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Iweagu H. E., (2012)
THE DETERMINANT OF LABOUR FORCE
PARTICIPATION AMONG WOMEN IN NIGERIA
BY
IWEAGU HELEN E.
REG. NO: PG/MSC/09/51347
An M.Sc dissertation submitted to the
Department of Economics
Faculty of the Social Sciences
University of Nigeria
In Partial Fulfillment Of The Requirements For The Award Of Master
Of Science (M.Sc) Degree in Economics
SUPERVISOR: ONYUKWU E. ONYUKWU
JULY 2012
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TITLE PAGE
THE DETERMINANT OF LABOUR FORCE PARTICIPATION AMONG WOMEN
IN NIGERIA
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Iweagu H. E., (2012)
CERTIFICATION
This is to certify that Iweagu Helen Elowho, an M.Sc student of the University of Nigeria
Nsukka with registration number PG/M.Sc/09/51347 has successfully completed the
research required for the Award of Masters of Science Degree in Economics in the afore
mentioned institution.
Iweagu Helen Elowho Date
PG/M.Sc/09/51347
Supervisor Date
Onyukwu E. Onyukwu
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Iweagu H. E., (2012)
APPROVAL The research work titled: “The Determinant Of Labour Force Participation Among
Women In Nigeria” has followed due process and has been approved to have met the
minimum requirement for the award of the Master of Science degree in the Department
of economics, University of Nigeria Nsukka.
Approved
Supervisor Date
Onyukwu E. Onyukwu
Head of Department Date
Prof. C. C. Agu
Dean of Faculty Date
External Examiner Date
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Iweagu H. E., (2012)
DEDICATION This work is dedicated to my parents Mr. and Mrs. Young Iweagu, whose
unrelenting support saw me through the course of this study.
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Iweagu H. E., (2012)
ACKNOWLEDGEMENTS
It is tangible to note that this research work would not have been realized without
the direct or indirect contribution of some persons. Therefore, it is eminent that
acknowledgements be given first of all to GOD ALMIGHTY, for Knowledge, protection
and life itself throughout this academic pursuit. His strength has been sufficient for me.
My in-depth gratitude goes to my project Supervisor; Onyukwu E. Onyukwu for
his particular attention and significant contribution to this study, and to Dr Nwosu
Emmanuel for his unyielding support and deep encouragements. Appreciations also go to
all the lecturers in the Department of Economics - University of Nigeria Nsukka, who in
one way or the other contributed to my academic success. Special mention is made here
of Prof N. I. Ikpeze, Mr. Chukwu Jude and Mr Ukwueze Ezebilo. Your profound
contributions and dedication will always be remembered. I also want to acknowledge all
sources and authors of literature cited in this study.
The researcher also remains grateful to all family members and relatives whose
sincere encouragements and continuous prayers, strengthened and exhilarated me
throughout this study. I equally make mention of Mr. & Mrs. Young Iweagu, my husband
Mr Michael Ebele Ejogo, Henry I., Josephine I., Gladys E., Kenneth I., Evelyn I.,
Kingsely I., Alex I., Faith I., amongst others. I would not forget in a hurry the care and
love you showed me in the course of this study.
This list would not be complete if I fail to acknowledge; Yuni Denis, Nzekwe
Henrietta, Ifeanyi Okafor, Shelly E., Mr and Mrs Emeka Okoh, Rev Canoon Ita, Rev
Josiah, Obayuwana Godwill and all other friends to whom i remain very grateful to. My
heartfelt thanks also go to all my colleagues and most especially my Judge; Justice A O.
Akpovi for the support and love throughout this study. Your fervent prayers, moral
support and continuous encouragements saw me through this study.
May God richly bless you all for contributing to my success in life.
Iweagu Helen Elowho.
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Iweagu H. E., (2012)
ABSTRACT
Female labour participation has been relatively stagnant from 2004 till present and it is
therefore important to investigate the current determinants of female labour participation.
However, we note that cultural and traditional beliefs are the main forces behind
husband’s willingness to permit their spouse work and this motivated the researcher to
investigate the determinants of labour force separately in urban and rural sectors of
Nigeria. We employed the logistic regression on a house hold survey data of employment
to find out that the determinants of female labour participation are not the same in urban
and rural areas. Our findings suggests that marital status, religion, poverty rate and per
capita income are significant determinants in the rural sector, while in the urban sector
we have age and literacy rate. Surprisingly, household size was neither a significant
determinant in both urban and rural Nigeria. The fact that the determinants in the urban
regions are completely different from those in the rural sectors leads us to recommend
that, discriminate policies should be encouraged when designing policies to improve
female labour participation in Nigeria.
Key words: Female, Labour, Participation, Rural, Urban, Nigeria
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TABLE OF CONTENT
Cover
Page…………………………………………………………………………..…………....i
Title
page…………………………………………………………………………….…………...
ii
Certification Page
…………………………………………………………………….………….iii
Approval Page ………………………………………………………………………....
……….iv
Dedication
…………………………………………………………………………….………….v
Acknowledgements
…………………………………………………………………….…….......vi
Abstract……………………………………………………………………………………
…......vii
Table of Content
….……………………………………………………………………….........viii
List of Tables
…………………………………………...……………………………..………….x
List of
figures…………………….……………………...……………………………..………….
x
Appendix…………………….……………………...……………………………..………
…..….x
CHAPTER ONE: INTRODUCTION
Background to the
Study…………………………………………………………………………..1
Statement of the
Problem……………………………………………………………...……..........4
Objectives of the
Study……………………………………………………………………………6
Hypothesis of the
research.......…………………………………………………………………... 7
Scope of the Study
…….………………………………………………………………………….7
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Justification of the
Study………………………………………………………………….............7
CHAPTER TWO: REVIEW OF LITERATURE
Theoretical
literature……………………….……………………………………………..............9
The Neoclassical Theory......……
……………………………………………………………….11
The Theory of Allocation of Time and Human Capital Investment
………..…………………...13
Women’s Supply of Labour
...……………………………………………………………….......14
Empirical literature: Global
Evidence......……………………………………………………….15
Empirical literature: Nigerian
Evidence......……………………………………………………. 20
Summary of literature
Review...................................................................................................... 23
Limitation of the previous
study.............................……………………………………………..27
CHAPTER THREE: METHODOLOGY AND DATA
Methodology of the research
................………………………………..…………………….....28
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Theoretical Framework
..................………………………………………………………….......28
Analytical Framework
...................………………………………………………………….......31
Model specification
...............................................................................................……………...32
Model
1..........................………………………………………....................................................32
Model
2.......................…………………………………………………………………………...33
Estimation Methods
.........................................................……………………………………….33
Justification of the model
.......................................................………….......................................33
Source of data
...................………………………………………………………………………34
CHAPTER FOUR: EMPIRICAL RESULTS
Presentation of Results
..………………………................……………………………………....35
logit results for female participation in urban areas
.....………………………………………….35
logit results for female participation in rural areas
.......................................................................38
CHAPTER FIVE: SUMMARY, POLICY IMPLICATIONS AND CONCLUSION
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Summary
……………………………………………………………………………………..…42
Policy
implications………………………………………………………………………............43
Limitations of the Study
………………………………………………………………….……..45
Suggestions for further Study
…………………………………………………………….…….45
Conclusion
……………………………………………………………........................................46
References…………………………………………………………………………………
…….47
LIST OF TABLES
Summary of literature
Review...................................................................................................... 23
Table 1: logit regression for urban female participation
............…………………………………..35
Table 2: logit regression for rural female participation
......………………………………….….….38
LIST OF FIGURES
Figure 1: Female pop, labour participation and ratio of female to male labour force
participation………………………………………………………………………………
……….2
APPENDICES
APPENDIX 1: Stata
Results....…………………………………………………………..……...52
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CHAPTER ONE
1.0 Introduction
1.1 Background of the study
The debate on female labour force participation has been on stage for over three decades
in many countries around the world. One of the most striking phenomena of recent times
has been the extent to which women have increased their share in the labour force; in
both developed and developing countries, the increasing participation of women in paid
work has been driving employment trends and the gender gaps in labour force
participation rates have been shrinking. Especially in the 1980s and early 1990s, labour
force growth was substantially higher for women than for men for every region of the
world except Africa. In the developed industrialized countries, increasing female labour
force participation has been linked to the completion of the fertility transition. In many
developing countries, however, fertility decline has been slow or stalled (Lim, 2002).
Lawanson (2008) argues that women constitute more or less half of any country’s
population. However, he opined that in most countries, women contribute much less than
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men towards the value of recorded production both quantitatively in labour force
participation and qualitatively in educational achievement and skilled manpower.
In the last three decades, the global economy has witnessed the increasing visibility of
women, which is partly an outcome of social and political movements that have
championed women’s rights (Ruwanpura, 2004). He further argues that feminist scholars
have equally been in the forefront of making women’s contribution to the political
economy visible through related scholarship and research. Counting women into the big-
picture, therefore, is a fundamental first-step in recognizing their role in socio-economic
structures. Along with women’s increasing visibility, it is necessary to analyse the
constraints and conditions within which women contribute to the economy.
Improvements in the wellbeing of women are not measured merely in terms of access to
resources but also in terms of their sense of worth and dignity. Forms of employment,
quality of employment and access to social security conditions are also invariably linked
to welfare of women. Employment opportunities available to women need to realize their
potential capabilities (Ruwanpura, 2004).
The Nigerian situation shows that between 1971 and 2004, the percentage of women rose
from 12% to 70% of the work force due to women’s participation in further and higher
education (Women and Work Commission, 2005). However distinct differences exist in
the types of occupation entered by women and men. Women got more jobs in
administrative, clerical, personal services and sales occupation, Apart from moving into
law, medicine and accountancy, there was no similar movement into science,
engineering, ICT and the skilled trades. Women were not found in managerial
occupations: overall, women make up only 32% of managers and senior officials
(Women and Work Commission, 2005). Equally, Okoro (1991) notes that apart from
traditional humanist professions like nursing, teaching, catering and law, the percentage
of women who venture into professions like engineering, architecture are low compared
to men. In the same light Umar & Karofi (2007) observed that female employment in the
Nigerian civil service was historically tended to be lower than male.
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The trend or behaviour of female labour participation has been assumed to be increasing
at an increasing rate in many countries in Nigeria the illustration below shows us what it
looks like;
Source: Illustration drafted based on World Bank indicator data
The illustration above shows that as adult female population remains relatively constant
over the years, the ratio of female to male labour force participation kept increasing over
the years. However it remained relatively stagnant between 2004 and 2010. In the same
light, the labour participation rate for female dropped in 2000 but later increased to 40%
in 2002 and continued at the same rate till 2010. This figures buttress that, until 2004
there was visible progress to increase the level of female labour participation, but there-
after this effort subsided and the same predicament is facing the country today.
The Nigeria Bureau of Statistics publications (2010) show that despite the great
improvement over the years very few women relative to men secure jobs. Out of these
few, a sizeable number of them are temporarily employed. The female Labour
participation rate (% of female population ages 15 and above) in Nigeria was 38.90 in
2008, 39.20 in 2009, according to a World Bank report published in 2010. These figures
show that there has been great improvement yet much still needs to be done. The Federal
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Civil Service in Nigeria is regarded as the government employed staff in Nigeria and this
is being used as a proxy to depict the employment situation in the country. The analysis
also indicates that the number of males employed far outweighs the number of females
during the period under investigation.
The Federal Government of Nigeria started contemplating a sort of drastic reduction of
its workforce in 2001 to make public sector leaner and more effective in service delivery.
The reduction in the public sector workforce at the federal level has not been easy to
implement either due to its fiscal implications or the socio-political problems that such a
program can wreak on the country. In order to drum up support for the policy, a number
of frightening projections were made to underline the need to reduce the federal
workforce. A case in point was the projection that constituted the fulcrum of the alarm
raised by a team of Federal Government technocrats in January 2003. The alarm
bordered, in the main, on the urgent need to prune government personnel costs, with a
stern warning that a failure to do so may result in government spending 95 per cent of her
earnings on personnel by 2007 (Aminu,2010).
Oladejo et al (2011) also noted that several factors, both economic and non-economic are
responsible for low female participation. Traditionally, women are regarded as
homemakers, who oversee and coordinate the affairs and activities at home. (Oladejo et
al 2011) explained that previously in Africa, women remained at home while their
husbands and sons went out to the farm to work. But at home, however, they were not
idle as they engaged in manual processing of food crops and other farm produce in
addition to their housekeeping duties. This is generally induced by the cultural, religious
and traditional beliefs of most developing countries. This is evident in Chaudhry &
Nosheen (2009) who conclude that women empowerment is considerably influenced by
the socio-cultural norms of the community, job of women and household participation
rate.
This situation is worse-off in rural areas given that cultural beliefs are more intense in
rural areas with women seen as inferior beings. Our interest in this study therefore is to
ascertain the determinants of female participation in the rural areas and urban areas. The
advent of western education, industrialization and paid employment, has neutralised this
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cultural beliefs in urban areas and exposed them to the knowledge of men and women
both involved in the labour force.
1.2 Statement of the problem
A major problem confronting Nigeria and other African countries is how to sustain a
stable growth in output (Collier and Gunning, 1999). This preoccupation is important due
to declining state of the country’s per capita income with the growing number of the
female population. It shall therefore be to the nation’s advantage to increase the level of
female participation to boost total output in today’s competitive world.
Indeed, income inequality in Nigeria is high and not favouring the women, females lose a
large proportion of their lifetime income by taking time out of the workplace to have
children according to Ogwumike et al (2006). The labour market is a very important
source that offers explanation for earnings and income inequality. The structure of the
labour market has a significant consequence on employment status and it serves as an
important determinant of household income and welfare. Like most labour markets in
developing countries, the Nigerian labour market represents one of the major sources of
risk through which people fall into poverty (Ogwumike et al, 2006).
The labour market in Nigeria presents opportunities for participants to earn incomes and
determine their welfare; however, few women in Nigeria are engaged in top management
cadre of formal sector establishments. The last population census analysis of 2006
showed that most Nigerian women dwelled in rural areas, which makes them to lag
behind in terms of employment opportunities. Also, educational and health facilities in
rural areas are not increasing. In some places, women are confronted with socio-cultural
restrictions (such as marital status, cultural and religious characteristics) especially in
northern Nigeria as regards to their involvement in public labour participation. It is
therefore important for us to ascertain the rural-urban determinants of female labour force
participation.
There is a consistent partitioning of women into predefined jobs. For example, many
more women work in the service sector as compared to men. In addition, for numerous
developing countries, there has been a growing tendency for more women to be engaged
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in the informal sector than men. Though many women still find restrictions in attaining
some managerial jobs and others who even have these jobs have to contend with
maternity decisions and family trade-offs (Murray & Syed, 2007).
Although, women have shown a continued interest in employment in the state civil
service, men continue to out-number them. By population, the potential female labour
force in Nigeria is 50 per cent though the actual figure ranges between 31 and 36 per cent
in both the public and private sectors of the economy (Salaam, 2003; Africa Action,
2003). At the higher administrative and managerial levels, the figure is even smaller. For
example, of the 191, 329 federal civil servants in 1992, only 45,881 (24 %) were females.
In Kebbi State civil service, female employees constituted only 12% (1,396) of the total
employment as at 1999 (Federal Character Commission, Kebbi State Office,
2004).Women have been relegated to both productive and reproductive roles in the
household. Their contributions are often unpaid for, and yet do not allow them to fetch
other paid productive jobs especially in the formal sector (as cited by Muhammad and
Usman, 2007)
Although, the problem of employee turnover has received much attention from
researchers in organizational sciences, very few of these studies have focused on female
labour participation. Moreover, in Nigeria few authors examined the sector of female
labour participation like Aminu (2010), Baridam (1996) and Lawanson (2008) but none
of them used logistic regression to investigate the determinants. The motivation behind
this study is based on theoretical and empirical literature that projects husband’s
willingness to let their spouse work, as the prime determinant of female labour
participation. This is usually induced by the culture and religion background of the men,
and we agree that cultural and traditional beliefs are even more binding in rural areas.
That is why we investigated the relative determinants of labour force participation in
rural as well as urban areas. In addition to the limitations of previous studies, none of
these studies examined the determinants from rural and urban areas separately, as we
investigate in this study.
Thus, this study investigates the determinants of female labour force participation in
Nigeria from the opinion that labour market participation of women will improve their
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relative economic positions and also increase overall economic efficiency of the country.
And in order to improve female Also based on the changing demographic trends,
globalisation and westernisation, it is necessary to examine the determinants of female
labour participation in urban as well as rural areas.
The study seeks to provide answers to the following questions;
1) What are the factors that determine the female labour force participation decision
in urban Nigeria?
2) What are the factors that determine the female labour force participation decision
in rural Nigeria?
1.3 Objectives of the study
The broad objective of this study is to investigate the determinants of female labour force
participation in Nigeria. To achieve this objective we use the specific objectives below:
(1) To investigate the factors that determines the female labour force participation
decision in rural Nigeria.
(2) To examine the factors that determines the female labour force participation decision
in urban Nigeria.
1.4 Hypothesis of the research
In order to actualize the objectives enumerated, the following null hypotheses are
therefore tested:
1) There exist no determinants for female labour force participation of women in rural
Nigeria.
2) There exist no determinants for female labour force participation of women in urban
Nigeria.
1.5 Scope of the study
This study focuses on microeconomic analysis using house hold survey employment data
for 2010/2011. The study did not use macroeconomic or time series data, which therefore
makes this a static analysis. The researcher concentrated on the participation of women in
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the labour force on formal and informal activities, since we employed the use of primary
data. The study also separately investigated the determinants of female labour force
participation in urban areas as well as rural areas.
1.6 Justification of the Study
The justification of this study cannot be overemphasised as the study is based on the
determinants of female labour force participation. Figure 1 shows us that very little effort
has been done since 2004 to improve the level of female labour force participation in
Nigeria. There is therefore need to revisit our policies to change the status quo by
investigating the current determinants of labour force participation in Nigeria. However
we also reflect the fact that there could be a difference in these determinants given that
most of the forces behind female labour participation is based on cultural and traditional
beliefs.
The results of this study would therefore go a long way to provide policy implications of
the determinants in both the urban and rural areas for both government and non-
government agencies. It also serves as contribution to knowledge and a reference for
further studies by authors that may want to investigate further. In addition to this, the
significant difference between the determinants of the urban and rural areas, it only points
out that the impact of the cultural and traditional beliefs in rural areas are still very high
also meaning that the females are still highly marginalised. This should therefore lead the
government to put in place the mechanism to educate and enlighten the men resident in
rural areas to the importance and significance of female labour participation.
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CHAPTER TWO
2.0 LITERATURE REVIEW
2.1 Theoretical literature
There is an immense literature available pertaining to women participation in economic
activities at the national and international level. Women represent a sizeable portion of
the population and require a lot of attention. They are considered as a supporting factor in
the economic development of the country and put a significant effect on overall business
and economic activities (Faridi, Chaudhry and Malik, 2011). According to Ruwanpura
(2004), “Economists explanations for the existence of segregated labour markets are not
new”. A review of the literature on women or gender in general indicates that there is
now a demand for a re-orientation of research and changes in the methodological
procedures used for the compilation and computation of national statistics so as to reflect
accurately the role of women and their labour input in the national economy. The trend is
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not only evident in the Third-world alone, but it is worldwide. The emphasis is now on
the productivity and efficiency of the labour input of women (Olukemi, 2008).
An analysis of trends in labour economics throughout the world reveals that sustained
increase in women’s participation in the labour force during the last century, particularly
during its second half. This fact has stimulated considerable interest in the economic
analysis of a woman’s decision to work (Rincon, 2007). The author noted that the
pioneering studies of Mincer (1962) and Cain (1966) in the United States have served as
a theoretical and empirical foundation for numerous studies of female labour force
participation. Ackah et al. (2009) were of the view that the increasing trend toward
women’s participation in the labour market in both developed and developing countries
has drawn both social and academic interest resulting in many insightful studies on
gender aspects of labour market issues.
A critical review of the large literature provides at least two general theoretical paradigms
to explain the changing patterns of female labour force participation in low-income
countries (Ackah et al, 2009). Equally, Nam (1991) categorizes the literature into two
perspectives, the modernization and the world system perspectives. According
modernization theorists, economic development is positively associated with female
labour force participation through change in the country’s occupational structure (i.e. the
increasing availability of service and white-collar jobs) and increased educational
opportunities, often accompanied by reduced fertility rates and household responsibilities
(Nam,1991).
The modernization process is associated with increased demand for labour, a general
social acceptance of women’s education and employment, as well as lower fertility
(Bauer and Shin, 1987). The relationship between education and female labour force
participation has been summarized by Standing (1981) under three hypotheses: the
opportunity cost hypothesis, the relative employment opportunity hypothesis, and the
aspiration hypothesis (Nam, 1991).
First, the opportunity cost argument conceives that to the extent that there is a positive
relationship between educational investments and earnings potential, education raises the
opportunity cost of economic activity, thereby giving people a positive incentive to seek
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employment (Bowen and Finegan, 1969). The relative employment opportunity
hypothesis posit that employers usually tend to have a positive bias towards a qualified
female work force rather than older male workers whose educational qualifications
increase their employment options (Oppenheimer, 1970).
Furthermore, the aspiration hypothesis is based on the human capital hypothesis that
women with higher levels of education are more likely to participate in the labour market.
From this view point that income aspirations and expectations of people are strongly
determined by levels of education, more-educated women are expected to have higher
income aspirations over their less-educated counterparts and therefore tend to be more
active in the labour market (Cain, 1966).
The world system perspective, on the other hand, explains the increasing labour force
participation in the context of traditional comparative advantage international trade
theory. From the perspective of the Stolper-Samuelson theorem, global trade
liberalisation would lead to a rise in the demand for unskilled labour in developing
countries (Ackah et al, 2009). In other words, since developing countries are more
likely to have a comparative advantage in producing unskilled labour-intensive goods,
one would expect international trade in these countries to lead to a rise in the demand for
and relative returns of the abundant factor; unskilled labour in the case of developing
countries (Harrison, 2005). Since more females than males tend to be unskilled and
female labour is usually cheaper than male labour, labour-intensive industries tend to be
relatively dominated by females, particularly those who are young and single (Grossman,
1979)
While a positive correlation between levels of education and female labour force
participation has been postulated theoretically, empirical findings in developing countries
are rather mixed (Standing, 1981). Studies have shown that female labour force
participation is another variable which appears to be associated with lower fertility rates
in different parts of the world (Kalwij, 2000). Empirical evidence from both developed
and developing countries confirm that female education is associated with a greater
incentive to participate in market activity.
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Neoclassical theory suggests that high levels of investment in human capital and greater
participation of women in the labour market are negatively associated with lower fertility
rates (Rincon, 2007). In general, however, the causal impact of female labour force
participation on fertility may occur along a number of complex pathways because both
female labour force participation and lower fertility may reinforce each other. The
relationships between female labour force participation and fertility have been studied
based on the maternal role incompatibility hypothesis, which states that an inverse
relationship occurs between women’s work and fertility only when the roles of worker
and mother conflict (Goldstein, 1972). According to the author, the implication of this
hypothesis is that a negative relationship between female employment and fertility exists
to the extent that they are competing uses of time. Otherwise, we should expect to find no
relationship, or even a positive relation between employment and fertility.
2.1.1 The neoclassical theory
The neo-classical economists’ interpretation of segregated labour markets is based on the
rationality of employers and workers. According to this argument, workers seek
appropriate employment after taking into account their endowment levels, constraints and
preferences; likewise as profit maximizing agents, employers will pay workers the worth
of their marginal product. Interactions of these two factors are argued to result in
competitive-efficient labour markets (Arrow, 1973). According to this theory, women
workers are paid lower wages because of lower human capital levels, truncated labour-
market participation, and minimal skill and training, acquired during employment. These
factors make women choose economic activities that reflect their constraints and
preferences, i.e. low paying jobs, flexible work, part-time work, etc. Lower monetary
rewards are also supposed to compensate for women’s “better” working conditions.
Becker (1957) argues that if an individual has a taste for discrimination, he must act as if
he were willing to pay something, either directly or in the form of a reduced income, to
be associated with some persons instead of others. The taste for discrimination is due to
individuals’ preferences and prejudices. Employers are prepared to sacrifice profit to
avoid female workers, by paying higher amounts to higher male workers due to the
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problems associated with employing women that include maternity leaves and inflexible
nature.
A key limitation of neo-classical theory, however, is that it does not move beyond to look
at the underlying mechanisms that hinder women from making different choices. Are
there social-cultural norms that impinge upon women affecting their human capital? For
example, women are unable to compete with men on an equal footing because usually
they have not acquired the appropriate education levels. This in turn is linked to
patriarchal norms and attitudes that factor into parents’ decision-making process, usually
with adverse consequences, against girls (Ruwanpura, 2004).
Similarly Anker (1997) explains that women have less skill and training experience than
men because,
(a) They do not have the same labour market opportunities as men, and
(b) Because family responsibilities lead them to exit-and-enter the labour
market
The explanation provided by neo-classical economists is a static account of the status
quo, but also its’ correspondence with labour market trends is debatable. Formal sector
employment is limited in low-income countries, but yet there are an equal proportion of
“highly” qualified educated men and women. According to neo-classical theory women
employees ought to be equally represented in formal sector jobs. Women are not,
however, adequately represented in formal sector employment. Does this imply the
existence of gender-based discriminatory practices in the labour market? A study done in
Peru notes that even with female education levels surpassing male education levels
during recent years, there has not been any change in gender wage-differentials
(Ruwanpura, 2004).
2.1.2 The Theory of Allocation of Time and Human Capital Investment
It is argued that the explanation for minority workers’ low relative pay and occupational
status lies in their relative deficiency in human capital. This theory, which relates an
individual’s investment in education and training with his or her lifetime earnings, was
developed by Mincer (1958) and Becker (1957). Two complementary theoretical
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approaches support the study of labour force participation of women. Both focus on
different aspects of the labour supply decisions. On one hand, the neoclassical model of
allocation of time deals with whether a woman will enter the labour market by comparing
the value of her time in the market to the value she places on her time spent at home and
if she decides to do so, how much time will be spent on market work. On the other hand,
the human capital investment theory stresses the relationship between the return on the
investment of acquiring valuable skills and the time the person expects to work during
his/her life (Becker, 1957). In other words, labour participation outcomes are related to
general skills acquired through education and training.
Indeed, those who are planning to participate in the labour market as full-time workers
are prompted to invest more in education and training (Altonji & Blank, 1999).
Moreover, the human capital model emphasizes the role of women's preferences and the
choices they may make to invest less in job-related education and training, as well as to
spend a smaller share of their adult years in the labour force (Blau et al., 2002). Other
factors include premarket discrimination, or societal discrimination, in which various
types of social pressures influence women's choices adversely.
2.1.3 Women’s Supply of Labour
Human capital theory suggests several reasons why women might decide to acquire
smaller amounts of formal education than men. Many scholars have emphasized the
traditional roles of women within the family of which childbearing is one of the most
important. Women know that bearing children might force them to leave the labour
market for a while. Again, the present value gives us the insight of the potential
behaviour of women. If a woman is planning to interrupt her participation in the labour
market, her investment in additional education might no longer be profitable since her
time out of the labour market results in a reduction in benefits since time would be
smaller (Rincon, 2007).
Moreover, a woman may decide against investment in the types of human capital that
require sustained, high-level commitment to the labour force because the investment
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Iweagu H. E., (2012)
depreciates rapidly during periods of work interruptions. The time out of the labour force
has cost her a reduction of earnings over the remainder of her working life. In this
example, the benefits of the investment in college education, the sum of the two shaded
areas, may not be large enough to make it worthwhile. Thus, a woman with an adherence
to the traditional roles in the family is less likely to pursue college and graduate study.
Anticipating time out of the labour force, she is likely to reduce her amount of
educational investment. Other kinds of human capital investments are those made after
one has started to work, in training received at the workplace. All forms of training,
whether formal training programs, informal training under the supervision of a more
experienced worker, or general training, are costly. If the training is specific to one firm
or employer, workers and the firm share the cost.
The role of education in determining women’s participation becomes stronger when we
consider women in urban areas only. Compared to illiterate women, those with higher
levels of schooling have progressively higher participation rates that peak for those with
higher education. Among rural women, illiterates and primary school graduates are not
any more likely to participate than illiterate women (Dayıoğlu and. Kırdar, 2010). The
authors noted that those with secondary and general high school education have a lower
likelihood of entering the labour market as compared to illiterate women, which may
stem from demand side factors: the unavailability of “socially appropriate” jobs for them
and the changing economic structure of rural households with the proportion engaged in
agriculture declining.
However, vocational high school graduates and those with university degrees have a
higher likelihood of entering the labour market. The effect is especially strong for
university graduates. Dayıoğlu and Kırdar (2010) was of the opinion that the age-
participation profiles are hump-shaped in both urban and rural areas, though age is a
stronger correlate of participation in urban areas. The authors assert that being married is
negatively associated with participation in both urban and rural areas, with a particularly
large effect in urban areas. Separated and divorced women are also less likely to
participate in rural areas but not in urban areas. In both places, it seems less likely for
widowed women to enter the labour market. The number of children in the household are
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Iweagu H. E., (2012)
also negatively associated with the participation probability of women in urban but not in
rural areas (Dayıoğlu and. Kırdar, 2010)
2.2 EMPIRICAL LITERATURE
2.21 Empirical literature: Global Evidence
Psachropoulos and Tzannatos (1989) pioneered the search for the female labour
determinants by examining the definitions and theories of female labour supply and relate
them to statistical evidence from 136 countries in the early 1980s. The research finding
support the view that, during the transformation from an agrarian subsistence economy,
the participation of women in the labour force initially decreases and picks up later after a
critical level of development has been achieved. They note that education is seen as a
potential booster of the officially recorded female labour supply in developing countries.
Jaumotte (2003) employed econometric analysis using a panel data of 17 OECD
countries over the period 1985-1999 to investigate the determinants of female labour
force participation. Their findings suggest that there is a positive impact of neutral tax
treatment of second earners on female participation. Unlike childcare subsidies, child
benefits reduce female participation due to an income effect and their lump-sum
character. And finally note that, female education, the general labour market conditions,
and cultural attitudes remain major determinants of female participation.
Ruwanpura (2004) examines themes related to quality of women’s employment in the
South Asian and African regions theoretically. The study explores the following issues:
What are the key determinants that influence the links between gender and employment
quality? Which institutional and economic factors increase women’s participation in the
labour force, and what is its relationship to quality of employment opportunities
available? the author notes that in the geographical areas under consideration this means
that an examination of informal sector activity is of paramount importance. He states that
addressing these issues will set the stage to investigate measures to reduce low-quality
employment, sometimes from unionised labour and at other instances from consumer
groups.
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Iweagu H. E., (2012)
Lisaniler & Bhatti (2005) investigate the determinants of female labour force
participation in North Cyprus for the year 2001. Analysis of data from the survey
“Gender Profile in Education and Employment in North Cyprus” suggests that women’s
education is the main factor increasing women’s likelihood of participation while age and
the residence are also significant factors influencing the women’s labour supply. Their
findings have also shown the effect of patriarchy and cultural factors on the labour supply
decisions of North Cypriot women.
Boca & Locatelli (2006) investigates the determinants of Motherhood and work status in
some European countries, and provide several interpretations of the differences across
countries. Their results suggest that most analyses indicate that social policies, taking into
account several variables (family background, the allocation of time within the
household, religion and culture), have a very relevant role in explaining different degrees
of incompatibility between employment and child rearing across different countries. The
incompatibilities between motherhood and careers find reconciliation in policies that
enhance employment flexibility and diminish the potential opportunity costs of children.
Ntuli (2007) uses survey data to examine the determinants of the low level and also of the
changes in African women’s labour force participation, during the first decade of
democracy (1995-2004) using decomposition technique devised by Even and
Macpherson (1990). The result shows that female participation responds positively to
education which has been the prime factor. The study finds that non-labour income,
marriage, fertility and geographical variations in economic development persistently
stifled participation.
Lawanson (2008) states that women constitute more or less, half of any country’s
population. The author notes that in most countries, women contribute much less than
men towards the value of recorded production both quantitatively in labour force
participation and qualitatively in educational achievement and skilled manpower. He
states that under-utilization of female labour has obvious implications for economic
welfare and growth. He notes several factors, both economic and non-economic
responsible for this. He concludes that the participation of women in the labour force
appears to depend much more on the social environment than is the case for men
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Pastore & Verashchagina (2008) investigates the determinants of female labour force
participation in 1996 and 2001 using data from the Belarusian Household Survey. The
selectivity corrected wage equation is estimated to compute an expected wage offer for
women. The latter is included, in the second step, as a regressor in the structural female
labour supply equation, estimated by probit. Several measures for the care of children and
elderly people, proxies for the opportunity cost of working, affect female participation,
but do not generate sample selection mechanisms. Their results suggest that the estimated
elasticity of female participation to wages is low, at about 0.45 in 1996 and 0.41 in 2001.
Moreover the data allows detecting poverty trap mechanisms, whereas women in low-
income households have much lower than average participation rates. At the same time
the elasticity of female labour supply with respect to the own wage appears to be much
higher for the low-paid groups of women.
Ackah et al (2009) investigate the determinants of female labour force participation in
Ghana at two points in time, 1991 and 2006, with the view that labour market
participation of women will improve their relative economic positions and also increase
overall economic efficiency of the country. The study utilizes data from the 1991/92 and
2005/06 Ghana Living Standards Survey. The OLS estimates result suggests that both
women’s educational attainment and fertility determine women's labour force
participation in Ghana. The study finds that women with primary school education or
above are more economically active than those with no education. They note that this
pattern is only found among women participating in wage employment. The study also
finds that high fertility acts as a constraint on female participation in wage employment;
and that the presence of children in the home significantly reduces participation in wage
work, controlling for age, education, ethnicity, religion and marital status.
Chaudhry and Nosheen (2009) explore the possible determinants of women
empowerment using regression analysis based on primary data from a district of Southern
Punjab. They construct a cumulative index for women empowerment using four indices
i.e. personal autonomy, family decision making, domestic economic decisions and
political autonomy. The empirical analysis shows some new and diverse results for three
different areas namely urban, rural and tribal areas. The results show that women
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Iweagu H. E., (2012)
empowerment is considerably influenced by education, access to media, socio-cultural
norms of the community, job of women and household participation rate.
Bbaale (2010) uses the Demographic and Health Survey 2006 to examine the relationship
between female education and labour force participation on the one hand, and fertility
rates on the other, for Uganda. His results confirm the hypotheses that female education,
especially at the secondary and post-secondary levels, reduces fertility and increases their
likelihood of being engaged in the labour force. He also finds that despite the near
universal knowledge of family planning methods in Uganda and the importance of
contraceptives in helping to reduce the number of children born, less than half of the
women were currently using them at the time of the survey. He suggests that efforts to
reduce fertility need to target measures that aim to educate women and to keep them in
school. The government programme to extend free education at the secondary level is
therefore an important measure that may help to reduce fertility.
Faridi et al (2011) investigate the factors which influence women’s participation in self-
employment in Pakistan. The study uses primary source of data for empirical analysis.
They employ Logistic regression technique to estimate the women self-employment
model. The study finds that age and experience positively affects women’s self-
employment. They also conclude that education, location and number of dependents
significantly reduce the women’s work participation as self-employed worker. The study
suggests that the government provide technical and vocational education to the women,
and also give old age benefits just to minimize the dependency burden.
Surjit & Kaur (2011) investigated the labour force participation of women in India and
found out that particular ethnic and socio-cultural groups tend to concentrate in various
sectors of the labour market. Studies in the area of gender and migration also point out
that marriage migration often leads to entry into the labour force and the two processes
are not mutually exclusive.
Ejaz (2011) analyzes the determinants of female labour force participation (FLFP) across
rural and urban Pakistan. Potential explanatory variables that determine FLFP include (i)
females’ own characteristics, (ii) household characteristics, and (iii) female
empowerment indicators. Endogenous explanatory variables, such as ownership of home
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Iweagu H. E., (2012)
appliances, fertility, and co-residence, can lead to biased and inconsistent results due to
reverse causality. They then use potential instruments which include (i) the average
number of home appliances owned in the locality, (ii) the gender of the firstborn child,
(iii) whether or not the first two children are of the same sex, (iv) proximity to a clinic,
(v) contraceptive use, and (vi) housing type. The probit model is used to estimate
variables, while the instrumental variable (IV) approach is used to tackle the issue of
endogeneity. In the first stage, the study’s results give estimates of endogenous covariates
separately, using the IV approach. In the second stage, the IV vector is used to show the
impact of explanatory variables on the dependent variable FLFP. Their results suggests
an inverse and significant relationship between FLFP and both fertility and the gender-
wage gap; and a direct and significant relationship between FLFP and ownership of home
appliances and co-residence.
Bibi & Afzal (2012) examines the factors which affect the decision of married women to
participate in the labour force. They found that education of the respondent, number of
off springs, number of dependents, family size, income of husband, monthly expenditures
of the family, positive attitude of husband and family towards the job of women, job
satisfaction, have a positive impact on the labour force participation of married women.
While age of the respondent, living with husband, strong relationship with spouse before
marriage, satisfaction of house wives with their current life, restrictions from family
regarding job, other earners in the family negatively affect the decision of married
women to participate in the labour force. They also suggest that the rate of inflation
prevailing in the economy of a country largely influences the labour force participation of
married women.
2.22 Empirical Literature: Evidence from Nigeria
Baridam (1996) pioneered the research in Nigeria by examining the determinants of
female labour force participation and family size using questionnaire and descriptive
statistics method. He sourced data from 300 female staff of Shell Petroleum, University
of Port-Harcourt and its metropolis shows that participation in labour force is due to
economic agents and love for children. The result also reveals that women avoid the
effect of their employment on their family size by employing house-helps.
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Iweagu H. E., (2012)
Ogwumike, et al (2006) analysed the distribution and structure of main job earnings,
determinants and income inequality in the Nigerian labour market. The study uses tabular
presentations, Gini Coefficient, Theil’s Entropy Index, Ordinary Least Squares technique,
Heckman’s two-stage selectivity bias correction procedure, Tobit analytical technique as
well as descriptive statistics for analyses. The results on labour participation show that
the aggregate data variables relating to age and education are all significant at 1per cent.
Age and education carry positive sign, which suggests that hours of labour offered in the
market increases with age and education of workers. All of marriage, divorce and loss of
spouse through death are all very significant and positive determinants of labour force
participation in the Nigerian job market. For married female, marriage affected
participation in 24 the labour market significantly, but negatively, suggesting that
marriage constitutes a source of restriction to female participation in the labour market in
Nigeria. He shows that the presence of children under-six also has significant negative
impact on the ability of women to participate in the labour market. Most of the variables
considered in disaggregated analyses in this empirical process are significant in
explaining time offered in the labour market in Nigeria.
Olusoji (2006) investigated the determinants of female labour participation in Nigeria,
using a Survey carried out between January and October 2001.They used regression
analysis to investigate the differences in hours put in by both women formal and informal
sectors separately. Their findings suggest that the number of hours worked were
determined by the respondents income, family size, relationship with household head,
sector of participation, education and location. The researcher also opines that women
with tertiary education work fewer hours than older and married women.
Umar and Karofi (2007) examine the impact of non-work factors on labour turnover
among female employees in Kebbi State Civil Service. The hypothesis of the study states
that the higher the perception of prevalence of certain non-work related factors, the
earlier the decision by female workers to disengage from the civil service. The study uses
administers questionnaire on 172 former female civil servants in Kebbi State. The result
indicates that non-work factors are statistically significant determinants of female labour
turnover. The finding also note that pressures from the matrimonial homes are very
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Iweagu H. E., (2012)
strong, standing out as the strongest of all the non-work factors responsible for female
labour turnover. The studies recommends that high-quality public childcare should be
provided at work places and that the government should also look at ways of making
work–environment reflect the culture of the society.
Aminu (2010) investigates the determinants of participation and earnings in wage
employment in Nigeria. He estimates Multinomial logit and Mincerian human capital
models for male and female employees across four wage employment segments
considered in the study. His results of the estimated multinomial logit model shows that
the probability of participation of employable household members in wage employment
segments is affected by the levels of education attained, possession of assets like own
homes, living in free accommodation and residing in urban areas. The probability of
participation in public sector wage employment increases with the level of education. He
finds that the main determinants of hourly wage are the levels of education, ages and the
location of residence of the employees. The returns to education and age differ for males
and females across the four segments of wage employment adopted for the study. He
finds that mean of hourly wage is highest in government ministries while it is lowest in
informal private sector organisations. Gender wage differential is lowest in government
ministries while it is highest in informal private organizations. He concludes that the
various segments of wage employment in Nigeria are not homogenous with respect to the
factors determining participation and earnings.
Chukuezi (2010) examines the participation of women in household labour in Nigeria . A
survey of married women in Owerri, Nigeria reveals that women do most of the
housework and childcare within the family. She explains that cultural expectations about
gendered responsibilities in the home despite their level of education and earnings are
mainly responsible for women doing more household work than men. She concludes that
both structured and cultural factors should be examined for an appropriate explanation of
gendered inequity in household labour in Nigeria.
Oladejo et al., (2011) analyse women participation in agricultural production in Egbedore
Local Government Area of Osun State, Nigeria. The study investigates the women’s
access to economic resources and examines the influence of selected socio-economic
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Iweagu H. E., (2012)
characteristics of women and access to economic resources on their participation in
agricultural production. Using multistage random sampling technique to select 50
respondents, it makes use of well-structured interview schedule to obtain the necessary
data. The study adopts both descriptive and inferential analytical tools. The study equally
uses probit analyses to investigate the determinants of women participation in agricultural
production in the study area. The results reveal that household size, marital status and
local taboos had significant impact on the women participation in agricultural production;
all at 5% probability level with a log likelihood of -96.160222, pseudo R2 of 0.0875 and
LR statistic of 18.44 which shows that the model has a good fit. They note that most of
the respondents were illiterate with non-formal educational status which directly
informed their participation in agricultural production. The study concludes that there is
high rate of involvement of women in agricultural production in the study area; hence the
role of some socio-economic variables as well as assets such as social capital, landed-
property, cash as well as savings are central in determining the participation level or
perception on agricultural production.
2.3 Summary of Literature
YEAR/AUTHOR LOCATION NATURE OF DATA METHODOLOGY FINDINGS
Psachropoulos and
Tzannatos (1989)
136 countries Time series data Panel analysis The participation of
women in the labour
force initially decreases
and picks up later after a
critical level of
development has been
achieved. And that
education is seen as a
potential booster of the
officially recorded
female labour supply in
developing countries.
Jaumotte (2003) 17 OECD countries Time series data 1985-
1999
Econometric panel
analysis
There is a positive impact
of neutral tax treatment of
second earners on female
participation. And that
female education, the
general labour market
conditions, and cultural
attitudes remain major
determinants of female
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Iweagu H. E., (2012)
participation.
Lisaniler & Bhatti (2005) North Cyprus 2001 cross-sectional
data
Binomial Logit Analysis Women’s education is the
main factor increasing
women’s likelihood of
participation while age
and the residence are also
significant factors
influencing the women’s
labour supply. And the
effect of patriarchy and
cultural factors on the
labour supply decisions of
North Cypriot women.
Boca & Locatelli (2006) some European
countries
cross-sectional data Structural model of
participation
that most analyses
indicate that social
policies, taking into
account several variables
(family background, the
allocation of time within
the household, religion
and culture), have a very
relevant role in explaining
different degrees of
incompatibility between
employment and child
rearing across different
countries
Ntuli (2007) Some African
countries
1995-2004 Decomposition technique Female participation
responds positively to
education which has been
the prime factor. The
study finds that non-
labour income, marriage,
fertility and geographical
variations in economic
development persistently
stifled participation.
Pastore & Verashchagina
(2008)
Belarus 1996 and 2001
Belarusian Household
Survey
Probit model The estimated elasticity of
female participation to
wages is low, at about
0.45 in 1996 and 0.41 in
2001. At the same time
the elasticity of female
labour supply with respect
to the own wage appears
to be much higher for the
low-paid groups of
women.
Ackah et al (2009) Ghana 1991/92 and 2005/06
Ghana Living Standards
Survey
OLS Technique Women with primary
school education or above
are more economically
active than those with no
education. And that high
fertility acts as a
constraint on female
participation in wage
employment; and that the
presence of children in the
home significantly
reduces participation in
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Iweagu H. E., (2012)
wage work, controlling
for age, education,
ethnicity, religion and
marital status.
Chaudhry and Nosheen (2009) Punjab primary data from a
district of Southern
Punjab
OLS method The results show that
women empowerment is
considerably influenced
by education, access to
media, socio-cultural
norms of the community,
job of women and
household participation
rate.
Bbaale (2010) Uganda Demographic and
Health Survey 2006
Probit model His results confirm the
hypotheses that female
education, especially at
the secondary and post-
secondary levels, reduces
fertility and increases
their likelihood of being
engaged in the labour
force
Faridi et al (2011) Pakistan Multiple Indicator
Cluster Survey 2007-08
data of Punjab
Heckman two step model
and Logistic regression
technique
Age and experience
positively affects
women’s self-
employment. They also
conclude that education,
location and number of
dependents significantly
reduce the women’s work
participation as self-
employed worker.
Surjit & Kaur (2011) India NSS data Tobit Particular ethnic and
socio-cultural groups tend
to concentrate in various
sectors of the labour
market. Studies in the
area of gender and
migration also point out
that marriage migration
often leads to entry into
the labour force and the
two processes are not
mutually exclusive.
Ejaz (2011) Pakistan Pakistan Social and
Living Standards
Measurement Survey
for 2006/07
Instrumental variable (IV) An inverse and significant
relationship between
FLFP and both fertility
and the gender-wage gap;
and a direct and
significant relationship
between FLFP and
ownership of home
appliances and co-
residence.
Bibi & Afzal (2012) Wah Cantt (Pakistan) Sample survey through
questionnaires
Descriptive analysis They found that education
of the respondent, number
of off springs, number of
dependents, family size,
income of husband,
monthly expenditures of
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Iweagu H. E., (2012)
the family, positive
attitude of husband and
family towards the job of
women, job satisfaction,
have a positive impact on
the labour force
participation of married
women. While age of the
respondent, living with
husband, strong
relationship with spouse
before marriage,
satisfaction of house
wives with their current
life, restrictions from
family regarding job,
other earners in the family
negatively affect the
decision of married
women to participate in
the labour force.
Baridam (1996) Port-Harcourt,
Nigeria
Data sourced from 300
female staff of Shell
Petroleum, University
of Port-Harcourt and its
metropolis
descriptive statistics
method
That participation in
labour force is due to
economic agents and love
for children. The result
also reveals that women
avoid the effect of their
employment on their
family size by employing
house-helps
Ogwumike, et al (2006) Nigeria General Household
Survey (GHS)
conducted in
1999 by the Federal
Office of Statistics
(FOS), Nigeria
Heckman’s selectivity bias,
Tobit analytical technique
as well as descriptive
statistics for analyses
Age and education carry
positive sign, which
suggests that hours of
labour offered in the
market increases with age
and education of workers.
While, marriage, divorce
and loss of spouse
through death are all very
significant and positive
determinants of labour
force participation in the
Nigerian job market.
Umar and Karofi (2007) Kebbi State, Nigeria Primary data through
questionaires
OLS Method The result indicates that
non-work factors are
statistically significant
determinants of female
labour turnover. The
finding also note that
pressures from the
matrimonial homes are
very strong, standing out
as the strongest of all the
non-work factors
responsible for female
labour turnover. The
studies recommends that
high-quality public
childcare should be
provided at work places
and that the government
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Iweagu H. E., (2012)
should also look at ways
of making work–
environment reflect the
culture of the society.
Aminu (2010) Nigeria General household
survey data (GHS)
conducted by NBS in
1998/99 and 2007/2008
Probit, Multinomial logit
and Mincerian human
capital models
The probability of
participation of
employable household
members in wage
employment segments is
affected by the levels of
education attained,
possession of assets like
own homes, living in free
accommodation and
residing in urban areas.
Chukuezi (2010) Owerri , Nigeria Primary data, Owerri Descriptive analysis That cultural expectations
about gendered
responsibilities in the
home despite their level
of education and earnings
are mainly responsible for
women doing more
household work than men
Oladejo et al., (2011) Osun State, Nigeria Primary data, Nigeria,
Osun state.
Descriptive and inferential
analytical tools and probit
analyses
The results reveal that
household size, marital
status and local taboos
had significant impact on
the women participation
in agricultural production.
Olusoji (2006) Nigeria Survey carried out
between January and
October 2001
OLS Regression Number of hours worked
were determined by the
respondents income,
family size, relationship
with household head,
sector of participation,
education and location.
2.4 Limitation of the previous study
From the literature review most of the works that sort the determinants of female labour
force participation relied on the assumption that there was no significant difference in the
region of residence of the individual, and just looked for the impact of rural urban
residency on female labour participation and therefore sort for the determinants generally.
We shall therefore capitalise on this to run regression analysis to test for the determinants
in the urban regions of Nigeria differently as well as those of the rural regions to ascertain
if there is no difference between them or there is need for separate policies to be carried
out in both regions to improve female labour participation if there is.
We also note that most of the works used methods like multi-stage random sampling
technique, OLS technique, decomposition techniques, descriptive statistics and other
regression analysis. However the closest of all these works is that of Faridi et al (2011)
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Iweagu H. E., (2012)
who used logistic regression but did his analysis based on primary data from Pakistan. In
Nigeria, Aminu (2010) used multinomial logit labour participation within 4 wage
brackets, while chukuezi (2010) examines the participation of women in household
labour participation and not general labour participation. Also we find, Baridam (1996)
who uses descriptive statistics to examine the determinant of female labour force
participation and family size in Nigeria and Lawson (2008) studied on the female labour
force participation: determinant and trend without applying any statistical techniques for
the estimation. We shall therefore use the logit approach to explore its odds ratio and
probability qualities in interpreting the results.
This study therefore attempts to fill the gap created in the literature by focusing on the
determinants of female labour force participation in Nigeria using logit regression in
urban Nigeria separately from rural Nigeria. The researcher employed the General house
hold survey employment data for 2010/2011, that we have employed has the advantage of
a very recent and national data unlike most works carried out in Nigeria.
CHAPTER THREE
3.0 Methodology of the research
3.1 Theoretical Framework
The theoretical framework of this study would be based on the Neoclassical Model of
Allocation of Time. Economists traditionally analyse labour supply through the use of the
neoclassical model of allocation of time or the model of labour-leisure choice, which is
an extension of the utility maximization problem of consumer theory. The model
analyses how individuals make choices in deciding how they will spend a fixed amount
of time. They must decide how many hours to work, and how many hours to spend
consuming a variety of goods, ranging from computers and cars to DVDs and theatre.
The study uses a standard participation model based on conventional theoretical
household models of time allocation (Mincer, 1962; Becker, 1965).
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Iweagu H. E., (2012)
In the simplest model, an individual has two uses for his/her time, either working in the
labour market at a real wage rate of W per hour, or “leisure”. According to this basic
model, individuals wish to maximize their utility or satisfaction (U) by purchasing goods
and services (C) in the marketplace and by consuming time in leisure activities
(L). amount of both consumed will depend on the individual’s market wage (W),
personal preferences, and the non-labour income (V) that person enjoys.
Becker (1965) while developing the model stated that the individual’s utility function will
be:
U = f(C, L) ……………………………………........................................................... (1)
where U is an index that measures the individual’s wellbeing, assuming people are able
to rank in order all possible situations from the least desirable to the most. Thus, a higher
index U means more C and/or L and more satisfaction.
Moreover, C and L are economic “goods” – that is, whatever economic quantities they
represent, we assume that more of any particular good is preferred to less.
Nicholson (1992) explained that when the individual seeks to maximize his/her utility
with respect to time in the period under analysis, he is bound by two conditions: first, he
must allocate the day’s discretionary time (T) – that is, 16 hours’ time, either to working
for pay (H) or to leisure (L). The other condition is related to the income he needs to buy
goods and services in the market place: Labour wages (W * H) and non-labour incomes
(V) are the only sources of the individual’s income. These constraints can be written as
the following:
L + H = T…………………………………………………………............................... (2)
C = (W * H) + V ……………………………………………………........................... (3)
The individual’s budget constraint is represented by equation (3). It tells us that
individual’s consumption expenditures must not exceed the total income. We can rewrite
(2) and (3) as follows:
C = W (T- L) + V
Setting up the Lagrangian expression to represent the individual’s utility maximization
problem yields
[ ]{ }( , ) ( )L U C L W T L V Cλ= + − + − ………………………………............................. (4)
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Iweagu H. E., (2012)
The first order conditions for a maximum are
0C
L UMU
C Cλ λ
∂ ∂= − = ∴ =
∂ ∂……………………………………….............................. (5)
0 LMUL UW
L L Wλ λ
∂ ∂= − = ∴ =
∂ ∂………………………..…………................................ (6)
Equating (5) and (6), we get
L
C
MUW
MU= ……………………………………………….……….................................. (7)
This expression can be interpreted as the utility-maximizing labour supply decision
principle. That is, in order to maximize utility, given the real wage, W, the individual
should choose to work that number of hours for which the marginal rate of substitution of
leisure for consumption is equal to W (Nicholson, 1992). The interior solution of the
model answers the question of the number of work hours to be supplied by the worker.
An increase in W, holding income constant, makes leisure more expensive.
Therefore, by consuming additional hours of leisure, the worker gives up more in forgone
wages, producing a negative substitution effect with respect to hours of leisure. On the
other hand, since leisure is a normal good, the income effect will be positive. That is, an
increase in the wage rate, W, will increase the consumption of leisure, L, since the person
now feels better off.
Since work and leisure are mutually exclusive ways to spend one’stime, these two
opposite reactions prevent the model from predicting the direction of the change in the
number of hours worked. The ambiguity cannot be solved unless one knows the worker’s
actual labour supply decision. If the substitution effect dominates, the result will be an
increase in the number of work hours supplied. On the other hand, if the income effect
dominates, the number of work hours supplied by the worker will decrease.
Nakamura A. & Nakamura N. (1994) noted that empirical studies have shown that the
income effect tends to dominate for men and the substitution effect, for women. When
non-labour income, V, changes, there is no ambiguity since the income effect operates
alone. Thus, an increase in V will cause an increase in leisure time and a decrease in the
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Iweagu H. E., (2012)
hours worked, and vice versa. A corner solution of the model will occur when the
individual has decided not to participate in the labour force. Economic theory explains
this case through the definition of reservation wage, W* as the measure an individual
places on his/her non-market time.
The reservation wage is the wage that would make a person indifferent between not
working and working that first hour. The value of W* is influenced by his/her tastes and
preferences, the level of non-labour income V, factors influencing the value of one’s time
at home such as the number of children, and marital status. This theory has been
successfully used to explain women’s labour force participation (Rincon, 2007). We
assume therefore that an individual maximizes a well behaved utility function (U) that is
defined over her within-period consumption of commodities (C) and leisure (L), the
model can be expressed formally as
( , , )U U C L X= …………......................................................................................…… (8)
where, X indicates individual and household characteristics such as age, marital status,
ethnicity, etc. The number of children and any other dependents are included in the vector
of individual and household attributes, X. Utility is assumed to be maximized subject to
the budget (income and time) constraint
C WL Y WT+ = + ………………………………………………...............................(9)
where W is the wage rate, Y is non-labour income and T is the total time available. The
individual maximizes a utility function subject to the constraint imposed by the fixed
time T and how to allocate her time to home production, market work and leisure. Thus,
the optimal allocation of time to market work will be determined by the personal and
household attributes as well as on the labour market characteristics. The labour market
conditions determine the costs of a job search and the remunerations of the market work.
The solution to the optimization problem results in the familiar first-order conditions
( , , ) , ( , , )C L
U C L X U C L X Wλ λ= ≥ …………………………................................…(10)
where λ is the marginal utility of income and equation (3) involves, on the one hand, the
demand function for the utility-generating commodities, and, on the other hand, the
optimal allocation of time among leisure, market work, and home production. If the
inequality in equation (3) holds strictly then the individual is not working and L=T, the
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Iweagu H. E., (2012)
wage, RW, such that ( , , )L R
U Y T X Wλ= is the reservation wage below which the
individual will not work; i.e., the individual participates in market work if and only if the
expected market wage is greater than the reservation wage.
3.2 Analytical Framework
The logit function is based on a binary random variable, say Y having a Bernoulli
distribution. We shall therefore relate is as stated by as follows;
Y~ B(1, ᴨ(x)).................................................................................................................(11)
That is, the variable Y takes either the value 1 or the value 0 with probabilities ᴨ(x) or
1- ᴨ(x) respectively. X ϵ Rp is a vector of p exogenous variables and ᴨ: Rp → [0,1] a
real-valued function. In fact, ᴨ(x) represents the conditional probability P(Y=1/x) of
Y=1, given x.
Let r = Y- ᴨ(x), which allows us to rewrite our model as
Y = ᴨ(x) + r.................................................................................................................... (12)
Where r has an expectation of
E(r) = E(Y - ᴨ(x)) = E(Y) - ᴨ(x) = ᴨ(x)- ᴨ(x)=0........................................................... (13)
And a variance of
Var(r) = Var(Y) = ᴨ(x)(1- ᴨ(x)).................................................................................... (14)
For the forthcoming analysis we are going to define the so-called logistic transformation
designated as;
............................................................................................. (15)
Which allows us to specify the probability function ᴨ as
ᴨ(x) = L(xTβ)...................................................................................................................(16)
with a vector β ϵ R of unknown parameters. This specification yields the logistic
regression model with parameter β.
If we denote the inverse function of L, referred to as the logit transformation, by
Logit ᴨ = ln ............................................................................................... (17)
3.3 Model Specification
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Iweagu H. E., (2012)
Since a female is participating in the labour force or not, labour force participation is a
yes or no decision. Hence the response variable, can take only two values. 1, if the
woman is in the labour force and 0 if she is not, Guajati, (2009). Following Afaredi et al
(2011) the study will employ the logit model for both objectives.
The logit model equation takes the following form:
FLF =Xi β + ui, ∀ i =1....n, .......................................................................................(18)
Where FLF represents the female labour force participation, X is a vector of explanatory
variables given as follows: ageyrs1 for age of respondent above 18 years old, martat for
marital status, religion, hhsize for Household size, pov for Poverty rate, lit for Literacy
rate, state, pcexp for Per capital expenditure, and lowage for Lowest wage willing to start
up work with, while β is a vector of parameters or coefficients to be estimated and µ is
the error term.
3.3.1a Model 1: This is for objective one; the logistic regression to ascertain female
participation in rural areas.
logit (yt) = ln 1
=
−
D
D .β0 + β1 ageyrs1 + β2 marstat + β3 religion + β4 lhhsize + β5 pov +
β6 lit + β7 state + β7 pcexp + β7 lowage + µ...................................................................(19)
3.3.1b Model 2: This is for objective one; the logistic regression to ascertain female
participation in urban areas.
logit (yt) = ln 1
=
−
D
D .β0 + β0 + β1 ageyrs1 + β2 marstat + β3 religion + β4 lhhsize + β5
pov + β6 lit + β7 state + β7 pcexp + β7 lowage + .............................................................(20)
Yt in this case is the female labour participation in rural areas.
3.4 Estimation Methods
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We address the first, objective by estimating the model for female labour force
participation and in so doing; we translate the theoretical model into an empirical logit
model. Labour supply or labour force participation in our case, measured at the time of
the survey is entered as a dependent variable in our model. The main objective of
estimating this model is to establish the factors that are more likely to influence a
woman’s decision to participate in the labour market.
3.5 Justification of the model
Since the main aim of this study is to find out the factors which affect the decision
making status of female as it concerns labour force participation, it becomes necessary to
use the Logit model analysis. This is due to the fact that our dependent variable is a
qualitative choice variable with 1 being female participation and 0 non-female
participation. According to Gujarati 2004, in such equations neither OLS nor weighted
least squares (WLS) are helpful. We have to resort to nonlinear estimating procedures
like the logit regression.
Logit analysis produces statistically sound results, by allowing the transformation of
dichotomous variable such as the female labour participation rate to a continuous
variable. Thus, the problem of out of range estimate is avoided. It provides results which
can be easily interpreted and it also gives parameter estimates which are asymptotically
consistent, efficient and normal.
We will use the logistic command so that we see the odds ratios instead of the
coefficients. In this example, we will simplify our model so that we have only one
predictor
3.6 Source of data
The data for the analysis would be the house hold survey employment data for
2010/2011. The data contains 57,372 observations from 37 states and 774 local
governments. The data set contains relevant information such as individual’s
demographic and social characteristics, characteristics of main occupation, total earnings,
sector of employment, number of hours worked and educational attainment. The survey
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Iweagu H. E., (2012)
covers both urban and rural areas and portrays a fair share of the national scope based on
the fact that samples were gotten from all the 37 states of the Federal Republic of
Nigeria. This will help to analyse the role of location on labour force participation.
CHAPTER FOUR
4.0 EMPIRICAL RESULTS
4.1 Presentation of Results
4.11 Logit results for female participation in rural areas
The logit regression result that is aimed at examining the determinants of female labour
participation in the rural sector as stated in objective 1 is presented below;
Logistic regression Number of obs = 781
LR chi2(9) = 45.53 Prob > chi
2 = 0.0000
Log likelihood = -35.044563 Pseudo R2 = 0.3938
Table 1: logit regression for rural female participation
Rural female labour part. Coef. Std. Err. z P>|z|
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Iweagu H. E., (2012)
Age>18 -.0127553 .0215002 -0.59 0.553
Marital status .5660326 .1872876 3.02* 0.003
religion -3.020461 1.190427 -2.54* 0.011
Household size -.6809934 .687956 0.99 0.322
Poverty rate 2.177998 1.00529 2.17* 0.030
Literacy rate -1.036897 1.145607 -0.91 0.364
state -.0139326 .2045547 -0.43 0.666
Per-capita exp. -3.482486 1.145607 -3.04* 0.002
Lowest wage willing to start
up work with
.0155558 .2045547 0.08 0.939
_cons 30.47918 10.06343 3.03 0.002
Coefficients with * denote significance at 95% confidence interval.
Prob > chi2 gives the probability that the null hypothesis is true and as we can see, Prob >
chi2 = 0.0000 shows that we should reject the null hypothesis as there is no statistical
probability that the null hypothesis occurred. Hence the model is statistically significant.
From the coefficients we see that age coefficient is negative with the value -.0127553.
This means that for a one-unit increase in age, we expect a 0.0127553 decrease in the log-
odds of the female participation in urban areas holding all other independent variables
constant. In other words, the exponential of 0.0127553 (e0.0127553 = 1.012836996) gives us
the odds ratio of female labour participation with respect to age, that is a unit increase in
age decreases the odds or probability that a female would participate by about 1.013. This
suggests that the older a female who lives in the urban area is, the less likely is she to
participate in the labour force and the female labour force is likely to increase with the
younger generation. We note however that the age coefficient is not significant with a z-
value of -0.59.
This could be attributed to the fact that women could work at whatever age in rural areas
and therefore would not play a significant role in determining whether women work,
rather other factors could be able to determine this such as marital status. Marital status
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Iweagu H. E., (2012)
has a strong positive effect in determining whether women in rural areas decision to take
up paid jobs. Marital status a coefficient of 0.5660326 that suggest that a unit increase in
every woman that gets married increases the probability that she takes up paid jobs by
about 1.76 (e0.5660326
). This is very surprising as we expect that due to the cultural beliefs
in Africa which is stronger in the villages, marriage should prevent women from taking
up paid jobs as the case maybe. However we understand equally that these rural sectors
are characterised by relatively poor families that the men may not have a choice than to
let their spouses take up paid jobs in order to increase the total household income to meet
the challenges of this new age.
Religion also appears to be one of the significant determinants of female labour
participation as portrayed by our findings, though it suggests a negative relationship. The
results show that a unit increase in women becoming Muslims or traditionalists reduces
the probability that a woman would take up paid jobs by 20.5 (e3.020461
= 20.50074035).
This also implies that regions with more muslims and traditionalists would have a lower
probability for women to participate in the labour force which is expected as these
religious groups give priority to men than women in most aspects of life.
Equally surprising is the fact that household size is not significant given the p-value of
0.322 which is higher than 0.05 considering a two-tailed test at 5% level of significance.
Therefore a unit increase in household size reduces rural female labour participation with
the log-odds ratio of -0.6809934, or the odds or probability of 1.976 (= e0.6809934
). The
negative relationship between household size and female labour participation is however
expected, given that the higher the household the higher the domestic responsibilities for
the woman. Nevertheless, the household size coefficient is insignificant and could be
attributed to the fact that rural areas tend to practice child labour such that even very
young children participate in paid jobs and thereby reducing the number of people
dependent on the woman’s assistance.
The poverty rate has a significant positive impact on female labour participation. The
higher the poverty rate the higher the probability that a woman would take up paid jobs.
In fact our results suggest that for a unit increase in poverty level the probability that a
rural woman would participate in active labour force increases by about 8.829 (e 2.177998
).
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Iweagu H. E., (2012)
This is expected a priori based on the fact that the poorer one is, the more he is compelled
to take up paid jobs, and in fact it becomes more a matter of obligation than choice.
However what is most surprising is that literacy rate has an insignificant impact on
female labour participation. Our results show that a unit increase in literacy rate decreases
the probability that a woman would participate in labour force by about 2.82. This could
only be explained by the fact that most people may not really work according to their
educational qualifications due to the scarcity of available jobs, and on the other hand
some of the jobs do not even necessary need educational qualifications, so at the end of
the day it is no longer a question of being educated or not but other factors could
contribute to female labour participation as we have discussed. The inverse relationship
could be attributed to the fact that if you are too qualified then you may be come
overqualified for the jobs in the rural areas.
Per-capita expenditure was seen as a very strong determined of female labour
participation in rural areas with a z-value of /-3.04/>2 and a low p-value of 0.002.
However what was surprising about this is that it had a negative relationship with female
labour participation. The results show that a unit increase in per-capita expenditure would
reduce the probability that a female participates by the probability of 32.5 (e 3.482486).
While the lowest wage they were willing to start up paid jobs with, was not significant
according to the findings. A unit increase in the amount of wage willing to start up paid
jobs with increases the probability that a female would participate by 1.0157 (e.0155558
).
This is definitely expected a priori given that economic theory projects remuneration as
an incentive to work. So wage willing to start up paid jobs and female labour
participation have a positive direction though it’s not a significant determine in the rural
areas.
The expected value of the log-odds of female participation in rural areas when all of the
predictor variables equal zero is 30.47918, with a very strong significant level. On a
general note we therefore state that the significant determinants of female labour
participation in rural areas at 5% level of significance are; marital status, religion, poverty
rate and per capita income, as has been discussed above.
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Iweagu H. E., (2012)
4.12 Logit results for female participation in urban areas
The logit regression result that is aimed at examining the determinants of female labour
participation as stated in objective 2 is presented below;
Logistic regression Number of obs = 781
LR chi2(10) = 24.62 Prob > chi
2 = 0.0034
Log likelihood = -22.877447 Pseudo R2 = 0.3499
Figure 2: logit regression for urban female participation
Urban female labour part. Coef. Std. Err. z P>|z|
Age>18 .1023051 .0483931 2.11* 0.035
Marital status .686181 .3156097 0.85 0.395
religion .0860819 .9740589 0.09 0.930
Household size -1.000363 .9489482 -1.05 0.292
Poverty rate -2.280907 1.983212 -1.15 0.250
Literacy rate 3.119392 1.222911 2.55* 0.011
state .0368884 .079485 0.46 0.643
Per-capita exp. .5510093 1.761261 0.31 0.754
Lowest wage willing to start
up work with
-.0854893 .2519644 -0.34 0.734
_cons -14.89962 15.52144 -0.96 0.337
Coefficients with * denote significance at 95% confidence interval.
Just like in the regression result for rural we see that Prob > chi2 = 0.0034, this shows us
that we should reject the null hypothesis as there is no statistical probability that the null
hypothesis occurred. We note that there are so many differences in urban female
determination of labour force from the rural. Strangely, while the factors that prove to be
the determinants of female labour participation in rural areas are not those that determine
those in the urban areas. In the urban areas age proves to be a very serious determinant of
female labour participation according to our results which was not the case in the urban
areas. Age has a coefficient of 0.1023051 that suggest that as a woman’s age increases
per unit the log of odds that a woman participates in the labour force is 0.1023051. That
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Iweagu H. E., (2012)
is for a unit increase in age, the probability that a female would participate is 1.108
(=e0.1023051
). The fact that there is a positive relationship between age and female labour
participation is what is expected a priori, because the older one gets all things being
equal, the more educated/qualified she becomes. It is not surprising however that this is
more apparent in urban areas or cities considering their level of exposure and
development.
On the other hand, marriage which was significant in the rural areas appears not to be
significant in the urban areas, which is expected given their level of exposure. A unit
increase in women getting married increases the probability that a woman participates in
labour force by 1.99 (=e0.686181
) but note that this is not significant so we can’t count on it.
However there exist a positive relationship between marriage women and her decision to
participate in the labour force just like in that of the rural sector. This is in line with the
age factor as women tend to get marry as they grow old so we expect a positive
relationship for age and marital status. Just like marital status, Religion and poverty rate
appears not to be significant in the urban regions unlike in the rural areas. However, just
like we explained for rural areas, some of these factors are influenced more in rural areas
by their customs and traditions while something like religion would no longer count in
the urban areas due to their level of westernisation and development, this might not be the
case with the rural sectors. We however expect poverty rate not to be a significant
determinant of female labour participation, as a majority of the inhabitants of urban areas
live above the poverty threshold value, so poverty might not really be the major force of
inducing a woman to work or not.
Household size is not significant in both cases which is rather strange and different from
many other works that show that household size is a determinant of female labour
participation. The fact that it is insignificant in both urban and rural according to our
results only guides us to suggest that household is not a determinant of female labour
participation, so policy makers should take note and pursue more serious determinants.
However the negative coefficient of household size still aligns with a priori expectation
due to the fact that the more the household is the higher would be the woman’s domestic
responsibilities and consequently might hinder her from taking up paid jobs.
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Iweagu H. E., (2012)
Literacy rate shows a significant positive relationship with female labour participation
which is highly expected more importantly on urban areas. Our result indicates that for a
unit increase in women becoming literates or learned, the log of odds that a woman
participates is 3.119392. That is a unit increase in literacy rate increases the probability
that women participate in labour force by 22.633 (e3.119392
). This is very high and makes
sense as the z-value is 2.55 with a very low p-value of 0.011at 5% level of significance.
The state of residence and lowest wage willing to work do not really appear to be female
labour determinants according to our results as they both have a z-value of 0.46 and -0.34
respectively, which is very low compared to the reference point magnitude of 2. In the
urban regions this could be explained by the fact that most urban areas tend to be the
same as development and competition increases, which may expose the women to the
same experiences such that women in different states turn to think alike with respect to
participating in female labour force. While the lowest wage willing to start up with might
not also b significant in urban regions because most employers rather look for those who
can deliver based on their level of qualification, and once they have that, how much one
is ready to start up with becomes a smaller issue to tackle.
Per-capita expenditure just like the other determinants in rural areas doesn’t seem to be a
determinant according to our result. The per-capita variable records a z-value of 0.31 and
a high p-value at 0.734 suggest that it is not a significant determinant of female labour
participation. An increase in per-capita expenditure increases the probability that females
participates by 1.735 (e0.5510093
) which is not significant. On the other hand, the fact that
the coefficient is positive also aligns with expected outcome as per-capita expenditure
might provoke a woman to take up paid jobs. The expected value of the log-odds ratio of
female participation in urban areas when all of the predictor variables equal zero is -
14.89962, however this appears to be insignificant with evidence in the z-value = -0.96
and a high p-value at 0.337. On a general note we therefore state that the significant
determinants of female labour participation in rural areas at 5% level of significance are;
age and literacy rate while the insignificant determinants are marital status, religion,
household size, poverty rate, state, per capita expenditure and lowest wage willing to start
up work with.
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CHAPTER FIVE
SUMMARY, POLICY IMPLICATIONS AND CONCLUSION
5.1 Summary
The study on the determinants of labour force participation was motivated by the interest
to boast female labour participation in rural and urban sectors of Nigeria. This has been a
global fight over the past decade and it is even more significant in developing countries
like Nigeria. The female sensitivity in the supply of labour has been attributed to cultural
and religious beliefs and traditions as most men prefer to keep their spouses home to take
care of domestic activities and children upkeep, while they pay the bills. This study
therefore determines the female labour participation in rural and urban areas separately so
as to understand if this notion of female participation differs in their determinants in the
different sectors.
This therefore leads us to the use of logistic regression that permits us to take advantage
of the log of odds ratio and probability designations of each of these variables. Our
finding aligns with those of existing literature as the determinants in both sectors have
been discussed by other authors as well. However the major surprise is that the
determinants in the rural areas are different from those in the urban regions. According to
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Iweagu H. E., (2012)
the results, marital status, religion, poverty rate and per capita income are significant
determinants in the rural sectors. While poverty rate and marital status have a positive
relationship with female labour participation, religion and per-capita income have a
negative relationship. On the other hand; age, household size, literacy rate, state, and
lowest wage willing to start up with are all not significant in the rural regions of Nigeria.
In the urban regions, age and literacy rate are significant positive determinants of female
labour participation which of course is expected as explained in the previous chapter.
However, marital status, religion, household size, state, per-capita expenditure, poverty
rate and lowest wage willing to start up paid work is not significant. Most of these are
significant in the rural sectors and the only reason for which it might not be significant in
the urban sectors is based on the level of exposure, development and westernisation. This
could not have been noticed if we did a general regression for both urban and rural areas.
5.2 Policy implications
The relevance of this study cannot be overemphasized as it uses more recent data from a
logistic perspective to ascertain the determinants of labour participation in Nigeria, which
is in line with the government’s objective to minimise the marginalisation of the female
population. The fact that marital status is significant in rural areas and not in urban areas
is rather unlike what we expected a priori. The motivation of this study was to crosscheck
the influence marriage has on female labour participation, and our results show that it is
very significant and interestingly, has a direct relationship with female labour
participation. This however maybe associated to the fact that rural families have awoken
to the reality of combining efforts to cover household expenditure and children upkeep,
which is therefore encouraging and means that sensitisation could also be improved on
the unmarried females to take up paid jobs and not only wait for marriage to start work.
According to our findings age is highly significant in the urban sectors and not in the
rural sectors which suggest that age is somehow proportionately related with qualification
of women in the urban sectors which is expected, however the reverse is the case in the
rural sector which suggest that residents in rural areas should keep up improving on their
educational and professional qualifications as they grow old. This can be done through
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Iweagu H. E., (2012)
setting up institutions that could offer such qualifications that may adapt to their
household-duty schedule, so as to induce them to improve on their qualifications even as
they grow old.
Religion appears to have a negative significant effect on female labour participation in
rural areas which suggest that some religious cultures seriously restrict some women into
participating in gainful employment. This is very important when we consider the
government’s objective to improve female participation in labour force. Policy
instrumentalists should therefore find a way of sorting out these religions that negatively
influence participation, to sensitise them and expose them to the benefits of women
participating in gainful employment amongst their negative ones. On the other hand the
fact that religion is not significant only show that these residents have been able to look at
the relevance of a female participating in female labour beyond the religion which further
strengthens our recommendation on the exposure and sensitisation of rural residents to
participate. However based on the dummy regressor for religion the significance for
religion was from the Muslim religion which is not very surprising following their
underlying principles for a female Muslim faithful.
What is most surprising is that household size had an insignificant effect in both rural and
urban sectors that leads us to suggest that most households have found ways of
contending their responsibilities without this affecting the labour force participation of
the woman. However though not significant, household still has a negative relationship
with labour force participation meaning that the higher the household size the lower the
participation in some few cases.
Poverty rate has a significant positive relationship with female labour force participation,
which is expected a priori though it insinuates a very sad situation, stating that the higher
the poverty rate the higher the participation in rural sectors. Though we expect to
improve on female labour participation we cannot infer that we should expect women to
become poor so that they participate, rather it shows us that poverty rate is very high in
rural regions such that they are compelled to work and not under choice. Policy makers
should therefore ameliorate that standards of living in these areas and encourage the poor.
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Iweagu H. E., (2012)
This however is not the case in the urban regions where poverty rate appears to be
insignificant.
Literacy rate further strengthens our argument on age in urban sectors, implying that on
the general sphere as women grow old they get more qualified and hence have access to
jobs, which is not the case with rural areas who are relatively lees qualified in terms of
educational attainment. This only suggests that the government can create a special fund
only for female scholarships in diverse fields in order to boast female labour participation
and set them a par with the men. State also appears to be insignificant in determining
female labour participation in both rural and urban sectors. Per-capita expenditure
however is significant in determining female labour participation in rural areas and this is
expected a priori. Nevertheless we note that there exists a negative relationship between
per-capita expenditure and female labour participation in the rural sectors which show
that richer individuals are unlikely to participate in the labour force as we can assume that
individuals with high per-capita expenditure are mostly relatively richer.
On the other hand per-capita expenditure is not significant in urban regions as most
people are rich and motivated to work not only for the income, but for other factors like
health, growth and development. In rural and urban areas the lowest wage an individual is
willing to work is not significant, which suggest that there are many other factors that
determine if a female would participate in the labour force but her choice of “starting
income” is not a determinant factor.
5.3 Limitations of the study
This research on female labour force participation has been very enriching, however we
encountered some limitations. The household survey data was not easy to come by. It
appears that time series data is made available in most of the data banks like the World
Bank indicators and Nigerian bureau of statistics, but micro data is rare. We however
recommend that all surveys carried out by non-governmental associations and
government associations should be published, the most accessible today is the National
living standard survey which sometimes very long as it occurs every 4 years and most
times not released on time.
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Iweagu H. E., (2012)
5.4 Suggestions for further Research
The logistic investigation that separated the sectors into urban and rural gave us very
interesting results and sets the stage for further research on this topic. The main
suggestion is for other researchers to explore the rural sector determinants, given that our
findings suggest that the determinants of rural female labour force participation differ
from that of urban women. Therefore other methods should be employed with more
national data if possible, to investigate further the determinants in rural sectors of
Nigeria, as their level of participation seem to be lower than in urban sectors.
The significance of marital status in rural areas and not in urban areas, helps to identify
with the hypothesis that married women’s decisions might be influenced by their
husbands. The positive relationship shows that marital status rather favours female labour
participation which contradicts previous research (at least a higher proportion of the
empirical findings), so further studies of this nature should be made to ascertain if the old
ideology of husbands influencing their wife’s participation is a myth today. The study
notes that religion has a negative significant relationship with female labour participation
and therefore earmarks a reference point upon which more research should be carried out
to identify those religions that discourage or restricts women from participating in labour
force.
5.5 Conclusion
In conclusion, we note that the finding of this study is very enriching and contributes to
knowledge significantly. The Nigerian government has as objective to, improve on
female representation nationally and primarily this impact must be felt in the labour
market. The Nigerian government has done a lot over the years to improve female labour
participation but a lot more still needs to be done. The determinants of female labour
participation in the rural sector is mainly marital status, religion, poverty rate and per
capita income are significant determinants in the rural sector, while in the urban sector is
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Iweagu H. E., (2012)
age and literacy rate. This therefore connotes that the determinants in urban sectors are
completely different from that of rural sectors. Researchers, policy analysers, policy
makers, and policy implementers should take this into consideration when designing
policies to improve labour force participation, thereby reducing unemployment rate in the
country.
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