Trends of income inequality and polarisation in Pakistan for the period 1990-2008.
Touseef-Ur-Rehman, Muhammad ; Mustafa, Usman ; Rashid, Humayun 等
The study aims to examine trends of income inequality and
polarisation in Pakistan, and their impact on rural and urban segments
across all provinces of Pakistan for the period 1990 to 2008.The study
is based on individual level household data of Pakistan for the years
1990-91, 1992-93, 1993-94, 1996-97, 1998-99, 2001-02, 200506 and
2007-08. Income inequality has been estimated using Gini coefficient,
generalised entropy and the Atkinson Index whereas, polarisation has
been estimated with the help of generalised Esteban, et al. (1999) and
Foster and Wolfson (1992) Polarisation Index. The results presented
fluctuating trends. In general, income inequality and polarisation
increased from 1990-91 to 1996-97, decreased till 2001-02, and again
increased till 2007-08. Previous studies mainly focused on the
difference between inequality and polarisation ignoring key features of
distributional change appearing due to changes in polarisation. This
study found that contrary to theoretical expectation, measures of
polarisation do not present very different results from the measures of
inequality. The study attempted to enhance understanding of when social
forces contribute to economic inequality, polarisation, poverty, social
tension, extremism and radicalisation in Pakistan.
JEL Classification: C23, D31, D63,13
Keywords: Polarisation, Inequality, Income Distribution, Welfare,
Poverty
1. INTRODUCTION
Trends of income inequality and polarisation previously were
calculated by Arshad, et al. (2008) in Pakistan for the period of 04
years from 1992-93 to 2001-02, using Gini-coefficient and Bossert and
Schworm (2006) measures respectively. Empirical analysis of polarisation
has huge importance in the economic policy making. However, polarisation
has been less probed, rather un-explored phenomenon. So far only a
handful studies have been conducted on this topic and most of the
covered western countries with an exception of India. This research area
appears to be unexplored in Pakistan, except for a few studies which led
to the foundation for the present study.
Problem statement is that in spite of handsome economic growth
rates and the rate of industrialisation, income distribution continues
to deteriorate in Pakistan and why masses have not been able to enjoy
the benefits of economic development. For social welfare analysis,
issues like inequality, poverty, per capita income and trickle-down
effect need to be addressed. Much empirical studies have been conducted
on these issues however it appears that per capita income is not
appropriate measure of the welfare in any economy because it hides a
wide range of fluctuation behind the score/value. However, still it is
treated as one of the foremost indicator of the wellbeing of the
economy.
Despite of the recent and more sophisticated tools to assess
effectiveness of economic growth, development and economic advancement
the historical importance and simplicity of per capita income as a
measure of the average level of prosperity in an economy still stands
valid.
In Pakistan, per capita income in Dollar terms has increased from
$586 in 2002-03 to $10,466 in 2008-09. Real per capita income in rupee
terms has also increased by 2.5 percent as compared to 0.3 percent
growth last year (Government of Pakistan, , 2009). However, In Pakistan
30 to 35 percent of the population is living on one dollar a day as
reported by World Bank (2002). For these people, it is very hard to
provide three square meals a day for family members.
At the same time, phenomena such as "the disappearing middle
class" or "clustering around extremes" do not appear to
be easily captured by standard measures of inequality such as the Gini
coefficient. It is to characterise such phenomena that Esteban and Ray
(1994), Foster and Wolfson (1992), Wolfson (1994), Tsui and Wang (1998),
Esteban et al., (1999) have proposed alternative indices of
polarisation. These indices seek evidence for clustering in the
distribution of personal income at the lower and upper ends. It is
claimed that, at least in theory, they represent a major departure from
standard measures of inequality.
It has also been discovered that high inflation rate deteriorates
income distribution. However, inflation may be a positive indicator for
macroeconomic and fiscal stabilisation in an economy which are also
pre-requisite for economic growth. Therefore, changes in food prices are
used as a determinant of income inequality. Inflation rates were at 7.9
percent in 2005-06 [Pakistan (2009)] and as of 2010-11 it was 14.1
percent. The study at hand attempts to answer a critical question
whether economic growth trickles-down to the poor and impact on income
distribution.
In Pakistan a number of attempts have been made to estimate the
income or expenditure inequality using the Household Income and
Expenditure Survey (HIES) data. The debate on trends in income
inequality during the 1990s, an era of stabilisation and structural
adjustment has been wide-ranging in Pakistan. However, lesser attempts
have been made to explore the extent of polarisation in Pakistan.
Polarisation is a phenomenon that has attracted much attention in recent
past. Polarisation refers to the situation where middle class gets
clustered towards the poles or in other words the population based on
income distribution gets clustered to one or the other income extremes.
It has been observed that, polarised societies are prone to competitive
rent-seeking activities and will have difficulty agreeing on public
goods such as infrastructure, education and good policies [Bossort, et
al. (2007)]. In recent years it has been agreed upon that income
inequality and polarisation capture different features of distribution
and can even move in opposite directions.
Existing measures of polarisation have been applied empirically in
many countries. Polarisation of income distribution and its causes have
been studied in Spain by Gradin (2000, 2002), in Italy by
D'Ambrosio (2001), and in China by Zhang and Kanbur (2001). Duclos,
Esteban and Ray (2004) estimated polarization for income distributions
of 21 countries. Seshanna and Decomez (2003) study polarisation across
various countries in the world. Ravallion (1997) estimate Foster and
Wolfson calculated polarisation indices for 67 developing and
transitional economies. Aighokan (2000) briefly alerts about the
possible problem of Polarisation in Nigeria. Leonid (2002) estimated the
regional inequality and polarisation in Russia. Arshad and Idrees (2008)
briefly introduced trends in Polarisation in Pakistan.
The present study focuses on the patterns and trends of regional
inequality and polarisation in Pakistan from 1990 to 2008. Study
calculates these trends in overall Pakistan, its urban and rural segment
and in the four (04) Provinces of Pakistan. For each component, the
study derives per capita real consumption expenditures from the
HIES/PIHS/PSLM data. Objectives of this study are as follows:
(i) To explore the trends of income inequality and polarisation in
Pakistan overall and its urban and rural segments during 1990 to 2008.
(ii) To measure the relationship of income inequality and
polarisation in all the provinces during the study period.
The study proceeds as the data set, unit of measurement and the
methodologies are discussed in Section 2. Empirical analysis of Pakistan
and its rural and urban segments are presented in Section 3, whereas
Section 4 highlights the study results of Provinces. Section 5concludes
the study.
2. FRAMEWORK OF STUDY
The choice of data set, units of measurement and the methodologies
used for the measurement of income inequality and polarisation are
discussed in this section.
2.1. Data
The data set of present study has been collected from various
issues of Household Integrated Economic Survey (HIES) (1) conducted and
published by Federal Bureau of Statistics (FBS), Government of Pakistan.
Statistics show that during all the years more than 60 percent of the
sampled households belong to rural areas of Pakistan (Table B1). The
province wise distribution shows that the maximum number of households
belongs to Punjab, followed by Sindh, Khyber Pakhtunkhwa (KPK) (2) and
Balochistan (Table B2). In 1998-99 Household Integrated Economic Survey
(HIES) was merged with Pakistan Integrated Household Survey (PIHS), and
the interrogation methodology was revised and split in two modules
separately for male and female respondents. The rationale behind this
sectioning was that none of either males or females is aware of all
income and expenditure details. In 2005-06, PIHS was replaced with the
Pakistan Social and Living Standards Measurement Survey (PSLM). PSLM
incorporated the HIES as well as the Core Welfare Indicators (CWIQ). The
survey consists of all urban and rural areas of the four provinces of
Pakistan defined as such by the various population censuses concerned.
The household and individual-level data used in the instant study has
been collected from eight rounds of HIES (Table B3). For the purpose of
this study, household and individual level data has been drawn from HIES
1990-91, HIES 1992-93, HIES 1993-94, HIES 1996-97, PIHS 1998-99, PIHS
2001-02, PSLM 2005-06 and PSLM 2007-08. Therefore, the data used in this
study combine sight rounds of micro data from household surveys to make
inference the trends in income inequality and polarisation in Pakistan.
2.2. Choice of Income Units
How the study use the data to manipulate the requisite outcome.
There can be many options in the HIES/PIHS/PSLM data for the choice of
income unit, i.e. aggregate household, per capita household income, or
per-adult equivalent. The aggregate household covers the household as a
single unit and thus ignores household size. Per capita household
incorporates household size but gives same weight to all household
members. Whereas 'adult equivalence' is a method based on the
calories required by the males or females in different age groups. There
is much literature on adult equivalence. Jamal (2006) has given a
summary of different adult equivalence scales used in different studies
for Pakistan. Among them the most acceptable is the calorie intake
approach.
Income does not always necessarily reflect the true living
standards. The households with high per capita income do not always
necessarily enjoy high living standards. Under such cases, consumption
expenditure can be a better indicator of living standards. Moreover
there are less chances of under reporting in consumption expenditures as
compared to income levels. In the present study it was, therefore, felt
worthwhile to measure consumption inequalities.
2.3. Methodology
The study calculates trends in income inequality by two
Lorenz-consistent inequality measures, namely the Gini coefficient
[Cowell (1995)] and the Generalised Entropy [Shorroks (1984)]. The Gini
coefficient is used because it is the most commonly referred to measure
of inequality and, therefore, can provide good benchmarking values. The
Generalised Entropy (GE) measure is used as it will introduce some
measures discussed later in this study. The Atkinson index of income
inequality is also used in the subject study. The study also measures
and discusses polarisation, which is a concept distinct from income
inequality as elaborated by the Generalised Esteban, et al. (1999) and
Foster and Wolfson (1992).
3. EMPERICAL ANALYSIS AT NATIONAL LEVEL
3.1. Trends in Overall, Urban and Rural Income Inequality in
Pakistan at National Level
Gini coefficients, Generalised entropy and Atkinson measure of
inequality for Pakistan as a whole as well as for urban and rural areas
of Pakistan have been estimated and explained in this section (Table
Al). Gini coefficient of overall Pakistan increases with the sluggish
pace from 1990-91 to 1998-99 almost 05 percentage points i.e from 0.298
to 0.343. Later, from 1998-99 to 2005-06 it declines 04 percentage
points i.e. 0.343 to 0.306 followed by an increasing trends in
2007-08vide Figure 3.1. The results of Gini coefficients as calculated
by Jamal (2006) also show that Gini increases from 199091 to 1998-99 and
later on it decreases till the study year 2001-02. Pakistan, Government
of (2001), FBS also explain that Gini coefficient decreases from 1998-99
to 2001-02.
[FIGURE 3.1 OMITTED]
The overall Generalised entropy increases with an energetic pace
from 1990-91 to 1996-97 almost 20 percentage points i.e. from 0.177 to
0.377. Subsequently from 199697 to 2005-06 it decreases 19 percentage
points i.e. 0.377 to 0.182 followed by an increasing trends in 2007-08.
The Atkinson measure of inequality shows the same trend as the
generalised entropy but with lesser variation. It increases from 1990-91
to 1996-97. According to World Bank (2002) for the same time period
household income inequality rose from 0.26 to 0.47 Gini points; and the
dynamics are similar to this study. After that from 1996-97 to 2005-06
it decreases.
The measures of inequality in Urban Pakistan illustrate that all
the inequality measures increases from 1990-91 to 1992-93 followed by a
decreasing trend in 1993-94. After that inequality increases till
1998-99 as shown by all measures. Afterward the urban inequality
decreases till 2005-06 but it increases swiftly in 2007-08 see Figure
3.2.
[FIGURE 3.2 OMITTED]
The measures of inequality in Rural Pakistan illustrate that all
the inequality measures increases from 1990-91 to 1993-94 with the
sluggish pace followed by a dynamic pace in 1996-97. After that income
inequality decreases in 1998-99 with an active pace followed by a
lethargic pace in 2001-02. After that the rural inequality increases
till 2005-06. After that the rural inequality increases till 2007-08
vide Figure 3.3. The rural Pakistan shows the different pattern with
more deviations. It is also observed that there is very high level of
income disparities in the year of 1996-97, in which there is a very high
level of income heterogeneity and income disparities which is
exceptional.
[FIGURE 3.3 OMITTED]
Pakistan (2001) FBS show that overall, urban and rural Gini
coefficient increases from 1992-93 to 1998-99. World Bank (2003) also
indicates the same results in overall and urban Pakistan whereas, rural
poverty decreases very minor from 1992-93 to 1998-99. Arshad, et al.
2008 also concluded that from 1992-93 to 1998-99 the overall, urban and
rural income inequality increases whereas, from 1998-99 to 2001-02 it
decreases. The present study also shows the similar trends as above
cited studies indicate.
One possible explanation for the results could be that rural
incomes are more human labour based than urban incomes. That is why
movement from household based data to persons based data has reduced the
value of Gini coefficients more in rural areas than in urban areas. In
other words high income households in rural areas are those which have
more people living in those households and low income households are
those which have less people living in them. That is why when incomes
were re-divided on persons or per capita basis the inequality fell as
high incomes of larger families were divided among more people and small
incomes of smaller households were divided among people living in
smaller households [Ahmed (2000)].
Another aspect is that the floods of 1992-93 had severe effect in
the rural areas. The effects of destructive floods of 1992-93 were
eliminated in year 1996-97 (Table Al). Consumption of rural population
especially agricultural dependent persons went up again in rural areas.
Secondly, the government after floods of 1992-93 gave special attention
to the agriculturists [Arshad, et al. (2008)].
In urban areas on the other band, huge profits of stockiest,
importers and constructors were eliminated. These reversed the situation
of inequalities in urban and rural segments of the country. Increasing
trends in inequalities are recorded till 1998-99. This period is
critical with reference to the Structural Adjustment Programme. Kemal
(2003) also concluded that "overall poverty and inequality
increased during the adjustment phase" [UNDP Pakistan Report
(2009), Brief-3],
The year of 1996-97 is the period of maximum inequality in overall
as well as in rural Pakistan, whereas, 1998-99 was the period of maximum
inequality in urban Pakistan. This was the period during which Pakistan
opted for nuclear explosions. As an after effect, many developed nations
imposed sanctions on Pakistan by stopping foreign aid and other
assistance. As a result poor segment of the society got affected
adversely and thus inequalities rose in Pakistan and its urban segment.
These statistics indicates that the sanctions of 1998-99 had more
adverse effects on low-income groups of urban Pakistan, and thus reduced
their consumption considerably deteriorating consumption inequalities in
overall Pakistan. Urban areas saw more adverse effects due to the fact
that most people of urban areas are employed in service departments and
multinational companies, which dropped their investments. Prices of
daily food items rose drastically and thus adversely affected the
consumption levels of urban citizens. On the other hand, as people of
rural areas mainly depend upon agriculture and most of them are not
purchaser of major food items such as rice, wheat, etc., from markets,
so the inequality level of low income groups did not significantly
affect the rural areas of Pakistan.
3.2. Trends of Overall, Urban and Rural Polarisation Measures in
Pakistan at National Level
The estimation of polarisation calculated and described by two
different methods i.e., Generalised Esteban, et al. H 999) and Foster
and Wolfson (1992) in Pakistan and its rural-urban segments in this
section (Table Al). The trends of polarisation in Pakistan estimated by
Arshad, et al. (2008) using the Bossert-Schworm measure (2006) and finds
the same result as calculated by Foster and Wolfson (FW) measure of
polarisation in the present study. While, Generalised Esteban, et al.
(EGR) measures show a different results.
[FIGURE 3.4 OMITTED]
Arshad, et al. (2008) estimates that polarisation decreases from
1992-93 to 199697 and then it increases from 1996-97 to 1998-99 followed
by a decreasing trend in 200102 in overall, urban and rural Pakistan.
The identical results in the current study are also shown by the Foster
and Wolfson measure in the same time period (Table Al). The estimation
of overall polarisation by Generalised Esteban, et al. (1999) indicates
that there is a consistent increase till 1996-97 and then it decreases
with the same pace. Whereas, the Foster and Wolfson measure of
polarisation shows more fluctuations as presented above in Figure 3.4.
The trends of urban polarisation from 1990-91 to 1992-93 increased
in urban Pakistan by a dynamic pace as estimated by either of the two
measures of polarisation. This increasing trend continues in urban
Pakistan as shown by the measure of Foster and Wolfson while,
Generalised Esteban et al., show a declining trend. Then from 1996-97 to
1998-99 the urban polarisation increased as shown by both measures.
Later on it decreases till the end of the study period (Figure 3.5).
[FIGURE 3.5 OMITTED]
The rural polarisation explains a very steady trend over the study
years. First it increases from 1990-91 to 1996-97 as shown by
Generalised Esteban, et al. (1999) measure whereas, Foster and Wolfson
measure shows an opposite trend in the same study period. Afterward,
from 1996-97 polarisation measure of Generalised Esteban, et al. (1999)
decreases till 2005-06 while, Foster and Wolfson measure shows a
contrary trend (Figure 3.6).
[FIGURE 3.6 OMITTED]
The increasing trend of polarisation with the dynamic pace from
1990-91 to 199293 indicates that the middle class weakened due to the
adverse effects of flood in 199293. After that from 1992-93 to 1998-99
polarisation increases with the sluggish pace. The rising trend in the
later years shows that the middle class strengthens over the years with
little fluctuations till 1998-99. Afterward, polarisation decreases with
a dynamic pace from 1998-99 to 2005-06. This declining trend is observed
mostly by all the polarisation measures. This decline in polarisation
has lot of factors involved i.e. helping of world's economics
giants in favour of Pakistan because of fight against terrorism, the
rescheduling of loans etc. Furthermore, the government of this period
has also worked a lot on poverty alleviation programmes like the
commencement of Poverty Reduction Strategy Paper (PRSP) collaborated
with the international agencies aiming to help poverty alleviation in
Pakistan and improving the factors involved in social indicators. Due to
increase in tax base by the present government, the burden of tax was
somewhat shifted to companies and industrial sector as compared to the
salaried class, which helped in strengthening of middle class [Arshad,
et al. (2008)].
3.3. Trends of Income Inequality vs. Polarisation of Overall,
Urban and Rural Pakistan
The trends of income inequality and polarisation in overall, urban
and rural Pakistan have been explained in detail in Sections 3.1 and 3.2
respectively. In this sections, an attempt has been made to correlate
the two concepts. To begin with, it must be understood that there is a
wide difference between the concept of polarisation and income
inequality. Income inequality looks at the distribution of income among
all income units while, polarisation focuses on the strengthening or
weakening of middle class. So the magnitudes of these measures are not
comparable at all. The only significance is of their mutual trend. The
estimates show that the Gini coefficients, Generalised Esteban, et al.
(1999) and the Atkinson measures have approximately same trend whereas,
Generalised entropy and Foster and Wolfson measures shows the different
pattern. Three features are immediately apparent from the measure of
income inequality and polarisation (Table A1 and Figures 3.1 and 3.4).
First, the overall trend for both inequality and polarisation measures
increases but at substantially different rates. Second, although there
is an overall upward trend, this is not uniform, from 1998-99 to onward,
inequality and polarisation has actually declined. Third, the
distinction between the three inequality measures is greater than the
two polarisation measures.
Figures of urban Pakistan illustrate that all the measures have a
consistent trend in the study period. The magnitude of the fluctuations
is approximately similar as shown by all the measures of income
inequality and polarisation. In case of urban Pakistan, the result of
income inequality and polarisation shows that from 1990-91 to 1992-93 it
increases followed by a decreasing trend from 1992-93 to 1996-97 except
the Foster and Wolfson measure. The result shows that the estimates from
1996-97 to 1998-99 increased followed by a decreasing trend till the end
of the study period. Whereas the Foster and Wolfson polarization measure
shows a different trend as compare to other measures.
This proves that decreasing inequalities do not ensure decreasing
polarisation. As from 2001-02 to 2005-06 all the inequality measures
decreases, while the Foster and Wolfson measure of Polarisation
increases. After that from 2005-06 to 2007-08 all the measures increases
(Figure 3.2 and 3.5). Though inequalities have increased from 200102 to
2007-08 still the proportion of middle class has increased. The
dispersion in incomes even in the middle-income groups can increase or
there may be a wider gulf in the incomes of the lesser than before
proportion of people at the poles.
Three features are revealed by the results of inequality and
Polarisation measures. First, the overall trend for both inequality and
polarisation measures increases but at substantially different rates.
Second, although there is an overall upward trend, this is not uniform,
from 1998-99 to onward inequality and polarisation has actually declined
and from 2001-02 to 2007-08 it increases. Third, the distinction between
the three inequality measures is greater than the two polarisation
measures (Figure 3.3 and 3.6).
Since the rural population accounts for more than 65 per cent of
total population [Pakistan (2007)] it is worthwhile, to compare the
measures of inequality and polarisation for rural Pakistan. Again, the
Generalised Esteban, et al. (1999) exhibits a similar pattern to the
Gini coefficients. This time, Foster and Wolfson index and Atkinson
index have the slightest increase during the whole period and they show
different patterns in 199697, 2005-06 and 2007-08 from other measures.
The Generalised entropy measure rises much faster than the Gini
coefficients, suggesting the different sensitivities of these two
measures to changes in different parts of the distribution. Because of
its sensitivity to the median value, the Foster and Wolfson index may
fluctuate more rapidly when the median value and its associated group
change. But an important aspect is that on the whole, polarisation and
the inequality measures agree on the trend over the sample period.
4. COMPARISON OF THE TRENDS OF INCOME INEQUALITY AND POLARISATIONIN
ALL PROVINCES OF PAKISTAN
In this section the study compared the trends of income inequality
and polarisation of all the provinces over the study period. The trends
of income inequality and polarisation in all the Provinces have been
depicted in detail in previous section. The main focus of this section
is a comparison of income inequality and polarisation in all provinces.
The estimates of income inequalities and polarisations of Punjab
have been presented and explained in Figures 3.7 and 3.8 respectively.
The Gini coefficients, Generalised entropy, Atkinson and Generalised
Esteban, et al. (1999) measures show approximately the same trend
whereas, Foster and Wolfson measure differs from other measures in the
period from 1993-94 to 1998-99. Three features are immediately apparent
from Figures 3.7 and 3.11. First, the overall trend for both inequality
and polarisation measures increases but at substantially different rates
till 1996-97 except the Foster and Wolfson measure. Second, although
there is an overall upward trend, it is not uniform, from 1998-99 to
onward inequality and polarisation actually decline. Lastly, the
distinction between the three inequality measures is greater than the
two polarisation measures.
[FIGURE 3.7 OMITTED]
[FIGURE 3.8 OMITTED]
The trends of income inequality and polarisation in the province of
Sindh are illustrated in Figures 3.9 and 3.10. The Gini coefficients,
Generalised entropy, Atkinson and Generalised Esteban, et al. (1999)
measures show approximately the same trend whereas, Foster and Wolfson
measure differs from other measures in the period from 1993-94 to
1998-99 and from 2005-06 to 2007-08.
[FIGURE 3.9 OMITTED]
There are two phases first, the trend for both inequality and
polarisation measures increases but at substantially different rates
till 1998-99 except the Foster and Wolfson measure. Secondly, from
1998-99 to onward inequality and polarisation has decreasing trends.
Lastly, these measures increase in 2007-08 except Wolfson measure.
[FIGURE 3.10 OMITTED]
The trends of income inequality and polarisation in the province of
Khaber Pakhtunkhwa are presented and explained by the help of Table A2
and Figures 3.11 and 3.12. Gini coefficients, Foster and Wolfson and
Generalised Esteban, et al. (1999) measures have the approximately same
trend whereas, Generalised entropy and Atkinson sows the similar trends.
All the measure shows the cyclical trends, however there magnitude and
pace is different. Due to cyclical trends there are many phases however,
looking at the trends it is obvious that as the inequality increases
polarisation also increases.
[FIGURE 3.11 OMITTED]
[FIGURE 3.12 OMITTED]
Figures 3.13 and 3.14 illustrate the trends of inequality and
polarisation in the province of Baluchistan. Gini coefficients, Atkinson
and Generalised Esteban, et al. measures have the approximately same
trend whereas, Generalised entropy and Foster and Wolfson measure
illustrate the different trends. Generalised entropy is a measure which
shows the greater magnitude of the fluctuations. It shows that there are
three phases. In first phase Inequality and polarisation measure as Gini
coefficients, Atkinson and Generalised Esteban, et al. (1999) increases
till 1996-97 indicating that as the inequality increases the middle
class become week. From 1996-97 to 1998-99 the inequality decreases by
strengthens the middle class. In the last study years inequality and
polarisation increases again.
[FIGURE 3.13 OMITTED]
[FIGURE 3.14 OMITTED]
5. CONCLUSION
The main purpose of this study is to calculate the trends of income
inequalities and polarisation in Pakistan as a whole and its urban-rural
segments as well as in its four provinces. The calculations of the study
show that Pakistan is fairly optimistic in terms of its distribution of
income.
The highest level of inequity is seen in Sindh and lowest level of
inequality is seen in Baluchistan. The fluctuation ratios in rural
Pakistan are more than in urban Pakistan indicating a very important
phenomenon in rural versus urban Pakistan i.e. the rural incomes are
more human labour based than urban income. In other words high-income
households in rural areas are those which have greater number of family
members and low income households are those which have less family
members. Therefore, when re-divided, income among persons or on per
capita basis the inequality fell as high incomes of larger families are
divided among larger number of people and small incomes of smaller
households are divided among smaller number of people.
The same phenomenon is observed in all provinces of Pakistan but a
bit higher in Sindh and Khyber Pakhtunkhwa. The overall trends in
inequalities and polarisation in Pakistan and its provinces are varying
i.e. from 1996-97polarisation has increased sharply. The trends have
reversed during 2001-02 and again polarisation declines during this
period. In general 1998-99 is the period of maximum polarisation in all
segments of Pakistan. In Brief, although the two polarisation measures
are theoretically different from standard inequality measures,
empirically the new measures of polarisation do not give us very
different results from the standard measures of inequality. Simply
looking at the trends of these measures will not help us capture the
distinctive concerns about polarisation versus increasing inequality in
Pakistan.
Moreover, the study also concludes that there is no trickle-down
effect of the growth rate and the inequality moved upward or downward
during the high growth rate years as it stirred in 1996-97 up and
2001-02 down. High inflation rate play an important role to enlarge the
gap between rich and poor. Inequality increase briskly as the inflation
rate goes in two digits indicating that the inequality is growing in the
era of the present Government.
APPENDIX "A"
Table A1
Trends of Income Inequality and Polarisation of Overall, Urban and
Rural Pakistan
Inequality Polarisation
Years Description Gini GE Atk EGR FW
1990-91 Overall 0.298 0.177 0.077 0.067 0.112
Urban 0.324 0.210 0.090 0.073 0.122
Rural 0.267 0.135 0.061 0.061 0.104
1992-93 Overall 0.321 0.254 0.098 0.072 0.114
Urban 0.360 0.272 0.112 0.081 0.135
Rural 0.287 0.226 0.083 0.065 0.103
1993-94 Overall 0.325 0.251 0.098 0.073 0.115
Urban 0.340 0.224 0.097 0.078 0.137
Rural 0.293 0.243 0.088 0.066 0.100
1996-97 Overall 0.339 0.377 0.123 0.078 0.108
Urban 0.337 0.271 0.104 0.079 0.127
Rural 0.351 0.618 0.160 0.082 0.095
1998-99 Overall 0.343 0.248 0.103 0.078 0.126
Urban 0.392 0.306 0.129 0.091 0.156
Rural 0.262 0.126 0.058 0.058 0.105
2001-02 Overall 0.304 0.189 0.081 0.070 0.116
Urban 0.352 0.252 0.106 0.081 0.131
Rural 0.248 0.108 0.050 0.056 0.100
2005-06 Overall 0.306 0.182 0.079 0.069 0.120
Urban 0.333 0.202 0.090 0.075 0.138
Rural 0.254 0.125 0.055 0.058 0.101
2007-08 Overall 0.316 0.200 0.086 0.072 0.123
Urban 0.348 0.242 0.103 0.079 0.140
Rural 0.270 0.134 0.061 0.061 0.106
Source: Calculated by author from various issues of HIES/ PIHS/ PSLM.
Table A2
Inequality and Polarisation Measures of all the Provinces of Pakistan
Years
Ineq. and Pol
Provinces Measures 1990-91 1992-93 1993-94 1996-97
Punjab Gini 0.297 0.326 0.334 0.348
GE 0.179 0.271 0.275 0.432
Atk 0.077 0.102 0.105 0.134
EGR 0.067 0.075 0.076 0.078
FW 0.114 0.118 0.118 0.107
Sindh Gini 0.319 0.336 0.336 0.332
GE 0.194 0.237 0.244 0.274
Atk 0.085 0.099 0.100 0.104
EGR 0.071 0.076 0.075 0.075
FW 0.123 0.121 0.125 0.119
KPK Gini 0.238 0.272 0.248 0.286
GE 0.112 0.226 0.141 0.298
Atk 0.050 0.082 0.058 0.097
EGR 0.054 0.061 0.056 0.065
FW 0.084 0.081 0.088 0.089
Balochistan Gini 0.249 0.248 0.278 0.290
GE 0.106 0.131 0.182 0.284
Atk 0.050 0.056 0.072 0.093
EGR 0.056 0.056 0.065 0.067
FW 0.103 0.097 0.107 0.093
Years
Ineq. and Pol
Provinces Measures 1998-99 2001-02 2005-06 2007-08
Punjab Gini 0.348 0.300 0.304 0.317
GE 0.257 0.169 0.181 0.191
Atk 0.106 0.075 0.078 0.084
EGR 0.080 0.068 0.068 0.072
FW 0.129 0.121 0.119 0.128
Sindh Gini 0.366 0.352 0.331 0.343
GE 0.280 0.277 0.211 0.258
Atk 0.116 0.111 0.092 0.105
EGR 0.083 0.080 0.075 0.077
FW 0.138 0.126 0.129 0.126
KPK Gini 0.284 0.233 0.259 0.262
GE 0.165 0.103 0.123 0.134
Atk 0.072 0.047 0.056 0.059
EGR 0.064 0.054 0.059 0.059
FW 0.104 0.088 0.102 0.097
Balochistan Gini 0.233 0.221 0.235 0.243
GE 0.101 0.088 0.097 0.110
Atk 0.046 0.040 0.045 0.050
EGR 0.053 0.050 0.053 0.054
FW 0.089 0.089 0.097 0.093
Source: Calculated by author from various issues of HIES/ PIHS/ PSLM.
Table A3
Inequality, Growth and Inflation Rate
Overall
Inequality (1)
Growth Inflation
Survey Years Gini GE Atk Rate (2) Rate (3)
1990-91 0.298 0.177 0.077 4.459 9.051
1992-93 0.321 0.254 0.098 7.835 4.851
1993-94 0.325 0.251 0.098 1.258 9.825
1996-97 0.339 0.377 0.123 4.847 10.789
1998-99 0.343 0.248 0.103 1.014 11.803
2001-02 0.304 0.189 0.081 1.865 4.41
2005-06 0.306 0.182 0.079 7.672 9.276
2007-08 0.316 0.200 0.086 5.638 7.771
Source: (1) Calculated by author from various issues of HIES/ PIHS/
PSLM.
(2, 3) IMF.
APPENDIX "B"
Table B1
Percentage of Distribution of Household in Urban
and Rural Areas by Survey Years
Percentage of
HH Sample Size
Survey Years Urban Rural Total
1990-91 31.9 68.1 100
1992-93 28.4 71.6 100
1993-94 30.4 69.6 100
1996-97 31.2 68.8 100
1998-99 29.5 70.5 100
2001-02 29.2 70.8 100
2005-06 33.6 66.4 100
2007-08 32.8 67.2 100
Source: Calculated from HIES, PIHS, PSLM (various issues).
Table B2
Percentage of Distribution of Household by Survey Years Province Wise
Percentage of HH Sample Size
Survey Years Punjab Sindh KPK Baluchistan Total
1990-91 61 23.5 12.6 2.9 100
1992-93 59.1 22.6 14.2 4.1 100
1993-94 58.4 23.8 13.3 4.5 100
1996-97 59.4 20.7 16.6 3.3 100
1998-99 56.7 23.5 14.1 5.7 100
2001-02 56.3 25.3 14 4.4 100
2005-06 55.8 24.8 14.5 4.9 100
2007-08 57.9 23.5 13.8 4.8 100
Source: Calculated from HIES, PIHS, PSLM (various issues).
Table B3
Distribution of Household by Survey Years
Survey Years HH Sample Size
HIES 1990-91 6516
HIES 1992-93 14593
HIES 1993-94 14668
HIES 1996-97 14261
PIHS 1998-99 14820
PIHS 2001-02 14831
SLM 2005-06 15453
PSLPM 2007-08 15512
Total Households 110654
Source: HIES, PIHS, PSLM (various issues).
Muhammad Touseef-Ur-Rehman is affiliated with the NESCOM,
Islamabad. Usman Mustafa <
[email protected]> is Chief, Project
Evaluation and Training Division, Pakistan Institute of Development
Economics (PIDE), Islamabad. Humayun Rashid <
[email protected]>
is PhD Candidate, AIOU, Islamabad.
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Comments
It is an important paper which takes into account not only
inequality but also polarisation as it takes both ends of income groups.
Polarisation is associated with disappearance of middle class. If income
concentrated around two opposite distributive poles, the size of the
middle class decreases. Sizeable middle class is a source of new
entrepreneurs, high saving, promote human capital and creates demand for
quality consumer goods which boost overall investment and productivity.
Therefore high level of polarisation affect growth negatively.
Following are few comments on the paper:
(1) The authors had taken consumption expenditure as a proxy of
income. So the title should be restricted to "Trends in
Inequality....
(2) The study had taken into account per capita expenditure as a
unit of measurement which gives equal weights to all members of
households and the economies of scale disappeared. Instead of it Adult
Equivalent Scale (AES) can be used giving different weights to
households members i.e. earner= 1, adult =0.8 and children <18
years=0.8.
(3) For measuring inequality the authors had used different
inequality indices i.e. Gini coefficient, generalised entropy and
Atkinson index. They had not discuss significance of these measures as
different inequality measures give different weights to changes in the
income (extreme end or mean or lower end of distribution).
(4) Also give significance of two measures of polarisations.
(5) Need correction of Fig. 14. It is written as Khyber
Balochistan.
(6) In graphical presentation a spike is found for the year 1996-67
for Pakistan and its different regions for GE index as this index takes
into account the transfer of income on both ends but this trend is not
seen in polarisation indices. Needs some discussion and look for the
authenticity of data for this particular year.
(7) The economic interpretation in analysis would help in improving
the readability of the paper.
(8) A proper citation style should follow using software, Endnotes
X7.
(9) Finally, needs a through look at text for minor corrections.
Overall, this paper is good contribution in the literature of
distributional issues.
Rashida Haq
Pakistan Institute of Development Economics, Islamabad.
(1) Most of the studies on inequality in Pakistan have used HIES
data.
(2) KPK (Khyber Pakhtunkhwa) is a new name of NWFP, Which was
changed in the 18th amendment of the Constitution of Pakistan, was
passed by the National Assembly of Pakistan on April 8, 2010.
