5 social and economic inequality sindh balochistan and pakistan

The Research Journal of Sciences and Technology 2(1&2):49-66 2011, ISSN 2226-0110 The official publication of Faculty of Sciences

FEDERAL URDU UNIVERSITY OF ARTS, SCIENCES & TECHNOLOGY

49

SOCIAL AND ECONOMIC DISPARITIES, SINDH, BALUCHISTAN

AND PAKISTAN - A COMPARATIVE STUDY

1Syed Nawaz ul Huda and

2Farkhunda Burke

1. Department of Geography, Federal Urdu University of Arts, Sciences and Technology, Gulshan Campus,

Karachi. Pakistan.

2. Department of Geography, University of Karachi, Karachi, Pakistan

Abstract

A high degree of internal inequality is a common characteristic of intermediate and less developed countries like

Pakistan. Its comprehension is an essential requisite for amelioration and this study is a pioneering work in the

context of the two provinces i.e. Sindh and Baluchistan, focusing on the inter-relationship of a gamut of factors

to enable the deciphering of comparative status of social and economic development. The study suggests that

ethnicity, which is the basis of administrative delineation in Pakistan, has fostered clan feudalism, and

development policies based on lines of Islamic justice and equity, embodied in the constitution of the country

can make inequalities bearable.

Article Received: 07-01-11, Accepted: 14-06-11

Key words: welfare state, inequality, Sindh, Baluchistan, Pakistan,

1 INTRODUCTION

Disparities cause uncertainty in society. They damage social values and drag the nation to

disaster. Inequalities strangle democracy and trigger dictatorship, igniting problems related to

human wellbeing. Development is the movement from one social state to a higher social state

and concerned with the improvement of social and economic welfare or quality of life (Islam

et al., 2001). Perhaps, rapid economic growth is not the most effective means of achieving

general social progress. One of the greatest dangers in the present situation of development

inequality is its potential for human conflict. This applies to inequality within nations as well

as among them (Smith, 1977). A high degree of internal inequality is a common characteristic

of intermediate and less developed countries like Pakistan.

Well-established socio-economic background is based on the income of any area. Inequality

in terms of income presents a narrow view of overall inequality prevailing in a society, while

the study referred to as social and economic inequality considers the disparities in income and

standard of living (Pandey and Nathwani, 1997).

During recent decades, most of the developing countries have been engaged arduously not

only in nation building processes but also in economic and social development to pull their

people out of the morass of poverty, ignorance, squalor and morbidity (Khanna, 1991). The

explicit engagement of geography with morality and social justice dates from the latter part of

the 1960s (Smith, 1994).

The economic life of any people includes activities of several different orders. As a

minimum, there are always formalized patterns controlling ownership, production,

distribution and consumption. Income and consumption are the most direct measures of

Social and economic disparities, Sindh, Baluchistan and Pakistan - A comparative study

50

living standards. In addition, income refers to the earnings from productive activities and

current transfers. It can be observed as comprising claims on goods and services by the single

or households. In general words, income permits people to obtain goods and services. The

empirical literature on consumption wealth effects intends to answer the question of how

much consumption will increase as a result of an exogenous increasing wealth (Bover, 2005).

The main difficulty for progress in this area is lack of household survey data that contains at

the same, direct measures of asset holdings and consumption.

Several works regarding inequality with special reference to income distribution and poverty

on the economic perspective in Pakistan are on record e.g. those of Bergen, 1967; Azfar,

1973; Naseem, 1973; Khundkar 1973; Alauddin, 1975; Chaudhry, 1982; Mahmood, 1984;

Krujik and Leeuwen, 1985; Krujik, 1986; Krujik, 1987; Ahmad and Ludlow, 1989; Malik,

1992, Ahmad, 2000, Anwar, 2003 and Kemal, 2003. Most of these studies are based on data

from FBS (Federal Bureau of Statistics, Govt. of Pakistan), Household Income and

Expenditure Surveys (HIES) and that of the Government of Pakistan census data.

These studies reveal a declining trend in income (or expenditure) inequality. These studies

mainly focus on the economic point of view, while there is dearth of spatial analysis.

According to the Economic Survey (2004-05), population in Pakistan has grown at an

average rate of 3 percent annually since 1951 to the mid 1980s. During the periods 1985-86 to 1999-2000, population growth reduced to an average rate of 2.6 percent per annum.

Subsequent to 2001, population of Pakistan is growing at an average, further reduced rate of

almost 2 percent annually. A welfare state has been defined in the Webster dictionary as a government that undertakes responsibility for the welfare of its citizens through programs in public health, housing, pensions,

and unemployment compensation, etc. There are a number of empirical studies of how quality of life is linked to demand for public facilities (Rosen, 1974; Liu, 1976; Roback, 1982; Blomquist,

et al., 1988; Mwabu, et al., 1993; Lavy and Germain, 1994; Alderman and Lavy, 1996; Ultee,

2006; Sorensen, 2006; Palme, 2006 and Moro, et.al., 2008).

As an Islamic welfare state, Pakistan in its Constitution provides a guarantee to the nation about

the promotion of social and economic well-being of people (Mahmood, 2007). In a country,

where there are a few monopoly houses who benefit by exploiting the less fortunate or less

influential classes, the existence of social and economic inequalities or disparities are

unacceptable in their intensity, complex in pattern, and persistent in occurrence and by no means

simple. The spatial dimensions of social and economic inequalities in Pakistan now is a prominent

outcome of development strategies reflected in its provision of basic necessities of life essential

for human development and an acceptable quality of life which has been hampered by various

delivery hurdles. UNDP being the pioneer of the National Human Development Report 2003,

(Hussain, et al, 2003) for Pakistan has presented a Human Development Index (HDI). However,

with reference to this aspect, Statistics Division of the Government of Pakistan (FBS, 2004; 2002

& 2001) published socio-economic indicators at district level and social indicators for Pakistan.

PMDG (2004, 2005, 2006, 2009 & 2010) provides valuable guidelines in terms of hunger and

poverty eradication, universal primary education target, enhancement in gender equality and

empowerment of women, child mortality reduction, health improvement, combating HIV/AIDS,

malaria and other diseases, ensuring environmental sustainability, etc.

The purpose of this paper is to decipher the comparative status of social and economic

development of Sindh and Baluchistan in the purview of Pakistan. For formulation of policies

and plans aimed at developing, a suitable operational strategy for minimizing and

eliminating, to the extent possible, such disparities, identification of socio-economically

depressed regions is a prerequisite. For this purpose z-score based standard score additive

model (SSAM) for inequality measurements have been introduced. In the present era,

technological advances have improved the researchers capacity to observe and analyze

Huda, et al., 2011

51

phenomena that occur over micro to macro matrixes. The modification or increased use of

new statistical tools in various disciplines provides support to researchers to increase their

capacity of analysis in their studies. The present study is a pioneering work in the context of the two provinces, Sindh and Baluchistan

of Pakistan, focusing on the varying dimensions of social and economic inequalities in spatial

perspective, based on the inter relationship of a gamut of factors represented by an array of

selected relevant variables. After the identification and delineation of inequality regions and

analysis of their contributory factors, strategies for a more just spatial social order may be

suggested for amelioration of disparities.

2 METHODOLOGY

No project can survive for long if the data produced are not put to proper use and this

is possible by quantitative methods. The traditional method of measuring inequality are

Lorenze Curve, which is closely related to the Gini-Coefficient, Williamsons Coefficient of Variation and computation of the Location Quotient, Schutz Coefficient of Equality and

Theils Index, Joint Count Statistics, etc. However, these are measures employed for the measurement of disparities on a limited scale, i.e. they have the limitation of being methods

of bi-variate interrelationship and are cumbersome. Therefore, in order to undertake a more

comprehensive study based on a wide array of variables the SSAM has been used to arrive at

a composite picture. The present study based on Census 1998 database is followed by two

major steps. (1) Selection of variables and (2) SSAM for disparities.

2.1 Selection of Variables

In regional planning, analysis of QOL has bounded within a range of indicators that

represent components in human well-being. Indicators provide reasons in the context of

quality assurance, to which the following definition can be employed: a specially

selected

measure or attribute that may indicate and point to good or poor quality. (Ader et al., 2001).

While there is an abundance of different types of governments promoting social and

economic welfare which have been suggested in several literatures, none can be considered as

one that would best support the construction of a good set of internationally applicable social and economic indicators (Kalimo, 2005). In the research and development of regional

planning, selection of indicators depends on the purpose of the study and mental level of the

people (Diener, et al., 1995, Diener, and Suh, 1997 and Rahman, et al., 2005).

For the representation of well-being many terms may be used, but the most commonly used

terms are quality of life, standards of living, human well-being and welfare. Due to

unequivocal meaning of those terms, sometimes various problems have been observed

(Veenhoven, 2000 and 2008). In the study of social sciences, it is generally assumed that

individuals behavior is guided by the goal of seeking a higher level of the QOL and that actual behavior should be seen as its reflection. However, in economic research utility

provides an alternative concept to QOL, while psychologists use the term, satisfaction or

happiness. A massive variety of literature is helping promote the study of well-being.

QOL is a multidimensional concept, which has many distinct domains (Hirschberg et al.,

2001). QOL is a broad term that encompasses notions of a good life, a valued life, a

satisfying life, and a happy life (McGregor et al., 2006). In what follows an attempt has been

made to select a set of indicators suitable for showing social and economic disparities. In multivariate analysis, a diversified collection of variables helps to depict the overall scenario of

the study area while their grouping or categorization assists in a comprehensive evaluation of

specific aspects under consideration. (Diener, and Diener2001; Graham, and Felton, 2006 and

Copestake, 2007).


52

Too many indicators that cannot be combined into an overall indicator or a set of sectoral

indicators fail to represent a summary view. At the same time, too few would gloss over

important trends that need to be noted. As a compromise, it has been thought best to pick up

one key indicator to reflect the progress towards each major goal with a few supplementary

indicators to reflect related trends or important components of the major goals. Social

indicators have been grouped under the following main heads:

1. Health and Nutrition (HN)

2. Housing and Environment (HE)

3. Education and Culture (EC)

4. Social Welfare (SW)

5. Urbanization (U)

Similarly, Economic indicators have been categorized as follows:

6. Income, Wealth and Consumption (IWC)

7. Occupational Structure (OS)

8. Agricultural Development (AD)

9. Industrial Development (ID)

and overall study of variables,

10. Composite Social and Economic Inequality (CSEI)

In all, forty-seven variables have been included in the study. A list of the variables along with

abbreviations used in the present study has been given in Table 1.

Table 1

Selected Variables CBR: Crude Birth Rate

HC: Percentage of Public Health Centers / Total Population

H : Percentage of Hospitals / Total Population

BAPHC&H Percentage of Beds available in Public Health Centers and Hospitals / Total Population

D: Percentage of Doctors / Total Population

LHW: Lady Health Workers / Total Female Population

CIV: Percentage of Children Immunized & Vaccinated (Less than 10 years)

SNU: Standard Nutrition Units

HP: Percentage of Houses to Population Age 18 & above

NOH: Percentage of Non-Ownership of Households

ARC: Average Room Congestion

PH: Percentage of Pacca Houses / Total Households

HUE: Percentage of Housing Units Electrified

HUPW: Percentage of Housing Units with inside Potable Water

HUG: Percentage of Housing Units with fuel Gas connection

PO: Proportion of Post Offices / Population Density

HTRA: Percentage of High Type Road / Total Area of the District

HTRP: Proportion of High Type Road Per Thousand Population

HTRTRN: Percentage of High Type Road to Total Road Network

L: Percentage of Literate

PE: Percentage of Primary Educated / Total Literate

M: Percentage of Matriculate / Total Literate

G+: Percentage of Graduates and above / Total Literate

S: Percentage of Schools / Total School Going Age (4-16 years)

ES: Percentage of Enrolled Student / Total School Going Age (4-16 years)

STR: Student Teacher Ratio

Huda, et al., 2011

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SCCH: Percentage of Seating Capacity in Cinema Halls / Population

(Age 10 & Above)

UP: Percentage of Urban Population

PD: Population Density

S&TW: Percentage of Secondary and Tertiary Workers / Total Workers

CC: Percentage of Cognizable Crimes / Population (Age 14 & Above)

PS: Percentage of Police Station / Population (Age 14 & Above)

NM: Percentage of Never Married / Population (Age 18 & Above)

GDP Gross Domestic Product Per Capita

CLAW: Ratio of Cultivable Land per Agricultural Workers

TRH: Percentage of Three Roomed Houses / Total Households

IS: Percentage of Information Services Availed Houses / Total Houses

DAP: Dependent to Economically Active Population

W: Percentage of Workers / Economically Active Population

(Age 10 & Above)

PW: Percentage of Primary Workers / Total Workers

SW: Percentage of Secondary Workers / Total Workers

TW: Percentage of Tertiary Workers / Total Workers

UR: Unemployment Rate

P_H: Productivity per Hectare

P_W: Productivity per Worker

IW_W: Percentage of Industrial Workers to Total Workers

VA_IW: Proportion of Value Added to Industrial Workers

2.2 Standard Scores Additive Model for Disparity Measurements

The identification of broad spatial pattern of inequality requires the derivation of a

single indicator or a restricted set of indicators measuring the major dimensions of the

concept. The SSAM is an easy method for analysis of inequality and other related studies

(Burke, et al. 2006a & 2006b). The derivation of selected variables involves the

transformation of data on individual variables into some kind of standard scores. This can be

achieved in various ways including conversion into ranking and the standardization of the

ranges, but the most common method is to use z-score (Smith, 1973; 1977). A specific

standard i.e., highest value has been selected for each variable in the study area. The Model

has been arranged in steps. For observation i on any variable, the Standard Score (Z i) is given by:

S

XXi Z =i

Where

Xi is the value for observation i

Xi = X Xs X is the value of variables

Xs is the specific standard for each variable

X is the mean of the specific standard

X = n

Xs

n is the number of observations

S is the Standard Deviation


54

S = 1

n

XXs

This model has been applied here to measure inequalities of social and economic parameters.

Firstly, the data has been converted into percentages and units i.e. variables.

Secondly, all selected variables have been arranged in descending order (X).

Thirdly, highest value of each variable has been selected as specific standard for each

variable in the study area (Xs).

Fourthly, the specific standard for each variable has been subtracted from the value of

variables formulated (Xi).

Fifthly, the mean and standard deviation of the set of specific standards for the set of

variables has been calculated.

Finally, Standard Score has been calculated for each variable (Zi).

To remove negativity of Zi the values have been squared. (Zi)2

The Standard Scores Additive Model (SSAM) has been used to develop a Composite Social

and Economic Indicator.

The magnitude of inequality of each set of selected indicators requires the addition of z-score

for each variable in the set. The model is thus:

Ij =

K

i

Zij1

Where

Ij is the magnitude of inequality of the set of indicator for district j Zij is the standard score on variables i in district j K is the number of variables measuring the criterion in question.

District scores on different indicators can thus be directly compared, irrespective of the

number of variables contributing to them. Composite Social and Economic Inequality (CSEI)

for any district will be:

CSEI j =

m

i

Zij1

or in this case

CSEI j =

47

1i

Zij

Where

CSEI Composite Social and Economic Inequality for district j Zij Sum of Standard Score on variables i in district j m is the last variable for district j I is the first variable for district j

3 PROVINCIAL STANDARD AND IDEAL PROVINCIAL INEQUALITY

Comparative analysis depends on a standard or fixed value of a variable, which is the

representative maximum beneficiary in that category. In the present study, all sets of

indicators have been analyzed with reference to the highest/lowest value of each variable.

Highest value for positively trending variables (e.g. percentage of electrified housing units)

and lowest value for negatively trending (e.g. volume of cognizable crimes) has been taken as

the provincial standard for analysis and ranking of districts. After the development of

standard variables SSAM provides a convenient method for calculating magnitude of

Huda, et al., 2011

55

inequality. In the present study the procedure for calculating Ideal Provincial Inequality (IPI)

is as follows:

Where:

IPI =Z i Z s

Z sX 100

S

XXi Z =i(i)

S

XX Z =s

s s

s

(ii)

4 RESULTS AND DISCUSSION

Disparity, socio-economic growth and welfare are related approaches. Inequality mainly rises

due to uneven distribution of resources and development. In addition, increased inequality

may culminate in slackened growth rates. Therefore, growth cannot be sustained without an

appropriate income distribution in the country. Welfare means the comprehensive good of

people considered as an aggregate.

In Pakistan there is a crucial problem of unsound growth over the years, and although

economic growth has remained high sometimes, yet it has failed to improve the living

standards of the poor sector of the society. In order to fulfill the needs of the exploding

population as well as to maintain their well being, sustainable growth is an essential pre-

requisite. Pronounced and prolonged inequality for any income bracket in a country can have

a negative and deprecatory impact on welfare. There are good reasons to focus our attention

on inequality and social welfare from aspects of comprehensive assessment of public policies

and social programs that go beyond an impact on poverty. This realization is important in

order to suggest amelioration policies and has prompted researchers to conduct studies on

income distribution and welfare aspects. Based on results depicted in Table 2, the present

study categorically reveals that Baluchistan is economically and socially more backward

compared to its neighboring province Sindh and the national level.

In its contemporary form, planning arises where communities give way to societies, where

the traditional pattern of social relations, clustered around the extended family, is disrupted

and replaced by a pattern in which the achievement of status, impersonal rules, large

collectivities, and rational administrative organization predominate.

Post independence Pakistan has witnessed, 8 Five Year Plans. The first launched for 1955-60

envisaged 93.52 million PKR, while the allocation in 1993-98 was 752.1 billion. Subsequent

to the 4th

five year plan i.e., for 1970-75, the eastern wing of Pakistan was lost and the funds

were totally for West Pakistan, specifically allocated for development of public sectors. After

independence Government of Pakistan introduced social and economic objectives for the

development of quality of life of the nation on the bases of resources of the country, within

the purview of the 1956 Constitution. The 5th

plan focused on the basic needs of people, i.e.,

nutrition, clothing, health and education (Isani, 2001), while the sixth plan (1983-88) focused

on womens development. The overall objective of the 8th five year plan was once again, enhancement of socio-economic development and well-being in Pakistan (Isani, 2001). The 5

years plans have been quite ambitious with reference to social and economic development but

something has definitely been cankerous as Pakistan is still a feudal dominated country, in-

spite of being an Islamic Republic which seeks the welfare of each and every individual.

Comparative study of indicators pertaining to the provinces of Sindh and Baluchistan to the

national standard has been depicted in Table 2, where highest scores indicate highest

disparities. At the national level, social and economic conditions are better for indicators


56

pertaining to HN, HE, EC and CSEI set of indicators, while Sindh leads in U, IWC, OS, AD

and ID. Baluchistan has shown better position for SW.

Table 2

Standard Scores on Nine Criteria of Social and Economic Inequality and on a Composite

Indicator Pakistan, Sindh and Baluchistan 1998

Indicators IPI Pakistan Sindh Baluchistan

HN 2.04 2.11 2.39 3.74

HE 15.81 20.56 28.16 42.15

EC 6.29 13.77 15.55 18.95

SW 1.03 1.52 1.33 1.03

U 3.98 5.49 4.35 6.88

IWC 4.38 5.41 5.14 10.69

OS 11.83 14.40 12.68 17.10

AD 9.14 29.74 9.14 20.60

ID 5.22 9.50 5.66 16.49

CSEI 40.65 54.05 60.17 88.75

0

50

100

150

200

250

HN HE EC SW U ICW OS AD ID CSEI

PakistanSindhBalochistan

Per

centa

ge

IPI

Indicators

Percentage Variation of Inequality of Standard Scores Above IPI

Pakistan, Sindh and Balochistan - 1998

Fig.1, shows disparities among indicators

Huda, et al., 2011

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Fig. 1 reveals the magnitude of inequalities. Conditions of health and nutrition at the national

level are much better (3.43 percent) while Baluchistan is 83.09 percent backward to IPI. The

percentage variation of inequality of standard scores above IPI is also better in the national

perspective, the level of development being 36.34 and 118.93 percent backward to IPI,

respectively, while Sindh and Baluchistan show greater inequality. Baluchistan has shown an

ideal situation with reference to SW. Sindh depicts higher urbanization, income, wealth and

consumption dynamics, situation of job opportunities, ideal agricultural productivity and

industrial development. Baluchistan has emerged as a more backward province in comparison

to national and Sindh levels. Fig. 2, is a graphical depiction of sixteen selected variables. It

has not been possible to calculate SNU at the national level due to data constraint. (Data of

FATA and F.R. are restricted). Sindh has shown better performance with reference to CBR,

ideal situation with reference to HP and HUE, HUW and HUG values are higher than

national standards. The figures of D, LHWs, CIV, PH and PO show much better performance at their respective national levels. Baluchistan shows comparatively better

performance for PHCs, BAPHC&H with reference to both national and Sindh standards.

Fig. 3 is a graphical depiction of the next sixteen variables. The national standards are highest

for HTRA, HTRP, PE, S and SE. High percentage of cognizable crimes coupled with low

facilities of PS has been recorded for Pakistan. A cause of great national social concern.

Sindh shows better than national performance for HTRTRN, L, M, G+, SCCH, PS, UP and

PD and education facilities have been responsible for high urban population and density of

population. Baluchistan reveals poor performance with reference to national and Sindh

standards except for M, S, STR, CC and NM.

Fig.4 is the graphical representation of the last fifteen variables for Pakistan, Sindh and

Baluchistan. Highest values at the national level have been recorded for S&TW, TRH, TW

and VA_IW. Sindh has shown better than national performance for GDP, while it is a little

less in Baluchistan. The performance of IS, W, PW, SW, P_H, P_W, IW_W is much more

appreciable than national standards. Sindh records lower than national standards. In addition

Sindh records lower than national standard for DAP, TW and UE indicating that dependency

and unemployment are much lower in Sindh. Agriculturally as well as industrially, Sindh is

in a better position. Baluchistan has poor standing with reference to IS and SW. IW_W is a

major cause of its economic and hence social backwardness.

Conclusion

A comparative study of social and economic inequality of Sindh and Baluchistan was

deemed essential as these provinces, although, being richly endowed by natural resources,

strategic location, and historical inertia remain the most backward in terms of development

and resource allocation seems to be lagging behind national standards.

Although, both provinces are contiguous in location, there seems to be a yawning gap in the

standards of living and quality of life of their populace, deeming identification of the

causative factors an essential prerequisite for formulation of ameliorative policies for the

reduction or minimization of disparities. One of the main objectives of this paper, the need of

the hour is to develop these areas in order to bring them at par to the national level and to

make them a viable part of the national setup which is possible by recognition of their

contribution to the national development, of which they have always held great potential.

Ethnicity, which is the basis of administrative delineation in Pakistan, has fostered clan

feudalism, hence the relative levels of development and inequality in the country. The

country needs to develop on the lines of Islamic justice and equity, which will promote

equity, hence make inequalities bearable. It is a country which needs incessant development

in order to support its population at a progressively better standard of living.


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Fig.2 Depiction of Variables

Huda, et al., 2011

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Huda, et al., 2011

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REFERENCES

(FBS) Federal Bureau of Statistics, (2001). Socio-Economic Indicators At District Level

Sindh. Statistics Division, Government of Pakistan, Islamabad.

(FBS) Federal Bureau of Statistics, (2002). Socio-Economic Indicators At District Level

Baluchistan. Statistics Division ,Government of Pakistan, Islamabad.

(FBS) Federal Bureau of Statistics, (2004). Social Indicators of Pakistan-2003. Statistics

Division ,Government of Pakistan, Islamabad.

(PMDG) Pakistan Millennium Development Goals Reports, (2004). Government of Pakistan.





Ader, M., Berensson, K., Carlsson, P., Granath, M., and Urwitz, V., (2001). Quality

indicators for health promotion programmes. Health Promotion International. 16(2): 187-195.

Ahmad, E. and Ludlow, S., (1989). Poverty, Inequality and Growth in Pakistan. The Pakistan

Development Review, 28(4): 831850

Ahmad, M (2000). Estimation and Distribution of Income in Pakistan, Using Micro Data.

The Pakistan Development Review 39:4, 807824.

Alauddin, T., (1975). Mass Poverty in Pakistan: A Further Study. The Pakistan Development

Review, 14(4): 431- 450.

Alderman, H. and Lavy, V., (1996). Household responses to public health services: Cost and

quality tradeoffs. The World Bank Research Observer, 11 (1): 322

Anwar, T. (2003). Trends in Inequality in Pakistan between 1998-99 and 2001-02, The

Pakistan Development Review, 42: 4. 809821

Azfar, J., (1973). The Distribution of Income in Pakistan: 1966-67. Pakistan Economic and

Social Review, 11: 4066.

Bergen, A., (1967). Personal Income Distribution and Personal Savings in Pakistan, 1963-64.

The Pakistan Development Review, 7: 160212.

Blomquist, G. C., Mark C.B. and John P. H., (1988). New Estimates of Quality of Life in

Urban Areas. American Economic Review, 78: 89-107.

Bover, O., (2005). Wealth Effects on Consumption: Microeconomic Estimates from the

Spanish Survey of Household Finances. Madrid, Banco De Espana.


62

Burke, F., Huda, S.N., Hamza, S. and Azam, M., (2006a). 8th October 2005 Earthquake:

Analysis of Foreign Aid. Pakistan Horizon, 59(4): 55-67.

Burke, F., Huda, S.N., Hamza, S. and Azam, M., (2006b). Health Inequalities in the Province

of Sindh - A GIS Perspective. Pakistan Journal of Geography, 16(1/2): 73-88.

Chaudhry, M. G., (1982). Green Revolution and Redistribution of Rural Income in Pakistan.

The Pakistan Development Review, 21(2): 173205.

Copestake, J. (2007). Reconnecting wellbeing and development: a view from Peru.

Introduction and overview. Bath: Wellbeing in Developing Countries Research Group

Diener, E., Diener, M and Diener, C. (1995). Factors predicting the subjective well-being of

nations, Journal of Personality and Social Psychology 69(5): 851-864)

Diener, E., Suh, E. and Oishi, S. (1997). Recent findings on subjective wellbeing, Indian

Journal of Clinical Psychology, 24(1): 24-41

Diener, R. B. and Diener, E. (2001). Making the best of a bad situation: Satisfaction in the

slums of Calcutta., Social Indicators Research, 55: 34-43.

GoP (Government of Pakistan). (1955) First Five Year Plan 1955-60, The Planning

Commission of Pakistan, Islamabad

GoP (Government of Pakistan). (1960) Second Five Year Plan 1955-60, The Planning


GoP (Government of Pakistan). (1965) Third Five Year Plan 1955-60, The Planning


GoP (Government of Pakistan). (1970) Fourth Five Year Plan 1955-60, The Planning


GoP (Government of Pakistan). (1977) Fifth Five Year Plan 1955-60, The Planning


GoP (Government of Pakistan). (1983) Sixth Five Year Plan 1955-60, The Planning


GoP (Government of Pakistan). (1988) Seven Five Year Plan 1955-60, The Planning


GoP (Government of Pakistan). (1993) Eighth Five Year Plan 1955-60, The Planning


GoP (Government of Pakistan, (2005). Economic Survey, 2004-05. Finance Division,

Economic Advisers Wing, Islamabad.

Huda, et al., 2011

63

Graham, C. and Felton, A. (2006), Inequality and Happiness: Insights from Latin America.,

Journal of Economic Inequality 4: 107-122.

Hirschberg, J.G., Maasoumi, E. and Slottje, J.D., (2001). Clusters of Attributes and Well-

being in the USA. Journal of Applied Econometrics, 16(3): 445-460.

Hussain, A., Kemal, A.R., Hamid, I.A., Ali, I., Mumtaz, K. and Qutub, A., (2003). Pakistan

National Development Report-2003: Poverty, Growth and Governance, UNDP, Pakistan.

Isani, U.A., (2001) Higher Education in Pakistan, Unpublished dissertation, National

University of National Institute of Modern Languages

Islam, S., Munasinghe, M., Clarke, M., (2001). Is Long-Term Economic Growth Sustainable?

Evaluating the Costs and Benefits. Centre for Strategic Economic\ Studies Mimeo, Victoria

University, Melbourne.

Kemal, A. R. (2003) Income Distribution Studies in Pakistan and the Agenda for Future

Research. In Human Condition Report 2003. Centre for Research on Poverty Reduction and

Income Distribution (CRPRID), Islamabad.

Khandkar, R., (1973). Distribution of Income and Wealth in Pakistan. Pakistan Economic and

Social Review 11.

Khanna. B.S., (1991). Rural Development in South Asia-2-Pakistan: Policies, Programmers

and Organization. Deep & Deep Publication, New Delhi.

Krujik, H. de (1986). Inequality in the Four Provinces of Pakistan. The Pakistan

Development Review 25: 685-706

Krujik, H. de (1987). Inequality in the Four Provinces of Pakistan. The Pakistan

Development Review 26, 659-672

Krujik, H. de and Leeuwen, M.V. (1985) Changes in Poverty and Income Inequality in

Pakistan during the 1970s. The Pakistan Development Review 24, 407-422

Lavy, V. and Germain, J. (1994). Quality and Cost in Health Care Choice in Developing

Countries. LSMS Working Paper 105. Washington D.C.: World Bank.

Liu, B. (1976). Quality of Life Indicators in U.S. Metropolitan Areas. Praeger, New York.

Mahmood, M. (2007). The Constitution of Islamic Republic of Pakistan-1973. Pakistan Law

Times Publications, Karachi.

Mahmood, Z., (1984). Income inequality in Pakistan An analysis of existing evidence. The Pakistan Development Review, 28: 831-850.

Malik, S. (1992) Rural Poverty in Pakistan. Unpublished Ph.D. Thesis Submitted to the

University of Sussex.

McGregor, P. (2006). Economic growth, inequality and poverty: An analysis of policy in a

two period framework. Journal of International Development, 7(4): 619-635.


64

Moro, M., Brereton, F., Ferreira, S. and Clinch, J. P., (2008). Ranking quality of life using

subjective well-being data. Ecological Economics, 65: 448-460.

Mwabu, G. M., Ainsworth M. and Nyamete A., (1993). Quality of Medical Care and Choice

of Medical Treatment in Kenya: An Empirical Analysis. The Journal of Human Resources,

28: 838-862.

Naseem, S.M., (1973). Mass Poverty in Pakistan, Some Preliminary Findings. The Pakistan

Development Review, 12: 317360.

Pandey, M.D. and Nathwani, J.S. (1997). Measurement of Socio-Economic Inequality Using

the Life-Quality Index. Social Indicators Research, 39: 187-202.

Rahman, T., Ron, C., Mittelhammer, and Wandschneider, P., (2005). Measuring the Quality

of Life across Countries: A Sensitivity Analysis of Well-being Indices, WIDER. Research

Paper No. 2005/06: 1-34.

Roback, J. (1982) Wages, Rent, and the Quality of Life. The Journal of Political Economy,

90(6): 1257-1258.

Rosen, S., (1974). Hedonic prices and implicit markets: product differentiation in pure

competition. Journal of Political Economy, 82: 34-55.

Smith, D. M., (1994). Geography and Social Justice. Oxford, Blackwell.

Smith, D.M., (1973). The Geography of Social Well Being in the United States. New York,

McGraw Hill.

Smith, D.M., (1977). Human Geography: A Welfare Approach. Edward Arnold, London,

UK.

Sorensen, A., (2006). Welfare states, family inequality, and equality of opportunity. Research

in Social Stratification and Mobility, 23(4): 405-411.

Ultee, W., (2006). Problem shifts in the study of welfare states and societal inequalities.

Research in Social Stratification and Mobility, 23(4): 405-411.

Veenhoven, R. (2008). Sociological theories of subjective wellbeing, in Eid, M. and Larsen,

R. (Eds), The Science of Subjective Wellbeing, Guilford Publications, New York, NY: 44-61.

Veenhoven, R., (2000). The Four Qualities of Life: Ordering Concepts and Measures of

Good Life. Journal of Happiness Studies, 1: 1-39.

Huda, et al., 2011

65

Annexure Illustration of SSAM Disparities Application

Step I: Selection of variables for study

Variables Pakistan Sindh Baluchistan

% HP(18) 30.51 31.60 30.38

% NOH 18.82 23.10 13.37

AC 03.10 03.33 02.80

%PH/H 58.50 46.70 14.19

%HUE 70.50 70.08 46.62

%HUW 28.10 37.17 25.31

%HUG 20.20 32.43 09.84

NPO/PD 80.08 08.38 31.00

LHTR/Area 00.17 00.15 00.01

HTR/P 01.01 00.72 00.78

% HTR/TRN 55.40 87.09 21.35

Step II: Selection of Standards among Selected Variables

Variables Standard

Variables

% HP(18) 31.60

% NOH 13.37

AC 02.80

%PH/H 58.50

%HUE 70.50

%HUW 37.17

%HUG 32.43

NPO/PD 80.08

LHTR/Area 00.17

HTR/P 00.78

% HTR/TRN 87.09

Step III: Calculation of Xi

Variables Standard Pakistan Xi = X - Xs (+)

Xs X Xi = Xs X (-)

% HP(18) 31.60 30.51 -10.09

% NOH 13.37 18.82 -50.45

AC 02.80 03.10 -00.30

%PH/H 58.50 58.50 00.00

%HUE 70.50 07.50 00.00

%HUW 37.17 28.10 -90.07

%HUG 32.43 02.20 -12.23

NPO/PD 80.08 80.08 00.00

LHTR/Area 00.17 00.17 00.00

HTR/P 00.78 01.01 -00.23

% HTR/TRN 87.09 55.40 -31.69

X 37.68

S 32.24


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Step IV: Calculation of z-score

Standard Pakistan

Xs X Xi = X - Xs

% HP(18) 31.60 30.51 -10.09 -1.20 1.45

% NOH 13.37 18.82 -50.45 -1.34 1.79

AC 02.80 03.10 -00.30 -1.18 1.39

%PH/H 58.50 58.50 00.00 -1.17 1.37

%HUE 70.50 70.50 00.00 -1.17 1.37

%HUW 37.17 28.10 -90.07 -1.45 2.10

%HUG 32.43 20.20 -12.23 -1.55 2.40

NPO/PD 80.08 80.08 00.00 -1.17 1.37

LHTR/Area 00.17 00.17 00.00 -1.17 1.37

HTR/P 00.78 10.01 -00.23 -1.18 1.38

% HTR/TRN 87.09 55.40 -31.69 -2.15 4.63

K

i

j ZijI1

Note: Value of mean depends on differences of variables and varies

Value of standard deviation variables differences and varies

S

XXi Z =i (Z ) i

2