-
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
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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
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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).
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Social and economic disparities, Sindh, Baluchistan and Pakistan
- A comparative study
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
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Huda, et al., 2011
53
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
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Social and economic disparities, Sindh, Baluchistan and Pakistan
- A comparative study
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
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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
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Social and economic disparities, Sindh, Baluchistan and Pakistan
- A comparative study
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
57
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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Social and economic disparities, Sindh, Baluchistan and Pakistan
- A comparative study
58
Fig.2 Depiction of Variables
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Huda, et al., 2011
59
Fig.3 Depiction of Variables
-
Social and economic disparities, Sindh, Baluchistan and Pakistan
- A comparative study
60
Fig.4 Depiction of Variables
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Huda, et al., 2011
61
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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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Social and economic disparities, Sindh, Baluchistan and Pakistan
- A comparative study
66
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