Wage labour 141 24.30 96.4

Service 21 3.6 100.00

Savings Bank Account Holder No 224 38.62 38.62

Yes 356 61.38 100.00

Self-Help Group Membership No 325 56.03 56.03

Yes 255 43.97 100.00

Mobile Phone Holder No 344 59.31 59.31

Yes 236 40.69 100.00

Dowry Given at Marriage No 179 30.86 30.86

Yes 401 69.14 100.00

Post Marriage Dowry Demand No 489 84.31 84.31

Yes 91 15.69 100.00

Experience of any kind of

Domestic Violence

No 194 33.45 33.45

Yes 386 66.55 100.00

Experience of Physical Violence

from Family members

No 253 43.63 43.28

Yes 327 56.37 100.00

Response toward Family Planning

Negative 236 40.69 40.69

Positive 344 59.31 100.00

Source: Author’s computation based on primary data, 2012-13

Most of the sample women (69.13%) have reported that their guardians gave dowry to

their bridegroom at the time of their marriage. It has been found that 15.69% of sample

women fulfil the post marriage dowry demand of their in-laws. Our study shows that

66.55% have the experience of any kind of domestic violence and 56.37% have the

experience of physical violence. This dissertation has tried to find out the nature and

causes of domestic violence of the rural women in the district of Bankura. We find that

59.31% have taken family planning decision. So, a large section of rural women in

Bankura district is still not conscious regarding the family planning. Therefore, the study

127

of the nature and causes of the response towards family planning in the area under study

is also a relevant issue and it has been addressed in this dissertation.

4.2.2 Socio-Economic and Demographic Characteristics of the Surveyed Population

This section describes the summary statistics of the quantitative variables in question.

Table-4.2.3 presents the demographic profile of sample women. Table-4.2.4A and table-

4.2.4B present the descriptive statistics of the socio-economic variables of our surveyed

households.

Table-4.2.3 Relevant Demographic Profile of the Sample Households

Family

Size

(Number)

Number

of

Children

Age

(Year)

Age of

Husband

(Year)

Spousal

Age

Gap

(year)

Duration

of

Marriage

(Year)

Age at

Marriage

Time

(Year)

Dependency

Ratio (%)

Mean 3.86 1.53 35.62 41.36 5.74 16.87 18.75 49.68

Median 4.00 2.00 35.00 40.00 5.00 17.00 19.00 50

Max. 8.00 5.00 65.00 72.00 22.00 55.00 42.00 100

Mini. 1.00 0.00 18.00 21.00 0.00 0.00 13.00 0

S D. 1.17 0.96 9.61 10.25 2.83 9.41 4.92 21.98

Skew. 0.29 0.23 0.50 0.47 1.52 0.62 0.25 -0.66

Kurtosis 3.30 3.02 2.99 2.95 6.79 3.36 6.94 2.95

Source: Author’s computation based on primary data, 2012-13

We find from table-4.2.3 that on an average each family has 3.86 members while

maximum number in a family is 8. This table shows that the half of the sample families

has more than 2 children. The average age of the respondents is 35.62 years. The Median

value of the age of sample women in the area under study is 35 years. The physical age

of the sample woman ranges from 18 years to 65 years. We find from this table that

average age of the husbands of the respondents is 41.36 years. The ages of the husbands

range from 21 years to 72 years. The average of the difference of ages between husband

and wife is 5.74 years, while the maximum age difference is 22 years. On an average

duration of married life is 16.87 years. The median value of the duration of married life

is 17 years. Our field survey has reported that the average age at the time of marriage is

18.74 years with a minimum age at marriage 13 years. Our household survey shows that

the average dependency ratio is 49.68%. This means that half of the family members in

average depend on other for their bread and butter.

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Table-4.2.4A describes the socio-economic variables of the sample households. The

average annual per capita income of a family is Rs 13790.00. The median of annual per

capita income is Rs 10510.00. This means that the majority of the sample family lies

below poverty line. The maximum value of per capita household income of the surveyed

households is Rs 150000.00 and the minimum of that is Rs 3900.00. This implies that

sample families are basically poor. Moreover, some families earn nothing to live their

livelihood. This table shows that average monthly income of the surveyed women is Rs

594.00 with its maximum value Rs 35000.00 and minimum value Rs 00.00. The median

value personal monthly income is Rs 350.00. This implies that half of the sample women

earn less that Rs 350.00 in a month. It focuses that majority of the working women in the

district of Bankura is ill paid.

Table-4.2.4A Socio-economic Characteristics of the Sample Households

Annual

Per capita

Income

(Rs. ‘000)

Monthly

Personal

Income

(Rs. ’00)

Monthly

Expenditure

for

Education

(Rs. ’00)

Monthly

Expenditure

for Energy

& Fuel

(Rs. ’00)

Monthly

Expenditure

for Food &

Nutrition

(Rs. ’00)

Monthly

Expenditure

for Health

& Hygiene

(Rs. ’00)

Land

Holding

(Bigha)

Mean 13.79 5.94 2.79 2.77 20.11 2.50 2.64

Median 10.51 3.50 1.50 2.00 18.50 2.00 2

Maximum 150.00 350.00 30.00 20.00 54.00 50.00 16

Minimum 3.90 0.00 0.00 0.00 2.14 0.20 0

Std. Dev. 13.87 20.50 4.01 2.78 8.54 2.76 2.99

Skewness 5.44 12.09 3.04 2.47 1.16 9.68 1.53

Kurtosis 41.42 177.56 15.24 10.95 4.66 154.63 4.99

Source: Author’s computation based on primary data, 2012-13

Table-4.2.4A shows that on an average each family spends Rs 279.00 per month for their

children’s education. The average monthly expenditures for ‘food and nutrition’ and

‘health and hygiene’ are Rs 2011.00 and Rs 250.00. The average of household’s

agricultural land holding for all sample households (including landless and landed) is

2.64 bigha (1 bigha= 0.4 acre). Agricultural land holding is one of the major sources of

income for poor rural household. The household’s agricultural landholding ranges from

zero to sixteen bigha. Apparently, holding sixteen bigha of agricultural land is good in

size. But it is not the fact. It is good only if it is in the fertile part of our study area,

Kotulpur. It does not necessarily imply the well economic condition of the households if

it is on rocked and drought prone area like the block Chhatna. So, we should not

129

concentrate on its range. The median value of household’s land holding is 2 bigha. This

means that half of the surveyed households own less that 2 bigha of land. In terms of

landholding this study confirms that households belong to small and marginal farmers.

We can conclude from the income as well as expenditure pattern of surveyed households

that we are going to examine the empowerment status of women of poor society in the

district of Bankura.

Table-4.2.4B Socio-economic Characteristics of the Sample Households

Statistics

Education

of the

Respondent

woman

(Year)

Spouse

Educational

Gap (Year)

Husband’s

Education

(Year)

Highest

Education level

among

household

males(Year)

Highest

Education

level

among

females

(Year)

Duration of

SHG

membership

(month)

Mean 3.59 1.27 4.87 6.99 5.54 27.24

Median 1.00 0.00 5.00 8.00 6.00 0

Maximum 17.00 15.00 17.00 17.00 17.00 145

Minimum 0.00 -10.00 0.00 0.00 0.00 0

Std. Dev. 4.16 2.98 4.77 4.57 4.55 36.79

Skewness 0.74 0.52 0.40 -0.12 0.21 1.15

Kurtosis 2.43 5.22 1.98 2.23 2.07 3.46 Source: Author’s computation based on primary data, 2012-13

We now illustrate the table-4.2.4B. It describes some socio-economic variables of

sample households. We see from this table that the level of education of the respondent

women varies from zero to seventeen years but mean of the level of education is only

3.59 years. This finding indicates that the average of sample women cannot complete the

primary level of education (fourth class standard). Besides the education level of the

respondent women, we have recorded information about the educational levels of the

other members of the family with the intention of exploring the relation between

family’s educational background and women’s empowerment. This table shows that the

average level of education of husbands of the respondent women is 4.87 years.

Education level of the husbands ranges from zero to seventeen years in formal

educational institution. We have calculated that the average of the gap of education

between husband and wife is 1.27 years. The positive value of this gap implies that in

most of the cases husbands are more educated than their wives. The median value of

these differences is zero. This means that in fifty percent cases wives are equally

educated as their husband.

130

Table-4.2.2B also shows that mean of the highest educational qualification among the

male members of family in the surveyed families is 6.99 years. The mean of highest

female education other than the respondent woman is 5.54 years. The table exhibits that

average of the highest education of female is lower than that of male among the sample

families. It has been noted that average of the highest education level of male and female

are relatively higher than the average education level of the persons interviewed for the

study. Therefore, in terms of education, our sample households as well as respondents

are not forward enough. Our study has captured another socio-economic attribute of the

sample women i.e., whether she is a member of SHG-based microfinance program or

not. We have found that the majority of the surveyed women are member of SHG with

average duration of membership of two years and three months. The highest length of

membership of our sample women is twelve years. During the course of our field survey

we have observed that regarding the financial service the primary cooperative societies

have come forward compared to the government program (SGSY) and banking sector in

the area under study.

4.3. Frequency Distribution of the Indicators of Women’s Empowerment at

Household Level and at Community Level

In this study we have measured empowerment of women at household and community

level. To this end, we have set some indicators. In this section we will show the frequency

distribution of these indicators. Table-4.3.1A and table-4.3.1B show the percentage

distribution of the indicators of women’s empowerment at household level. We have

presented the percentage distribution of the indicators of women’s empowerment at

community level in table- 4.3.2A and in table-4.3.2B.

Table-4.3.1A illustrates the indicators of economic, political and socio-cultural

dimensions of women’s empowerment at household level. From the economic dimension

we see that that 71.9% respondents have control over their own income, 79.83% have

access to household resources. This table exhibits that 12.07% of the sample women bear

more than fifty percent of household expenditure, 46.38% bear less than fifty percent of

household expenditure and 41.55% bear no part of it. We see that 6.9% respondent

women take the saving and investment decision of their own; 79.66% take this decision

jointly with their husbands; 8.62% decide on this matter by consulting with other

member in the family and 4.83% cannot opine in this matter.

131

Table-4.3.1A Percentage Distribution of the Indicators of Women’s Empowerment

at Household Level Indicator Value Frequency Percent Cumulative (%)

Eco

no

mic

Dim

ensi

on

Whether she has control over her personal

income/asset (COPI) (Yes=1) 0 163 28.1 28.1

1 417 71.9 100

Whether she can have access to household

resources (ACHR) (Yes=1)

0 117 20.17 20.17

1 463 79.83 100

Proportion of household expenditure that she

bears (PHESB)(None = 0/ less than 50% = 1

/greater than 50%=2)

0 241 41.55 41.55

1 269 46.38 87.94

2 70 12.06 100

Who decide the use of saving/ loan? (DUSOL)

(Own =4 / with spouse = 3/ with other family

member =2 /other members =1)

1 28 4.83 4.83

2 50 8.62 13.45

3 462 79.66 93.1

4 40 6.9 100

Does she take part in the decision for selling or

buying asset for household? (SOBHA) (Yes=1) 0 53 9.14 9.14

1 527 90.86 100

Does she enjoy freedom in choosing her

occupation? (CHOU) (Yes=1) 0 377 65 65

1 203 35 100

Po

liti

cal

Dim

ensi

on

Do you get domestic support for your political

engagement? (DSPE)(Yes=1) 0 502 86.55 86.55

1 78 13.45 100

Does she know the name of local (panchayat

pradhan / councilor/ MP/ MLA)? (KLPL)

(Yes=1)

0 92 15.86 15.86

1 488 84.14 100

Whether she know the candidate of opposition

party in the last election. (KOPL) (Yes=1) 0 423 72.93 72.93

1 157 27.07 100

Did she cast her vote in the last election?

(CASVO) (Yes=1) 0 83 14.31 14.31

1 497 85.69 100

Does other influence her to cast her vote?

(INVO) (Yes=0) 0 46 7.93 7.93

1 534 92.07 100

So

cio

-Cu

ltu

ral

Dim

ensi

on

Does she regularly enjoy Radio, telephone, TV

and Newspaper? (ENTM) (Yes=1) 0 244 42.07 42.07

1 336 57.93 100

Whether she is free to move outside your home.

(FMOH) (Yes=1) 0 73 12.59 12.59

1 507 87.41 100

Do you want to educating your girl or other

girls in your household (GEDU) (Yes=1)

0 190 32.76 32.76

1 390 67.24 100

Whether or not she participates in local cultural

programs.(PLCP) (Yes=1) 0 298 51.38 51.38

1 282 48.62 100

Whether she want to send her child for earning.

(CLAB) (Yes=0) 0 348 60 60

1 232 40 100

Would you arrange the marriage of the girls

before their eighteen years old or support it?

(CMAR) (Yes=0)

0 402 69.31 69.31

1 178 30.69 100 Source: Author’s computation based on primary data, 2012-13

132

It is revealed that 90.86% of sample women take part in the decision of selling or buying

household asset and 35% of them enjoy the freedom in choosing their own occupation.

We have seen that in the case of some indicators women in the district of Bankura are

well-off but in many cases they are worse-off. Therefore, it is difficult to judge the

nature of economic empowerment of the sample women from the percentage distribution

of the indicators.

This study has considered five indicators to cover the political dimension of women’s

empowerment at the household level. Table-4.3.1A shows that only 13.45% of the

sample women get domestic support for their political engagement. We have come to

know from this table that 84.14% of the respondents know the names of local Panchayet

-pradhan/ MP/MLA where as only 27.07% know the name of the candidate of opposition

party. This table also discloses the fact that though 85.69% cast their vote in last election

and 7.93% has been influenced by other regarding the issue of casting of vote and whom

to cast vote. We see that there is a disparity regarding the favourable responses towards

political empowerment at the household level of our sample women.

Let us consider the socio-cultural dimension which has five criteria. This table shows

that 57.93% of respondent enjoy radio, television, telephone and newspaper regularly;

87.41% have the freedom to move outside of their home and 67.24% want to educate

their own girl child and other girl in their family. We find from this table that 48.62%

participate in local cultural programme. It has also been reported that 60% of the

respondents are ready to send their child for earning and 69.31% support the marriage of

girl before reaching the age of eighteen. These results portray a very awful picture of

poverty as well typical psychology about girl chid in our society.

We, now, turn to table-4.3.1B. It is an extension of the previous table. It shows the

frequency distribution of the indicators of familial/personal dimension and that of legal

dimension. The familial/personal dimension and legal dimension have five indicators

each. From our field survey, we have come to know that only 6.9% of the sample

respondents’ marriages were arranged on self decision. It has been reported that 79.83%

of respondents can articulate their personal problems to other family members. We have

observed that in 17.41% cases some other person/household members interfere during

the time of the interview. More than half of the respondents (53.45%) have told us that

133

they can independently decide on their child education, health, food etc. This table

shows that 63.97 % of sample women have decision making power regarding their

personal health, body and family planning.

Table-4.3.1B Percentage Distribution of the Indicators of Women’s Empowerment

at Household Level

Indicator Value Frequency Percent

Cumulative

Percent

Per

son

al /

Fam

ilia

l D

imen

sio

n

Whether her marriage is arranged or self selection.

(MATY) (Self selection=1)

0 540 93.1 93.1

1 40 6.9 100

Can she articulate her personal problem to other

family members? (ARTIP) (Yes=1)

0 117 20.17 20.17

1 463 79.83 100

Whether anybody interfere when she talk to

stranger. (INFE) (Yes=0)

0 101 17.41 17.41

1 479 82.59 100

Whether or not she can independently decide about

your child education, health, food etc.(INDEC)

(Yes=1)

0 270 46.55 46.55

1 310 53.45 100

Whether she has decision making power regarding

her personal health, body, and family planning

(PDEC) (Yes=1)

0 209 36.03 36.03

1 371 63.97 100

Leg

al D

imen

sio

n

Whether she know about the mechanism of justices

used in the locality (KAMJ) (Yes=1)

0 96 16.55 16.55

1 484 83.45 100

Does she think women and men get equal treatment

from this system? (TRMW) (Yes=1) 0 189 32.59 32.59

1 391 67.41 100

Whether she knows the laws and legislation

available in favour of women. (LAFW) (Yes=1) 0 197 33.97 33.97

1 383 66.03 100

Whether she know about the various kinds of

public services available in the locality. (PUBS)

(Yes=1)

0 238 41.03 41.03

1 342 58.97 100

Whether your marriage is registered or not(MARR)

(Yes=1) 0 558 96.21 96.21

1 22 3.79 100 Source: Author’s computation based on primary data, 2012-13

Let us now consider the indicators of the legal dimension. Table-4.3.1B shows that

83.45% of the sample women know about the mechanism of justice used in the locality.

This study finds that 67.41% of the respondents think that women and men get equal

treatment from this system of justice. It is revealed that 66.03% of respondents are

familiar with the laws and legislation available in favour of women and 58.97% know

the various kinds of public services available in their locality. This study unveils the fact

that the marriage of only 3.79% of the respondents is registered. The above information

regarding the indicators of empowerment tells us that in terms of some indicators women

134

in the district of Bankura are forward but in other cases they have huge lag. Therefore,

the percentage distribution of the indicators of women’s empowerment at the household

level is not sufficient to understand the overall nature of empowerment at the household

level. With this end in view, we have tried to make component analysis for analysing the

overall empowerment of the women at the household level.

Table-4.3.2A and table-4.3.2B show the percentage distribution of the indicators of

women’s empowerment at the community level. Table-4.3.2A shows the percentage

distribution of indicators of economic, political and socio-cultural dimension of women’s

empowerment at the community level. We find that 52.07% women earn money; 85.17%

have land or property of their own and 54.83% has access to formal saving, insurance,

loan etc. Half of the sample women (50.17%) have access to formal education and

training as per their own requirement. About 4.14% report that other person threats them

to evict from property. Table-4.3.2A shows that the occupation of 51.55% of the sample

women is secured. It roughly indicates that almost half of the sample women have no

livelihood security.

The indicators of political dimensions of women’s empowerment at community level

reveal that one fifth of the respondents are involved in active politics and 8.10%

introduce themselves as volunteer of any political party. It has been reported that 42.93%

willingly attend political gathering and 3.62% contest any kind of vote as a

representative at least once in life. We have found that one third of our sample member

act as leader of an organization.

Frequency distribution of the indicators of the socio-cultural dimension tells that 47.07%

of the respondents are member of any social organization. About 22.07% of sample

women think that they can influence the election or selection of leader of these

organization or group. This table shows that 63.79% participates in community activity.

We know from the table-4.3.2A that almost all of the sample women (95.34%) know the

location of nearest post office, school, hospital, club, vegetable market etc. This study

reveals that 15% of the sample women feel exclusion from participation in some

community activities because of being women.

135

Table-4.3.2A Percentage Distribution of the Indicators of Women’s Empowerment

at the Community Level

Indicator Value Frequency Percent

Cumulative

Percent

Eco

no

mic

D

imen

sio

n

Whether she is employed/earner or not.(EARN)

(Yes=1)

0 278 47.93 47.93

1 302 52.07 100.00

Whether she has ownership of land or property or

not.(OWLP) (Yes=1) 0 86 14.83 14.83

1 494 85.17 100.00

Whether she has access to formal savings,

insurance, loan etc.(ASIL) (Yes=1) 0 262 45.17 45.17

1 318 54.83 100.00

Whether she has access education or training

service when she needs it.(AEDU) (Yes=1) 0 289 49.83 49.83

1 291 50.17 100.00

Whether anybody threats you to evict from

property (THPRO) (Yes=0) 0 24 4.14 4.14

1 556 95.86 100.00

Whether your present occupation is secured or not

(SEOC) (Yes=1) 0 281 48.45 48.45

1 299 51.55 100.00

Po

liti

cal

Dim

ensi

on

How does she involve in political process?

(INVOL) (Yes=1) 0 460 79.31 79.31

1 120 20.69 100.00

Whether she is a volunteer of any political party

(VOLP) (Yes=1) 0 533 91.90 91.90

1 47 8.10 100.00

Whether she attends any political gathering or not

(ATPM). (Yes=1) 0 331 57.07 57.07

1 249 42.93 100.00

Did you ever contest vote as a representative

(CTEST) (Yes=1) 0 559 96.38 96.38

1 21 3.62 100.00

Are you leader of any organization (LEAD)

(Yes=1) 0 381 65.69 65.69

1 199 34.31 100.00

So

cio

-Cu

ltu

ral

Dim

ensi

on

Whether she is a member of any social

organization or group (MEMSO) (Yes=1) 0 307 52.93 52.93

1 273 47.07 100.00

Whether she can influence the election/ selection

in the organization/group (INFLU) (Yes=1) 0 452 77.93 77.93

1 128 22.07 100.00

Does she participate in community activity?

(CACT) (Yes=1) 0 210 36.21 36.21

1 370 63.79 100.00

Whether or not she knows the location of the

nearest post-office, school, hospital, club,

vegetable market, etc. (KLSI) (Yes=1)

0 27 4.66 4.66

1 553 95.34 100.00

Does she feel exclusion from participation in any

community activity? (SEXL) (Yes=0) 0 86 14.83 14.83

1 494 85.17 100.00

Does she oppose the social curses a) Dowry

system, b) against Inter-caste marriage, c)

preference of male child d) against women

reservation e) child marriage f) against family

planning (OSOC)

(Value indicates number of opposed item )

0 9 1.55 1.55

1 78 13.45 15.00

2 203 35.00 50.00

3 139 23.97 73.97

4 113 19.48 93.45

5 31 5.34 98.79

6 7 1.21 100.00 Source: Author’s computation based on primary data, 2012-13

136

Table-4.3.2B Percentage Distribution of the Indicators of Women’s Empowerment

at the Community Level

Indicator Value Frequency Percent

Cumulative

Percent

Per

son

al/F

amil

ial

Dim

ensi

on

Did she ever campaign against social curse like

dowry, violence? (CASC) (Yes=1)

0 547 94.31 94.31

1 33 5.69 100.00

Whether she has professional training or not

(PTRN)(Yes=1)

0 421 72.59 72.59

1 159 27.41 100.00

Has she voluntarily changed her occupation

after marriage?(CHAM) (Yes=1)

0 295 50.86 50.86

1 285 49.14 100.00

Did she sacrifice employment or membership

of any organization due to familial ground?

(SACE)(Yes=0)

0 7 1.21 1.21

1 573 98.79 100.00

Whether she immunize her children in due

time.(EMUN) (Yes=1)

0 58 10.00 10.00

1 522 90.00 100.00

Leg

al D

imen

sio

n

Whether she ever used the local mechanism to

justices (ACCJ) (Yes=1)

0 538 92.76 92.76

1 42 7.24 100.00

Is she active in complaining about any problem

to the system of justice? (ACTC) (Yes=1)

0 189 32.59 32.59

1 391 67.41 100.00

Whether authorities are more or less effective

when other people’s concern compared to

yours? (AATY) (More= 0, less=1).

0 157 27.07 27.07

1 423 72.93 100.00

Whether she complains about the deficiency of

public services in her locality (CDPS) (Yes=1)

0 542 93.45 93.45

1 38 6.55 100.00

Source: Author’s computation based on primary data, 2012-13

Let us concentrate on table-4.3.2B where the indicators of personal/familial dimension

and legal dimension of women’s empowerment at community level have been presented.

It is revealed that only 5.69% of sample women have campaigned against social curses

like dowry, violence etc. This table shows that 27.41% have professional training and

49.14% have voluntarily changed their occupation after marriage. This table shows that

1.21% sacrifice their employment or membership of any organization due to familial

ground. We find from this table that 90% of sample women immunize their children in

due time. It is good for the health of future generation.

Statistics of the indicators of the legal dimension shows that 7.24% have got the help of

local mechanism to justice in contrast to 67.41% is active in complaining about any

problem to the system of justice. About 27.07% of respondents complain that the

authorities are more effective to other people compared to them in the matter of justice.

In our sample 6.55% women complain about the deficiency of public services in their

137

locality. The description of the indicators of the women’s empowerment at the

community level shows that in some cases women are advantageous and in other cases

they are disadvantageous in position. Therefore, it is not sufficient to study the overall

empowerment at the community level. We, therefore, have planned to construct

empowerment indices at the household level and at community level. The findings of the

empowerment indices have been discussed in the next section.

4.4. Analysis of Women’s Empowerment Indices

In order to quantify the empowerment level for the women in the district of Bankura we

have developed the women’s empowerment index in two ways. We have first computed

the degree of empowerment at the household level as well as at the community level.

The degree of empowerment has been computed by the ratio of the number of favourable

responses of the indicators of empowerment to the total number of indicators set for

capturing the empowerment. The degree of empowerment has been expressed as

percentage. This section along with its subsections gives the descriptive statistics of the

degree of empowerment and the descriptive statistics of the composite index of women’s

empowerment at the household level as well as at the community level.

4.4.1. Outcomes of Principal Component Analysis of the Household Level

Empowerment of Women

Before going to discuss the findings of the PCA we have checked the applicability of this

analysis in our study sample. For this purpose we have applied Kaiser-Meyer-Olkin

(KMO) measure of sample adequacy and Bartlett’s test of Sphericity. Now we look at

the findings of these tests.

Table 4.4.1 Results of KMO and Bartlett’s Test for Sample Adequacy for Factor

Analysis of Women’s Empowerment at the Household Level

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.718

Bartlett's Test of Sphericity

Approx. Chi-Square 2384.175

Degrees of freedom 351

Significance. 0.000

Source: Author’s computation based on primary data, 2012-13

KMO measure evaluates the total correlation and partial correlations to determine

whether the data are likely to coalesce on components. By definition the value of KMO

138

measure ranges from 0 to 1. From the above table- 4.4.1 we find that the value of Kaiser-

Meyer-Olkin (KMO) measure of sampling adequacy is 0.71 (greater than 0.6 is desirable

as prescribed by UCLA Academic Technology Service). It indicates that the sample size

of this study is adequate for Principal Component Analysis. The Bartlett’s Test of

Sphericity examines whether the correlation matrix of the variables under consideration

is an identity matrix. The value of chi-square statistic in Bartlett’s Test of Sphericity is

also statistically significant. It confirms that the selected indicators of empowerment of

women are inter-correlated. Therefore, PCA is appropriate methodology for analyzing

the importance of the selected indicators in measuring empowerment of women at the

household level.

Table-4.4.2 presents the detailed results of the Principal Component Analysis which

reveal the variance explained by the components at initial situation, after extraction and

after rotation. The components have been extracted using Kaiser Criteria and rotated

imposing Varimax rotation method. This study has considered nine Principal

Components which have Eigen values greater than one. Rotation Sums of Squared

Loadings indicate that the first rotated principal component explains 10.46 per cent of

total variation in household level empowerment of women. The second and third rotated

principal components explain 7.41 per cent and 6.51 per cent of variance respectively.

Nine components altogether account for 55 per cent of total variation in the

empowerment of women at the household level.

Table-4.4.3 shows the rotated component matrix of women’s empowerment at the

household level. It represents rotated factor loadings. We see that the indicators

belonging to legal dimension have got highest importance in the construction of

Component-1. It indicates that legal dimension is the most important factor of women’s

empowerment at household level. Most of the important indicators of Components-2 and

Component-4 are belonging to socio-cultural dimension. Component-3 has been

weighted high by the indicators of economic dimension. The Component-5 and the

Component-8 capture the political dimension of the empowerment. The indicators that

load high on Component-6 and Component-9 are belonging to personal/familial

dimension. The indicators with highest loading in Component-7 don’t cover any specific

dimension. Therefore, the components under consideration cover all dimensions and are

not inter-correlated. Finally, weighted sum of the components, where weights are the

139

percentage of variance in the data set of the indicators explained by the particular

component, has been considered as the composite index of empowerment at the

household level for the women in the district of Bankura.

Table-4.4.2 Total Variance in the Indicators of Women’s Empowerment Explained

by the Components at the Household Level

Extraction Method: Principal Component Analysis

Rotation Method: Varimax

Co

mp

on

ent Initial Eigen values

Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

Total % of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 3.432 12.712 12.712 3.432 12.712 12.712 2.824 10.459 10.459

2 2.102 7.785 20.496 2.102 7.785 20.496 2.001 7.412 17.870

3 1.831 6.783 27.279 1.831 6.783 27.279 1.758 6.511 24.381

4 1.385 5.130 32.409 1.385 5.130 32.409 1.751 6.484 30.865

5 1.306 4.837 37.246 1.306 4.837 37.246 1.424 5.275 36.140

6 1.272 4.709 41.955 1.272 4.709 41.955 1.410 5.222 41.363

7 1.214 4.496 46.451 1.214 4.496 46.451 1.222 4.527 45.889

8 1.139 4.220 50.671 1.139 4.220 50.671 1.197 4.434 50.323

9 1.066 3.950 54.621 1.066 3.950 54.621 1.160 4.298 54.621

10 0.971 3.597 58.218

11 0.928 3.437 61.655

12 0.920 3.406 65.061

13 0.889 3.292 68.353

14 0.816 3.021 71.374

15 0.793 2.936 74.310

16 0.780 2.887 77.198

17 0.754 2.793 79.990

18 0.743 2.752 82.742

19 0.714 2.644 85.386

20 0.669 2.478 87.864

21 0.647 2.397 90.261

22 0.600 2.221 92.482

23 0.508 1.881 94.363

24 0.490 1.814 96.177

25 0.463 1.713 97.891

26 0.354 1.313 99.204

27 0.215 .796 100.00

Source: Author’s computation based on primary data, 2012-13

140

Table-4.4.3 Rotated Component Matrix of Women’s Empowerment at Household

Level

Extraction Method: Principal Component Analysis

Rotation Method: Varimax with Kaiser Normalization

Rotation converged in 9 iterations

Indicator Component

1 2 3 4 5 6 7 8 9

eco

no

mic

COPI 0.099 0.504 0.234 -0.024 -0.220 0.116 0.023 -0.241 -0.030

ACHR 0.001 0.054 0.599 0.027 -0.111 0.086 0.138 -0.083 0.001

PHESB -0.062 -0.140 0.585 -0.050 0.091 -0.056 0.187 0.458 0.101

DUSOL -0.003 0.085 0.717 -0.003 0.138 -0.026 -0.155 0.012 -0.006

SOBHA 0.019 0.112 0.486 0.232 -0.019 0.226 -0.066 -0.262 -0.014

CHOCU 0.054 -0.193 0.088 0.028 -0.029 -0.003 0.653 0.187 -0.028

po

liti

cal

DSPE 0.067 0.013 0.003 0.105 0.727 -0.033 0.049 -0.178 0.008

KLPL 0.004 0.632 -0.085 0.009 0.251 0.055 -0.257 0.090 -0.028

KOPL 0.173 0.156 0.047 0.164 0.698 0.104 -0.050 0.080 0.049

CASVO -0.001 0.264 -0.017 -0.299 0.360 0.112 0.476 0.011 -0.095

INVO 0.153 0.124 -0.127 0.092 -0.157 0.120 0.068 0.667 0.029

So

io-c

ult

ura

l

ENTM 0.219 0.646 -0.049 0.264 0.069 -0.094 -0.059 0.087 0.012

FMOH 0.327 0.480 0.130 -0.114 0.119 0.146 0.098 -0.158 0.053

GEDU -0.128 0.192 -0.196 0.283 -0.032 -0.069 0.473 -0.282 0.156

PLCP 0.067 0.576 0.133 0.071 0.036 -0.263 0.156 0.110 0.055

CLAB -0.066 0.074 0.084 0.768 0.127 -0.092 0.022 0.010 -0.027

CMAR 0.007 0.034 0.032 0.793 0.114 0.033 0.009 0.043 0.008

per

son

al/f

amil

ial

MATY -0.076 0.063 0.045 -0.097 0.065 0.157 0.085 0.184 0.704

ARTIP 0.044 0.178 -0.037 0.300 -0.084 0.282 0.114 -0.133 -0.432

INFE 0.067 0.034 0.171 0.115 -0.028 -0.556 0.056 -0.231 0.018

INDEC 0.045 0.029 0.174 0.012 -0.064 0.593 0.278 -0.011 0.004

PDEC 0.016 -0.070 0.177 0.027 0.118 0.635 -0.143 -0.063 0.103

leg

al

KAMJ 0.571 0.275 -0.181 -0.029 0.003 0.041 -0.142 0.085 0.006

TRMW 0.835 0.043 0.050 -0.031 0.055 0.049 0.006 0.024 -0.025

LAFW 0.879 0.056 0.000 -0.012 0.091 -0.062 0.059 0.004 -0.013

PUBS 0.863 0.097 0.052 0.031 0.071 -0.040 0.037 0.038 0.017

MARR 0.113 0.053 -0.042 0.231 -0.075 0.012 -0.052 -0.287 0.639

Source: Author’s computation based on primary data, 2012-13

141

4.4.2. Outcomes of Principal Component Analysis of the Community Level

Empowerment of Women

The value of Kaiser-Meyer-Olkin (KMO) measure of Sampling Adequacy for studying

women’s empowerment at community level in table-4.4.4 is 0.707 (greater than 0.6 is

desirable). It also ensures that the sample size in this study is adequate for Principal

Component Analysis. The value of chi-square statistic in Bartlett’s Test of Sphericity is

highly statistically significant. It ensures that the selected indicators of empowerment of

women at the community level are inter-correlated. Therefore, here PCA is also an

appropriate methodology for analyzing the importance of the selected indicators in

measuring empowerment of women at the community level. We have depicted the major

findings of PCA for women’s empowerment at the community level in table-4.4.5 and in

table-4.4.6.

Table-4.4.4 Results of KMO and Bartlett’s Test for Sample Adequacy for Factor

Analysis of Women’s Empowerment at the Community Level

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.707

Bartlett's Test of Sphericity

Approx. Chi-Square 1989.652

Degrees of freedom 325

Significance 0.000

Source: Author’s computation based on primary data, 2012-13

Table-4.4.5 reveals the variance explained by the components at initial situation, after

extraction and after rotation. We have extracted the components applying Kaiser Criteria

and rotated imposing Varimax rotation method. We have found in table-4.4.5 that nine

principal components have Eigen values greater than one. So, this study has considered

nine Principal Components for measuring the composite index of women’s

empowerment at the community level. Rotation Sums of Squared Loadings indicate that

the first rotated principal component explains 9.29 per cent of total variation in

community level empowerment of women. The second and third rotated principal

components explain 7.47 per cent and 6.94 per cent of variance respectively. Nine

components altogether account for 55.26 per cent of total variation in the empowerment

of women at the community level.

142

Table-4.4.5 Total Variance in the Indicators of Women’s Empowerment Explained

by the Components at the Community Level

Extraction Method: Principal Component Analysis

Rotation Method: Varimax

Co

mp

on

ent

Initial Eigenvalues Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

Total % of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 3.223 12.396 12.396 3.223 12.396 12.396 2.416 9.292 9.292

2 2.048 7.876 20.272 2.048 7.876 20.272 1.944 7.478 16.769

3 1.617 6.219 26.491 1.617 6.219 26.491 1.806 6.946 23.715

4 1.561 6.003 32.494 1.561 6.003 32.494 1.672 6.430 30.145

5 1.465 5.633 38.127 1.465 5.633 38.127 1.595 6.136 36.282

6 1.304 5.014 43.141 1.304 5.014 43.141 1.396 5.368 41.650

7 1.086 4.177 47.318 1.086 4.177 47.318 1.283 4.935 46.585

8 1.046 4.024 51.342 1.046 4.024 51.342 1.174 4.516 51.100

9 1.020 3.921 55.263 1.020 3.921 55.263 1.082 4.163 55.263

10 .990 3.809 59.072

11 .964 3.709 62.781

12 .918 3.529 66.310

13 .907 3.490 69.800

14 .841 3.234 73.035

15 .769 2.958 75.993

16 .732 2.815 78.807

17 .688 2.647 81.455

18 .673 2.589 84.044

19 .627 2.413 86.457

20 .611 2.348 88.805

21 .592 2.276 91.080

22 .540 2.075 93.156

23 .477 1.834 94.990

24 .469 1.805 96.795

25 .444 1.708 98.502

26 .389 1.498 100.000

Source: Author’s computation based on primary data, 2012-13

143

Table-4.4.6 Rotated Component Matrix of Women’s Empowerment at the

Community Level

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 9 iterations.

Indicator Component

1 2 3 4 5 6 7 8 9

eco

no

mic

EARN 0.213 -0.052 0.169 -0.436 -0.014 0.193 -0.330 0.301 0.036

OWLP 0.034 -0.277 0.355 0.160 0.179 0.280 0.115 0.346 -0.269

ASIL 0.736 0.006 0.179 0.169 -0.066 -0.004 0.064 -0.002 0.044

AEDU -0.017 0.084 0.000 0.562 0.180 -0.025 0.216 -0.003 0.212

THPRO -0.063 0.100 0.007 -0.234 0.028 0.091 0.175 0.612 0.214

SEOC -0.060 -0.104 -0.007 0.583 -0.087 0.071 0.142 -0.030 -0.054

po

liti

cal

INVOL 0.019 0.724 0.190 0.064 0.014 0.210 -0.024 -0.032 0.046

VOLP 0.023 0.701 0.009 0.095 0.021 0.067 -0.082 0.022 -0.040

ATPM 0.120 0.630 0.089 -0.164 0.085 0.147 0.216 0.007 -0.072

CTEST 0.180 0.397 -0.093 0.150 -0.041 -0.266 -0.088 0.487 0.025

LEAD 0.779 0.033 0.024 -0.040 0.017 0.173 0.050 -0.127 0.049

So

io-c

ult

ura

l

MEMSO 0.252 0.304 -0.071 -0.038 -0.128 0.606 0.056 -0.128 0.045

INFLU 0.135 0.217 0.034 0.178 0.035 0.676 -0.024 0.029 -0.023

CACT -0.042 -0.016 0.560 0.127 0.060 0.357 -0.225 0.069 0.297

KLSI 0.037 -0.070 0.025 0.066 0.028 0.013 0.031 0.009 0.849

SEXL 0.100 0.113 0.219 0.113 0.068 -0.117 0.606 -0.205 0.189

OSOC -0.009 0.117 -0.003 0.674 0.002 0.152 -0.187 0.143 0.003

per

son

al/f

amil

ial

CASC -0.002 0.112 0.106 0.125 0.700 -0.136 -0.089 -0.084 -0.064

PTRN 0.633 0.040 0.031 -0.181 -0.134 0.057 0.044 -0.006 -0.111

CHAM 0.772 0.116 0.058 -0.092 0.035 0.061 -0.139 0.016 0.061

SACE -0.133 -0.107 0.029 0.136 -0.025 -0.068 -0.086 0.448 -0.136

EMUN -0.028 -0.071 -0.128 0.096 -0.076 0.104 0.689 0.167 -0.088

leg

al

ACCJ -0.032 -0.025 -0.159 -0.113 0.697 0.081 -0.061 0.109 0.062

AATY 0.167 0.093 0.775 -0.184 -0.102 0.069 -0.022 -0.007 -0.024

ACTC 0.138 0.204 0.732 0.034 -0.073 -0.231 0.106 -0.010 -0.035

CDPS -0.083 -0.001 -0.043 0.020 0.681 0.016 0.105 -0.028 0.032

Source: Author’s computation based on primary data, 2012-13

In order to understand the relative importance of the indicators we have computed the

rotated component matrix of women’s empowerment at community level. Table-4.4.6

represents rotated factor loadings of the women’s empowerment at community level. We

144

see that the indicators that have more weight on Component-1 are; financial inclusion,

leadership, professional training and freedom of changing occupation. Therefore, these

are the most important factor of women’s empowerment at community level. They

altogether explain 10% of the total variation among the indicators of women’s

empowerment at the community level. All of the indicators that have high contribution

on Components-2 are belonging to political dimension. Component-3 and Component-5

have been weighted high by the indicators of legal dimension. The indicators of the

economic dimension load high on Component-4. The indicators that contribute high on

Component-6 and Component-9 are belonging to socio-cultural dimension. The

indicators with highest loading in Component-7 are social exclusion and child

immunisation. These are explaining 5% of total variance. The indicators namely whether

the woman faces evicting from own property, whether she contested any vote and

sacrifices employment or membership due to familial ground load high on Component-9.

Finally, similar to the composite index of empowerment at the household level we have

computed the composite index of empowerment at the community level for each woman

in the district of Bankura.

4.4.3. Descriptive Statistics of the Empowerment Indices

The Principal Component analysis has helped us construct the women’s empowerment at

the household level as well as at community level for each sample woman. We have got

two separate constructed variables for our sample women- composite index of women’s

empowerment at household level (CIWEH) and composite index of women’s

empowerment at community level (CIWEC). The descriptive statistics of these two

variables have been depicted in table-4.4.7. It is seen that the means of these variables

are close to zero. The median statistics of these two variables point out that the

empowerment at household level of the majority of the sample women is higher than its

mean while the empowerment at community level of the majority of the sample women

is lower than its mean. It says that majority of the women in the district of Bankura

enjoys higher empowerment in their households compared to in their community. The

Jarque Bera statistics for both the constructed variables, CIWEH and CIWEC, ensure

that the variables are normally distributed around mean zero. This is the main strength of

the PCA. This strength is reflected in this table-4.4.7. However, it is very difficult to

interpret the principal components and they have no unit of measurement. In order to

carry on with this shortcoming we have also constructed the degree of empowerment for

145

each sample women. We have seen that the average of the degree of empowerment at the

household level of the sample women is 68 in hundred points scale. This figure at the

community level is 54 in hundred points scale. Therefore, it also suggests that the

average empowerment of the women at the household level is higher than that at the

community level.

Table-4.4.7 Descriptive Statistics of the Women’s Empowerment

CIWEH CIWEC DOWEH DOWEC

Mean 3.00E-06 1.10E-06 68.21 54.38

Median 1.6 -0.24 70.37 53.85

Maximum 64.85 69.2 100 96.15

Minimum -52.6 -50.7 33.33 23.08

Std. Dev. 19.09 18.98 13.58 13.42

Skewness -0.19 0.17 -0.31 0.13

Kurtosis 2.83 3.16 2.69 2.76

Jarque-Bera 4.25 3.31 11.82 2.9

Probability 0.12 0.19 0 0.24

Source: Author’s own computation based on sample observations, 2012-13

Table-4.4.8 Percentage Distribution of Women’s Empowerment in Bankura

District

Levels of Empowerment As per Composite Index As per Simple Index

Number of Women Percent Number of Women Percent

Household Level Empowerment

Very low (-52≤CIWEH<-23) 72 12.41 65 11.21

Low (-23≤CIWEH<06) 271 46.72 211 36.38

Moderate (06≤CIWEH<35) 225 38.79 232 40.00

High (35≤CIWEH<65) 12 2.07 71 12.24

Community Level Empowerment

Very low (-50≤CIWEC<-20) 83 14.31 89 15.34

Low (-20≤CIWEC<10) 330 56.90 291 50.17

Moderate (10≤CIWEC<40) 156 26.90 182 31.38

High (40≤CIWEC<70) 11 1.90 18 3.10 Source: Author’s own computation, 2012-13

146

Figure-4.4.1 Percentage Distribution of Women’s Empowerment at Household

Level

Source: Author’s own computation based on table-4.4.8

Figure-4.4.2 Percentage Distribution of Women’s Empowerment at Community

Level

Source: Author’s own computation based on table-4.4.8

In addition to the mean median statistics, we have intended to analyse the relative level

of empowerment of the sample women shown in table-4.4.8. In accordance with the

range of the empowerment index values we have categorized the sample women into

four equal groups: high, moderate, low and very low. According to degree of

empowerment measure 12% (3%) of sample women have relatively high level of

empowerment at the household level (at the community level). About 40% (31%) of

147

sample women enjoy relatively moderate level of empowerment at the household level

(at the community level). We find that the women’s empowerment at the household level

(at the community level) is relatively low for 36% (50%) of the women. It is observed

that 11% (15%) have very low level empowerment at the household level (at the

community level). Therefore, we have found that a few women in the district of Bankura

have high level of empowerment. Majority of the women suffers from the lack of

empowerment at the household level and at the community level in the district of

Bankura.

With respect to the composite index computed applying PCA, we have seen that 2.07%

(1.9%) of sample women are highly empowered at the household level (at the

community level). On the other extreme, we observe that 12 % (14%) of the surveyed

women have very low level empowerment at the household level (at the community

level) and 39% (26%) of sample women enjoy relatively moderate level of

empowerment at the household level (at the community level). The empowerment at the

household level (at the community level) is relatively low for 46% (56%) of the women.

Therefore, the measure of composite index obtained following PCA, reveals more or less

same results regarding the level of empowerment of the rural women as we have

obtained from simple indices of empowerment.

4.5. Bivariate Correlation among Selected Variables

In this section, we test statistical significance of the correlation coefficients among the

different socio-economic and demographic variables of our sample women/households.

Although, the matrix of correlation coefficients considering all possible socio-economic

and demographic variables related to the surveyed population is computed, we discuss

only the correlation coefficients, which are relevant for our empirical models. First, we

analyze the strength of correlation between the household welfare indicating the decision

towards family planning, nature of domestic violence against women and expenditure for

education and women’s empowerment at the household level and at the community level

along with some individual/household and community characteristics of the surveyed

population. Second, we discuss the degree of association between the women’s

empowerment and the socio-economic and demographic traits, which have been

considered as determinants of empowerment of the rural women in the district of

Bankura. In order to test the significance of the correlation coefficient between two

148

particular variables we have used the test statistic 2

2,

1

r nt

r

with degrees of freedom

(n-2), where ‘r’ is the sample correlation coefficient between the pair of variables under

consideration and n stands for sample size. The results of the test of correlation

coefficients have been presented in the tables 4.5.1, 4.5.2, 4.5.3, 4.5.4and 4.5.5.

It has been revealed that women’s empowerment at the household level and at the

community level are highly correlated with the decision towards family planning. Refer

to table-4.5.1. The value of the correlation coefficient between the composite index of

empowerment at household level (community level) and family planning decision is 0.34

(0.47), which is statistically significant at 1% level. Thus, it is expected that the

probability of taking family planning increases with higher degree of empowerment of

women. The values of the bivariate correlation coefficients show that empowerment

variables are negatively correlated with the incidence of domestic violence against

women. These relations are statistically significant at 99% level of confidence. The

education expenditure as proportion to the annual household income has a positive and

statistically significant correlation with the women’s empowerment at the household

level and with the empowerment at the community level. Therefore, we can say that the

women’s empowerment reduces the incidence of domestic violence and inspire to spend

for education. The bivariate correlation analysis has justified our regression models for

assessing the impact of women’s empowerment on household welfare indicating the

decision towards family planning, nature of domestic violence against women and

expenditure for children’s education.

Table-4.5.1 Bivariate Correlation Matrix

DOWEH DOWEC CIWEH CIWEC DRFP PEDUX DVIO AGE

DOWEH 1 .605**

.947**

.530**

.324**

.126**

-.128**

-.039

DOWEC

1 .590**

.928**

.454**

.206**

-.116**

-.043

CIWEH

1 .503**

.345**

.124**

-.104* -.044

CIWEC

1 .477**

.199**

-.115**

-.069

DRFP

1 .079 -.056 -.094*

PEDUX

1 -.034 .060

DVIO

1 .000

AGE

1

*stands for significant at 5% level and ** stands for significant at 1% level

Source: Author’s own computation based on sample observations, 2012-13

149

Refer to table-4.5.2. It has been found that there is negative relation between the

women’s empowerment variables and the duration of married life. This relation is

significant only for composite index of empowerment at the household level. All

empowerment variables under consideration are highly correlated with the women’s

education and with the highest female education in the family. Women’s empowerments

at household level and at community level are negatively correlated with spousal age

gap. There is a negligible degree of association of the family planning decision with the

age at marriage and with the spousal age gap which are statistically insignificant. This

result points out that age at marriage and spousal age gap are immaterial to influence the

decision towards family planning. It is exhibited that there is a positive and significant

association between the education of the women and decision towards family planning.

Not only that, highest education level of male and female members in the family have

some favourable correlation with the decision towards family planning. It supports the

fact that educated couples usually prefer to have a small family.

Table-4.5.2 Bivariate Correlation Matrix

DURM AGAM HAGE SAGEG EDU HEDU EDUG HIMEDU HIFEDU

DOWEH -.062 .041 -.066 -.130**

.123**

.080 -.045 .035 .170**

DOWEC -.073 .055 -.060 -.144**

.235**

.222**

.028 .166**

.248**

CIWEH -.084* .075 -.077 -.148

** .126

** .077 -.054 .036 .140

**

CIWEC -.078 .014 -.067 -.088* .305

** .288

** .035 .222

** .299

**

DRFP -.110**

.027 -.075 -.023 .326**

.308**

.037 .262**

.206**

PEDUX .088* -.052 .041 .013 .093

* .127

** .074 .312

** .383

**

DVIO -.034 .065 -.016 -.011 -.261**

-.291**

-.101* -.260

** -.203

**

AGE .866**

.297**

.931**

.084* -.360

** -.259

** .089

* -.043 -.178

**

DURM 1 -.220**

.841**

.195**

-.361**

-.272**

.069 -.027 -.166**

AGAM

1 .211**

-.209**

-.013 .014 .041 -.034 -.029

HAGE

1 .349**

-.336**

-.239**

.087* -.023 -.180

**

SAGEG

1 -.037 -.022 .016 .029 -.018

EDU

1 .786**

-.139**

.543**

.712**

HEDU

1 .502**

.686**

.607**

EDUG

1 .340**

-.022

HIMEDU

1 .541**

HIFEDU

1

*stands for significant at 5% level and ** stands for significant at 1% level

Source: Author’s own computation based on sample observations, 2012-13

150

This table shows that women’s education and their husband education are significantly

and positively associated with their children’s education expenditure. The correlation

coefficient of education expenditure as a proportion of total income with mother’s

education and father’s education are 0.09 and 0.12 respectively. These results are

statistically significant at 5% level and 1% level respectively. Moreover, the highest

male and female education in the family positively affects the education expenditure in

the family. This result is also accepted at 99% confidence level. However, the degree of

domestic violence has insignificant association with duration of marriage, age at

marriage, husband age and spousal age gap. The correlation coefficient between

women’s education and degree of domestic violence is -0.26 which is statistically

significant at 1% level. Husband’s education is also negatively and significantly

associated with the degree of domestic violence. Besides highest male education, highest

female education and educational gap is negatively associated with the degree of

domestic violence. This result confirms that educational background of the family helps

reduce the intensity of domestic violence against women.

Refer to table-4.5.3. We see the correlation coefficient regarding the different types of

family occupation and other variables. There is a negative linear association between the

household level empowerment and the fact that the occupation of the family is

cultivation. We see that there is a positive and significant correlation coefficient between

the household level empowerment as well as community level empowerment and the

fact that the major occupation of the family is non-farm business. The correlation

coefficient between the community level empowerment and the wage-labour occupation

of the family is a negative and significant. There is a positive and significant correlation

coefficient between the household level empowerment as well as community level

empowerment and the fact that the earning members of the family are mainly employed

in the service sector. There is a negative and highly significant (1%) degree of linear

association between the household level empowerment and the dependency ratio in the

family. It has been identified that the association between the community level

empowerment and dependency ratio is insignificant. We see that the correlation

coefficient between the household level empowerment as well as community level

empowerment and average per capita household income is positive and significant at 1%

level. We find a positive and significant correlation between the community level

empowerment and household landholding.

151

Table-4.5.3 Bivariate Correlation Matrix

CULTI NFARM LABC SERV DRATIO APCHIN HLAND TYFAMI

DOWEH -.250**

.170**

-.008 .264**

-.114**

.179**

.036 .085*

DOWEC -.090* .156

** -.114

** .170

** -.058 .134

** .228

** .047

CIWEH -.274**

.186**

-.009 .290**

-.133**

.176**

.056 .027

CIWEC -.035 .173**

-.173**

.151**

.028 .158**

.249**

.033

DRFP -.010 .058 -.136**

.191**

-.006 .195**

.203**

-.043

PEDUX .048 .086* -.122

** .015 .372

** -.064 .060 .068

DVIO -.097* -.107

** .267

** -.157

** -.043 -.220

** -.071 -.007

AGE .040 .066 -.115**

.044 -.240**

.142**

.172**

.059

DURM .042 .075 -.102* .004 -.206

** .136

** .110

** .033

AGAM -.002 -.015 -.029 .079 -.076 .016 .126**

.051

HAGE .087* .041 -.133

** .021 -.215

** .131

** .201

** .028

SAGEG .139**

-.029 -.076 -.087* .053 -.009 .122

** -.071

EDU .100* .168

** -.370

** .259

** .251

** .304

** .245

** -.126

**

HEDU .153**

.193**

-.442**

.253**

.289**

.337**

.371**

-.134**

EDUG .106* .075 -.190

** .044 .112

** .115

** .253

** -.039

HIMEDU .184**

.206**

-.452**

.197**

.323**

.316**

.369**

-.142**

HIFEDU .126**

.163**

-.353**

.185**

.361**

.248**

.243**

-.096*

CULTI 1 -.365**

-.642**

-.249**

.210**

-.083* .362

** -.049

NFARM

1 -.294**

-.114**

.062 .045 .127**

.039

LABC

1 -.201**

-.252**

-.267**

-.499**

.046

SERV

1 -.025 .587**

.048 -.041

DRATIO

1 -.051 .104* -.089

*

APCHIN

1 .200**

-.012

HLAND

1 -.197**

TYFAMI

1

*stands for significant at 5% level and ** stands for significant at 1% level

Source: Author’s own computation based on sample observations, 2012-13

We get a positive and statistically significant correlation between simple index

household level empowerment and family composition. Therefore, family type may

determine the household level empowerment. The correlation coefficients of family

planning decision with annual per capita household income and with household

landholding are 0.195 and 0.203 respectively which are statistically significant.

Therefore, per capita family income and household landholding may be considered as

determinants of the probability of taking family planning decision. Each type of

household occupation is significantly correlated with the incidence of domestic violence.

The sign of correlation coefficient shows that women of labour class family are suffering

more violence compared to others. The correlation coefficient between the incidence of

152

violence and per capita family income is negative and significant. The figures of

correlation coefficients of education expenditure and households occupations tell us

households’ occupations affects education expenditure for children.

Table-4.5.4 Bivariate Correlation Matrix

GEN OBC SC ST LABOR FARM SELF HWIFE PERINC

DOWEH -.056 .060 .055 -.077 -.284**

.001 .066 .209**

.222**

DOWEC .045 .078 .011 -.180**

-.194**

.029 -.013 .151**

.126**

CIWEH -.076 .063 .066 -.070 -.275**

-.015 .083* .205

** .236

**

CIWEC .132**

.080 -.032 -.246**

-.179**

.050 -.033 .132**

.077

DRFP .088* .099

* -.057 -.167

** -.071 -.002 -.059 .093

* .068

PEDUX .003 .060 -.082* .041 -.013 -.005 .027 .002 -.026

DVIO -.18**

-.075 .177**

.094* .069 -.009 .026 -.065 -.115

**

AGE .005 .009 -.058 .071 -.026 -.032 -.005 .050 .064

DURM .013 .029 -.018 -.024 -.056 -.011 .018 .047 .012

AGAM -.014 -.037 -.079 .185**

.056 -.043 -.045 .009 .102*

HAGE .027 .002 -.058 .049 -.028 -.027 .002 .044 .033

SAGEG .094* -.051 -.055 .014 .007 -.015 .011 .000 -.087

*

EDU .299**

.121**

-.314**

-.136**

.009 .016 -.028 -.006 .149**

HEDU .349**

.122**

-.325**

-.195**

.005 -.004 -.015 .007 .109**

EDUG .141**

.027 -.082* -.122

** -.005 -.028 .015 .019 -.034

HIMEDU .244**

.131**

-.260**

-.149**

-.005 .011 .027 -.018 .075

HIFEDU .209**

.135**

-.282**

-.069 -.026 .040 -.005 -.007 .132**

CULTI .193**

.190**

-.282**

-.120**

.020 .002 .038 -.039 -.130**

NFARM .160**

.043 -.093* -.149

** -.036 .028 -.055 .037 -.034

LABC -.344**

-.242**

.404**

.224**

.041 .004 .000 -.039 -.028

SERV .042 .019 -.072 .022 -.065 -.050 .001 .095* .347

**

DRATIO .135**

.080 -.148**

-.084* .055 .033 .015 -.081 -.146

**

APCHIN .155**

.040 -.144**

-.064 -.065 -.029 .016 .070 .478**

HLAND .168**

.191**

-.255**

-.125**

-.046 -.027 -.001 .061 -.011

TYFAMI -.031 .005 .060 -.037 -.015 -.070 -.063 .100* -.039

GEN 1 -.371**

-.479**

-.245**

.061 -.041 -.041 .001 -.050

OBC 1 -.392**

-.201**

-.093* .015 -.025 .081 .076

SC

1 -.259**

-.046 .065 .060 -.043 -.060

ST

1 .093* -.053 .004 -.040 .063

LABOR

1 -.274**

-.156**

-.563**

-.064

FARM

1 -.133**

-.480**

-.043

SELF

1 -.274**

-.003

HWIFE

1 .090*

PERINC

1

*stands for significant at 5% level and ** stands for significant at 1% level

Source: Author’s own computation based on sample observations, 2012-13

153

In table-4.5.4 we see that the associations between household level empowerment and

caste variables are insignificant. But community level empowerment is significantly

related with dummies for GEN and ST. We have observed that the women who work for

wage have less empowerment compared to others. The correlation analysis reveals that

personal income of women is significantly correlated with the women’s empowerment at

the household level and at the community level. It has been seen that personal

occupation is significantly associated with women’s empowerment at household level as

well as at community level. In particular homemakers compared to others are enjoying

more empowerment at the household level and at the community level. Therefore, we

can adopt the personal income and personal occupation as determinants of women’s

empowerment at the household level and at the community level. Correlations of

personal income with the decision towards family planning and with the education

expenditure are insignificant. However, the personal income is negatively and

significantly correlated with the incidence of domestic violence.

Refer to table-4.5.5. We find a positive and statistically significant correlation of the

access to formal credit with the empowerment variables. This result suggests for

considering the access to formal credit as a determinant of women’s empowerment at the

household level and at the community level. There is a positive and significant

correlation between the decision towards family planning and access to formal credit and

between accessibility to formal credit and education expenditure as proportion to

household income. It indicates that access to formal credit is an influential factor in the

determination of the family planning decision and educational expenditure.

The bivariate correlation matrix shows that the degree of association between the decision

towards family planning and the duration of the SHG membership status for the women

under study is positive and significant. Further, we have found that the correlation

coefficient between the education expenditure as proportion to the annual household

income and the duration of SHG membership is positive and significant. However,

surprisingly we find a positive and statistically significant correlation between the

incidence of domestic violence and the duration of SHG membership status. Therefore, in

the area under study family co-members do not want that women participate in the SHG-

centric microfinance program in which women move outside home and interact with the

officials of the programs and her co-members.

154

Table-4.5.5 Bivariate Correlation Matrix

ALOAN DSHGM ADDIC DOW PMDOW

DOWEH .286**

.175**

.094* .033 .036

DOWEC .487**

.389**

.064 .130**

.026

CIWEH .277**

.202**

.143**

.004 .050

CIWEC .489**

.329**

.023 .207**

.028

DRFP .243**

.162**

.020 .092* .049

PEDUX .104* .146

** -.069 .069 -.022

DVIO -.009 .131**

.257**

.097* .236

**

AGE .031 .151**

.017 -.253**

-.098*

DURM .015 .083* -.053 -.210

** -.076

AGAM .032 .136**

.135**

-.091* -.048

HAGE .020 .131**

.002 -.247**

-.087*

SAGEG -.088* -.036 -.104

* -.090

* -.009

EDU .041 -.106* -.228

** .188

** -.064

HEDU .075 -.073 -.240**

.227**

-.097*

EDUG .063 .032 -.067 .100* -.067

HIMEDU .090* .009 -.182

** .184

** -.052

HIFEDU .078 -.024 -.194**

.164**

-.092*

CULTI -.048 -.079 -.210**

.175**

-.108**

NFARM .074 .038 -.002 .102* .013

LABC -.019 .083* .213

** -.212

** .139

**

SERV .026 -.051 .015 -.087* -.066

DRATIO -.015 -.065 -.135**

.172**

.038

APCHIN .066 -.131**

-.093* -.041 -.060

HLAND .163**

.172**

-.089* .122

** .004

TYFAMI .032 -.013 .059 .035 -.031

GEN .006 -.083* -.111

** .184

** -.117

**

OBC .049 -.029 -.146**

.156**

.032

SC .015 .026 .139**

.033 .165**

ST -.100* .125

** .153

** -.522

** -.113

**

LABOR -.132**

-.070 .028 -.004 .065

FARM .103* .032 .015 .019 .009

SELF -.034 -.056 -.057 .010 -.008

HWIFE .049 .064 -.006 -.016 -.059

PERINC .064 -.044 -.014 -.172**

-.056

AFCT 1 .542**

.084* .046 .068

DSHGM 1 .196**

-.079 .032

ADDIC

1 -.094* .062

DOW

1 .216**

PMDOW

1

*stands for significant at 5% level and ** stands for significant at 1% level

Source: Author’s own computation based on sample observation, 2012-13

155

The correlation coefficient between drug addiction by husband and incidence of domestic

violence is positive and statistically significant. This finding tells us that addiction may

induce the risk of domestic violence. It also supports the addiction as a determinant of

domestic violence. This study shows that dowry at marriage and the post marriage

demand for dowry are positively and significantly associated with the violence against

women. With this end in view, we have considered dowry at marriage and the post

marriage demand for dowry as important determinants of domestic violence in our

regression model.

The analysis of correlation coefficient among different socio-economic and demographic

traits of the women/households actually guides us to select the important explanatory

variables for the econometric models specified for analyzing the impact of women’s

empowerment on household welfare and for examining the influential factors of

empowerment for the women in the district of Bankura. The above explanation helps us

recognize the relevant explanatory variables regarding the models of the decision towards

family planning, incidence of domestic violence, spending for education and women

empowerment.

Once we have diagnosed and identified the explanatory variables/determinants for the

models under consideration, we shall be able to measure the impact of these

determinants. This exercise will come to our help in prescribing the economic policies in

connection with the women’s empowerment.

4.6. Conclusion

This chapter has presented the detailed descriptions of the sample women and their

households. A description of the indicators of empowerment shows that women in the

district of Bankura are highly deprived of several aspects of empowerment. We have

computed the degrees of household level as well as community level empowerment for

each sample woman. Using PCA a composite index of empowerment at the household

level and at the community level for each sample women has also been estimated. The

measures of the degree of empowerment and PCA constructed four empowerment

variables reveal that average levels of empowerment at the household level and at the

community level of the sample women are not commendable. The bivariate correlation

analyses suggests that empowerment at the household level as well as at the community

156

level are significantly associated with the decision regarding family planning, incidence

of domestic violence and with the spending for child education. Based on these

associations we have estimated the regression models to assess the impact of

empowerment variables on household and child welfare. We also examine the factors

affecting empowerment at the household level and at the community level. The results of

the empirical models have been discussed in chapter five.

157

Chapter Five

__________________________________________________

Empirical Estimates and Analysis

5.1. Introduction

We have formulated the relevant working models and hypotheses related to the study of

women’s empowerment in the district of Bankura. The descriptive statistics of several

household and individual characteristics including focussed constructed variables degree

of women’s empowerment and the composite index of women’s empowerment have

been explained in the last chapter. In this chapter our plan is to describe the empirical

findings and analyze the econometric models duly estimated.

The route of journey of this chapter has been designed as follows. In section 5.2 we have

interpreted and analyzed the estimated results of the model for the decision towards

family planning. The estimated impacts of women’s empowerment status along with the

other determinants on the incidence of domestic physical violence have been analyzed in

section 5.3. Section 5.4 has explained the impact of women’s empowerment along with

other socio-economic and demographic traits on the expenditure for children education.

Section 5.5 deals with the determinants affecting the women’s empowerment at

household level as well as at community level. The determinants of the household level

empowerment have been discussed in sub-section 5.5.1. Sub-section 5.5.2 has

interpreted the results of the estimates of community level empowerment of women in

the district of Bankura. Finally, section 5.6 concludes the chapter.

5.2. Impact of Women’s Empowerment on Decision regarding Family Planning

In chapter three we have specified an econometric model regarding the decision towards

family planning. It has been pointed out that we use a Probit model for assessing the

probability of taking family planning decision for the women in the district of Bankura.

158

The probability of taking family planning decision depends on a number of determinants

divided into individual/household and community characteristics of the women. Among

them most important variable is definitely the women’s empowerment. We expect that

after controlling for individual/household and community characteristics, the women

with higher level of empowerment at the household level and at the community level

have better position to take family planning decision. This implies that the likelihood of

taking family planning is expected to increase with higher empowerment at the

household level and at the community level. In addition to women’s empowerment at the

household level and at the community level, male child bias, age, spousal age gap,

education of the woman, husband education, household occupation, income,

landholding, dependency ratio and the duration of SHG-membership have been

considered as important explanatory variables in the probit model for the decision

regarding family planning.

Based on the methodology of computing empowerment we have estimated two models

for each issue of household welfare achieved through empowerment. In order to explain

the decision towards family planning we have estimated two models, Model-1A and

Model-1B, in each model all the variables being the same, except empowerment

variables. In Model-1A we consider the empowerment variables measured by simple

average method and Model-1B incorporates the composite index for the women’s

empowerment computed by principal component analysis. For each model the number of

observation is 580.

5.2.1. Model-1A: Probit Model with Simple Empowerment Indices

In this sub-section we discuss the results of the estimated probit model of the decision

regarding family planning where empowerment variables have been measured by simple

average of the indicators which is called the degree of empowerment, i.e., Model-1A.

The results of the Model-1A are presented in table-5.2.1 and in table-5.2.2. First, we

interpret the coefficients of the individual/household characteristics as explanatory

variable; then we come to the community characteristics.

In table-5.2.1 the coefficient of women’s empowerment at the household level is positive

and statistically significant. One percent higher household level empowerment increases

the log-odds in favour of taking family planning by 1.3 percentage points. It is indicative

159

that household level empowerment is an important factor for taking decision regarding

family planning. Refer to table-5.2.2. We have found that the probability of taking

decision regarding family planning increases by 0.5 percent point due to one percent

increase in the degree of empowerment from the mean level household empowerment of

the women. It implies that household level empowerment has a positive marginal impact

on the probability of taking family planning decision. Empowered women at the

household have the decision making power and consciousness regarding family and

child welfare. So, the result is consistent with the logic.

The coefficients of the dummies for first two child combinations turn out to be negative.

The dummy for first child male and second child female (FMSF=1) is statistically

insignificant to determine family planning decision. The dummy for first child female

and second male (FFSM=1) and the dummy for first and second children female

(FFSF=1) are statistically significant determinants of the decision regarding family

planning. The estimated probit model shows that the probability of taking family

planning decision is 26% lower for the women having first two children female than the

women having one child or first two children male. We also find that the women having

first child female and second child male are 13% less likely to adopt family planning in

contrast to the women having one child or first two children male. Therefore, women

having first two children female are worst in position to have family planning decision.

These findings prove that our sample women have male child bias and this is the reason

they did not want to take family planning before having two male children. So our male

child bias hypothesis regarding family planning turns out to be true.

It is revealed that age at marriage has some positive impact on the log-odds towards

family planning for the women in the district of Bankura. The marginal change of

probability states that if average age of the women at marriage increases by one year

probability of taking family planning decision increases by 0.6 percentage point from

mean. This result is, however, statistically insignificant. High age at marriage increases

the consciousness of the women regarding familial and biological know how of family

planning. So, the result is expected. We have also found that the coefficient of spousal

age gap is positive and statistically significant at 6% level. The magnitude of the

coefficient of spousal age gap says that age gap is suitable for positive decision

regarding family planning. We have seen that average age gap of our sample couples

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(husband’s age – wife’s age) is 5.7 years. The marginal change of probability calculation

in table-5.2.2 implies that ceteris paribus one year increase in spousal age gap from mean

increases the probability of taking family planning by 1.6 % points. This result supports

the Indian culture regarding age of husband and wife and goes against our hypothesis.

Therefore, Indian culture may be suitable for taking family planning. However, the result

is not highly significant at all.

Table-5.2.1 Results of the Probit Model for the Decision regarding Family Planning

When Women’s Empowerment is the Simple Average of the Indicators

Dependent Variable: DRFP (Decision regarding Family Planning)

Method: ML - Binary Probit (Newton-Raphson)

Included observations: 580

Convergence achieved after 5 iterations

Covariance matrix computed using second derivatives

Explanatory Variable Coefficient Std.

Error

z-

Statistic Prob.

Constant -3.341 0.569 -5.875 0.000

Personal/Household characteristics

DOWEH (%) 0.013**

0.006 2.246 0.025

Women having at least two child (FMSF =1) -0.080 0.166 -0.480 0.631

Women having at least two child (FFSM =1) -0.355**

0.166 -2.134 0.033

Women having at least two child (FFSF =1) -0.695*

0.184 -3.780 0.000

Age at Marriage AGAM (Year) 0.016 0.013 1.194 0.233

Spousal Age Gap (SAGEG) (Year) 0.042***

0.023 1.827 0.068

Education of the Woman (EDU) (Year) 0.082*

0.026 3.087 0.002

Husband’s Education (HEDU) (Year) 0.020 0.024 0.870 0.384

Type of Family (TYFAMI) (Nuclear = 1) -0.258 0.169 -1.527 0.111

Household Occupation CULTI, (Cultivation =1) -0.144 0.173 -0.835 0.404

Household Occupation, NONFARM, (Non-Farm= 1) -0.437**

0.218 -2.009 0.045

Household’s Land holding, HLAND, (bigha, = 0.4hector) 0.014 0.029 0.474 0.636

Dependency Ratio in the Household DRATIO (%) -0.002 0.003 -0.589 0.556

Annual Per Capita Household Income (APCHIN) (Rs. ‘000) 0.023**

0.011 2.186 0.029

Community characteristics

DOWEC (%) 0.038*

0.007 5.304 0.000

Duration of SHG-membership DSHGM (Month) 0.003 0.002 1.530 0.126

Caste (OBC=1) 0.153 0.177 0.864 0.388

Caste (SC=1) 0.063 0.180 0.351 0.726

Caste (ST=1) -0.436***

0.243 -1.792 0.073

Summary Statistics

LR statistic (19 df) (probability) 224.996 (0.000) Akaike information Criterion 1.032

McFadden R-squared 0.287 Schwarz criterion 1.183 Source: Author’s own computation based on sample observations, 2012-13

*, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

161

Table-5.2.2 Marginal Probability of the Decision regarding Family Planning When

Women’s Empowerment is the Simple Average of the Indicators

Marginal effects after probit

Dependent Variable(y): Probability of the Decision regarding Family Planning (DRFP)

(predict) = .6445

Included observations: 580

Explanatory Variable

dy/dx

evaluated

at mean

Std.

Error z-Statistic

Prob.

>|z|

Mean of the

Explanatory

Variable(x)

Personal/Household characteristics

DOWEH (%) 0.005**

.0022 2.25 0.025 68.12

Women having at least two child (FMSF=1)# -0.029 .0629 -0.48 0.634 0.20

Women having at least two child (FFSM =1) # -0.136

** .0649 -2.10 0.036 0.19

Women having at least two child (FFSF =1) # -0.269

* .0706 -3.81 0.000 0.16

Age at Marriage AGAM (Year) 0.006 .005 1.20 0.232 18.75

Spousal Age Gap (SAGEG) (Year) .0158***

.0086 1.83 0.068 5.74

Education of the Woman (EDU) (Year) 0.030* .0098 3.09 0.002 3.59

Husband’s Education (HEDU) (Year) 0.007 0.87 .0087 0.384 4.86

Type of Family (TYFAMI) (Nuclear = 1) # -0.092 .0582 -1.59 0.111 .818

Household Occupation CULTI, (Cultivation =1) #

-0.053 .0645 -0.84 0.404 0.443

Household Occupation NONFARM (Non-Farm= 1) # -0.169

** .0855 -1.98 0.048 0.143

Household’s Land holding, HLAND, (bigha) .0051 .0109 0.47 0.636 2.64

Dependency Ratio in the Household DRATIO (%) -.0006 .0011 -0.59 0.556 49.68

Per Capita Household Income (APCHIN) (Rs. ‘000) .0086**

.0038 2.22 0.027 13.78

Community characteristics

DOWEC (%) 0.014* .0026 5.31 0.000 54.37

Duration of SHG-membership DSHGM (Month) 0.001 .0007 1.53 0.126 27.23

Caste (OBC=1) # 0.056 0.88 0.06 0.378 0.23

Caste (SC=1) # 0.023 .066 0.35 0.725 0.33

Caste (ST=1) # -0.169

*** .096 -1.76 0.079 0.11

(#) dy/dx is for discrete change of dummy variable from 0 to 1

*, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively. Source: Author’s own computation based on sample observations, 2012-13

Education of the women has also some direct impact on the decision regarding family

planning. Our marginal probability computation has shown that one additional

completed year of formal education after primary level increases the probability of

adopting family planning by 3 percentage points. Education of women inculcates the

knowledge and importance of family planning for family welfare as well as for social

welfare. Therefore, education is very much important factor affecting the decision

regarding family planning as we have found. The coefficient of husband’s education in

Model-1A is also positive but statistically insignificant. One year extra above primary

162

level (mean education of the husband) education of husband increases the probability of

adopting family planning by 0.8% point. By the same logic as we have mentioned for

women’s education the impact of husband’s education on the probability of adopting

family planning is consistent. However, impact of women’s education is more important

than that of husband’s education on the probability of adopting family planning.

Estimates of the probit model shows that the dummy for family type (Nuclear =1) has

negative effect on the log-odds in favour of family planning. It tells us that women

belonging to nuclear family are less likely to be ideal family planner. The probability

towards family planning reduces by 9.2 percentage point if the woman is belonging to

nuclear family. This result is statistically significant at 11% level.

We have examined the impact of household occupation on the attitudes of sample

women towards family planning. Household occupation, CULTI (cultivation =1) has

some negative impact on log-odds towards the decision regarding family planning. It

means that women belonging to cultivator family relative to women belonging to wage

labour class are less likely to adopt family planning. However, this empirical result is

statistically insignificant. The coefficient of household occupation, NONFARM (Non-

farm=1) in Model-1A points out that women in non-farm self-employed households

compared to wage labour class are less likely to take family planning. Table-5.2.2 shows

that, if a household shifts to self-employed occupation from service or wage earning

jobs, the probability of taking family planning will reduce by sixteen percentage points.

It may happen due to the fact that wage labour households/couples think the opportunity

cost of child rearing whereas women in farm and self-employed family do not think

regarding opportunity cost of child rearing. Rather in farm and petty business family

children are viewed as earner at least in rural area.

It turns out that dependency ratio in the households has some adverse but insignificant

impact on the decision regarding family planning. We find that the coefficient of

household’s landholding is positive in our estimated probit model. It means that

household’s landholding is favourable for adopting family planning decision but this

empirical finding is statistically insignificant. The coefficient of annual per capita

household income, which is significant at 2% level, reports that one thousand rupees

additional annual per capita household income increases the log-odds in favour of

adopting family planning by 2.3% points. Table-5.2.2 shows that if annual per capita

163

household income increases one thousand rupees probability of adopting family planning

would increase by almost 1% point. It is fact that rich households are very much

concerned regarding child care i.e. about health, education and future economic status

and thereby cost of child care. So, it is an expected result.

The prime community trait captured by the women’s empowerment at the community

level has some positive and statistically significant impact on the probability of adopting

family planning. As women’s empowerment increases 1% the probability of taking

family planning increases by 1.4% points. Not only that, community level empowerment

is more important than the household level empowerment in the determination of the

probability of adopting family planning. Therefore, employment outside home,

association with community affairs, and mobility of the women are most important for

taking family planning. Mobility of the women in different social institutions helps her

understand the importance of family planning.

The coefficient of the duration of SHG-membership is positive and statistically

significant at 12% level. It has been observed that one year extra participation in SHG

from mean increases the probability of taking family planning by 0.1%. Participation in

SHG ensures the financial inclusion of the women. As duration of participation increases

the intensity of financial inclusion increases ensuring higher amount of borrowing if

needed. A large number of sample women has reported that availing SHG loan they are

now self-employed. Therefore, availability of fund to the women increases the

opportunity cost of time to her. Besides, participation in SHG inculcates the

consciousness in women member. It induces them to take family planning. However, the

impact of SHG-membership is too small in the determination of the probability of taking

family planning.

In order to answer whether caste is a matter or not to take family planning decision we

have considered three dummies for caste of the women. In this study Caste (general caste

=1) has been considered as comparison category. The coefficients of dummies for caste

(OBC=1) and for caste (SC =1) indicate that the women belonging to other backward

classes and scheduled castes in contrast to general caste women are more likely to take

family planning decision. But these findings have no statistical base. We also find that

the coefficient of the dummy for caste (ST =1) is negative but significant at 7% level. So

164

the probability of adopting family planning for the tribal couple is 16% lower than that

of the general caste couples. It may arise due to ignorance, unawareness and lack of

consciousness of the tribal women.

This study reveals that empowerment of women at the household level and at the

community level, male child bias, education of woman, family type, household income,

participation in SHG and caste are significant determinants of the decision towards

family planning for the women in Bankura district.

5.2.2. Model-1B: Probit Model with Composite Empowerment Indices

In this section we consider the probit model (Model-1B) for the decision regarding

family planning where empowerment variables are composite indices along with the

same other explanatory variables as had in Model-1A. This new model is denoted by

Model-1B and results have been depicted in table-5.2.3 and table-5.2.4.

Refer to table-5.2.3 and table-5.2.4. The coefficients of the composite index of women’s

empowerment at household level and at community level are positive and statistically

significant at 1% level. Women’s empowerment at household level and at community

level increases the probability of taking family planning measures for the sample

women. It is important to note that compared to household level empowerment,

community level empowerment has higher impact on family planning decision.

Therefore, methodological difference in measuring women’s empowerment does not

alter the findings regarding the impact of women’s empowerment on the probability of

adopting family planning decision.

In addition to empowerment, male child bias has same line impact on the decision

regarding family planning as we have in Model-1A. Like Model-1A we have found that

women’s education is significant determinant of the decision towards family planning.

The estimates of the probit model show that one year extra education of the woman from

mean education increases the probability of taking family planning decision by 2.7

percent point while one year extra education of husband from mean education increases

the probability of taking family planning decision by 0.97 percent point. Therefore,

women’s education compared to husband education is more important in family planning

decision as we have seen in Model-1A.

165

Table-5.2.3 Results of the Probit Model for the Decision regarding Family Planning

When Women’s Empowerment is Composite Index of the Indicators

Dependent Variable: Decision regarding Family Planning (DRFP)

Method: ML - Binary Probit (Newton-Raphson)

Included observations: 580

Convergence achieved after 5 iterations

Covariance matrix computed using second derivatives

Explanatory Variable Coefficient Std. Error z-Statistic Prob.

Constant -0.356 0.423 -0.841 0.400

Personal/Household Characteristics

CIWEH 0.016*

0.004 3.758 0.000

Women having at least two child (FMSF =1) -0.059 0.168 -0.350 0.727

Women having at least two child (FFSM =1) -0.367**

0.169 -2.174 0.030

Women having at least two child (FFSF=1) -0.708*

0.187 -3.795 0.000

Age at Marriage AGAM (Year) 0.015 0.014 1.144 0.253

Spousal Age Gap (SAGEG) (Year) 0.041***

0.024 1.752 0.080

Education of the Woman (EDU) (Year) 0.073*

0.027 2.719 0.007

Husband’s Education (HEDU) (Year) 0.026 0.024 1.098 0.272

Type of Family (TYFAMI) (Nuclear = 1) -0.230 0.171 -1.345 0.179

Household Occupation CULTI, (Cultivation =1)

-0.123 0.175 -0.700 0.484

Household Occupation NONFARM (Non-Farm= 1) -0.490**

0.221 -2.219 0.027

Household’s Land holding, HLAND, (bigha) 0.014 0.030 0.471 0.637

Dependency Ratio in the Household DRATIO (%) -0.002 0.003 -0.770 0.441

Per Capita Household Income (APCHIN) (Rs. ‘000) 0.021**

0.010 2.046 0.041

Community Characteristics

CIWEC 0.026*

0.005 5.492 0.000

Duration of SHG-membership DSHGM (Month) 0.003 0.002 1.561 0.119

Caste (OBC=1) 0.161 0.180 0.894 0.372

Caste (SC=1) 0.093 0.183 0.508 0.611

Caste (ST=1) -0.329 0.250 -1.317 0.188

Summary Statistics

LR statistic (19 d f) (Probability) 238.393 (0.000) Akaike information Criterion 1.009

McFadden R-squared 0.304 Schwarz Criterion 1.160 Source: Author’s own computation based on sample observations, 2012-13

*, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

The coefficient of household occupation (Non-farm=1) in Model-1B points out that non-

farm self-employed households compared to wage labour class are less likely to take

family planning. Table-5.2.4 shows that if a household shifts to self-employed

occupation from service or wage earning jobs the probability of taking family planning

will reduce by 18 percentage points. Like Model-1A we find that household income

increases the probability of taking family planning as we expect. The coefficient of the

duration of SHG-membership is positive and statistically significant at 11% level. One

166

year extra participation in SHG from mean increases the probability of taking family

planning by 1.1% magnifying the consciousness in the member women that induces

them to take family planning. However, age at marriage, spousal age gap, family

composition, household’s landholding and caste are insignificant factors determining the

probability of accepting family planning decision.

Table-5.2.4 Marginal Probability of the Decision regarding Family Planning When

Women’s Empowerment is measured by Composite Index

Marginal effects after probit

Dependent Variable(y): Probability of the Decision regarding Family Planning (DRFP)

(predict) = .6457

Included observations: 580

Explanatory Variable

dy/dx

evaluated

at mean

Std. Error z-Statistic Prob.

>|z|

Mean of the

Explanatory

Variable(x)

Personal/Household Characteristics

CIWEH 0.005* .0015 3.77 0 3.00E-06

Women having at least two child (FMSF =1)# -0.021 .0631 -0.35 0.728 0.208

Women having at least two child (FFSM=1) # -0.140

** .0659 -2.14 0.033 0.191

Women having at least two child (FFSF =1) # -0.274

* .0716 -3.83 0 0.163

Age at Marriage AGAM (Year) 0.005 .0050 1.15 0.252 18.75

Spousal Age Gap (SAGEG) (Year) 0.015***

.0087 1.75 0.08 5.743

Education of the Woman (EDU) (Year) 0.027* .01 2.73 0.006 3.593

Husband’s Education (HEDU) (Year) 0.009 .0089 1.1 0.272 4.867

Type of Family (TYFAMI) (Nuclear = 1) # -0.082 .0593 -1.4 0.162 0.818

Household Occupation CULTI, (Cultivation =1) #

-0.045 .0654 -0.7 0.484 0.443

Household Occupation NONFARM (Non-Farm= 1) # -0.189

** .0866 -2.19 0.029 0.143

Household’s Land holding, HLAND, (bigha) 0.005 .011 0.47 0.637 2.646

Dependency Ratio in the Household DRATIO (%) -0.001 .0011 -0.77 0.441 49.68

Per Capita Household Income (APCHIN) (Rs. ‘000) 0.007**

.0038 2.07 0.038 13.78

Community Characteristics

CIWEC 0.009* .0017 5.48 0 1.10E-06

Duration of SHG-membership DSHGM (Month) 0.001 .0007 1.56 0.118 27.23

Caste (OBC=1) # 0.058 .064 0.91 0.362 0.232

Caste (SC=1) # 0.034 .0672 0.51 0.609 0.336

Caste (ST=1) # -0.126 .0983 -1.29 0.198 0.117

(#) dy/dx is for discrete change of dummy variable from 0 to 1 *, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

Source: Author’s own computation based on sample observations, 2012-13

We, therefore, observe that almost all the findings remain intact in Model-1B as they

were in Model-1A. The major findings in this section are as follows. Women’s

167

empowerments at the household level as well as at the community level are significant

determinants of the decision regarding family planning. We find that male child bias,

education of women, non-farm household occupation, dependency ratio, per capita

income and participation in SHG are important factors influencing the decision regarding

family planning.

5.3. Impact of Women’s Empowerment on Domestic Violence against Women

In this section we have explored the determinants of the incidence of domestic violence

for the women in the district of Bankura. At the outset, we would look into the nature of

domestic violence against women with respect to their age. We have observed that

younger and older women are experiencing higher risk of violence relative to the middle

aged group women. It indicates that newly married women (mean age at marriage is 19

years) and older suffers from more violence than the others. This finding supports that in

the middle age when women are physically and mentally more active to protest violence

and other family members become scared to make violence against women. However,

figure-5.3.1 shows that in all age group a major section of women is suffering from

domestic violence.

Figure-5.3.1 Age-Group Wise Prevalence of Domestic Violence against Women in

Bankura District

Source: Author’s own computation based on sample observations, 2012-13

In figure-5.3.1 we see that the relation between age and the incidence of domestic

violence against women is non linear. If we try to draw the line joining the mid points of

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the bars we get an approximately U shaped curve. It is already revealed in the profile of

inter correlation (refer to table-4.5.1) that the correlation between age and the incidence

of domestic violence is almost zero. We could not include age of the women as

determinant of the probability of the incidence of domestic violence, although, most of

the existing empirical study regarding domestic violence has included the age as

determinant of domestic violence.

So far, the examination of the impact of women’s empowerment on the probability of

experiencing domestic violence is our main motto. In addition to women’s

empowerment we have included spousal age gap, husband education and education of

other family members, household occupation, income, dependency ratio, dowry, drug

addiction of the husband, participation in SHG and caste of the women/household as

determinants of the incidence of domestic violence.

In accordance with the methodology of measuring women’s empowerment we have

estimated two models Model-2A and Model-2B for the incidence of domestic violence.

In Model-2A we consider the empowerment variables measured by simple average

method and Model-2B incorporates the composite indices of women’s empowerment

computed by PCA. In each model we have 580 observations.

5.3.1. Model 2A: Logit Model with Simple Empowerment Indices

In this sub-section, we discuss the results of the estimated logit model of the incidence of

domestic violence where empowerment variables have been measured by simple average

of the indicators. This average is termed as the degree of empowerment. The outcomes

of the Model-2A have been presented in table-5.3.1 and in table-5.3.2.

The coefficient of empowerment of women at the household level is -0.024, which is

statistically significant at 1.2% level. It indicates that other things remaining the same,

the household level empowerment of women reduce the log odds towards domestic

violence against them. The marginal change of probability has reported that one percent

increase in women’s empowerment at the household level from mean reduces the

probability of the incidence of domestic violence by 0.6% point. An empowered woman

can logically establish her views and she has some decision making power.

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Table-5.3.1 Results of the Logit Model for the Incidence of Domestic Violence

When Women’s Empowerment is Simple Average of the Indicators

Dependent Variable: Incidence of Domestic Violence (DVIO)

Method: ML - Binary Logit (Newton-Raphson)

Included observations: 580

Convergence achieved after 4 iterations

Covariance matrix computed using second derivatives

Explanatory Variable Coefficient Std. Error z-statistic Prob.

Constant 1.650 0.936 1.764 0.078

Individual/household Characteristics

DOWEH (%) -0.024*

0.010 -2.511 0.012

Duration of Married life (DURM), (Year) 0.010 0.013 0.780 0.435

Spousal Age Gap (SAGEG) (Year) -0.022 0.027 -0.812 0.417

Husband’s Education (HEDU) (Year) -0.054*

0.033 -1.632 0.103

Highest education among male household members

HIMEDU(Year) -0.078

* 0.032 -2.408 0.016

Type of Family, TYFAMI (Nuclear = 1) -0.162

0.278 -0.582 0.561

Household Occupation CULTI, (Cultivation =1)

-0.659*

0.278 -2.372 0.018

Household Occupation NONFARM (Non-Farm= 1) -0.676**

0.347 -1.945 0.052

Household’s Land holding, HLAND, (bigha) 0.089**

0.044 2.037 0.042

Dependency Ratio in the Household DRATIO (%) 0.004 0.005 0.822 0.411

Per Capita Household Income (APCHIN) (Rs. ‘000) -0.024**

0.012 -2.063 0.039

Dowry Given at Marriage (DOW)(Yes=1) 1.434*

0.287 4.994 0.000

Post Marriage Dowry Demand (PMDOW) (Yes=1) 1.366*

0.345 3.964 0.000

Drug Addiction of the Husband (ADDIC) (Yes=1) 0.885*

0.210 4.223 0.000

Community Characteristics

DOWEC (%) -0.014 0.011 -1.368 0.171

Duration of SHG-membership DSHGM (Month) 0.007**

0.003 2.202 0.028

Caste (OBC=1) 0.098 0.269 0.364 0.716

Caste (SC=1) 0.436 0.283 1.537 0.124

Caste (ST=1) 1.064*

0.425 2.502 0.012

Summary Statistics

LR statistic (19 d f) (Probability) 175.734 (0.000) Akaike information Criterion 1.136

McFadden R-squared 0.221 Schwarz Criterion 1.286

Source: Author’s own computation based on sample observations, 2012-13 *, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

The estimated coefficient of the duration of married life and the coefficient of spousal

age gap have appeared statistically insignificant. Besides, direction of the effect of the

duration of married life, which was expected as a reducing factor of domestic violence

against women, is rambling in determination of the probability of the incidence of

domestic violence. We also find that higher spousal age gap reduces the incidence of

domestic violence which is also unexpected. However, we are not worried about these

two findings because these empirical relations are statistically insignificant.

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Table-5.3.2 Marginal Probability for the Incidence of Domestic Violence When

Women’s Empowerment is Simple Average of the Indicators

Marginal Effects After Logit

Dependent Variable (y) = Probability for the Incidence of Domestic Violence (PDVIO) (predict) =0.5922

Included observations: 580

Explanatory Variable

dy/dx

evaluated

at mean

Std.

Error

z-

Statistic Prob.>|z|

Mean of the

Explanatory

Variable(x)

Personal/Household Characteristics

DOWEH (%) -0.0058**

0.0023 -2.5200 0.0120 68.2120

Duration of Married life (DURM), (Year) 0.0024 0.0031 0.7800 0.4350 16.8690

Spousal Age Gap (SAGEG) (Year) -0.0054 0.0066 -0.8100 0.4170 5.5940

Husband’s Education (HEDU) (Year) -0.0131***

0.0080 -1.6300 0.1030 4.8670

Highest education among male household members

HIMEDU(Year) -0.0187* 0.0078 -2.4100 0.0160 6.9930

Type of Family, TYFAMI (Nuclear = 1) # -0.0387 0.0657 -0.5900 0.5560 0.8180

Household Occupation CULTI, (Cultivation =1) #

-0.1588* 0.0661 -2.4000 0.0160 0.4430

Household Occupation NONFARM (Non-Farm= 1) # -0.1667

** 0.0854 -1.9500 0.0510 0.1430

Household’s Land holding, HLAND, (bigha) 0.0214**

0.0105 2.0300 0.0420 2.6460

Dependency Ratio in the Household DRATIO (%) 0.0010 0.0012 0.8200 0.4110 49.6840

Per Capita Household Income (APCHIN) (Rs. ‘000) -0.0058**

0.0028 -2.0500 0.0400 13.7884

Dowry Given at Marriage (DOW)(Yes=1) # 0.3431

* 0.0639 5.3700 0.0000 0.6910

Post Marriage Dowry Demand (PMDOW) (Yes=1) # 0.2816

* 0.0549 5.1300 0.0000 0.1568

Drug Addiction of the Husband (ADDIC) (Yes=1) # 0.2137

* 0.0504 4.2400 0.0000 0.5200

Community Characteristics

DOWEC (%) -0.0035 0.0026 -1.3700 0.1720 54.3760

Duration of SHG-membership DSHGM (Month) 0.0017**

0.0008 2.2000 0.0280 27.2390

Caste (OBC=1) # 0.0235 0.0642 0.3700 0.7140 0.2320

Caste (SC=1) # 0.1034 0.0657 1.5700 0.1160 0.3360

Caste (ST=1) # 0.2261

* 0.0752 3.0100 0.0030 0.1170

(#) dy/dx is for discrete change of dummy variable from 0 to 1

*, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively. Source: Author’s own computation based on sample observations, 2012-13

The coefficient of husband’s education is -0.054. It confirms that with higher educated

husband women gain strong foothold to fight against domestic violence. The estimation

of marginal probability also supports this result. The probability of facing domestic

violence reduces by 1.3% if the husband is educated one year more from mean education

level. Highest education among the male members in the family also reduces the

probability of the incidence of domestic violence against women. One year extra

schooling of the highest qualified male person in the family from mean education level

reduces the probability of having experience of domestic violence by 1.8% points.

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The coefficient of the dummy for family type is negative but insignificant. We have

measured the impact of household occupations with reference to wage labour class. The

coefficient of major household occupations CULTI and NONFARM are negative and

statistically significant at 1.8% and 5% level of significance respectively. It implies that

the incidence of domestic violence among women belonging to cultivator family and

non-farm employment holder family is less than that among the women belonging to

wage labour class. In table-5.3.2 we see that the probability of experiencing domestic

violence among the women belonging to cultivator family is 15% lower than that among

the labour class women. If a woman belongs to non-farm employment family instead of

belonging to the wage labour family the chance of domestic violence will reduce by 16%

points. In case of cultivator family and non-farm employment family women have some

control over asset and have some decision making power. Whereas in case of labour

family women may have some earning but it is controlled by family members and

usually they have no physical assets. As a result women belonging to labour class face

more violence compared to others.

The estimate of domestic violence shows that household’s landholding is a significant

determinant of the incidence of domestic violence against women. One bigha extra

landholding over the mean landholding increases the probability of domestic violence by

2.1% points. Landholding is a strong indicator of economic status at least in rural areas.

Higher size of landholding by a family implies the higher social and economic status of

that family. However, in rural area most of the women have no ownership of land. So,

higher size of household’s landholding means higher inequality in asset holding against

women. It often makes women exclusively dependent on male persons. This factor

makes domestic violence easy against women. Estimate of the logit model shows that

dependency ratio is a stimulating factor of domestic violence. Ten percent additional

dependency ratio increases the probability of domestic violence by one percent point.

This result supports our hypothesis but it is not significant.

We have found that higher per capita family income reduces the probability of

experiencing domestic violence against women, this relation is statistically significant. In

table-5.3.2 we see that one thousand additional household’s annual per capita income

above mean reduces the probability of experiencing domestic violence by 0.5% point.

Higher household income means higher economic status and occupational status and

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higher access to asset and wealth. These facts usually give honour the women in the

family as we expect. Our empirical analysis strongly supports our expectation.

Therefore, poor women in terms of land and income are more victimised in domestic

violence compared to others.

We have found that a major section of sample women has given dowry at marriage. The

coefficient of dowry given at marriage tells that women whose houses paid dowry at the

time marriage face more risk of domestic violence. The probability of facing domestic

violence for the women who paid dowry is 34% greater than the probability of facing

domestic violence for the women who did not pay dowry. Further, women who are

forced to pay extra dowry after marriage are more likely to face domestic violence. This

result is statistically significant at 1% level. In table-5.3.2 we find that post marriage

dowry demand increases the probability of domestic violence by 28%. Usually, women

are not willing to bring dowry from her natal house after marriage. This disagreement

often creates quarrel between the woman and in-laws or husband and thereby the women

face domestic violence. So, the result is justified. We have got that the coefficient of

drug addiction of the husband is positive and statistically significant. Drug addition of

the husband increases the probability of facing domestic violence 21% points. Usually

women protest against drug addiction of the husband. But addiction does not tolerate any

protest and thereby make violence against women. Our findings agree with this view.

Therefore, dowry at the marriage and post marriage time and drug addiction of the

husband are the main cause of domestic violence in the area under study.

We have observed that the community level empowerment of women reduces the

probability of domestic violence. The marginal change of probability reports that one

percent higher degree of community level empowerment above mean reduces the

probability of facing domestic violence by 0.35% but the result is statistically significant

at 17% level. It establishes that household level empowerment is more important that the

community level empowerment of the women for combating the curse of domestic

violence against them.

The coefficient of the duration of SHG membership is positive and statistically

significant at 2% level. Our empirical result shows that probability of domestic violence

will increase by 2% points if the duration of SHG membership increases by one year

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from average. Therefore, duration of SHG membership has been found to stimulate the

probability of suffering from domestic violence. The marginal probability of domestic

violence against women increases due to increase of the duration of SHG membership in

the area under study. This result goes against our hypothesis. This empirical result tells

us that women participate in SHG movement at the cost of domestic violence. By local

customs households don’t want that their women will move outside home and form a

group for social and economic movement. Sometimes women become member of SHGs

even when their family members oppose to do it. As a result there occurs domestic

violence within the family. So, domestic violence against women is an impediment of

financial inclusion for women in rural Bankura.

We have considered the women belonging to general caste as base category for assessing

the impact of caste dummies on the probability of facing domestic violence. The

coefficient of caste (OBC =1) is positive but insignificant. The coefficient of Caste

(SC=1) is positive and statistically significant at 11% level. This result is indicative that

the women belonging to scheduled castes are suffering more from domestic violence in

contrast to the women of general castes. Moreover, the coefficient of the caste dummy

(ST=1) is positive and statistically significant. The marginal probability calculation

shows that the probability of experiencing domestic violence is 22% (10%) higher for

the Scheduled tribe (scheduled castes) women compared to general caste women. During

our field survey we have noticed that there exist several types of superstitions among the

people of ST community such as Daini (witch) etc. which provokes violence against

women within the family. Therefore, scheduled tribes women are more vulnerable in

terms of domestic violence in the area under study.

We, therefore, conclude that women’s empowerment at the household level is an

important determinant of the probability of facing domestic violence. Moreover, we have

found that husband education, household occupation, dowry at marriage and at post

marriage and husband’s drug addiction are effective factors of domestic violence. This

empirical estimation, however, reveals that community level empowerment of women,

duration of married life, spousal age gap, type of family, dependency ratio and caste SC

and Caste OBC are statistically insignificant in the determinant of the probability of

domestic violence against women in the area under study.

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5.3.2. Model-2B: Logit Model with Composite Empowerment Indices

In this model composite index of women’s empowerment at the household level and at

the community level have been considered as exogenous variables along with the other

exogenous variables (as they were in Model-2A) for estimating the impact of

empowerment on the incidence of domestic violence. Table-5.3.3 and table-5.3.4

represent the results of the Model-2B.

Table-5.3.3 Results of the Logit Model for the Incidence of Domestic Violence

When Women’s Empowerment is Composite Index of the Indicators

Dependent Variable: Incidence of Domestic Violence (DVIO)

Method: ML - Binary Logit (Newton-Raphson) Included observations: 580

Convergence achieved after 4 iterations

Covariance matrix computed using second derivatives

Explanatory Variable Coefficient Std.

Error z-Statistic Prob.

Constant -0.736 0.727 -1.013 0.311

Individual/household Characteristics

CIWEH -0.018*

0.006 -2.781 0.005

Duration of Married life (DURM), (Year) 0.010 0.013 0.830 0.407

Spousal Age Gap (SAGEG) (Year) -0.022 0.027 -0.827 0.408

Husband’s Education (HEDU) (Year) -0.056***

0.033 -1.693 0.091

Highest education among male household members

HIMEDU(Year) -0.077

* 0.032 -2.397 0.017

Type of Family, TYFAMI (Nuclear = 1) -0.234 0.278 -0.845 0.398

Household Occupation CULTI, (Cultivation =1)

-0.641*

0.277 -2.313 0.021

Household Occupation NONFARM (Non-Farm= 1) -0.659**

0.346 -1.903 0.057

Household’s Land holding, HLAND, (bigha) 0.088**

0.043 2.032 0.042

Dependency Ratio in the Household DRATIO (%) 0.005 0.005 0.911 0.362

Per Capita Household Income (APCHIN) (Rs. ‘000) -0.024*

0.011 -2.087 0.037

Dowry Given at Marriage (DOW)(Yes=1) 1.403* 0.287 4.893 0.000

Post Marriage Dowry Demand (PMDOW) (Yes=1) 1.363*

0.343 3.979 0.000

Drug Addiction of the Husband (ADDIC) (Yes=1) 0.902*

0.210 4.303 0.000

Community Characteristics

CIWEC -0.007 0.007 -0.975 0.330

Duration of SHG-membership DSHGM (Month) 0.006**

0.003 2.005 0.045

Caste (OBC=1) 0.084 0.268 0.312 0.755

Caste (SC=1) 0.428 0.283 1.516 0.129

Caste (ST=1) 1.053*

0.426 2.474 0.013

Summary Statistics

LR statistic (19 d f) (Probability) 172.282 (0.000) Akaike information Criterion 1.142

McFadden R-squared 0.217 Schwarz Criterion 1.292

Source: Author’s own computation based on sample observations, 2012-13

*, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

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Table-5.3.4 Marginal Probability of the Incidence of Domestic Violence When

Women’s Empowerment is Composite Index of the Indicators

Marginal Effects After Logit

Dependent Variable (y) = Probability for the Incidence of Domestic Violence (PDVIO) (predict)

= 0.59081508

Included observations: 580

Explanatory Variable

dy/dx

evaluated

at mean

Std.

Error

z-

Statistic Prob.>|z|

Mean of the

Explanatory

Variable(x)

Individual/Household Characteristics

CIWEH -0.004* 0.0016 -2.7800 0.0050 3.00E-06

Duration of Married life (DURM), (Year) 0.002 0.0030 0.8300 0.4070 16.8690

Spousal Age Gap (SAGEG) (Year) -0.005 0.0066 -0.8300 0.4080 5.5948

Husband’s Education (HEDU) (Year) -0.0135***

0.0080 -1.6900 0.0900 4.8672

Highest education among male household members

HIMEDU(Year) -0.0185

* 0.0077 -2.4000 0.0170 6.9931

Type of Family, TYFAMI (Nuclear = 1)# -0.0557 0.0648 -0.8600 0.3890 0.8190

Household Occupation CULTI, (Cultivation =1) #

-0.1546* 0.0661 -2.3400 0.0190 0.4431

Household Occupation NONFARM (Non-Farm= 1) # -0.1626

** 0.0852 -1.9100 0.0560 0.1431

Household’s Land holding, HLAND, (bigha) 0.0213**

0.0105 2.0300 0.0420 2.6465

Dependency Ratio in the Household DRATIO (%) 0.0011 0.0012 0.9100 0.3620 49.6845

Per Capita Household Income (APCHIN) (Rs. ‘000) -0.0059**

0.0028 -2.0900 0.0370 13.7884

Dowry Given at Marriage (DOW)(Yes=1) # 0.3363

* 0.0642 5.2400 0.0000 0.6914

Post Marriage Dowry Demand (PMDOW) (Yes=1) # 0.2817

* 0.0549 5.1300 0.0000 0.1569

Drug Addiction of the Husband (ADDIC) (Yes=1) # 0.2181

* 0.0507 4.3000 0.0000 0.5207

Community Characteristics

CIWEC -0.0016 0.0017 -0.9700 0.3300 1.10E-06

Duration of SHG-membership DSHGM (Month) 0.0015**

0.0008 2.0100 0.0450 27.2397

Caste (OBC=1) # 0.0202 0.0643 0.3100 0.7540 0.2328

Caste (SC=1) # 0.1018 0.0656 1.5500 0.1210 0.3362

Caste (ST=1) # 0.2247

* 0.0758 2.9600 0.0030 0.1172

(#) dy/dx is for discrete change of dummy variable from 0 to 1 *, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

Source: Author’s own computation based on sample observations, 2012-13

In the model of the incidence of domestic violence where empowerment is measured by

the composite index of the indicators, we have found almost the same results as we have

found in Model-2A (table-5.3.1 and table-5.3.2). Table-5.3.4 shows that one percent

increase in women’s empowerment at the household level from its mean reduces the

probability of the incidence of domestic violence by 0.43% point. However, the

coefficient of community level empowerment of woman is statistically insignificant.

Therefore, in this model we also observed that household level empowerment is effective

176

to reduce domestic violence against women whereas community level empowerment is

not so important for reducing domestic violence. In addition to the household level

empowerment of women we find that husband education and education of other family

member reduce the incidence of domestic violence for the sample women. On the other

hand, dowry demand, drug addiction and participation in SHG stimulate domestic

violence against women in the district of Bankura, West Bengal. Therefore, change of

methodology for estimating the impact of women’s empowerment did not alter our

findings regarding the incidence of domestic violence.

5.4. Impact of Women’s empowerment on Expenditure for Child Education

In this section, we have interpreted the estimated results of child education expenditure

as proportion to annual household income. It is quite natural that in our sample all

women do not have children of school going age. So the estimation of the impact of

women’s empowerment on child education expenditure as proportion to household

income would be on the basis of those sample members who have school aged children

during the time of interview. Although our study is based on 580 observations, only 431

sample women have school aged children, who are either enrolled or not in school.

Therefore, the estimation of child education expenditure as proportion to annual

household income is based on only 431 observations. The issue of child education

expenditure as proportion to annual household income has been estimated using two log-

lin models, Model-3A and Model-3B. In Model-3A we have included the degrees of

women’s empowerment at the household level and at the community level in addition to

some selected households and community characteristics as exogenous variables. We

have considered the composite index of women’s empowerments including the other

exogenous variables in the determination of child education expenditure as proportion to

annual household income in Model-3B. Among other variables, we have incorporated

education level of father and other household members, household’s land holding,

household occupation, dependency ratio, composition of family, annual per capita family

income in the range of individual and household characteristics. Caste and the duration

of SHG-membership have been included as other community characteristics. The results

of the Model-3A and Model-3B have been presented in table-5.4.1 and in table-5.4.2

respectively. In these log-linear models we have a few dummy independent variables.

We have interpreted the coefficients of the dummies following the formula of Halvorsen

and Palmquist, (1980) [{exp (coefficient of dummy variable) – 1} x 100]. The summary

177

statistics shows that the log-linear models for child education expenditure are good fitted

and there is no heteroscedasticity problem in the estimates.

In table-5.4.1 the coefficient of women’s empowerment at the household level is 0.0014.

This result supports our expected direction but it is statistically insignificant. If we look

into the coefficient of community level empowerment, we find that community level

empowerment has a positive and significant impact on the proportion of household

income on child education. It implies that one percent increase in the degree of women’s

empowerment at the community level increases the proportion of household income

spent on child education by 0.48%. For Model-3B, this line of findings has also been

confirmed. It means that although both the household and community level

empowerment are instrumental for spending on child education, the community level

empowerment of women is more fruitful for spending more on child education.

Empowerment at the community level increases the spending in three ways. First, a

woman always wants that her child would be educated. This want is more active for

empowered women. So, it is expected that empowered women at the community level

spend or force to spend more of household income for her child. Second, empowered

women have own decision making power regarding the matters relating to children. This

power can increase expenditure for her children. Third, empowered women at the

community level are more conscious of the education of their children. This

consciousness induces to increase the expenditure for children out of school like private

tuition, school uniform, expenditure for co-curricular activities etc.

From the sign of the coefficient of father’s education (husband’s education, HEDU) we

can say that educated father spend smaller percentage of household income for his child

education. This result is statistically significant at one percent level. In table-5.4.1 and in

table-5.4.2 we find that one year extra schooling of father reduces the share of household

income spending for child education by 2.8%. Apparently, one may argue that this result

is unexpected. But this result may be supported by some economic logic. It is expected

that educated father earns more; so it is expected that as income increases due to higher

education of father the share of education expenditure will reduce. Therefore, our

empirical finding regarding the impact of father education on spending for child

education has a logical base.

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Table-5.4.1 Results of the Log-Linear Model for Child Education When Women’s

Empowerment is Simple Average of the Indicators

Dependent Variable: LEDEX{ln(Child Education Expenditure as Proportion to Annual Household

Income)}

Method: Least Squares

Included observations: 431

White heteroskedasticity-consistent standard errors & covariance

Explanatory Variable Coefficient Std. Error t-Statistic Prob.

Constant 1.8434 0.4438 4.1537 0.0000

Individual/household Characteristics

DOWEH (%) 0.0014 0.0017 0.8179 0.4139

Father’s education (HEDU) (Year) -0.0285*

0.0059 -4.8157 0.0000

Highest education among male household members,

HIMEDU,(Year) 0.0361* 0.0063 5.7362 0.0000

Highest education among female household

members HIFEDU(Year) 0.0217* 0.0056 3.8770 0.0001

Type of Family TYFAMI, (Nuclear =1) 0.2271* 0.0481 4.7262 0.0000

Household Occupation CULTI, (Cultivation =1)

0.0031 0.0471 0.0649 0.9483

Household Occupation NONFARM (Non-Farm= 1) 0.0371 0.0623 0.5951 0.5521

Household’s Land holding, HLAND, (bigha) 0.0058 0.0073 0.7896 0.4302

Dependency Ratio in the Household DRATIO (%) 0.0048* 0.0012 4.0110 0.0001

ln(APCHIN) -0.2408* 0.0493 -4.8827 0.0000

Community Characteristics

DOWEC (%) 0.0048* 0.0018 2.6326 0.0088

Duration of SHG-membership DSHGM (Month) 0.0004 0.0005 0.7179 0.4732

Caste (OBC=1) -0.0437 0.0461 -0.9484 0.3435

Caste (SC=1) -0.0880***

0.0521 -1.6891 0.0920

Caste (ST=1) -0.0938 0.0729 -1.2861 0.1991

Summary Statistics

R-squared 0.3402 Akaike information criterion 0.7690

Adjusted R-squared 0.3147 Schwarz criterion 0.9294

Durbin-Watson statistic 0.7178 F-statistic (Probability) 13.339 (0.000) Source: Author’s own computation based on sample observations, 2012-13

*, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

The coefficient of highest education among male household members in family is

positive and statistically significant. The magnitude of the coefficient speaks that one

year extra education of the highest qualified male member in the households increases

the proportion of household income spent on child education by 3.6% point. We have

got the same effect of highest education among male household members for Model-3B.

This result supports our hypothesis. The qualified male and female members understand

better the importance of education and accordingly oblige the parents to spend more for

the children. We have also found that highest education among female household

members have also positive and significant impact on child education expenditure as

proportion to household income. One year extra education of the highest qualified

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female increases share of child education expenditure in income by 2.1% point for both,

Model-3A and in Model-3B. We have observed that effect of male education is greater

than the effect of female education on the share of child education expenditure in

household income. It may happen due to the fact that the average education of the

highest qualified male is greater than the education of the highest qualified female. In the

course of field survey we have generally observed that highest educational qualification

goes in favour of the younger members who are still studying or seeking jobs. Naturally,

parents are inspired for spending more out of their income for their children’s education.

Therefore, educational back ground of the household is an important determinant of the

share of child education expenditure in household income.

Table-5.4.2 Results of the Log-Linear Model for Child Education When Women’s

Empowerment is Composite Index of the Indicators

Dependent Variable: LEDEX{ln(Child Education Expenditure as Proportion to Annual Household

Income)}

Method: Least Squares

Included observations: 431

White heteroskedasticity-consistent standard errors & covariance

Explanatory Variable Coefficient Std. Error t-Statistic Prob.

Constant 2.2103*

0.4314 5.1235 0.0000

Individual/Household Characteristics

CIWEH 0.0016 0.0012 1.3933 0.1643

Father’s education (HEDU) (Year) -0.0282* 0.0060 -4.7438 0.0000

Highest education among male household members,

HIMEDU,(Year) 0.0361* 0.0063 5.6883 0.0000

Highest education among female household

members HIFEDU(Year) 0.0218* 0.0056 3.9008 0.0001

Type of Family TYFAMI, (Nuclear =1) 0.2343* 0.0479 4.8936 0.0000

Household Occupation CULTI, (Cultivation =1)

0.0071 0.0472 0.1506 0.8804

Household Occupation NONFARM (Non-Farm= 1) 0.0406 0.0625 0.6484 0.5171

Household’s Land holding, HLAND, (bigha) 0.0061 0.0073 0.8373 0.4029

Dependency Ratio in the Household DRATIO (%) 0.0047* 0.0012 3.8351 0.0001

ln(APCHIN) -0.2430* 0.0489 -4.9680 0.0000

Community Characteristics

CIWEC 0.0027* 0.0011 2.3576 0.0189

Duration of SHG-membership DSHGM (Month) 0.0005 0.0005 0.9632 0.3360

Caste (OBC=1) -0.0397 0.0464 -0.8554 0.3928

Caste (SC=1) -0.0815 0.0528 -1.5422 0.1238

Caste (ST=1) -0.0866 0.0725 -1.1955 0.2326

Summary Statistics

R-squared 0.3376 Akaike information criterion 0.7729

Adjusted R-squared 0.3120 Schwarz criterion 0.9333

Durbin-Watson statistic 0.7115 F-statistic (Probability) 13.187 (0.000) Source: Author’s own computation based on sample observations, 2012-13

*, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

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According to our hypothesis the coefficient of the dummy for type of family (1= Nuclear

family) in Model-3A and in Model-3B are expected to be positive. In the empirical

estimation these coefficients are 0.227 in the Model-3A and 0.234 in Model-3B. These

results are statistically significant at 1% level. These indicate that the child education

expenditure as proportion to household income for the nuclear families is greater than

that for the joint or extended families. Following the formula of Halvorsen and

Palmquist, (1980) the coefficient of the dummy for type of family in the Model-3A

indicates that the mean child education expenditure as proportion to the household

income is 25.49% higher for the nuclear family than that for the other types of family.

Qualitatively almost same results we have found for Model-3B. These results support

our hypothesis. Therefore, we come to the conclusion that the nuclear composition of

family increases the child education expenditure as proportion to household income in

the district of Bankura. During the field survey we have seen that most of the parents in

nuclear family compared to joint and extend families are more serious and have soul

authority to spend for their child. It justifies our result regarding the effect of family

composition on child education expenditure.

In order to assess the impact of household occupation on pattern of spending on child

education we have categorized the household occupation into three categories –

cultivation, non-farm self employment/service and wage labour class. For econometric

analysis labour class has been considered as reference category. Table-5.4.1 and table-

5.4.2 exhibit that the household occupations (Cultivation=1) and (Non-farm self

employment=1) have positive impact on child education expenditure. We find that in

both the models child education expenditure as proportion to household income is higher

for cultivator family (0.31%) and for self-employed/service holder family (3.77%) than

labour class family. However, the impacts of household occupation on child education

expenditure are not statistically significant. The coefficient of landholding in both the

models indicates that landholding has a direct effect on child education expenditure. It is

compatible with our expectation but this result is statistically insignificant.

This study asserts that dependency ratio has some favorable effect on child education

expenditure as proportion to household income. The estimated coefficient shows that one

percent increase in dependency ratio increases the share of child education expenditure

by 0.48% in Model-3A (0.47% in Model-3B). This result is statistically significant at 1%

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level. Although this finding goes against our hypothesis we can explain the findings

based on our ground experiences. In the course of field survey we have observed that a

major portion of the sample households are nuclear and dependents are children.

Therefore, the higher is the value of dependency ratio the higher is the number of

children. Number of children definitely increases the share of income spent on child

education. That is why, we have obtained a direct relation between dependency ratio and

child education expenditure as proportion to household income.

We know that any kind of expenditure depends on income. Like other expenditure child

education expenditure necessarily depends on household income. In our log-linear model

we have tried to examine the effect of the log of per capita income on the log of child

education expenditure as proportion to household income. For both Model-3A and

Model-3B, we find that the coefficient of the log of per capita household income is –

0.24 which is statistically significant at one per cent level. It indicates that one per cent

increase in per capita household income reduces the share of income spent one child

education by 0.24%.

Now we interpret the impact of community characteristics on child education

expenditure. We have already explained that community level empowerment of women

have a significant impact on child education expenditure as proportion to household

income. We have observed that a large section of household particularly women have

joined SHG-centric microfinance which organize the poor women for financial inclusion

and let them to understand the importance of child education and health and other social

issues. With this end in view, we have taken the duration of SHG membership as an

explanatory variable in the spectrum of community characteristics in this model of child

education expenditure. The coefficient of the duration of SHG-membership is found to

be positive. It means that if any member in household participates in SHG and continues

the membership, child education expenditure increases. It is as per with our expectation.

However, this empirical result in both model are statistically insignificant. It is indicative

that SHG movement may be successful to ensure financial inclusion but it is less

important to enhance the expenditure for child education.

Like other issues regarding women’s empowerment in the estimation of child education

expenditure as proportion to household income we have considered three dummies for

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castes. The households belonging to general castes are reference category. The

coefficients of the caste dummies are negative. They indicate that the share of household

income spent for child education is lower for the OBC, SC and ST households in

contrast to the general caste households. The coefficient of the dummy for caste (SC=1)

is statistically significant at 9% level in Model-3A and at 12% level in Model-3B. We

compute that child education expenditure as proportion to household income for

scheduled castes household is 8.42 % smaller than that for general castes households.

However, the coefficient of the dummies Caste (OBC=1), Caste (ST=1) are not

statistically significant. The backwardness of the lower castes and unconsciousness

regarding child education gives these results. It makes the vicious circle of educational

poverty. Due to backwardness and income poverty, the lower castes could not spend

more for education which in turn keep these people backward in terms of education and

income.

This section, therefore, concludes that women’s empowerment i.e. mothers

empowerment, father’s education, highest education of the male persons in the family,

highest education of the female persons in family, family type, dependency ratio, income

and caste are the most important determinants of child education expenditure as

proportion to household income for the households in the district of Bankura.

5.5. Determinants of Women’s Empowerment in Bankura District

In the last three subsequent sections, we have interpreted and explained the impact of

women’s empowerment at the household level and at the community level along with

selected household and community characteristics on three issues of household and child

welfare. We have found that women’s empowerment at the household level and at the

community level have some positive and significant effect on the probability of adopting

family planning decision for the households in the district of Bankura. Women’s

empowerment at the household level and at the community level reduces the probability

of the incidence of domestic violence against women. Our empirical research has also

shown that women’s empowerment is very much important on spending more for child

education. Therefore, it has been empirically established that women’s empowerment are

instrumental for household and child welfare in the district of Bankura. Once we have

found the instrumental role of women’s empowerment, we should examine the

determining factors of women’s empowerment at the household level and at the

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community level. To this end, we have estimated two multiple linear regression models –

one for women’s empowerment at the household level and another for women’s

empowerment at the community level. In this section, with two sub-sections we interpret

the estimated models relating to women’s empowerment at the household level and at

the community level.

5.5.1. Determinants of Women’s Empowerment at the Household Level

In this sub-section, we explain the estimated multiple linear regression model relating to

women’s empowerment at the household level. Based on two measures of women’s

empowerment at the household level, we have estimated two multiple liner regression

models with same set of explanatory variables. Both these multiple regression models

include some quantitative explanatory variables and some dummy variables. This

implies that our regression models relating to the women’s empowerment are known as

Analysis of Covariance Models (ANCOVA). First, we discuss the findings of the model

(Model-4A) where household level women’s empowerment has been measured by

simple average of its Indicators. Next we explain the models (Model-4B) of household

level women’s empowerment measured by weighted average of PCA of the indicators.

The empirical estimates of models have been presented in table-5.5.1 and table-5.5.2

respectively. The goodness of fit is reasonable for both the models. Again F-statistics is

significant for both the model. The result of White test of heteroscedasticity reveals that

estimates of the models for household empowerment of women do not suffer from

heteroscedasticity problem.

Age is a very important factor for growing personality of a person. Although age of a

person is quantitative variable, in this study sample women have been divided into four

age groups for examining the impact of age on their empowerment. We have included

three dummies and the older age group (age>45 Years) has been considered as reference

category. The coefficient of age group (< 25 years) is positive. It indicates that

controlling other explanatory variables, the age group (< 25 years) enjoys 3% point

higher empowerment at the household level compared to the household level

empowerment of the older group. But the result is statistically significant at 14.5 % level.

The age group AGE2 (25-35 years) of the women has positive and significant impact on

empowerment index. The average degree of empowerment of women at the household

level increases by 4.26% points if the women belong to AGE2 group instead of AGE4.

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Further, women under age group AGE3 (36-45 Years) enjoy 3% points higher

empowerment at the household level compared to the empowerment at the household

level of the reference age group. In Model-4B we have got the qualitatively same result

regarding the effect of age on women’s empowerment at the household level. We have,

therefore, found that young women in contrast to the older women are more empowered.

However, it does not mean the reduction of traditional respects of elder rather now a-

days elders share their power with the younger.

The coefficient of the education level of the women is negative in Model-4A and

positive in Model-4B. The result of Model-4B justifies our hypothesis. But both the

results are statistically insignificant. It is indicative that women’s education is not so

much important in the determination of the women’s empowerment at the household

level in the district of Bankura. Education of women should have positive and significant

impact on household level women’s empowerment. Yet we should point out the fact that

most of the sample women have education below primary level. So, what impact should

we expect from this level of education on empowerment? Further, in the time of

interview we have observed that many educated women could not take several familial

decisions and don’t have any say regarding economic matter of the households. On the

other hand, many illiterate women in the low caste family enjoy commendable

empowerment at the household level.

Personal occupation of the women is, no-doubt, a crucial determinant of women’s

empowerment at the household level. Personal occupation of our sample women has

been categorized in three groups – wage labour, self-employed or formal service holders

and homemakers. Homemaker is here benchmark category. Our empirical estimates

shows that the coefficient LAB (Wage labour =1) is negative and statistically significant.

Controlling the other things, the magnitude of the coefficient of LAB (Wage labour =1)

signifies that average household level empowerment of wage labour women is 6.1%

point lower than that of the homemakers. It goes against our hypothesis. Wage labourers

earn some income but in most of the cases earnings are controlled by their families,

particularly, by their husbands. Besides, wage earners are usually illiterate or just

literates, accordingly they are less concern regarding the economic decisions. It may

explain the causes of the low level household empowerment of the wage labourers

compared to homemakers. On the other hand, the coefficient of SELF (Self employed or

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service=1) is positive (4.26) and statistically significant. It says that mean of household

level empowerment of self employed or service holder women is higher by about 4.26%

point than mean of household level empowerment of the benchmark category. This result

has justified our hypothesis. Relative to common homemaker self employed and formal

service holders are definitely more powerful to take several household level decisions

and hold some more physical and financial asset. In Model-4B, we have obtained almost

same findings regarding the impact of personal occupation on household level

empowerment of the women.

Estimating the ANCOVA model for women’s empowerment at the household level we

find that personal income of the women has some positive and statistically significant

impact on household level empowerment of women. The coefficient of personal income

shows that one thousand additional average annual personal income of the woman

increases the household level empowerment by 9.36% points from average. In Model-4B

we have seen the qualitatively same result regarding the impact of personal income on

household level empowerment. Therefore, our empirical results support the hypothesis.

When a woman earn, she becomes economically independent. We have projected that

income of wage labor women is controlled by other family members. But in average for

all we can say that women earners have some economic dignity or empowerment in their

households.

In order to assess the impact of financial inclusion on household level empowerment of

the women we have included the dummy AFCT (access to formal credit, Yes=1) as an

explanatory variable in the model for empowerment at the household level. Our

empirical estimates of the ANCOVA models, Model-4A and Model-4B, show that the

coefficient of AFCT is positive and statistically significant. The coefficient refers to that

other factors remaining same if a woman has access to formal credit it increases her

empowerment at the household by 4.45% points from the average. This result supports

our hypothesis and is not hard to explain the logic behind. Access to formal credit

enhances the importance of the women in her household through borrowing from

institution in different difficult situations. Further, when a woman can borrow from

formal institution it is expected that she is powerful in different familial decision making

process. Having access to formal credit, women may take decisions regarding children’s

education and saving credit decision independently. So, it is expected that access to

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formal credit by women inculcates women’s empowerment. Therefore, financial

inclusion increases the household and child welfare through the channel of women’s

empowerment at the household level.

We obtain that the coefficient of the dummy for the type of family is 4.99 in Model-4A

and it is 5.45 in Model-4B. Therefore, the coefficient of the dummy for family type tells

us that household level empowerment of women of nuclear families is almost 5% points

higher from average household level empowerment of the women of joint/extended

families. It is not surprising that women in the nuclear families enjoy exclusive power in

economic and familial decision making process. So, our empirical result regarding the

effect of family type on household level empowerment of women is reasonably

conclusive.

We have observed that dependency ratio has some adverse effect on the household level

empowerment of women. In both the regression analysis the coefficient of the

dependency ratio is negative and statistically significant. In Model-4A the coefficient of

the dependency ratio interpret that one percent increase in dependency ratio from

average level reduces the household level empowerment of the women by 0.5% points

from average empowerment. However, dependency ratio reduces empowerment but the

effect is marginal. In the family with higher dependent members like old or child,

women have to spend more time in the household’s jobs. They get less time for earning

as well for knowing and thinking about various economic issues. So, higher dependency

ratio reduces women’s empowerment within the household.

In our empirical estimation we have got a favourable impact of per capita household

income on women’s empowerment at the household level in both the models– Model-4A

and Model-4B. The coefficient of the per capita household income tells us that

household level empowerment of women increases with household income. However,

the empirical relation between household income and women’s empowerment is not

statistically significant. Therefore, our study suggests that although personal income is

significantly important, household income is immaterial in the determination of women’s

empowerment at the household level for the women in the district of Bankura of West

Bengal.

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Table-5.5.1 Estimates of degree of Women’s Empowerment at Household Level

Dependent Variable: Degree of Women’s Empowerment at Household Level (DOWEH)

Method: Least Squares

Sample: 1 580

Included observations: 580

Explanatory Variable Coefficient Std. Error t-Statistic Prob.

Constant 59.001*

2.391 24.677 0.000

Individual/Household Characteristics

Age Group (<25 Years) AGE1 (Yes=1) 2.941 2.015 1.459 0.145

Age Group (25-35 Years) AGE2 (Yes=1) 4.261* 1.512 2.819 0.005

Age Group (36-45 Years) AGE3 (Yes=1) 3.037**

1.413 2.150 0.032

Education of the Woman, EDU (Year) -0.036 0.193 -0.184 0.854

Occupation of the Woman, LAB (Wage Labour=1) -6.102* 1.132 -5.389 0.000

Occupation of the Woman, SELF (Self employed or

Service =1) 4.268

* 1.874 2.277 0.023

Average Monthly Personal Income PINC (Rs. '00) 0.078* 0.027 2.865 0.004

Access to Formal Credit AFCT (Yes=1) 4.458* 1.166 3.823 0.000

Type of Family TYFAMI (Nuclear =1) 4.998* 1.279 3.907 0.000

Dependency Ratio in the Household DRATIO (%) -0.058**

0.025 -2.313 0.021

Per Capita Household Income (APCHIN) (Rs. ‘000) 0.051 0.045 1.151 0.250

Household Occupation CULTI, (Cultivation =1)

-5.514* 1.297 -4.251 0.000

Household Occupation NONFARM (Non-Farm= 1) 1.336 1.660 0.805 0.421

Household’s Land holding, HLAND, (bigha) 0.258 0.199 1.295 0.196

Highest education among male household members,

HIMEDU,(Year) -0.173 0.139 -1.240 0.216

Highest education among female household members

HIFEDU(Year) 0.547

* 0.161 3.399 0.001

Community Level Characteristics

Duration of SHG membership DSHGM (Month) 0.021 0.017 1.291 0.197

Caste (OBC =1) 1.578 1.309 1.205 0.229

Caste (SC=1) 1.134 1.366 0.830 0.407

Caste (ST=1) -0.412 1.824 -0.226 0.821

Summary Statistics

R-squared 0.341 Akaike information criterion 7.712

Adjusted R-squared 0.316 Schwarz criterion 7.878

Durbin-Watson statistic 1.691 F-statistic (Probability) 13.744 (0.000)

White Heteroskedasticity Test: H0: Variance of random disturbance term is constant

F-statistic (Probability) 0.985(0.548) Obs×R-squared (Probability) 228.262(0.520)

Source: Author’s own computation based on sample observations2012-13

*, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

We have taken two dummy variables for major household occupation in our ANCOVA

model. The coefficient of the major household occupation dummy (Cultivation=1) is –

5.51. It implies that the average degree of household level empowerment of the women

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belonging to cultivator family is 5.51% points lower than that of the women belonging to

wage labour family. This result is statistically significant in both the models. This

empirical result does not support our hypothesis. But, this empirical finding is insightful.

During the course of data collection we have seen that women in the wage labour family

are more vocal than the women in cultivator family. Wage labour families are usually

tribal or low castes where by custom women enjoy empowerment at the household level.

Further, in the wage labour family women are earner which often inculcates

empowerment at the household level. On the other hand, the coefficient of the dummy

indicating (self employment=1) is positive in both the models. It means that the degree

of empowerment at the household level of the women under self employed family is

higher than that of the women under wage labour. However, this result is not statistically

significant at all.

The coefficient of landholding shows that other things remaining unchanged, one bigha

extra landholding increases the household level empowerment by 0.25% points in

Model-4A and 0.52% points in Model-4B. The result in Model-4B is statistically

significant at 6% level. Therefore, the estimation of the Model-4B establishes that

household’s landholding increases the household level empowerment of the women in

the district of Bankura. Large land size of the household ensures livelihood security of

the family and the women. Often women have the land ownership in the household with

higher landholdings. These matters may enhance dignity of the women and accordingly

the empowerment at the household level.

The coefficient of highest education among the male household members is statistically

insignificant as an explanatory variable in the models for women’s empowerment at the

household level. On the other hand, the coefficient of the highest education among the

female members is positive and statistically significant at 1% level. The coefficient

implies that one extra completed year of education of the highest qualified female

member increases the average degree of empowerment at the household level by 0.55%

points. We have got almost the same result in Model-4B regarding the highest female

education. Therefore, female education is more imperative than the male education in the

family for inculcating women’s empowerment at the household level. It is expected that

most of the educated women persuades the decisions making power and the personality

of the women. Hence, our result is expected.

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Table-5.5.2 Estimates of Composite Women’s Empowerment Index at Household

Level

Dependent Variable: Composite Index of Women’s Empowerment at Household Level (CIWEH)

Method: Least Squares

Sample: 1 580

Included observations: 580

Variable Coefficient Std.

Error

t-

Statistic Prob.

Constant -11.627 3.350 -3.471 0.001

Individual/Household Characteristics

Age Group (<25 Years) AGE1 (Yes=1) 3.757 2.823 1.331 0.184

Age Group (25-35 Years) AGE2 (Yes=1) 6.190* 2.118 2.923 0.004

Age Group (36-45Years) AGE3 (Yes=1) 4.207**

1.979 2.126 0.034

Education of the Woman, EDU (Year) 0.180 0.270 0.664 0.507

Occupation of the Woman, LAB (Wage Labour=1) -7.964* 1.586 -5.020 0.000

Occupation of the Woman, SELF (Self employed/Service =1) 7.563* 2.626 2.880 0.004

Average Monthly Personal Income PINC (Rs. '00) 0.127* 0.038 3.342 0.001

Access to Formal Credit AFCT (Yes=1) 5.017* 1.634 3.071 0.002

Type of Family TYFAMI (Nuclear =1) 5.453* 1.792 3.043 0.003

Dependency Ratio in the Household DRATIO (%) -0.089* 0.035 -2.533 0.012

Per Capita Household Income (APCHIN) (Rs. ‘000) 0.061 0.063 0.969 0.333

Household Occupation CULTI, (Cultivation =1)

-8.544* 1.817 -4.702 0.000

Household Occupation NONFARM (Non-Farm= 1) 2.666 2.325 1.147 0.252

Household’s Land holding, HLAND, (bigha) 0.521**

0.279 1.866 0.063

Highest education among male household members,

HIMEDU,(Year) -0.207 0.195 -1.059 0.290

Highest education among female household members

HIFEDU(Year) 0.488

** 0.225 2.165 0.031

Community Level Characteristics

Duration of SHG membership DSHGM (Month) 0.052**

0.023 2.237 0.026

Caste (OBC =1) 2.979***

1.834 1.624 0.105

Caste (SC=1) 2.435 1.914 1.272 0.204

Caste (ST=1) -0.085 2.555 -0.033 0.974

Summary Statistics

R-squared 0.345 Akaike information criterion 8.387

Adjusted R-squared 0.321 Schwarz criterion 8.552

Durbin-Watson statistic 1.662 F-statistic (Probability) 14.019 (0.000)

White Heteroskedasticity Test: H0: Variance of random disturbance term is constant

F-statistic (Probability) 1.224 (0.045) Obs×R-squared (Probability) 258.931 (0.092)

Source: Author’s own computation based on sample observation, 2012-13 *, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

Let us now interpret the impact of selected community level traits on women’s

empowerment at the household level. A large section of the sample women have joined

SHG-centric microfinance programme which has nowadays taken the shape of social

190

movement. It inspired us to take the duration of SHG-membership as an explanatory

variable in the spectrum of community characteristics in the determination of women’s

empowerment at the household level. The coefficient of the duration of SHG

membership tells us that one year extra participation in SHG increases the empowerment

at the household level by 0.24% points. This result is statistically significant at 19% level

in Model-4A and 2% level in Model-4B. The logic behind this result comes out as

follows. First, the participation in SHG ensures the access to formal savings and credit of

the member women. It increases the financial asset holding of the women. Second,

access to formal credit increases the importance of the women within household. Third,

frequent meeting of group inculcate the political consciousness and democratic behavior

of the women. As a result, the duration of SHG membership has a direct effect on

women’s empowerment at the household level.

Caste is another community level trait which has been considered as a determinant of

women’s empowerment at the household level. This study shows that the coefficients of

the dummies for caste (SC=1) and caste (OBC=1) are positive. It points out that

empowerment at the household level is higher for the women under scheduled castes and

other backward classes in contrast to that for the women under general castes. On the

other hand, the coefficient of dummy for caste (ST=1) tells us that women belonging to

scheduled tribes are less empowered compared to women belonging to general castes.

However, Caste variables are not statistically significant determinants of women’s

empowerment at the household level.

Hence, estimates of women’s empowerment at the household level reveal that age,

occupation personal income, financial inclusion of the women, family type, dependency

ratio, household occupation, highest female education in the family are the major

determinants of women’s empowerment at the household level for the women in the

district of Bankura.

5.5.2. Determinants of Women’s Empowerment at the Community Level

We have computed the community level women’s empowerment applying two

alternative methodologies. The multiple regression models relating to the women’s

empowerment at the community level include some quantitative explanatory variables

and some dummy variables. So, these are known as Analysis of Covariance Models

191

(ANCOVA). In this sub-section we interpret the estimated ANCOVA models relating to

women’s empowerment at the community level. We have considered the same

household and community characteristics as explanatory variables in the model for

community level empowerment as they were in the model for household level

empowerment of women. First, we discuss the findings of the model (Model-4C) where

community level women’s empowerment has been measured by simple average of its

indicators. Next we explain the models (Model-4D) of community level women’s

empowerment measured by weighed average of principal components of the indicators.

The empirical estimates of Model-4C and Model-4D have been presented in table-5.5.3

and table-5.5.4 respectively. We find that goodness of fit for both the models is at

satisfactory level. F-statistic is statistically significant for both the models. The result of

White test of heteroscedasticity confirms the absence of heteroscedasticity problem in

the estimates of these models.

No doubt age of woman is an imperative factor for developing personality and mobility

in the society. The coefficient of age group (< 25 years) is positive. It tells us that the age

group (< 25 years) enjoys 0.82% point higher empowerment at the community level

compared to that of the aged group. But the result is statistically insignificant in both the

models. The age group AGE2 (25-35 years) of the women is found to be favourable for

community level empowerment. The average degree of empowerment at community

level of the women belonging to AGE2 group (belonging to age group AGE3 (36-45

Years)) is 3.7% (3%) points higher than that of AGE4. Further, in the estimation of

community level empowerment measured by PCA we have got qualitatively the same

result regarding the effect of age on women’s empowerment. Therefore, from this

finding we conclude that middle aged women in contrast to the aged women are more

empowered at the community level. Thus, middle aged women relative to aged women

have more mobility and socio economic consciousness.

The coefficients of the education level of women are positive and statistically significant

in Model-4C and in Model-4D. The coefficient of women’s education demonstrates that

one extra completed year of education increases the community level empowerment by

0.34% points from the mean level of empowerment. These results justify our hypotheses.

It is indicative that women’s education is a key factor in the determination of the

women’s empowerment at the community level in Bankura district. Although we have

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reported that education of women is immaterial in the determination of household level

empowerment, but education has positive and significant impact on community level

empowerment of the women. Higher level of education expands the job opportunity,

mobility and accessibility to social institutions which are imperative to empowerment at

the community level. However, we should remember that most of the sample women

have education below the primary level. As a result we have got a marginal effect of

women’s education on their community level empowerment.

Among the dummies for personal occupations the coefficient of personal occupation

LAB (Wage labour=1) is negative and statistically significant. It implies that average

community level empowerment of wage labour women is 2.32% points lower than that

of the homemakers. Usually the earnings of women wage labourers are low and

controlled by their family members, particularly, by their husbands. As they are illiterate

or just literates and poor, they are less concern regarding the economic decisions and

several rights and opportunities. Thereby they have less participation on social and

community activities. Moreover, wage labour is not a respectful occupation in our

society. That is why, community level empowerment of the wage labourers is lower than

compared to that of homemakers. On the other hand, the coefficient of the dummy for

personal occupation SELF (Self employed or service=1) is positive but statistically

insignificant. It says that self-employed or service holder women are more empowered

than the homemakers in their community. This result has justified the expected direction

of relation. These findings are almost same for Model-4D.

In the estimation of the Model-4A and Model-4B we have seen that personal income of

women significantly affects women’s empowerment at the household level. But for

community level, the coefficients of personal income are positive but statistically

insignificant in Model-4C and Model-4D. Therefore, our empirical results explore that

personal income is important for accelerating household level empowerment but it is less

important to increase the degree of empowerment at the community level. We have

observed that most of the women earn from informal sector and they are ill paid.

Besides, these jobs do not get respect in our traditional society. This causes the

insignificant relation between the personal income and community level empowerment

of the women.

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Table-5.5.3 Estimates of degree of Women’s Empowerment at Community Level

Dependent Variable: Degree of Women’s Empowerment at Community Level (DOWEC)

Method: Least Squares

Sample: 1 580

Included observations: 580

Explanatory Variable Coefficient Std. Error t-Statistic Prob.

Constant 41.023 1.985 20.670 0.000

Individual/Household Characteristics

Age Group (<25 Years) AGE1 (Yes=1) 0.828 1.673 0.495 0.621

Age Group (25-35 Years) AGE2 (Yes=1) 3.692*

1.255 2.942 0.003

Age Group (36-45 years) AGE3 (Yes=1) 3.047* 1.173 2.598 0.010

Education of the Woman, EDU (Year) 0.347**

0.160 2.163 0.031

Occupation of the Woman, LAB (Wage

Labour=1) -2.324

* 0.940 -2.472 0.014

Occupation of the Woman, SELF (Self employed/

Service =1) 2.106 1.556 1.354 0.176

Average Monthly Personal Income PINC (Rs. '00) 0.032 0.023 1.427 0.154

Access to Formal Credit AFCT (Yes=1) 7.457* 0.968 7.704 0.000

Type of Family TYFAMI (Nuclear =1) 2.286**

1.062 2.153 0.032

Dependency Ratio in the Household DRATIO (%) -0.064* 0.021 -3.065 0.002

Per Capita Household Income (APCHIN) (Rs.

‘000) 0.017 0.037 0.456 0.648

Household Occupation CULTI, (Cultivation =1)

-2.534**

1.077 -2.353 0.019

Household Occupation NONFARM (Non-Farm=

1) -0.403 1.378 -0.293 0.770

Household’s Land holding, HLAND, (bigha) 0.459* 0.166 2.775 0.006

Highest education among male household

members, HIMEDU,(Year) -0.008 0.116 -0.067 0.947

Highest education among female household

members HIFEDU(Year) 0.390

* 0.134 2.923 0.004

Community Level Characteristics

Duration of SHG-membership DSHGM (Month) 0.076* 0.014 5.542 0.000

Caste (OBC =1) 0.699 1.087 0.643 0.520

Caste (SC=1) 1.276 1.134 1.125 0.261

Caste (ST=1) -3.420**

1.514 -2.260 0.024

Summary Statistics

R-squared 0.535 Akaike information

criterion 7.340

Adjusted R-squared 0.518 Schwarz criterion 7.505

Durbin-Watson statistic 1.809 F-statistic (Probability) 30.609(0.000)

White Heteroskedasticity Test: H0: Variance of random disturbance term is constant

F-statistic (Probability) 1.065(0.298) Obs×R-squared (Probability) 239.167(0.325)

Source: Author’s own computation based on sample observations 2012-13

*, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

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Table-5.5.4 Estimates of Composite Women’s Empowerment Index at Community

Level

Dependent Variable: Composite Index of Women’s Empowerment at Community Level (CIWEC)

Method: Least Squares

Included observations: 580

Explanatory Variable Coefficient Std. Error t-Statistic Prob.

Constant -19.691 2.835 -6.947 0.000

Individual/Household Characteristics

Age Group (<25 Years) AGE1 (Yes=1) 0.306 2.389 0.128 0.898

Age Group (25-35 Years) AGE2 (Yes=1) 4.723*

1.792 2.635 0.009

Age Group (36-45 Years) AGE3 (Yes=1) 3.606**

1.675 2.153 0.032

Education of the Woman, EDU (Year) 0.693* 0.229 3.027 0.003

Occupation of the Woman, LAB (Wage Labour=1) -3.126**

1.343 -2.328 0.020

Occupation of the Woman, SELF (Self employed or

Service =1) 1.334 2.222 0.600 0.548

Average Monthly Personal Income PINC (Rs. '00) -0.008 0.032 -0.237 0.813

Access to Formal Credit AFCT (Yes=1) 11.937* 1.382 8.635 0.000

Type of Family TYFAMI (Nuclear =1) 3.063**

1.516 2.020 0.044

Dependency Ratio in the Household DRATIO (%) -0.039 0.030 -1.318 0.188

Per Capita Household Income (APCHIN) (Rs.

‘000) 0.065 0.053 1.235 0.218

Household Occupation CULTI, (Cultivation =1)

-2.563***

1.538 -1.667 0.096

Household Occupation NONFARM (Non-Farm= 1) -0.225 1.968 -0.114 0.909

Household’s Land holding, HLAND, (bigha) 0.551**

0.236 2.329 0.020

Highest education among male household

members, HIMEDU,(Year) -0.030 0.165 -0.184 0.854

Highest education among female household

members HIFEDU(Year) 0.503

* 0.191 2.635 0.009

Community Level Characteristics

Duration of SHG-membership DSHGM (Month) 0.078* 0.020 4.002 0.000

Caste (OBC =1) -0.775 1.552 -0.499 0.618

Caste (SC=1) -0.148 1.620 -0.092 0.927

Caste (ST=1) -8.596* 2.162 -3.976 0.000

Summary Statistics

R-squared 0.526 Akaike information criterion 8.053

Adjusted R-squared 0.508 Schwarz criterion 8.218

Durbin-Watson statistic 1.862 F-statistic (Probability) 29.487 (0.000)

White Heteroskedasticity Test: H0: Variance of random disturbance term is constant

F-statistic (Probability) 0.862(0.888) Obs×R-squared (Probability) 210.152 (0.822)

Source: Author’s own computation based on sample observations2012-13

*, ** and *** imply that coefficients are significant at level 1%, 5% and 10% respectively.

The coefficient of financial inclusion i.e. the coefficient of dummy AFCT (access to

formal credit, Yes =1) in Model-4C and Model-4D are found to be positive and highly

significant. The coefficient of access to formal credit indicates that the community level

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empowerment of the women will increase by 7.45% points if she has access to formal

credit. When a woman can borrow form formal institution it makes an identity in society

or in social institutions. Again access to formal credit, particularly, from SHGs or

cooperative inculcates the banking habits and democratic idea allowing them in election

and selection process. In this way formal borrowing accelerates the women’s

empowerment at community level. Therefore, our study reveals that financial inclusion

increases women’s empowerment at the household level and at the community level.

It is seen that the type of family is a significant determinant of community level

empowerment of women. Our empirical estimate reports that community level

empowerment is 2.28% points higher of the women in nuclear families compared to the

women in joint/extended families. Women in the nuclear families enjoy more freedom to

participate in social and community decision making process. Besides, women in nuclear

families are compelled to move outside more for several household requirements which

definitely improve the community level empowerment. So, the result regarding the effect

of family type on community level empowerment of women is meaningful.

Like the estimation of the models for household level empowerment of women, we have

observed that dependency ratio has negative effect on indices of community level

empowerment. But it is statistically significant only in Model-4C. Table-5.5.3 shows that

one percent increase in dependency ratio from average level reduces the community

level empowerment of the women by 0.06% points from average. Although the finding

is supporting our hypothesis but the magnitude is negligible. Generally higher

dependency implies more number of older and children in the family. So, women spend

more time in the household’s jobs and rearing the children and older. It respects the

motherhood duties of women, but provides less time to manifest her potentially in

community. As a result women with higher dependency ratio have lower participation in

community level activities which are crucial for empowerment. So, our finding has a

logical base.

The empirical estimations of Model-4C and Model-4D confirm that per capita household

income increases women’s empowerment at the community level. However, the

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empirical result is not statistically significant. Therefore, household income is immaterial

in the determination of women’s empowerment at the community level.

In table-5.5.3 the coefficient of the dummy for major household occupation

(Cultivation=1) tells us that the average degree of community level empowerment of the

women belonging to cultivator family is 2.53% points lower than that of the women

belonging to wage labour family. This result is statistically significant in both the

models. This finding goes against our hypothesis. But, this empirical finding is

meaningful. Usually the women of wage labour family are also wage labour. These

women come in contact with many people outside home. It helps them get experience in

broader arena of life. We also find that degree of empowerment at the community level

of the women under self employed family is lower than that of the women under wage

labour family. However, this result is not statistically significant at all.

Our empirical study reveals household’s landholding as a crucial factor for accelerating

women’s empowerment at the community level in the district of Bankura. The

coefficient of landholding in table-5.5.3 and in table-5.5.4 imply that one bigha extra

landholding increases the community level empowerment by 0.45% points and by 0.55%

respectively. Large land size of the household secures livelihood of the family and of the

women. Often women have the land ownership in the household with large landholdings.

These matters may enhance dignity of the women within and outside home and

accordingly the empowerment at the household and community level.

It has been obtained that the coefficients of highest education among the male household

members are statistically insignificant as an explanatory variable in the models for

women’s empowerment at the community level. However, the coefficient of the highest

education among the female members is positive and statistically significant at 1% level.

The coefficient implies that one extra completed year of education of the highest

qualified female member increases the average degree of empowerment at the

community level by 0.39% points in the area under study. We have got almost same

result in Model-4D regarding the highest female education. Therefore, female education

is more imperative than the male education in the family for inculcating women’s

empowerment at the community level. It is expected that most educated woman inspires

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the other women to develop their personality in and outside home. Hence, our result is

significantly conclusive.

In the spectrum of community characteristics we have duration of SHG-membership and

caste variables as determinants of women’s empowerment at community level. In table-

5.5.3 and table-5.5.4 we find the coefficient of the duration of SHG-membership positive

and statistically significant. This result tells us that one year extra participation in SHG

increases the empowerment at the community level by 1% point. The logic behind this

outcome as follows. Participation in SHG ensures the financial inclusion allowing the

opportunity of formal savings, financial literacy and credit. These increase the financial

asset holding of the women and thereby the importance of the women within and outside

home. Further, frequent meeting of the group inculcate the political consciousness and

the association among members reduces several social barriers of empowerment.

Therefore, it is not surprising that SHG-membership induces women’s empowerment at

the community level.

This study shows that the coefficients of the dummies for caste (SC=1) and caste

(OBC=1) are positive. It may be argued that empowerment at the community level is

higher for the women under scheduled castes and other backward classes in contrast to

that for the women under general castes. However, we are not worried of these results, as

they are not statistically significant at all. On the other hand, the coefficient of dummy

for caste (ST=1) is negative and statistically significant. Women belonging to scheduled

tribes are less empowered at the community level compared to women belonging to

general castes. We observed that due to language barriers and community rituals tribal

women are socially backward in the context of general castes. Tribal women are less

educated compared to general caste women. As a result, their empowerment in respect to

other castes is lying far below. However, it should be noted that tribal women have full

dignity in their own society.

We, therefore, conclude from this study that age, education, occupation, financial

inclusion of the women, family type, dependency ratio, household occupation, highest

female education in the family, duration of participation in SHG and caste are the major

determinants of community level empowerment for the women in the district of Bankura

West Bengal.

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5.6. Conclusion

This chapter has vividly discussed the empirical finding of our estimated econometric

models. We conclude this chapter with the significantly conclusive findings of the study

as follows. We find that women’s empowerment at the household level and at the

community level significantly increases the probability of adopting family planning.

Household level empowerment is more important than community level empowerment

of women for reducing the probability of experiencing domestic violence. We have

obtained that both the empowerment has some favourable impact on child education

expenditure. Therefore, women’s empowerment is an effective factor for improving

household welfare. Finally, our study has shown that women’s age, personal income,

personal occupation, financial inclusion, family type, household occupation and

participation in SHG are major determinants of household level empowerment. On the

other hand, women’s education, personal occupation, family type, household occupation,

highest female education and duration of SHG-membership are important determinants

of community level empowerment. Based on the empirical findings, we may suggest

some policies for improving the level of empowerment and its consequences in

households and in society at least in the area under study. In chapter six we suggest the

alternative policy prescriptions on the basis of our empirical results.

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Chapter Six _______________________________________________________________________

POLICY PRESCRIPTIONS

6.1. Introduction

In order to explore a glimpse of women’s empowerment in Bankura district we have

computed women’s empowerment at the household level and at the community level

using a set of primary data. In the last two chapters we have discussed the empirical

findings of our dissertation. On the basis of these empirical findings, we would like to

discuss the some policy issues relating to women’s empowerment in this chapter. This

chapter has been divided into five more sections. The major findings of this empirical

study have been reproduced in section 6.2. There are several government and non-

government programs in favour of women in India. We present them in section 6.3 along

with its sub-sections. In section 6.4 we have discussed the policy prescriptions and

implications based on our empirical findings. It has four sub-sections. We conclude the

study in section 6.5.

6.2. Major Findings

Let us recapitulate the major findings of our empirical study which help us formulate the

relevant policies towards better empowerment of women and its consequences in the

district of Bankura and in major rural area in India.

1) Majority of our sample households are poor. This study has shown that forty percent

of sample women have not adopted any family planning measure. Domestic violence

against women is a major socio-economic problem in the rural areas of Bankura district.

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2) The average empowerment at the household level is higher than that at the community

level for the women in the district of Bankura. Only one third of the sample women in

our study are relatively empowered at the household level and at the community level.

3) Both women’s empowerment at the household level and empowerment at the

community level are positively correlated with the decision regarding family planning in

the area under study. The empowerment variables are negatively correlated with the

incidence of domestic violence against women. Child education expenditure as

proportion to the annual household income has a positive and statistically significant

correlation with mother’s empowerment.

4) The important findings of our empirical estimation of the decision regarding family

planning are as follows.

Household level empowerment of women directly affects the probability of

adopting family planning decision.

Households in the district of Bankura have bias for male child which reduce the

probability of taking family planning decision.

Age of woman at marriage and spousal age gap increase the probability towards

family planning.

Education of the woman and their husband are favourable for adopting family

planning decision.

The women belonging to non-farm self employed family are less likely to adopt

family planning decision.

The dependency ratio in the family adversely affects the probability towards

adopting family planning decision.

Household income is an important determinant of the decision regarding family

planning.

The community level empowerment is instrumental for adopting family planning

decision.

Participation towards SHG-centric microfinance program persuades the women to

take family planning decision.

Tribal women in contrast to the women under general castes are less likely to take

family planning decision.

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5) The main findings relating to the estimation of the probability of the incidence of

domestic violence against women are presented below.

Household level empowerment of women reduces the probability of facing

domestic violence of the women.

Education level of husband and other male members in the household reduces

domestic violence against women.

Women belonging to non-farm self-employment household are less victimised in

domestic violence than the rate of domestic violence of the women belonging to

wage labour class.

Higher the size of landholding of the household, the higher is the probability of

facing domestic violence for the women in the district of Bankura.

Household income is favourable to reduce the probability of domestic violence

against women.

Although household level empowerment significantly reduces the extent of

domestic violence, community level empowerment is less important for

combating the curse of domestic violence in the area under study.

Longer duration of SHG-membership increases the probability of facing domestic

violence against women.

Women from the scheduled castes and scheduled tribes in contrast to those from

general castes women are suffering more from domestic violence.

6) We now mention the important results regarding the issue of the proportion of

household income spent for child education.

Women’s empowerment at the household level successfully increases the share of

household income for child education for the rural households.

Our study reveals that father’s education adversely affects the child education

expenditure as proportion to household income.

Highest male education and highest female education have some favourable

impact on child education expenditure as proportion to household income.

The share of household income spent for child education is higher in nuclear

families than that in joint or extended families.

Dependency ratio positively affects the child education expenditure.

Higher per capita income reduces the share of spending for child education.

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The community level empowerment of women increases the share of household

income for her child education.

Households in different castes in Bankura district are indifferent in terms of child

education expenditure.

7) We now turn to the major empirical determinants of women’s empowerment at the

household level.

The women under young age group enjoy higher empowerment in their

households than the women under older age group.

In contrast to homemakers, wage labour women enjoy lower but self-employed or

service holders enjoy higher level of household empowerment.

Though personal income of the women significantly increases the degree of

women’s empowerment at the household level, household income is less

important in this regard.

Financial inclusion has a favourable effect on household level empowerment.

The women of nuclear family enjoy higher empowerment within household

relative to the women of joint family.

The dependency ratio in the household has a negative impact on the degree of

women’s empowerment at the household level.

Household level empowerment of the women under cultivator households is lower

than that of the women under wage labour households.

It is interesting to mention that although women’s education has no significant

effect on their household level empowerment, highest female education

accelerates the household level empowerment of the women.

The duration of SHG-membership increases the household level empowerment.

The household level empowerment of the women doesn’t vary across the castes.

8) The major findings of community level empowerment are pointed below.

Community level empowerment, of the women under age group 25-35 years and

age group 36-45 years, are higher than that for the women of older age group.

Women’s education improves the community level empowerment of the rural

women. But, it is unimportant for determining household level empowerment.

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Community level empowerment of the wage labour women is lower than that of

the homemakers.

The financial inclusion enhances women’s empowerment at the community level

in the area under study.

Compared to the women living in joint families the women living in nuclear

family enjoy higher empowerment in her community.

The dependency ratio in the household adversely affects the degree of women’s

empowerment at the community level.

Community level empowerment of the women under cultivator households is

lower than that of the women under wage labour households.

Household landholding directly affects the community level empowerment of the

rural women.

Highest female education in household significantly accelerates the community

level empowerment of the women.

Participation in SHG-based microfinance movement has inculcated the

community level empowerment of the sample women.

Community level empowerment of the tribal women is comparatively lower than

that of the general caste women.

6.3. Existing Policies and Programs towards Empowering Women

The Indian Constitution ensures the principle of gender equality. Moreover, it authorizes

the State to adopt measures of positive discrimination in favour of women for balancing

the cumulative social, economical, and political backwardness of women. Furthermore,

India is a signatory member of the Convention on Elimination of All Forms of

Discrimination against Women (CEDAW) in 1993. So India has taken several measures

for women to ensure gender equality in all spheres of life. Before going to the imperative

policy implications of our empirical study we review the existing policies and

legislations regarding women’s empowerment and related issues.

6.3.1. National Policy and Legislation for Women in India

The government of India has established the National Commission for Women in 1992

for monitoring all constitutional and legal security measures for women and to review

the existing legislations related to the rights of women so that women can enjoy equality

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in all spheres of life and have equal participation in the development of the nation. It was

constituted as an apex level statutory body under the National Commission for Women

Act, 1990.

The 73rd

Constitutional Amendment Acts, 1992 ensure one-third of the total seats for

women in all elected offices in local bodies whether in rural areas or urban areas.

The National Plan of Action for the Girl Child (1991-2000) was taken to ensure survival,

protection and development of the girl child for better future.

In order to address women's advancement, development and empowerment, The

National Policy for Empowerment of Women, (NPEW) has been formulated in 2001.

The major objectives of this national policy were as follows

The advancement, development and empowerment of women in all spheres of life

Introduction of more responsive judicial systems in favour of women’s needs

Ensuring women's equality in power sharing and active participation in decision

making

Mainstreaming a gender perspective in development process

Strengthening and formation of relevant institutional mechanism

Partnership with community based organizations; and

Implementation of international obligations, commitments and cooperation at the

international, regional and sub-regional level

In February 2012, the Government of India has also formed a High Level Committee to

undertake comprehensive study to understand the status of women since 1989 as well to

evolve appropriate policy interventions based on a contemporary assessment of women's

needs. The committee is already functioning.

We have seen that recent policies and programmes of the Government for women

welfare are already directed towards achieving inclusive growth and in line with the

objectives of the national policy for women’s empowerment. Following Constitutional

mandate the state has passed several legislation for removing social discrimination

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against women and the protection of the women from different social and cultural evils

against women. We now list some relevant legislation relating to our study.

The Dowry Prohibition Act, 1961

In order to protect the female from the curse of dowry and to prohibit the evil practice of

giving and taking of dowry our government has passed The Dowry Prohibition Act in

1961. The Act has been in implementation since 1961. The Act underwent amendments

in the year 1984 and again in 1986. The Act goes for further amendment for considering

the suggestions of National Commission for Women (2009). For this purpose, a Review

committee was constituted in 2012. In a meeting with the women Members of

Parliament in 2012 Ministry of Women and Child Development has suggested many

proposals for the amendments of the Dowry Prohibition Act. These are to be examined

and finalised in the Ministry.

The Indecent Representation of Women Act, 1986

The Indecent Representation of Women Act was enacted in 1986. The objective of this

act was to prohibit indecent representation of women in advertisement, publication,

writing and painting or in any other manner and references that are insulting to the

dignity of women. Violation of this Act is punishable with imprisonment up to two

years. Still now this Act is applicable only to the print media. Very recently, the

Government has approved amendments to apply the law to audio visual media and

material in electronic form and revising the penalties. The amendment Bill is currently

with the Parliament.

The Protection of Women from Domestic Violence Act (PWDVA), 2005

The PWDVA is a civil law in India. It favours the victim women of domestic violence

to get immediate support in the form of shelter, medical facility and reliefs in the nature

of protection, residence, compensation, maintenance and give orders for temporary

custody of children. The law also widens the meaning of the word 'aggrieved woman' by

including women who face domestic violence in relationships other than matrimonial

relationships like daughters, mothers, sisters and those involved in marriage like

relationships and providing a woman's right to reside in the shared household. The Act

came into force on 26th

October 2006. The Ministry has formulated a scheme for

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assistance to State Governments for implementation of the Act, as a component of the

Umbrella scheme on Protection and Empowerment of Women.

Sexual Harassment of Women at Workplace (Prevention, Prohibition and Redressal),

Act 2013

The Act seeks to cover all women, irrespective of their age or employment status and

protect them from sexual harassment at workplaces both in public and private sector,

whether organised or unorganised. Women who are employed as well as those who enter

the workplaces as clients, customers and apprentices, students in educational institutions

and patients in hospitals etc. are also sought to be covered under this Act. Under this Act

Sexual Harassment of Women at Workplace is illegal and punishable.

Therefore, governments have taken several legal and constitutional steps for

development of the status of women. In addition to these constitutional and legal steps,

the governments have introduced several schemes and programme for improving overall

status of women.

6.3.2 Governmental Programmes for Enhancing Women’s Empowerment in India

Since independence the Government of India has been enacting different pro-female

laws and rules and implementing various plans and programmes to improve the status of

women in our country. In the First Five Year Plan period (1951-56), mainly welfare

oriented plans and programmes were taken for women. In that era the Central Social

Welfare Board (CSWB) undertook a number of welfare measures through the voluntary

sector. As far as women’s issues were concerned, the then government implemented the

programmes through the National Extension Service Programmes through Community

Development Blocks. In order to ensure better implementation of the welfare schemes

during the Second Five Year Plan period (1956-61) the Government emphasised to

organise “Mahila Mandals” (women’s groups) at grass-roots levels. Subsequently,

during the next three Five Years plans and four annual plans period, the governments put

importance on women’s education, improved maternal and child health services, feeding

for children, nursing and expectant mothers for improving the status of women. Sixth

Five Year Plan (1980-85) is regarded as a landmark in women’s development

programmes. In this Plan the government adopted a multidisciplinary approach with a

three-pronged thrust on health, education and employment of women. Development

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programmes for women were continued with the next Plan. One of the major objectives

of Seventh Five Year Plan (1985-90) was the improvement of economic and social status

of women and brings them under the mainstream development process. In this plan

period an important step was to identify and promote “beneficiary-oriented programmes”

which extended direct benefits to women.

For women development, agendum of Eighth Five Year Plan period (1992-97) was to

ensure that the benefits of development of different sectors did not deprive women. For

this purpose some special programmes were implemented to complement the general

development programmes. In order to ensure the functions of women as equal partners

and participants in the developmental process the government introduced reservation in

the membership of local bodies. This unique initiative marks a sharp departure from

‘development’ to ‘empowerment’ of women. This initiatives of women’s empowerment

were forwarded to Ninth Five Year Plan (1997-2002) by adopting women’s component

plan at the Central and State levels. The Tenth Five Year Plan (2002-2007) emphasised

to ensure the requisite access to information, resources and services for women, and

advance gender equality goals. In order to achieve inclusive growth in the Eleventh Five

Year Plan (2007-2012) the authority had taken several initiatives which facilitate the

women to develop their full potential and share the benefit of economic growth and

prosperity. In this time government undertook special measures for gender

empowerment and equity. The Ministry of Women and Child Development has tried to

make synergistic use of gender budget and gender mainstreaming process. The Twelfth

Five Year Plan (2012-17) has emphasised on gender equity.

Let us now look at the brief history of the schemes and programmes which have been

framed to alleviate poverty vis-à-vis to increase the empowerment level of women. Some

of these programmes are IRDP, DWRCA, TRYSEM, NRDP, RLEGP, JRY, and SSEGS

etc. Different studies suggest that most of the programmes help the rural people little and

they are not self-sustaining (Swaminathan, 1990, Kaladhar, 1997). Moreover, if there

was any success of these programmes, it was in favour of men not in favour of women.

That means these programmes were not fruitful in generating women’s empowerment.

Under this background, in 1999, SHG was introduced under SGSY to improve socio-

economic conditions of women in general and empowerment in particular. We have

already said that the women are resource-poor and so they have no collateral assets or

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security, which ensure them to have loan. SHG was mainly formed to provide formal

loan to the un-banked women of the society without physical collateral security. SHGs

not only accelerate the accessibility to formal credit for the member women but also

inculcate the values and dignity of the women in the society through generating their

empowerment. Therefore, the recent government policy has also emphasized on the

women’s empowerment in India.

In 2001, Swayamsiddha Scheme was introduced in West Bengal along with a few other

states in India as an additional program of the Integrated Child Development Scheme

(ICDS). It is a central Government sponsored program for empowering rural poor

women, economically and socially, through formation and mobilization of SHGs. The

project has been functioning in the district of Bankura since 2002 under the ICDS

network. In this scheme ‘anganwari’ workers facilitate the poor women to form and

nurture the SHGs. Finally, the ‘anganwari’ worker introduces the formed group with the

Banks. As per annual report 2005, in different states the SHG members under the

scheme are doing income generating activities such as food preservation, dairy farming,

cutting and tailoring, embroidery, kitchen gardening, beautician, rope making, etc.

However, in our study area, no SHG under this scheme undertakes any income-

generating activity. This scheme is not implemented in all the states of India. Recently

the government of India has stopped the funding for this scheme. As a result the existing

groups have also lost their power of functioning. So this type of short run scheme is not

suitable for enhancing the empowerment of the rural women.

Currently, the following schemes and programmes have been functioning under the

Ministry of Women and Child Development for assisting the women and children in

India (Statistics on Women in India, 2010).

Support to Training and Employment Programme (STEP)

Rajiv Gandhi Scheme for Empowerment of Adolescent Girls, SABLA

Swawlamban

Construction/Expansion of Hostel Building for Working Women with a Day Care

Centre (WWH)

Balika Samriddhi Yojana (BSY)

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National Programme for Adolescent Girls (Kishori Shakti Yojana)

Shishu Greha Scheme

Integrated Scheme for Street Children

Scheme for Welfare of Working Children in Need of Care and Protection

Prevention and Control of Juvenile Maladjustment

Integrated Child Protection Scheme (ICPS)

Conditional Cash Transfer Scheme for the Girl Child with Insurance Cover

General Grant-in-Aid for Voluntary Organisations in the Field of Women and

Child Development

National Mission of Empowerment of Women

Scheme for Leadership Development of Minority Women

Conditional Maternity Benefit Scheme

Education Scheme, Food and Nutrition Board (FNB)

Ujjawala, Scheme for Combating Trafficking

Nutrition Programme for Adolescent Girls (NPAG)

Wheat Based Nutrition Programme

Anganwadi Karyakati Bima Yojana

Therefore, governments have taken a lot of initiatives for improving the socio-economic

and demographic status of women in India. To meet the needs of women and children

there has been a progressive increase in the plan outlays over the last six decades of

planned development. The outlay of Rs. 4 crores in the First Plan (1951-56) has

increased to Rs. 13,780 crores in the Tenth Five Year Plan. The important feature of the

programmes for women was “welfare” oriented during the pre liberalisation era (1951-

1979). During the weak liberalisation era (1980-1990) these were “development”

oriented. There has been a shift from “development” oriented approach in the weak

liberalisation era to “empowerment” of women in strong liberalisation era (since1991).

In 2010, the Government of India has taken National Mission for Empowerment of

Women (NMEW). It is an initiative for holistic empowerment of women by securing

convergence of schemes/ programmes of different Ministries/Department of Central

Government as well as State Governments. In addition to these schemes the governments

have conducted several conferences, seminar and events relating to women’s

empowerment during the last few years. Very recently, the Government of West Bengal

210

has taken ‘Kanyashree Prakalpa’. It is expected to be fruitful to improve the status and

well being of the girl child in West Bengal by incentivizing schooling of all teenage girls

and delaying their marriages until the age of 18, the legal age of marriage.

6.4. Policy Prescriptions and Implications

This empirical study has measured the empowerment of women at the household level

and at the community level in Bankura district of West Bengal using two alternative

methodologies. We have assessed the impact of women’s empowerment along with

some socio-economic and demographic characteristics on the decision regarding family

planning, on incidence of domestic violence against women and on children’s education

expenditure. It has also identified the factors responsible for affecting empowerments.

On the basis of these empirical findings, we can suggest some supplementary and

alterative policies for empowering women. These policies may help the policy makers to

inculcate women’s empowerment at the household level and at the community level in a

better way in future. We are going to discuss the policies, which come out as a

consequence of this empirical study conducted in the district of Bankura.

Our field observation reveals that a large portion of our sample women have very little

empowerment at the household level and at the community level. It indicates that the

existing policies are not enough for the improvement of the empowerment among

women. Therefore, inculcation of women’s empowerment is a challenge ahead to the

government and policy makers in our country. In spite of this, we find that women’s

empowerment at the household level and at the community level significantly increases

the probability of adopting family planning program and reduces probability of domestic

violence against her. Further, women’s empowerment at the household level and at the

community level in Bankura district have improved their spending attitudes towards

child education. It is indicative that women’s empowerment are favourable for

household and child welfare, broadly social welfare. Therefore, in order to increase the

welfare of our study area we can suggest for improving empowerment of women in the

district of Bankura. The particular policies which are appropriate for improving women’s

empowerment have been proposed in section 6.4.1.

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6.4.1. Suggestions for Empowering Women in Bankura District

In our study we have established that women’s empowerment at the household level and

at the community level increases the probability of adopting family planning and reduces

the probability of facing domestic violence. Community level empowerment increases

the share of household expenditure on child education. Therefore, women empowerment

at the household level and at the community level is an alternative instrument for

improving household and child welfare in the district of Bankura. Hence, we need to

search the factors suitable for enhancing women’s empowerment at the household level

and at the community level. We have done this job in the estimation of the models for

women’s empowerment. Based on the empirical results we recommend the following

policy towards empowering women at their households and community.

First, this dissertation concludes that elder women in the district of Bankura have lower

level of empowerment relative to the women in the younger age groups. We think that it

happens due to livelihood insecurity and lower control over household assets. In order to

change this picture we need to have some special package for empowering elder women

and for ensuring livelihood security of the older women. In this regards NGOs like

DHAN Foundation in Tamil Nadu, SEWA in Gujarat, function effectively. SEWA

extends social security to its members by ensuring the access to health care, shelter,

banking services and income security. On the other hand DHAN foundation provides

mutual insurance called ‘People Mutuals’ for social security. This initiative safeguards

the poor from risk and vulnerabilities through mutual solutions and collaboration with

insurance providers. In addition to our existing insurance policies we, therefore, propose

to launch these types of policies for livelihood security of the elder women in rural

Bankura. In this case local panchayet, existing women organization, NGOs would be

more helpful.

Second, women’s education is very much important to improve the community level

empowerment of women. In addition to this we have found that highest education level

of the female members in the households is favourable factor for empowering women.

Education has an intergenerational impact on women’s empowerment. However, in our

study we have observed that most of the sample women cannot cross the primary

education level. All women should be ensured of getting minimum level of education. It

is, therefore, a common policy demand that we have to increase the level of women’s

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education for improving their empowerment. So, it is necessary to setup more

educational institution for women. It is also necessary to monitor the enrolment of

women in the educational institution. We can also suggest for establishing informal

educational institutions by NGOs or other voluntary organizations for aged women.

Besides, the government should implement women’s education programme more

effectively in rural areas, particularly in the area under study.

Third, self-employed and service holder women have higher empowerment at the

household level and at the community level compared to the empowerment of the

homemakers. Further, personal income is imperative for enhancing empowerment at the

household level and at the community level. So we have to create an environment that

helps the women participate in formal workforce or participate in self-employment

activity. We have seen that, in Bankura district, there are some famous cottage industries

like ‘Teracota’, ‘Dogra’, ‘Baluchari Silk’, ‘Bishnupuri silk’ and ‘cotton Handloom’.

These industries are dominated by women workers. But the fact is that these women

worker are still informal and unskilled in nature and thereby controlled by male persons

and to some extent by moneylenders. So the government should implement financial

assistance and different training programmes that will be helpful to make women

financially independent and to develop skill among women. In Gujarat SEWA, a

membership based organization of self employed women, has been playing a

commendable role in the empowerment of women. It works to ensure full employment

and self-reliance for its members. We may propose to establish the organization like

SEWA to extend the self employed activities and hence self-reliance of the women in the

district of Bankura. Not only that we have to be conscious regarding the formal

employability of the educated women. All these will be helpful to achieve the goal of

employability and increased income of women effectively. Thereby empowerment of

women will increase automatically.

Fourth, it has been found that access to formal credit is an important factor to inculcate

the empowerment of women. Therefore, banking institutions and non-bank financial

institutions have to take some special programs for ensuring the access to formal credit

for the rural women. In this regards bank have to relax some conditions like asset

holding, income earning that hinder the accessibility of formal credit for the rural

women. Besides, banks should expand their branches in rural area.

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Fifth, the duration of SHG-membership increases the community level empowerment of

the member women. So, we can say that the SHG-based microfinance program plays an

active role to accelerate community level empowerment of the women. Therefore, we

have to implement the SGSY policy in more intensive and extensive way and we have to

encourage the NGOs with some incentives. Formal financial institutions have to be more

enthusiastic in the matter of financial inclusion of the rural women.

Sixth, this study has reported that women belonging to scheduled tribes are less

empowered at the community level contrasted to the women belonging to general caste

women. During the time of data collection we have observed that ST people have very

poor accessibility to various primary needs of life like education, health, housing etc.

They do not come forward to participate in community activities. These lead to have

lowering effect on empowerment of ST people. So in order to improve the community

level empowerment of the tribal women we need to take some exclusive programs for

ST women like development of education system by tribal language, social awareness

programs etc. Some special programme should be taken to increase the confidence of

tribal women so that they can come forward to organize social or community

development programme.

From our field observations show that most of the sample women do not know about the

legal rights and government initiatives in favour of them. They live within the periphery

of social, cultural, regional and caste customs. They are unaware of their right. These are

the causes of low empowerment of women of the selected region under study.

Government should establish a legal cell integrated with the panchayet to give free

advice to women about their rights. Again community leaders and local elite should

serve and support women in social participation. They can jointly organize meeting,

group discussion, speeches and counseling for motivating people about gender equality

and encouraging women to participate in community development. Moreover various

programmes in electronic media, organizing rallies and public meeting could be effective

tools to create massive awareness among women and thereby help in empowering of

women.

Women, as we find in the district of Bankura during the time of field survey, are oriented

internally in such ways that they think that living under the layer of someone like father,

214

husband and son is respectable for them. They also believe that women should obey the

instructions of their husband, sons, father etc. regarding family and social decision. They

should not inherit physical asset etc. This type of internal orientation of the women is

really a constraint of women’s empowerment. So to bring to the change in the internal

orientation of women, long-term consciousness generation programmes are badly needed

in the area under study. Governmemt should think over it and do the needful.

Finally, we know that some leading international organizations such as World Bank,

WHO, UNICEF, UNDP etc. launch various programmes for the development of women

in India by funding in different projects related to education, health, human rights etc.

They have been playing a major role in eliminating gender discrimination. These are

implemented through government organization, NGOs and women’s organizations. But

in the region of our study these organizations are not functioning well. So the

government should take some steps so that various local organizations can support the

international organizations to be more effective.

6.4.2 Suggestions for Improving the Likelihood towards Family Planning

In the estimated model for the decision regarding family planning we have found that in

addition to women’s empowerment there are several socio-economic-demographic

features which significantly affect the decision regarding family planning. Based on

these results, we can prescribe the policies for improving the likelihood towards family

planning decision.

First, it has been reported that women’s empowerment at the household level and at the

community level significantly improved the likelihood towards family planning. So, we

have to repair the loopholes of the existing policies/schemes for improving women’s

empowerment at the household level and at the community level. In section 6.4.1 we

have already suggested some alternative policies which are suitable for enhancing

empowerment of women in the area under study.

Second, our study has shown that there is male child bias which is a crucial impediment

towards taking family planning decision in Bankura district. In order to neutralise this

bias we need to inculcate awareness regarding gender equality. So governments,

particularly the health departments, and NGOs have to launch the awareness generation

215

programs in the rural areas in more and more extensive form. We, the members of civil

society, also have to be dutiful to guide our fellow citizens regarding gender equality

and the importance of family planning. Lesson of gender equality should be

incorporated in the school level syllabus. It has been turned out that age at marriage

directly affects the probability towards family planning decision. Further spousal age

gap is suitable for family planning. We have to restrict child marriage. On the other

hand, we have to allow age gap between bride and groom. We have already legal age of

marriage (18 years for female and 21 years for male) but in rural area majority of the

parents are not conscious of the law and regulations and its implications. The

‘Kanyashree Prakalpa’ of the Government of West Bengal is no doubt an innovative

step to stop female child marriage and to encourage female child education. Besides, we

have to play a vital role to aware them about the bad effect of child marriage. Health

department should arrange various programmes about the bad effect of lower age

pregnancy and frequent pregnancy and its effect on women’s health.

Third, we find that the level of education of women is an important factor of the

probability of taking family planning decision. Husband’s education has also a positive

effect on the probability of adopting family planning decision. However, the sample

women and their respective husbands do not have the significant level of education.

Educated parents are eager to have healthy baby rather than have large number of

babies. They want to spend more for their children’s health, education. If they have large

number of babies it becomes very difficult for parents to spend more on their children’s

education and health. Therefore, the government and the social institutions have to take

incentives to extend the education facilities. In addition to the extension of formal

education the government should arrange health conscious training, awareness

generation programme etc. in order to make the family planning programs successful.

Government can open women education center, girls’ schools, adult education center in

the rural area. Again Government can provide subsidies and different facilities to spread

women education.

Fourth, our study shows that wage employed class where women are also employed have

higher probability of taking family planning decision than farm or self-employed

occupation and higher dependency ratio reduces the probability of taking family

planning decision. So, higher worker population ratio in the household is suitable for

216

taking the decision family planning. Therefore, we need to create an environment that

helps people to move from farm or self-employed occupation to wage employment

occupation for improving the status of family planning in our study area. The

government needs to consider industrialization exclusively for this district or favours

private companies in this regard. Besides, it is needed to improve the communication

system in the district to help the people for searching and holding suitable wage

employment.

Fifth, household income is directly related with the probability of taking family planning

decision. So, it is needed to strengthen the policies of income poverty alleviation and

policies regarding employment generation of the rural households. In this sense NREGA

is suitable one. Besides, the government may take some policies in favour of small and

cottage industries and agro-based industrialization.

Sixth, we find an encouraging effect of SHG centric microfinance program on the

likelihood of adopting family planning decision. This finding establishes the

effectiveness of the SGSY program in household welfare. Therefore, we have to

implement this group based microfinance program more actively and extend it through

opening more and more channels in the rural areas.

Seventh, our study concludes that the scheduled tribe women who are the most deprived

section in the district are less likely to take family planning decision in contrast to the

other castes. They have deep dependence on their own social customs. During the time

of field survey, we have observed that the people of tribal community are most ignorant

of the government policies and health facilities available for them. Most of them have no

formal education or vocational training. Although there exists some special program like

LAMPS (Large Sized Agricultural Multi-purpose Cooperatives Society) for economic

development of the tribal community but the result of our study indicates the

insufficiency of these programs. Therefore, government has to launch some exclusive

health care program for this community for inculcating family planning habits.

6.4.3. Suggestions for Alleviating Domestic Violence against Women

Violence against women is a serious problem in our society. The present data regarding

violence against women inside and outside home tell us that existing polices failed to

217

save women from violence. We now prescribe the alternative policies for reducing the

likelihood of domestic violence against women.

First, we have found that women’s empowerment at the household level is necessary for

curbing domestic violence against women. It indicates that we have to ensure her

empowerment inside home. For this purpose, we have to rectify the customs and

resolution which give space for the women in the socio-economic decision making

process in their households. Besides empowerment at the household level, we have

identified several socio-economic-demographic traits influencing the probability of

facing domestic violence.

Second, our empirical estimation reveals husband education as a panacea for reducing

likelihood of domestic violence against women. Not only that, education of other male

members is important to reduce the suffering of women from domestic violence. But we

have seen that average education level of husbands of our sample women is just at

primary level and average education of other male persons in the households is less than

eighth standard. Therefore, the expansion of male education is urgent in order to prevent

the women from the disease of domestic violence. For this purpose, we have to spread

our educational system. That means initiatives should be taken to increase the qualitative

as well as quantitative aspects of education.

Third, the nature of household occupation, Cultivation and Non-farm self employment,

reduce the probability of domestic violence. Further, the household landholding

increases the probability of domestic violence. We also observe that even in landed

households women do not have any land ownership. It makes gender inequality and

sometimes, causes violence against female members of the family. In order to reduce the

curse of domestic violence against women, redistribution of land in favour of women is

required. We agree that in India, particularly in our state of West Bengal, land reforms

have been progressed during the last fifty years towards landless farmers. But it is hard

to find out the programs and policies towards land redistribution in favour of women in

our state and in the area under study. This negligence may be a vital cause of the low

status of women. Therefore, for reducing domestic violence we recommend to take some

effective land reform policies and programs which make redistribution of land in favour

of women. We may follow the land purchase scheme for SC/ST women in Tamil Nadu.

218

Under this scheme, landless women can purchase land for cultivation with a maximum

project cost rupees two lakhs. This scheme entails 50 per cent subsidy from Tamil Nadu

Adi Dravidar Housing and Development Corporation Ltd. and remaining part comes as

bank loan.

Fourth, household income is inversely related with the probability of facing domestic

violence. We, therefore, have to strengthen the policies of income and employment

generation for the rural households. Government may take some policies in favour of

small and cottage industries and agro-based industrialization for rural households which

are indirectly helpful to reduce domestic violence.

Fifth, this study has reported that dowry at marriage and at post marriage amplifies the

likelihood of domestic violence against women. We have found that drug addiction of

the husband is a major cause of domestic violence. So dowry deterrence act and laws and

regulation against drug addiction have to be implemented seriously. In addition to the

acts and regulations we have to campaign in favour of dowry deterrence and against drug

addiction. We need to inculcate the consciousness among people about the curse of

dowry and drug. In this regard Governmental officials and NGOs, and even we the

common people may take part in the conscious generation programs.

Sixth, our study shows that the scheduled tribe women are more victimized compared to

other sample women. Although there exists some dedicated program like LAMPS for

economic development of the tribal community but the result of our study indicates the

insufficiency of these programs. Therefore, government has to launch some exclusive

consciousness program for this community for reducing domestic violence in this

community.

6.4.4. Suggestions for Improving Children’s Education Expenditure

In this section we have proposed some policies for improving child education

expenditure of the households in the district of Bankura.

First, women’s empowerment at the community level has been found as an important

factor affecting child education expenditure out of household income. So improvement

of community level empowerment of women is an alternative approach for improving

219

the proportion of household expenditure on child education. Suggestions for

improvement of women’s empowerment at the community level have already been

presented in section 6.4.1.

Second, we find highest education of male and female in the family as a stimulating

factor for increasing children’s education expenditure. In other words, the household

with low level of educational background, as we have observed in the course of field

survey, do not like to spend more for children’s education and thereby the children

remain uneducated which in future will be the cause of low education of future children

of the household. Therefore, low education of the household members makes an inter-

generational vicious circle of education. Therefore, in order to break this vicious circle,

the government needs to implement some policies to ensure the access to higher

education for the rural people at affordable cost. Nowadays government has already

taken some policies to expand the higher education across our country. But the point is

that the government needs to monitor the existing system and implement new institutions

making clear-cut vision and mission for better achievement.

Third, we have observed that poor household could not spend the necessary amount for

their children’s education. Although, occupation is insignificant in the determination of

children’s education expenditure, we find that income is vital for it. So we suggest for

implementing more income generating projects in rural area as like NREGA and to some

extent SGSY etc.

Fourth, children’s education expenditure as proportion to household income of lower

caste households like OBC, SC and ST is lower than that of the general caste

households. So we need to have some special financial support programs for the lower

caste households regarding children’s education. We know that for the students

belonging SC and ST financial support system already exists. But these are not sufficient

and have very low coverage at the initial stage of education. However, for the poor

students of OBC and General caste, there is no such financial support system. Therefore,

we propose to the governments and private institutions to provide a range of subsidy in

fees or financial support for poor family for education of their children who are the

future our nation also.

220

Thus, we can conclude that to achieve the goal of real development we have to create an

environment where women get equal dignified opportunity to work hand in hand with

men. The policies recommended above actually are the results of our empirical research

conducted in the district of Bankura. It is, therefore, obvious that these policies are

suitable for the women residing this district. These policies may also be applicable for

the people of any region with the same type of socio-economic and demographic

characteristics as in Bankura district. However, the implementation and success of the

policies ultimately depend on the efficiency of the administrators of the local

government, its transparency and willingness to do for the rural women.

6.5. Conclusion

In this chapter we have presented the outlines of the existing policies and their

insufficiencies. Some supplementary and additional policies have been proposed for

further improvement of empowerment level of the rural women and welfare of their

families in the district of Bankura. We conclude this chapter and this study with the

fundamental results of our dissertation as follows.

Women’s empowerment at the household level and at the community level

increases the probability of adopting family planning decision of the rural

people in the district of Bankura.

Household level empowerment of women reduces the probability of

domestic violence against women.

Women’s empowerment at the community level is instrumental to

increasing the share of household income spent for child education.

Age, personal occupation, personal income, financial inclusion, dependency

ratio and highest female education are important determinants of

household level empowerment of the women in Bankura district.

We find age, education of women, access to formal credit, household

landholding, highest female education, the participation in the SHG and

caste as crucial in the determination of women’s empowerment at the

community level.

221

Therefore, women’s empowerments at the household level and at the community level

are instrument of enhancing the household and child welfare of the rural people in the

district of Bankura. However, majority of the sample women do not have admirable level

of empowerment inside and outside home. In order to improve empowerment of women,

which is instrumental for household and child welfare, we have to take some effective

policies that ensure financial inclusion, employment and political participation of the

women and help women undertake income-generating activity. In this regard, micro

enterprise may be the suitable one. Finally, we need to start our journey with fruitful

health and effective education facility towards removing the social and household

practices that act against empowerment and dignity of women. We have to remember the

speech of Swami Vivekananda that a nation which doesn’t respect women will never

become great now and nor will in future. Therefore, to make India a great nation, let us

work towards giving the respect that women deserve in society.

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