Economic Conditions of the Poor in South Asia: Is the Picture Rosier Today?
Udaya R. Wagle
School of Public Affairs and Administration
Western Michigan University
1903 West Michigan Ave.
Kalamazoo, MI 49008
Udaya.wagle@wmich.edu
February 4, 2007
Abstract
Development literature is replete with statistics showing significant progress toward reducing
poverty in South Asia. The notion of poverty headcount ratio giving rise to this conclusion is
consistent with carrying out sensitivity analyses of economic growth and restructuring. Yet,
policymakers facing enormous resource constraints find it more useful to think of the progress in
terms of reduction in poverty headcount, for any policy ought to target specific number of people
with different characteristics. While poverty headcount ratios are declining in some instances, I
find it misleading to construe that poverty is declining to the extent these ratios indicate. The
actual poverty headcounts have not declined if not increased in the last 25 years. The relative
economic condition of the poor has considerably worsened and although the aggregate human
development statistics show an improvement, it is far from certainty that the poor have equally
benefited. This paper draws attention to the need to go beyond the popularly reported statistics.
In process, this paper also assesses the appropriateness of the official and international poverty
lines for a comparison of the poverty statistics.
Keywords: Poverty; Headcount; Headcount ratio; Poverty gap; Inequality; Human development;
South Asia.
I. Introduction
South Asia has remained one of the highly impoverished regions in the world. With a population
over 50 times larger, the gross domestic product of this region (US$996 billion) was
considerably less than that of Canada’s ($1,115 billion) in 2005 (World Bank 2006). This region
is relatively homogeneous economically with GDP per capita ranging from $270 in Nepal to
$1160 in Sri Lanka. Yet, the region as a whole has come a long way to GDP per capita of $677
in 2005 when compared with those of the 1960s that barely exceeded $100. In constant 2000 US
1
dollars, the total GDP in the region grew over 7.58 times during the last 45 years, making
possible an annual growth in per capita GDP of 4.9 percent to $599 in 2005.
While country experiences vary, a meaningful opening up of the South Asian economy
intensified in the late 1980s and early 1990s, which was when the regional giant, Indian
economy, effectively took off. Consequently, the regional economy grew at a much faster rate
after 1980 with its GDP in aggregate expanding almost 13 percent per year by 2005. Despite a
relatively high population growth averaged at two percent, this enabled the region to realize an
annual GDP per capita growth of almost six percent during this period. Although this regional
economic expansion is still lagging behind that of East Asia and the Pacific averaging close to
eight percent during 1980 to 2005, this has been a highly impressive rate of growth, much
needed to counter an astounding rate of impoverishment in the region. This growth, made
possible by the ‘good’ economic policies in the region (Ahmed 2006), was instrumental at
reducing the incidence of poverty as measured by the international $1/day poverty line to slightly
over 30 percent in 2001 from over 50 percent in 1981.
Reducing poverty is a difficult task especially when a large portion of the population is still
rural and agrarian and thus is unable to effectively participate in the modern economy, as is
happening in much of this relatively under-globalized region today (Mahbub ul Haq Human
Development Centre 2003; McKinley 2003; Sinha 2005). But it is important to assess the
progress that the region has made towards this difficult challenge. Because the expanding
economy essentially benefits some segments of the population, it is also time to evaluate whether
the poor have benefited equally or more specifically whether the economic condition has
improved for the poor in this region. This is also to ask, in what way if any the poor in South
Asia are better off today than they were prior to this period of accelerated economic growth and
liberalization? Given that there are official and international poverty lines as well as other
2
inequality and human development measures to assess the conditions of the poor, issues also
emanate regarding the best approach to make such analysis and claim.
This paper attempts to address these issues by looking at estimates of poverty, inequality, and
other human development measures available for the five major countries in South Asia—
including Bangladesh, India, Nepal, Pakistan, and Sri Lanka. The key data on poverty and
economic indicators come from the World Development Indicators database (World Bank 2006)
where as inequality data come from the comprehensive inequality database assembled by the
World Institute of Development Economics Research (WIDER 2005).1 Data on human
development measures were derived from the WDI as well as various Human Development
Reports (UNDP various years).
Before proceeding further, however, it is opportune to discuss the timeline. The selected
duration of 1980 to 2004 is quite appropriate for this study. Although Sri Lanka and Pakistan, the
two early liberalizing economies, introduced partial liberalization measures in the 1960s and
1970s, only in the 1980s and early 1990s did all countries in the region take more effective
liberalization measures (Wagle Forthcoming). This period of 25 years covers two related but
substantively distinct eras—early liberalization and intense liberalization—with relevance for
relating to the actual progresses made. The availability of consistent sets of data and results also
makes this period more appropriate. Bangladesh was constituted in 1971 and countries like
Nepal, Pakistan, and Sri Lanka did not carryout systematic studies of poverty and inequality
almost until the 1980s. Although the surveys of the 1990s and onwards constitute the only
temporal studies that can be meaningfully compared with each other in these countries, there still
were a few systematically carried out studies. A cutoff point of 2004 was selected, despite the
availability of partial data for 2005, for consistent sets of data across countries and over time.
1
This comprehensive World Income Inequality Database draws from much acclaimed Deininger and Squire (1996),
WDI (World Bank 2005), and others.
3
This paper is organized into six sections. Next section takes a closer look at the GDP estimates
in the region. The extent of poverty is discussed in section three, as indicated by both official and
international poverty lines. Because the poverty situation in a given country largely depends on
specific poverty lines used, this section also examines the appropriateness of the official or
international poverty lines. Using consumption distribution as the basis, fourth section assesses
the conditions of the poor relative to those of others in society. Discussed in section five are the
human development measures indicating how condition of the bottom strata of society may have
changed over time. Section six discusses the findings and concludes.
II. GDP in the Region: A Closer Look
Apparently, the sheer size of the Indian economy with 1.1 billion people skews the statistics for
the entire subcontinent which has only 400 million more. But all five countries in the region have
witnessed positive economic growth during the period with a few odd years especially in Nepal
and Sri Lanka owing mainly to the political and ethnic strife. As Figure 1 depicts, Pakistan and
especially Sri Lanka, the two early liberalizing economies, started the 1980s with measurably
higher GDP per capita figures. Sri Lanka led the entire region on GDP per capita for all of the 25
years period, where as India caught up Pakistan after lagging behind for all of the 1980s and
1990s. While all four countries other than Sri Lanka started out with the GDP per capita of much
less than $400 in constant 2000 prices, by 2004 India and Pakistan both hit close to the $600
mark with Bangladesh hitting the $400 mark and Nepal lagging much behind. Especially
phenomenal were the progress in India after the 1990s and yet Sri Lanka’s long and sustained
growth rate.
Figure 2 plots the GDP per capita estimates expressed in constant 2000 purchasing power
parity dollars. These estimates are based on the special exchange rates measuring the relative
4
strength of national currencies to buy goods and services in the local market. Data confirm the
trend observed above with Sri Lanka leading the entire region and Nepal lagging behind
throughout the period. In 2004, for example, the lowest GDP per capita estimate was close to
$1500 (Nepal), with Sri Lanka’s reaching close to $4000 and India’s close to $3000 in 2000
constant prices. Particularly striking, however, was the constant rise in GDP per capita in Sri
Lanka and India with Pakistan witnessing declining estimates. India’s ability to constantly raise
its GDP in PPP terms is more straightforward to understand as its massive urbanization and
transformation of the manufacturing and service sectors indicate, thus with many previously untraded goods and services entering into the ever expanding market. Sri Lanka’s rising estimates
are also explicable given its high economic growth with booming manufacturing industries. The
relative strength of the Pakistani GDP, however, did not constantly increase primarily because
the already expanded ‘marketization’ process served against including the previously un-traded
goods and services, which would have typically lowered the overall price level.
Figures 1 and 2 demonstrate an increasingly divergent economic performance across countries,
thus leading to larger between-country differences. Yet, one can expect these rising GDP figures
to increase the overall living standard. Even in Nepal with the lowest GDP per capita figures, for
example, economic growth has been mostly positive averaging over two percent since 1980,
indicating that the Nepali population is generally much better off today than it was 25 years ago.
III. Extent of Poverty
There are essentially two different approaches that are used to develop poverty lines in an
attempt to identify the poor in developing countries. The poverty lines officially embraced by
governments are appropriate to assess the absolute poverty situation in respective countries.
Unlike many industrial countries, most developing countries previously lacked official poverty
5
lines. But this has been almost an essential element of poverty reduction strategy today. In South
Asia, in particular, while India adopted the concept of poverty line in 1962—which interestingly
was three years earlier than it took place in the United States—other countries did not formally
establish until the 1990s (Ahmed 2004; Chhetry 2004; Gunetilleke and Senanayake 2004;
Qureshi and Arif 2001; Sharma 2004). Consistent, however, is the use of normative consumption
level to develop official poverty lines in these countries, indicating that anyone with income
short of these levels would be deemed poor.
International poverty lines are used to measure poverty especially for cross-country
comparisons. The lower international poverty line initially conceived in 1990 referred to the per
capita consumption level of $1/day in PPP terms in constant 1985 values (Ravallion, Dutt, and
van de Walle 1991; World Bank 1990), which was later updated to $1.08/day in constant 1993
values (Deaton 2001; Chen and Ravallion 2001; Sillers 2006). While the international poverty
line of $2/day is sometimes used for identifying the poor in high income countries, this higher
poverty line is useful to assess the relative condition of those slightly above the $1/day income
(Chen and Ravallion 2001).
Official Poverty Lines
Table 1 reports estimates based on the official poverty lines in the five South Asian countries.
Since all countries except India lacked official poverty lines prior to the 1990s, their poverty
estimates for this period are based on different studies close to or in line with their official
poverty lines for the 1990s. Data for poverty studies come from household surveys and Nepal did
not conduct such survey between 1985 and 1994. While poverty studies were conducted in
Pakistan during 1980 to 1984,2 they lacked comprehensive methodological treatments for
arriving at the reported poverty estimates.
2
See, for example, Amjad and Kemal (1997).
6
As the estimates reported in Table 1 indicate, the poverty headcount ratio remained historically
lower in Pakistan, where between 29 and 34 percent of the population were officially designated
as the poor, and especially Sri Lanka, where between 23 and 29 percent of the population were
poor. The ratio was increasing ever since it was monitored in Pakistan, where as it slightly
increased in Sri Lanka up until the latter half of the 1990s and fell afterwards beyond the initial
rate found in the early 1980s. Of the other three countries, poverty remained consistently high in
Bangladesh throughout the period with estimates ranging from 48 to 52 percent, where as it was
between 26 and 45 percent in India and between 42 and 31 percent in Nepal. The progress was
impressive in India not only because of the whopping 19 percent decline in poverty incidence but
equally importantly because of the massive size of the population that these figures represent.3
Moreover, India reported a steady decline in poverty where as in Nepal all of the decline
occurred during the late 1990s and/or the early 2000s. Table 1 tells the story that poverty
incidence has been either stubbornly persistent as is happening in Pakistan, Sri Lanka,4 and
especially Bangladesh or measurably declining as is happening in India and Nepal. Yet even the
simple averages indicate that it has been declining in South Asia, which occurred after a relative
stagnation during the late 1980s and the 1990s.
While poverty declined in the region when measured by the headcount ratio, the data on the
actual number of poor provide a slightly different picture. Table 2 reports, for example, that the
number of the officially designated poor actually remained very close between the early 1980s
3
A part of this decline was attributable to the methodological change in computing consumption between the
1993/1994 and 1999/2000 surveys, leading to likely overestimation of consumption expenditures. (Deaton 2003;
Palmer-Jones and Sen 2001; Sunderam and Tendulkar 2001). Notwithstanding these anomalies, Deaton’s (2001)
revised estimates suggest that the reduction in poverty headcount ratios would not be substantially different for
1999/2000 had the methodology not changed.
4
While persistent, the poverty incidence in Sri Lanka is the lowest in the region. It is important to note, however,
that these statistics, as well as all the statistics presented in this paper, do not cover the Tamils from the northern and
eastern provinces who have been launching a prolonged ethno-political war against the Sinhalese government in Sri
Lanka. It is, therefore, impossible to know the condition of the poor in these provinces, or of the entire Tamil
population for that matter. Prior to the war, however, the two groups did not significantly differ in the economic and
human development conditions (Shriskandarajah 2005).
7
and early 2000s.5 It peaked during the early 1990s and then climbed again in the early 2000s.
Behind these are the individual country estimates incorporating the dynamic effects of
population growth, which has remained generally high in South Asia, and the actual progress on
poverty reduction as a result of individual efforts, national policies, and the effects of the
international political economy. Yet, what matters to national or international policymakers
thinking about designing or reframing policy interventions to reduce poverty is the actual
number of poor people. It is precisely for this reason that economists and policymakers disagree
on the approach to analyze poverty with policymakers expecting each piece of the policy to
incrementally help people escape poverty and economists thinking about the sensitivity of a
change in particular policy or policy expenditures in terms of the percent change in poverty
figures.
After accounting for the population growth, Bangladesh and Pakistan have witnessed an almost
steady increase in the number of poor with the former registering 44 percent and the latter
registering 59 percent increase in the number of poor during 1980 and 2004. Not coincidentally,
these are the two countries that have witnessed consistently stubborn or increasing poverty
headcount ratios.6 While the figures were considerably higher in the late 1990s, the poverty
headcounts settled at lower than these levels and yet much higher than the initial figures in Nepal
and Sri Lanka. It was only in India, where poverty headcounts showed a consistently declining
trend just like the trend in its poverty headcount ratios.
International Poverty Lines
Tables 3 and 4 provide headcount ratios and headcounts using the $1/day and $2/day
5
This is based on the conservative estimates reported in Table 2. If we were to assume, perhaps more accurately
given the trend based on the remaining estimates, that the poverty headcount in fact increased in Pakistan, we would
come up with the conclusion that the number of poor people increased between the early 1980s and the early 2000s.
6
Partially, this has to do with the validity of the survey data and, in case of Bangladesh, the use of upper poverty
lines (see footnote 15 below). Yet, the widening rural-urban inequality with a slow growth of the agricultural and
service sectors and a lack of employment creation in rural areas help explain these consistently high poverty rates
(Hussain 2003; Mahbub ul Haq Human Development Centre 2003; Ravallion and Sen 1996; Quadir 2000).
8
international poverty lines.7 As Table 3 details, the poverty headcount ratio remained between
four and 50 percent during 1980 and 2004 in South Asia following the $1/day standard, with
Pakistan reporting the highest estimate and Sri Lanka reporting the lowest estimate. Starting in
the 1980s with 50 percent of its population earning less than $1/day in PPP international 1985
dollars, Pakistan achieved a spectacular progress during 1980 and 1995, thus reducing the
poverty headcount ratio to 13 percent, after which it increased to 17 percent by the early 2000s.
Sri Lanka consistently registered the poverty headcount ratios at single digits. Anomalous to all
other countries reporting estimates, Bangladesh, which started with a modest estimate, recorded
increasing poverty headcount ratios. Again, India was the only country where poverty headcount
ratio consistently declined following the $1/day standard.
The $2/day poverty line offers a similar but interesting observation. While Sri Lanka was the
leading country in lowering poverty headcount ratio, Pakistan’s estimates were not significantly
better unlike in case of the $1/day poverty line, suggesting that a significant proportion of the
Pakistanis were only slightly better off than the $1/day of income. A relatively large segment of
the Pakistani population, therefore, still had a chance to slip into poverty should they face major
lifecycle changes or crises such as flooding and dill-health (Sen 2003). Starting with comparable
estimates, Bangladesh was again the country with consistently higher poverty headcount ratios.8
From the regional perspective, South Asian countries made a sizable progress in reducing
poverty with percent poor population declining consistently across different time periods. Over
the 25-year period ending in early 2000s, for example, poverty headcount ratio fell over nine
percent following the $1/day poverty line and over 15 percent following the $2/day poverty line.
7
Although the actual poverty line used represents $1.08/day of per capita income in 1993 constant PPP dollars, I am
still calling it the $1/day poverty line to be consistent with the poverty line in 1985 constant PPP dollars.
8
While estimates suggested earlier may have been higher due to the application of upper bound official poverty
lines (see footnote 15 below), these estimates following the international poverty lines, though not very close as in
other cases, are still comparable.
9
Yet, by the end of the period, close to a quarter of the South Asian population was living on less
than $370 a year of income, a clear sign of inability to afford basic necessities. Moreover, over
two thirds of the population was living on less than $2/day of income, essentially facing a risk of
falling into poverty.
Where as the poverty headcount ratio consistently declined in South Asia following the
international poverty lines, the actual headcount of the poor did not. Consistent with the
headcount estimates of the official poverty lines, Table 4 indicates that the number of people
living on less than $1/day of income hovered essentially around 450 million between the early
1980s and the early 2000s. Even though the size of the poor population declined to 400 million
in the late 1990s, it reverted back to the previous levels by the end of the period.9 The actual size
of the poor population becomes even larger by the end of the study period when one employs the
more lenient $2/day poverty line. This population estimated at close to 900 million steadily
increased during this period, comfortably surpassing the one billion mark by early 2000s. This is
a suggestion that only 400 million would not be considered poor by any standard, out of the
estimated 1.4 billion people in South Asia.
Depth of Poverty
Estimating the size of the poor population is only one step to getting a clear picture of the
conditions of the poor population. Accurate information on how far away the poor were from the
applicable poverty line will be useful for policymakers contemplating effective poverty reduction
strategies. From the distributional standpoint too, it is important to ascertain how much extra
(re)distribution would be needed if a country were to introduce bold measures to eradicate
9
Part of the reason may be the use of the 1999/2000 survey results to estimate the poor population in India for both
time periods: 1995-1999 and 2000-2004. But only if the Indian headcount ratio falls sufficiently so that the size of
the poor population goes down at least 44 million after accounting for the population growth that the estimate for the
entire region will be lower in 2000-2004 than in 1995-1999. Given that poverty headcount has fallen only slightly in
the previous periods in India, however, the likelihood of this occurring is not very high.
10
poverty. Operationally, poverty gap is the most fundamental concept to measure this depth, the
estimate of which is both straightforward to understand and widely available for usage. Poverty
gap is defined as the shortfall in the consumption of the poor people from the normative level,
which is measured as a percent of the total consumption volume.
Tables 5 and 6 provide poverty gap estimates in percentage terms following the official and
international poverty lines. Following the official poverty lines, Table 5 exhibits that the poverty
gap in South Asia remained around 10 percent with consistently declining trend suggesting that
the poor would have to be able to increase their consumption levels by about 10 percent of the
total. During the 25 years period, for example, the poverty gap declined by five percent,
indicating that the poor in the region were closer to the normative consumption level at the end
of the period than they were at the beginning of the period. Individual country experiences were
diverse, however, with the largest improvement in India, reversing trend in Pakistan, consistently
lower estimates in Sri Lanka, and consistently larger estimates in Bangladesh.
While the size of the poverty gap and its drop following the $1/day standard were almost the
same as those following the official poverty lines, the estimates hovered around 35 percent
following the $2/day standard. This is to suggest that the percentage of the total consumption that
would have to be reallocated to the poor is estimated at around 10 following the $1/day standard
and around 35 following the $2/day standard. By the $1/day standard, moreover, the estimates
have been surprisingly lower and yet unpredictable for Bangladesh, consistently lower for Sri
Lanka, and precipitously declining in Pakistan. Although this is generally true of the $2/day
standard, the declines have been less smooth and unpredictable.
What Poverty Line?
I have thus far presented poverty measurement outcomes essentially following the two (even
three) different sets of poverty lines, entirely shunning the debate over methodology. Yet, no
11
other field in social science has been more controversial than poverty research with the
measurement outcomes drawing enormous debate over the substantive as well as methodological
elements. On the one hand, there has emerged enormous pressure to expand the very notion of
poverty, conventionally defined in income or consumption terms. The notions of capability,
social inclusion, and multidimensional poverty represent a few innovative approaches conceived
to deal with this complex social problem with the argument that policy measures to eradicate
poverty need to be comprehensive including economic, political, and social elements (Gordon
2000; Levitas 2005; Sen 1993, 1999, 2000; Siddhisena and Jayathilaka 2006; Wagle 2002,
2005). These approaches have evolved primarily in response to the inability of the contemporary
approaches to accurately measure poverty and help policymakers to better target resources.
On the other hand, those involved in dealing with poverty at the practical level have been
working on incrementally refining existing poverty measurement tools to make them more
practicable. Whatever the theoretical arguments, policymakers find income or consumption as
the easiest indicators of poverty and therefore have every reason to adopt them as the proxy
measures.10 Within this tradition, however, there are sufficient challenges with regard to
accurately measuring one’s income or consumption, which becomes more daunting when
consumption can happen without formal income. To make the matters worse, these countryspecific poverty measures, however immaculate in design and implementation, may not serve as
the adequate basis for making international comparisons. This is where we see developments in
both the official poverty lines to be used for policymaking and international poverty lines to be
used for international comparisons. But the question is, how accurately do these two sets of
poverty measures capture the state of poverty in a given country? Is it essential to use both
10
Realizing that it is exceedingly low, for example, program administrators in some government and nonprofit
agencies in the United States use difference upscale percentages of the official poverty lines (such as 15, 200, or
even 300 percent) as easy and more realistic cutoff points.
12
poverty lines for the specific purposes for which these are developed?
Historically, most developing countries including those in South Asia lacked official poverty
lines and those that were proposed or used by individual researchers were not officially adopted.
Only in the 1990s, for example, did the South Asian countries (other than India) make significant
effort toward development of official poverty lines, rendering assessment of the state of poverty
much more manageable. Yet, at the heart of all official poverty lines is the idea of basic needs,
comprising a set of widely agreeable, normative needs indispensable to secure a minimum
standard of living (Citro and Michael 1995; Dasgupta 1999; Haveman 1987; Wagle 2002). These
basic needs include food and non-food items. Operationally, all of the contemporary poverty
lines in South Asia have been developed by creating and pricing a basket of goods that satisfies
the combination of certain minimum calories needed to physically survive and be adequately
healthy. The established minimum calories depend on one’s demographic characteristics as well
as physical activity, rural/urban lifestyle, and occupation. But the food part of the poverty lines in
South Asia ranges from 2020 (Sri Lanka) to 2400 (India) calories with different variations across
areas and characteristics (Ahmed 2004; CBS/Nepal 2005; Chhetry 2004; Gunetilleke and
Senanayake 2004; Qureshi and Arif 2001; Sharma 2004). The process determining an official
poverty line involves developing a food poverty line by valuing the cost of a basic basket of
foods with appropriate variations. Nonfood poverty lines (or adjustment amounts) are then
developed by estimating the amount needed to acquire minimal nonfood items including
housing, clothing, transportation, and other basic essentials. These two estimates are added
together to come up with the official poverty line for a country. Albeit seemingly
straightforward, the actual process involved in computing these poverty lines can be very
different. Difficulties can arise, for example, in estimating the cost of the basic basket of foods
and, even more importantly, the cost of nonfood essentials, which can run anywhere from
13
minimal amounts as in rural areas to large amounts as in expensive metropolitan areas. These
poverty lines are periodically adjusted for changes in consumer price indices.
The international poverty line of one dollar a day, though seemingly arbitrary, is also largely
consistent with the way these official poverty lines are established. Originally introduced in the
World Development Report 1990 (Ravallion et al. 1991; World Bank 1990), the idea was to find
a way to aggregate official poverty lines used in developing countries and come up with a
uniformly appropriate measure for comparing progress across the developing world. The process
involved examining 34 existing national poverty lines at the time representing a wide range of
developed and developing countries and coming up with poverty lines supported by a large
number of countries. The $1/day of income was established by averaging the official poverty
lines for 10 of the 12 poorest countries in the sample in the international 1985 PPP dollars11
(Ravallion et al. 1991; Sillers 2006; World Bank 1990). This poverty line was further reaffirmed
from another set of comparisons for 1993, which led to $1.08 per day of consumption as the
international poverty line expressed in international 1993 PPP dollars.12 The $2/day is the upper
poverty line used to monitor the progress of high income developing countries.
Because of the way they are designed and the purpose they are supposed to serve, the official
and international poverty lines are somewhat different right from the beginning, however. The
former, for example, allows adjustments for cost of living variations,13 demographic
characteristics, and the provision of public goods where as the latter does not.14 Notwithstanding
11
This original set of 10 countries included Bangladesh, China, India, Indonesia, Nepal, Pakistan, Tanzania,
Thailand, Tunisia, and Zambia. The poverty lines in the remaining two nations were used to estimate the standard
for extreme poverty established at $270 of income in PPP 1985 prices (Ravallion et al. 1991).
12
This was based on the median figure estimated from the official poverty lines for the same set of 10 countries as
in the 1990 study (Chen and Ravallion 2001).
13
Indian, for example, has urban and rural poverty lines for all 28 states thus creating a complex set of official
poverty lines within the same country.
14
Kanbur and Squire (2001) provide a succinct summary of the critiques on the international poverty line. For more
elaborate treatments, see Ravallion and van de Walle (1991), van de Walle and Nead (1994), and Lanjouw and
Ravallion (1995).
14
these differences, it will be interesting to see how different these are at the national level, which
would then set the stage to make further comments on their appropriateness for the given
countries as well as for regional comparisons.
Table 7 provides a summary of the official poverty lines that are used in this study. Apparently,
the poverty lines are not comparable across countries when expressed in national currencies and
also are difficult to compare over time when expressed in current prices. But they become much
more comparable temporally as well as across countries when expressed in the international
1993 PPP dollars as presented in the lower part of Table 7. Interestingly, these estimates range
from less than $1/day in 1981/1982 in Sri Lanka to $1.98 in 2002 in Bangladesh.
Comparing temporally, there is very little variation in Bangladesh, India, and Nepal, moderate
variation in Pakistan, and very large variation in Sri Lanka. These changes are consistent with
the change in GDP figures for almost all countries except India, as the poverty line is steadily
growing in Sri Lanka where GDP per capita is also growing relatively faster, it is declining in
Pakistan where GDP per capita is growing slow, and it has remained almost the same in
Bangladesh and Nepal where GDP per capita growth has been mediocre. From the cross-national
perspective, the poverty lines have tended to run consistently high in Bangladesh, consistently
low in India and Nepal, in the medium range in Pakistan, and very low to moderately high in Sri
Lanka. One can generally expect the size of the poverty lines to follow the size of the GDP per
capita after controlling for the differences in the PPP conversion rates. This does not appear to
hold in South Asia, however, as the highest poverty lines are set in Bangladesh, a country with
the second lowest GDP figures throughout the period.15 But the fact that poverty lines are
15
As noted on footnotes 6 and 8 above, this partly explains why the poverty incidence has tended to be consistently
higher in Bangladesh. This upper bound, however, applies only to the non-food part of the poverty line suggesting
that the estimates would not considerably attenuate following the lower bound. More specifically, where as the
upper bound poverty lines computed at the nation level for 2000 and 1995/1996 would be 804 and 648 taka
respectively (see Table 7) the corresponding lower bound poverty lines would be 16 percent lower in 2000 and 19
percent lower in 1995/1996. See Ahmed (2004) for the actual estimates for different regions.
15
considerably lower in India and especially Sri Lanka can be related with the extent of public
services available from the state. Compared to Bangladesh, Nepal, and Pakistan, for example,
these two countries have measurably larger array of services publicly available from the state,16
enabling people with considerably lower income to attain comparable degrees of well-being.
Of course, factors such as the cost of living, urban-rural composition, and the degree of
marketization matter in determining the size and distribution of consumption in a given society.
The development of official poverty lines also pay particular attention to the normative level of
nutrition needed in a geography, the consumption behavior of households in a few deciles at the
lowest end of the distribution,17 and the size of the national accounts statistics that can vary
depending on what goods and services enter and what do not into these statistics.18 But these
dynamics get reflected in the more organically developed, official poverty lines, as is evidenced
in these countries.
Clearly, none of the official poverty lines of the five South Asian countries reported in Table 7
(other than in Sri Lanka in 1981/1982) is set below the international poverty line of $1.08 in
1993 PPP terms. Similarly, only in Nepal and especially India do the official poverty lines come
little closer to the international poverty line. This suggests that where as the international poverty
16
While there are a number of public services that have impacts on one’s living conditions, public expenditure in
education is a strong indicator of the public provision of these services so that people can consume them without
having to pay. If this is true, the levels of public expenditure on education as percent of GDP estimated at 3.7
percent in India and 3.2 percent in Sri Lanka are considerably larger than those that run 1.5 percent in Bangladesh,
two percent in Nepal, and even 2.6 percent in Pakistan (UNDP 2006). In Pakistan, in particular, the increasing
incidence of poverty in the 1990s and onwards has been attributed with the lack and inefficient provision of public
services (ADB 2002).
17
This is important in developing the food as well as nonfood poverty lines. In most cases, both poverty lines
depend on how much those within certain range of the expenditure associated with having just the normative level
of food calorie intake have been spending in food and nonfood expenditure.
18
There can be many goods and services that may or may not be counted in the national account statistics to the
extent that the GDP estimates as well as their PPP conversion rates can be fairly unreliable. An obvious case in point
is childcare, where one earning income to pay for childcare expenses simply adds value to the GDP estimates
without increasing net monetary welfare. While there are propositions for replacing the poverty statistics based on
the sample household surveys with those from the national account statistics (Sundaram and Tendukar 2001), for the
validity and reliability issues attached, one can be equally skeptical about the value added that the latter can offer to
the accuracy.
16
line set for developing countries like in South Asia is useful to monitor the relative progress of
countries in reducing extreme poverty as the World Bank (1990) purports to perform, this comes
nowhere close to what is realistic for the individual countries.19 It is interesting that the official
poverty lines in this region fall between the $1/day and $2/day international poverty lines. But
the fact that the national poverty lines are uniform neither across countries nor over time after
converting into the uniform PPP measures indicates that the use of the international poverty lines
may not be highly relevant in South Asia, thus rendering the poverty trend indicated by the
international poverty lines somewhat less relevant.
IV. Relative Economic Conditions
The contemporary approaches to measure poverty do not relate to economic inequality in
society. While the official or international poverty lines discussed above have been derived by
looking at the consumption distribution in some deciles at the lower end, they are independent of
the distribution at the higher end. It would be ludicrous to assume that the amount of income or
consumption at the higher end directly affects the basic needs indispensable for everyone. This is
especially the case with absolute poverty where the focus is on the basic human needs that must
be fulfilled unconditionally. Although what needs are basic depends on the specific context, they
can change only in a relatively longer term, owing to major lifestyle changes in a given society.
Poverty lines once developed are used for long periods with minor adjustments consistent with
consumer price indexes and without needing major overhaul.20 Even the notion of relative
poverty defined as some percentage of the mean or median figure disregards the distribution at
19
This could also be attributed with the use of faulty PPP conversion rates as Deaton (2001) suggests, which would
then support the case for either working on creating more accurate PPP conversion rates or not using the PPP
concepts entirely.
20
Poverty lines developed in the 1960s are still in use in the United States, without any overhaul despite major
pressures and challenges (Citro and Michael 1995; Short 2001). In India, poverty lines have not seen major overhaul
since they were established in 1979 using data from the 28th Round (1973/1974) of the National Sample Survey
(Sharma 2004).
17
the higher end.21 Three of the four latest Poverty Reduction Strategy Papers, the most
comprehensive documents assessing the progress on, and outlining the plan of action for, poverty
reduction, in South Asia do not even consider economic inequality as a factor in examining
poverty (Government of Sri Lanka 2002; MOF/Pakistan 2003; NPC/Nepal 2005).
Yet, the overall distribution maters for poverty, as does the absolute income or consumption at
the high end for the relative condition of the poor. For one, economic inequality and poverty
always go hand in hand (UNDP 2005). Where as income is essentially what defines poverty, the
UNDP (2005) finds that inequality can make the poor in more developed countries like Brazil (or
the United Kingdom) live with less incomes than do the poor in less-developed yet more equal
countries like Viet Nam (or Poland). Research also shows that initial economic inequality can
adversely affect a country’s ability to reduce poverty, as any growth realized would
disproportionately benefit the wealthy (Furman and Stiglitz 1998). Just as the global experience
has left the arguments on whether growth helps or hurts the poor completely unsettled (Dollar
and Kraay 2001a, 2001b; Kuznets 1955; Wagle Forthcoming; Wade 2004), studies in India have
not been highly conclusive simply because the rates of poverty reduction have not surpassed the
rates of economic growth in states where inequalities are higher (Meenakshi and Ray 2003). It is
also well known that economic inequality hurts the development of human capital among the
poor and their offsprings and disenfranchises them with wide policy and redistribution
consequences (APSA Task Force on Inequality 2005; UNDP 2005; Wagle 2007). High
inequality can be very challenging for the poor especially if most of the inequality concentrates
on the low end of the distribution. Soaring consumption for the upper classes imposes additional
21
The original idea was to used 50 percent of the medial income as the poverty line in the United States (Fuchs
1965). But this has been applied with different variations depending on the overall distribution. The United
Kingdom, for example, uses 60 percent of the median income as the official poverty line (Kahn and Kamermann
2002) where as researchers have used two-thirds of the median consumption as the relative poverty line in India
(Meenakshi and Ray 2003).
18
economic pressure on the poor, leading to a psychological mindset that they are ‘different’ and
incapable of being equals, an issue economists often ignore. This form of inequality, for
example, has fueled the recurrent ‘culture of poverty’ or ‘urban underclass’ debates in the United
States (Lewis 1966; Murray 1999; Wilson 2006). It is for these possible deleterious effects that
looking at the degree of inequality is important in determining whether the relative condition of
the poor improved.
Gini coefficients, the most popular measures of inequality, reported in Table 8 indicate a
relatively low yet rising inequality trend in South Asia.22 While data provide less than smooth
trends, inequality over time slightly increased in Bangladesh and Sri Lanka, moderately
increased in India, rapidly increased in Nepal, and remained unchanged in Pakistan. For
countries with rising inequality, moreover, most of the increase occurred during the 1990s with
Nepal experiencing a considerable increase between the late 1990s and early 2000s.23 While Gini
coefficients demonstrate the general inequality trend without identifying its specific locus,24 the
household shares of consumption reported in Table 9 help identify such locus. Data indicate that
the bottom quintiles in South Asia saw their share of consumption declining over time where as
the top quintile saw its share rising by close to four percent. This led the ratio of consumption for
the top to bottom quintile increase by one to 5.5 at the end of the period. Clearly, the richest 20
percent increased their share at the expense of all other households including those at the next
quintile in the distribution.
22
This is notable that these data use consumption expenditure as the basis of inequality. Inequality may appear to be
different following other bases including income and assets, as private transfers and especially government transfers
through food support and other social welfare programs tend to attenuate inequality. Yet, data on income or assets
are more difficult to accurately measure and therefore they are not available for all countries and time periods. See
WIDER (2005) for a scan of sources and types of data.
23
Partly, this has been due to a massive surge in foreign employment and remittances (CBS/Nepal 2005). A crosscountry analysis, however, suggest that economic liberalization has an important role to play increasing inequality in
South Asia especially coupled by a lack of adequate social provisions leaving the poor more vulnerable (Wagle
Forthcoming).
24
Ravallion and Chen (1997) eloquently argue that Gini index does not capture polarized distribution that further
exacerbates the effects of inequality.
19
Over time, the top quintile was able to steadily increase its share of consumption in India and
Nepal, observing a whopping 10 percent increase in the latter between the late 1990s and early
2000s.25 For the bottom 40 percent of the population, the share of consumption slightly declined
in Bangladesh and India, drastically decreased in Nepal, and yet slightly increased in Pakistan. In
Sri Lanka, the share of the bottom quintile slightly increased where as that of the second quintile
measurably worsened.26
It is difficult to draw a definitive conclusion on the relative economic conditions of the poor
during the period in South Asia. Notwithstanding country specific differences, especially for the
lowest stratum in Sri Lanka, however, one observation is clear. The top quintile of the
households expanded their relative strength and that at the expense of all other and especially the
bottom three quintiles. While economic inequality was not seen as a very serious concern in
South Asia historically, it began to increase in Bangladesh, India, Sri Lanka, and especially
Nepal indicating that the relative condition of the poor consequently worsened.
V. Qualities of Human Development
Poverty essentially entails a lack of decent quality of life or welfare. With increasing emphasis
on multidimensional approaches to poverty, issues of capability and social inclusion
fundamentally enter the equation (Sen 1992, 1999, 2000; Wagle 2002, 2005). Income,
consumption, or other resources are the means to attain one’s desired lifestyle, constituting the
end. Freedom is at the center of achieving the lifestyle one values and has reason to value.
25
While the explanations regarding foreign remittance and increasing liberalization (see footnote 23 above) apply to
both of these countries, massive push to industrialization has been found to further increase inequality in India (Warr
2005). From an analysis of extensive time series data covering 1957 to 1997, Warr shows that a lack of growth in
the agriculture sector, together with growing manufacturing sector, has adversely affected the rural poor thus
increasing inequality.
26
While Sri Lanka has more extensive social welfare programs, more obvious reason in this case may be the food
aid that was available for people with low incomes thus bringing their consumption to a certain level (Glewwe
1988).
20
Defined not just in a political but broader sense, freedom constitutes the choice one has in
achieving a combination of ‘functionings’ including the desired lifestyle. Yet, neither freedom
nor these outcomes are easy to measure. In essence, capability, which can be measured by
looking at what one has and can do, is the chief driving force behind freedom and functionings
(Sen 1992, 1993, 2006). Operationally, however, capabilities can also be difficult to measure as
they can take many forms and one needs to decide which of these are more important. Despite
these difficulties, capabilities get reflected, inter alia, in the degree of knowledge and selfrespect, enabling one to make informed decisions, and other antropometric measures such as
health condition, child mortality, and life expectancy that specify the needed bodily requirements
for proper human functioning.27
By incorporating these capability indicators, the UNDP (1990) has established what has now
become a long-held tradition of calculating the ‘human development indices’ for any country,
state, or locality. While determining the degree of human development is a way to assess the
progress on achieving a long, healthy lifestyle, the calculated human development indices are
only relative with usefulness to compare across countries and over time. Yet, these indices serve
as a powerful tool to ascertain the quality of life in a country especially when combined with the
actual indictors used in computing them.
As reported in Table 10, the region is making a steady progress in human development with an
average person expecting to see an improvement of almost twenty percentage points between
1980 and 2004. Sri Lanka led the entire subcontinent in the level of human development,
followed by India, with indices for Bangladesh, Nepal, and Pakistan becoming comparable
especially at the end of the period. Despite this, Pakistan and especially Sri Lanka recorded less
progress over time than the other three countries.
27
These measures also indicate functionings, however, since they have both instrumental and constitutive values,
making them the means as well as ends in human well-being (Muellbaur 1987; Sen 1992, 1999).
21
The actual, observable measures contributing to this progress include literacy, life expectancy,
and child mortality. South Asia made a sizable progress by increasing the literacy rate by 21
percent to over 60 percent by the end of the period. Despite this, however, 40 percent of the adult
population was functionally illiterate, with the rate for women running much higher. Literacy
rate was much higher in Sri Lanka at over 90 percent at the end of the period, with India close to
the average and Bangladesh performing the lowest. During the period, Nepal recorded the
highest progress (26 percentage points), with Sri Lanka showing the least progress (5 percentage
points).
Thanks to the enormous technological progress and massive effort to deliver basic healthcare
services to the urban and especially rural areas, the average life expectancy increased in the
region, with much of the progress achieved during the 1980s and early 1990s. Yet an average
newborn in South Asia could expect to live little over 63 years, a far lower than in many other
regions in the world. Again, Sri Lanka had the highest life expectancy for the entire period, with
all other countries standing close to the average. Bangladesh and Nepal made the largest progress
(13 years each), enabling them to catch up India and Pakistan, which had life expectancy over
five years higher in 1980.
Progress in health service delivery was even more instrumental in reducing the child mortality
in this region, historically recording enormous loss of children before they reached five. Child
mortality rate was more than halved from 173 per 1000 children to less than 85. Nepal and
especially Bangladesh with close to 200 deaths per 1000 children in 1980 each were the
countries making the most progress, with their rates surpassing those of India and Pakistan in
2004. Again, Sri Lanka led the entire region with its rates (14 in 2004) surpassing the levels of
Europe and Central Asia in aggregate (34) and reaching almost the levels of high income OECD
countries (6) (UNDP 2006).
22
Clearly, the human development indicators have significantly improved in South Asia during
the period. But does this mean that the economic conditions of the poor have improved? Despite
variations in the experience across different sections of the population, these improvements are
less likely to run amok, unlike those in economic well-being. Even across countries, for example,
the human development indices can be as large as one indicating that the average of 0.6 in South
Asia in 2004 was not too far away from those of Europe and North America (UNDP 2006). Yet,
more important than cross-country differences are the differences between the poor and nonpoor, which are not readily observable with these statistics. What is true, however, is that the
richer section of the population already scores much better on these indicators, even when the
average degree of human development is relatively low. Starting with the rich section, any
improvement on these indicators is likely to improve the condition of people at the incrementally
lower sections. Most of the poor are not only illiterate, with high morbidity, high child mortality,
and short life expectancy,28 they are also difficult to reach out with education, health, and other
fundamental services. In Sri Lanka, the country with world class record to avoid child mortality,
for example, the 1.4 percent of the children who did not make past their fifth birthday would
come disproportionately from very poor families. These would be the same families that were
illiterate and did not have access to basic healthcare or even if they did, they did not understand
the causes and consequences of even minor health issues. From this standpoint, the fact that the
child mortality rate declined from 4.8 to 1.4 percent marks a progress in human development of
the lives of the poor as a group, even though the very poor may not have experienced significant
improvements.
This holds true for almost 40 percent of the South Asian adult population that was still
28
The 2006 HDR uncovers, for example, that the poorest 20 percent of the population in many countries do not have
access to safe drinking water and basic sanitation facilities, which are considered the essential components of
livelihood among the rich sections of the population (UNDP 2006).
23
illiterate, with an overwhelming majority of this being women, families with over 8.4 percent of
the children destined to die before reaching five, and people unlikely to continue their lives way
before their 63rd birthday. Yet, statistics indicate that the size of the population unaffected or
marginally affected by these improvements was shrinking over time, with an expectation for
qualitative improvements in human development of even the very poor. With the increasing and
sustained policy emphasis on education and health, one can only hope that the most-hard-toreach people realize some benefits through demonstration or diffusion effects quite common in
policy implementation.
VI. Discussions and Conclusion
Assessing the economic conditions of the poor over time is a challenging task as no single
yardstick can sufficiently capture it. Increasing income or consumption is no foolproof for the
improvement in one’s economic condition. Nor does the improvement in human development
conditions alone or the economic condition of the poor relative to those of others in society. In an
attempt to assess the economic conditions of the poor in South Asia, this paper examined several
important aspects and found mixed results.
First, one’s economic conditions have some absolute components that are needed to escape
poverty. Although what is absolutely necessary to maintain non-poor lifestyle depends partly on
the overall economic condition in society, very difficult was to ascertain if the poor were moving
out of poverty. Despite eight percent reduction in the poverty headcount ratios following the
official and international poverty lines ($1/day), the actual head count of the poor remained
stubbornly persistent during the 25-year period. Even for those with slightly better economic
positions by these official and international poverty standards, the prospect remained highly
volatile as the number of people whose incomes were less than $2/day actually increased despite
24
declining trend on the headcount ratios. This is not to claim that the size of the non-poor
population did not expand in the region. In fact, where as the population increased 1.5 times, the
non-poor population increased close to two times following the $1/day standard and over 6.5
times following the $2/day standard. Thanks to the ‘good’ economic liberalization policies
(Ahmed 2006) and conducive international political economy, which were instrumental in
making this happen.
Yet, the success of a policy depends on its ability to improve the conditions of the lowest strata
of the population much more than on doing so for those in the upper echelon of society (Quadir
2000). One measure of this is the ability to lift people out of poverty. Although the region saw an
expansion of the non-poor population, it was not enough to significantly lift the poor given that
the population grew 1.5 times during the period. That said, the actual living condition of the poor
may have slightly improved as indicated by the reduction in poverty gap. Interestingly, the gap
did not improve by the $1/day or $2/day poverty standards, but it did close to five percent
following the official poverty lines. One must be cautious, however, whether this reduction
resulted from the veritable improvement in the ability of the poor to afford a larger array of basic
necessities or from the increasing cost of living induced by the process of marketization above
and beyond what the consumer price indices embedded in the official poverty lines capture. But
the fact that official poverty lines were somewhat closer to the actual country and regional
experiences suggests that some improvement did take place during the period.
Since the massive Indian population heavily skews this trend for the region, it is important to
look at the individual country experiences to arrive at more realistic assessment. Thanks to the
massive economic liberalization in India starting in the 1990s; it was the only country to make
consistent progress in reducing both poverty headcount and headcount ratios following the
official poverty lines, with all other countries recording increasing poverty headcounts. Both
25
poverty headcount and headcount ratios progressively declined in Pakistan following the $1/day
standard; this was not the case following the $2/day standard, however. Moreover, the declining
poverty headcounts and headcount ratios in India were also consistent with its poverty gap,
which together with a drop in the gap in Nepal, led to a sizable improvement in poverty gap for
the entire subcontinent. The improvement clearly was less than encouraging in Bangladesh,
Pakistan, and Sri Lanka. Although the observation about the poverty gap decline holds for India
and Nepal, this was also improving in Pakistan and Sri Lanka and yet was worsening in
Bangladesh following the $1/day and $2/day standards. This provides further indication that the
bottom segment of the population may have seen slight increase in their incomes, although it was
well short of what is needed to get by even from the official poverty lines running slightly higher
than $1/day standard in these increasingly liberalizing economies.
Second, the economic condition of those in the lower echelon depends on their position relative
to those of others in society. After all, it is the society in aggregate that determines what is
absolutely indispensable to achieve a decent living standard, suggesting that any improvement in
the economic conditions of the poor should be accompanied by their increasing share in
consumption. The distribution of consumption expenditures remained increasingly unequal in
South Asia with the Gini coefficients for an average person jumping over four points to 35 by the
end of the period. Inequality has yet to reach an alarming level if other countries and continents
are any guide29 but what matters is the economic structure of society which in this region was
more egalitarian historically. Particularly disturbing was the increase of over 17 points in Nepal
to 47.2, followed by India observing a five-point increase to 36 by the 2000-2004 period.30
Data further indicate that the share of the bottom three quintiles in consumption expenditures
29
Based on the same consumption data, for example, the latest Gini coefficients available were 44.7 for China, 49.5
for Mexico, 46 for the Philippines, and 57.8 for South Africa (World Bank 2006).
30
Economic inequality may have seen further boost in India after 1999/2000, the year in which these were collected.
26
slightly worsened. While no specific group considerably lost its share, the top quintile further
strengthened its position by almost four percentage point during the period. A real improvement
in the relative conditions of the poor would necessitate an increasing share of the bottom
quintiles in consumption, which apparently did not occur. Bangladesh, India, and Nepal saw the
condition of the poor worsen, as their economic growth primarily led by urban manufacturing
industries did not benefit the poor in rural areas.31 The top echelon was the only group to
significantly benefit out of the growth, suggesting that any reduction in poverty in these
countries was not the result of real improvement in the economic condition of the bottom strata
that typically need additional redistributive measures to bear fruit of economic liberalization
(Topalova 2005; Wagle Forthcoming).
Third, the human development situation considerably improved in the region as propelled by
improvements in all its measures including adult literacy, life expectancy, and under five
mortality. Nevertheless, progress in these measures does not automatically warrant positive
implications for the poor since they are always hard to reach even with such basic services as
health and education.32 Those included in these improved statistics would typically be the not-sopoor as they are easy to reach and are relatively more informed with the ability to seek public
services. Yet, adult literacy and basic health services were aggressively promoted by the state
with massive supports from the donor community and one can cautiously expect some
improvement in the living conditions of the poor as a result of the improvement in the overall
statistics.
31
As Datt and Ravallion (1997) show, for example, the inflation together with fluctuations in average farm and nonfarm yields adversely affected the rural poor at least in the short run in India. While the initial endowments of
physical infrastructure and human resources including irrigation, literacy, and infant mortality are additional factors
to augment it, the urban-rural distinction can explain a large part of the within country variations in poverty rates.
32
Birth attended by skilled health personnel is one basic indicator on which the rich and poor vastly differ. Despite
massive training and extension services, only four percent of the births to mothers from the poorest quintile are
attended by trained personnel compared to over 42 percent of their counterparts from the richest quintile in
Bangladesh and Nepal (UNDP 2006). These figures are 5 and 16 percent for the poorest quintile and 55 and 84
percent for the richest quintile in Pakistan and India respectively.
27
Clearly, it is enormously difficult to ascertain if the economic conditions of the poor improved
over time in South Asia. The poor in Pakistan found them with more incomes that helped some
to escape poverty as indicated by $1/day of income standard. But this was not consistent with the
outcomes from official poverty lines, as they tended to run slightly higher. While the
international poverty lines were not very realistic after the specific economic conditions are
taken into consideration, the diverging trends suggested by the official and international poverty
lines indicate that the actual number of poor did not decrease in South Asia despite some
declining percentages. Widely used to assess progress, percentages are not helpful to
policymakers seeking to allocate resources to help specific number of people. Additionally,
although poverty gap slightly declined, it was due to the progress in India and Nepal as well as
the increase in income for the very poor, realized to cope with the increasing marketization
making them buy goods and services primarily not bought before. Added to this was the slightly
worsening economic condition of the poor relative to those at the top of the distribution.
Countries became increasingly unequal, with the record high gaps between the rich and poor.
Also, while the human development conditions improved in the entire region, it is difficult to
ascertain if the poor benefited equally. Additional cross-sectional data are needed to make more
specific observations.
Any analytical outcomes can be as good as the quality of data used. The quality of data used
here is highly problematic. This is especially the case with the consumption data, occupying the
center-stage in this analysis, suggesting that the analytical outcomes need to be taken with grain
of salt. It is good that these data have been collected from nationally representative surveys. Yet,
one can raise serious validity and reliability concerns over the data since the data collectors have
to rely on the information provided by people of variety of backgrounds. Especially problematic
was the valuation of consumption, for which no market price readily existed. Added to this are
28
the respondents’ ability to recall past consumption history, which can be even more seriously
inaccurate in case of illiterate and otherwise incapable people included in the survey. Studies
have looked at the best ways to collect data in these circumstances including using shorter recall
periods (Deaton 2001), different approaches to derive poverty measures (Palmer-Jones and Sen
2001), and different price indices (Deaton 2003). Clearly, part of the variations in poverty
estimates could be due to the use of unreliable data. The serious data quality concerns have even
led some to propose using data from the national account statistics (Bhalla 2001; Sundaram and
Tendulkar 2001). But until more accurate data are available, we are stuck with what we have.
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35
Tables
Table 1
Poverty Headcount Ratios
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Periods
(Using National Poverty lines)
Banhgladesh*
India**
Nepal
52.30
44.50
41.40
47.80
38.90
49.70
36.00
51.00
26.10
41.76
49.80
26.10
30.85
Pakistan
29.20
28.70
30.60
34.46
Sri Lanka South Asia***
24.10
40.58
27.40
35.83
26.10
35.13
28.80
35.65
22.70
32.78
* Figures for the last two periods are based on the upper poverty lines as discused in Ahmed (2004). While the food poverty lines are the same, the
upper poverty lines allow for larger allowances for non-food items.
** Identical poverty estimates are included for India for the last two periods. These estimates are based on a 1999/2000 survey of households, after
which not survey estimates are available.
*** This is disregarding the missing values that exist for Pakistan and especially Nepal.
Source: Ravallion and Sen (1996) and Ahmed (2004) for Bangladesh; Sharma (2004) for India; CBS (2005) and Chhetry (2004) for Nepal;
MOF/Pakistan (2003, 2006) for Pakistan; and Tudawe (2000), Gunetilleke and Senanayake (2004), and DCS/Sri Lanka (2006) for Sri Lanka.
Table 2
Poverty Headcount
(Using national poverty lines)
Bangladesh
India
Nepal
Pakistan
Sri Lanka
South Asia*
1980-1984
47,004,625
319,701,350
6,286,176
3,611,626
405,790,053
1985-1989
48,846,820
310,686,520
29,186,276
4,324,816
399,330,608
1990-1994
56,648,060
317,815,200
32,591,720
4,340,691
417,681,847
1995-1999
63,444,000
251,977,230
8,955,432
39,308,760
5,098,176
368,783,598
2000-2004
67,568,640
273,684,600
7,442,563
46,512,900
4,314,589
399,523,292
* This is after replacing the missing values with the estmates for the former (or latter in case of Pakistan) periods. Albeit not highly realistic, this
provides reasonably conservative estimates as the purpose is to look at the differences over time.
Source: Author'
s calculations.
Periods
Table 3
Poverty Headcount Ratios*
(Using International Poverty lines)
Periods
Banhgladesh
India
Nepal
Pakistan
One Dollar a Day Poverty line
1980-1984
26.16
39.72
1985-1989
33.75
46.31
49.63
1990-1994
35.86
42.31
33.90
1995-1999
26.70
35.30
39.13
13.36
2000-2004
36.03
34.70
24.10
17.00
Two Dollars a Day Poverty line
1980-1984
84.02
85.45
1985-1989
85.39
87.30
88.87
1990-1994
86.40
85.70
80.56
1995-1999
76.13
80.60
80.94
65.56
2000-2004
82.82
79.90
68.50
73.60
* The poverty line of $1 of daily income increased to $1.08 of daily income as indicated by the 1993 survey.
** This is disregarding the missing values that exist for India, Nepal, Pakistan, and Sri Lanka.
Source : World Bank (2006)
Sri Lanka
South Asia**
9.39
3.82
6.56
5.60
32.94
34.77
28.97
24.21
23.49
51.27
40.58
45.35
41.60
84.74
78.21
73.31
69.72
69.28
36
Table 4
Poverty Headcount
(Using international poverty lines)
Periods
Bangladesh
India
Nepal
Pakistan
Sri Lanka South Asia*
One Dollar a Day Poverty line
1980-1984
23,511,300
6,031,085
450,499,884
1985-1989
34,489,125
369,868,708
49,606,674
1,482,118
461,477,709
1990-1994
40,873,228
373,521,142
38,496,840
635,304
459,557,599
1995-1999
33,214,800
340,796,790
8,391,429
17,162,256
1,161,251
400,726,526
2000-2004
48,885,504
363,864,200
5,814,125
24,633,000
1,064,392
444,261,221
Two Dollars a Day Poverty line
1980-1984
75,512,975
12,974,728
882,656,031
1985-1989
87,260,041
697,247,640
88,828,231
8,092,457
894,403,097
1990-1994
98,478,720
756,576,740
91,483,936
6,748,860
966,262,984
1995-1999
94,705,720
778,136,580
17,357,583
84,218,376
8,027,857
982,446,116
2000-2004
112,370,176
837,831,400
16,525,625 106,646,400
7,906,912
1,081,280,513
* This is after replacing the missing values with the estmates for the former or adjecent periods. Albeit not highly realistic, this provides
reasonably conservative estimates as the purpose is to look at the differences over time.
Source: Author'
s calculations.
Table 5
Poverty Gap
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Periods
(Using National Poverty Lines)
Banhgladesh*
India**
Nepal
14.40
10.98
12.50
9.31
13.60
8.31
13.30
5.04
11.75
12.90
5.04
7.55
Pakistan
5.10
6.40
7.03
Sri Lanka
6.54
5.60
6.60
5.10
South Asia***
11.36
9.62
8.49
6.13
6.07
* Figures for the last two period are based on the upper poverty lines as discused in Ahmed (2004).
** Figures are computed from the urban and rural estimates using populaiton weights for those in poverty.
*** Figures represnt the averages for the given poverty gaps, weighted by the size of the population.
Source: Ravallion and Sen (1996) and Ahmed (2004) for Bangladesh; Sharma (2004) for India; CBS (2005) and Chhetry (2004) for Nepal;
MOF/Pakistan (2003, 2006) for Pakistan; and Tudawe (2000) and Gunetilleke and Senanayake (2004), and DCS/Sri Lanka (2006) for Sri Lanka.
Table 6
Poverty Gap
(Using international poverty lines)
Periods
Bangladesh
India
Nepal
Pakistan
Dollar a Day Poverty line
1980-1984
5.99
9.94
1985-1989
7.72
12.68
14.84
1990-1994
8.77
10.86
8.45
1995-1999
5.14
7.22
11.01
2.36
2000-2004
8.10
8.20
5.40
3.10
Two Dollars a Day Poverty line
1980-1984
32.95
39.02
1985-1989
36.54
42.52
44.75
1990-1994
37.88
40.10
35.03
1995-1999
30.28
34.89
37.58
21.97
2000-2004
36.33
35.30
26.80
28.10
* Figures represnt the averages for the given poverty gaps, weighted by the size of the population.
Source: World Bank (2006).
Sri Lanka
South Asia*
1.68
0.67
1.00
<0.5
6.56
12.22
10.26
6.49
7.50
15.95
10.76
13.49
11.90
33.83
41.73
38.93
32.86
34.17
37
Table 7
National Poverty Lines
(Poverty Lines Per month in Local Currency and PPP Conversion)
Periods
Bangladesh*
India**
Nepal
Pakistan*** Sri Lanka****
Current Local Currencies (values in parentheses are the actual years)
1980-1984
302
96
145
104
(1983/1984)
(1983) (1984/1985)
(1981/1982)
1985-1989
454
127
248
225
(1988/1989)
(1987/1988)
(1987/1988)
(1985/1986)
1990-1994
535
226
393
475
(1991/1992)
(1993/1994)
(1992/1993)
(1990/1991)
1995-1999
648
363
424
674
833
(1995/1996)
(1999/2000) (1995/1996) (1998/1999)
(1995/1996)
2000-2004
804
363
641
723
1423
(2000)
(1999/2000) (2003/2004) (2000/2001)
(2002)
International 1993 PPP $ (values in parentheses are the actual years)
1980-1984
1.86
1.22
1.36
0.83
(1983/1984)
(1983) (1984/1985)
(1981/1982)
1985-1989
1.85
1.14
1.68
1.22
(1988/1989)
(1987/1988)
(1987/1988)
(1985/1986)
1990-1994
1.82
1.12
1.72
1.54
(1991/1992)
(1993/1994)
(1992/1993)
(1990/1991)
1995-1999
1.87
1.28
1.25
1.66
1.62
(1995/1996)
(1999/2000) (1995/1996) (1998/1999)
(1995/1996)
2000-2004
1.98
1.23
1.32
1.35
1.67
(2000)
(1999/2000) (1995/1996) (2000/2001)
(2002)
* Poverty lines for the first three periods are computed from the rural and urban poverty lines as provided in Ravallion and Sen
(1996), using the respective population weights. For the last two periods, they represent simple averages of the upper level
poverty lives computed for the 14 different statistical areas as discussed in Ahmed (2004). Using the actual population weights,
may cause these latter poverty lines to slightly change.
** Poverty lines computed from urban and rural poverty lines (Sharma 2004), using their respeictive populaiton weights. The
1995-1999 and 2000-2004 values are similar other than their slightly different rural and urban population weights.
*** Poverty lines for the first two periods computed using the poverty lines for the
1995-1999 period (MOF/Pakistan 200) with appropriate consumer price adjustments.
**** Poverty lines for the first period computed using per capita food expenditure of Rs. 70 per month at 1978/79 prices
(Bhalla and Glewwe 1986). Also, while the selected estimates originally coming from Balla and Glewwe (1986) and
Gunaratne (1985) are based on different food caloric intakes, the measurement outcomes are more consistent and therefore
Source: Balla and Glewwe (1986); Ravallion and Sen (1996); Ahmed (2004); Sharma (2004); CBS (2005); Chhetry (2004);
MOF/Pakistan (2003, 2006); Gunetilleke and Senanayake (2004).
Table 8
Gini Coefficients
(Using household consumption as the basis)
Year
Bangladesh
India
Nepal
Pakistan
1980-1984
25.90
31.40
30.00
32.00
1985-1989
28.80
31.50
33.20
1990-1994
28.20
31.70
31.20
1995-1999
33.50
37.80
36.66
32.99
2000-2004
31.70
36.00
47.20
30.60
* Indicate population-weighted averages.
Source: WIDER (2005) and World Bank (2006)
Sri Lanka South Asia*
27.60
30.84
35.80
31.46
30.10
31.27
34.40
36.82
33.20
35.16
38
Table 9
Other Measures of Inequality
(Using housdehold consumption as the basis)
Bottom
Quintile
Household Share of Consumption
2nd
3rd
4th
Quintile
Quintile
Quintile
Country and Year
Bangladesh
1980-1984
9.72
1985-1989
9.45
1990-1994
9.35
1995-1999
8.71
2000-2004
9.00
India
1980-1984
8.60
1985-1989
8.90
1990-1994
8.80
1995-1999
8.10
2000-2004
7.66
Nepal
1980-1984
9.10
1985-1989
1990-1994
1995-1999
7.60
2000-2004
6.00
Pakistan
1980-1984
8.58
1985-1989
8.35
1990-1994
8.40
1995-1999
8.75
2000-2004
9.30
Sri Lanka
1980-1984
7.86
1985-1989
7.64
1990-1994
8.90
1995-1999
8.00
2000-2004
8.33
South Asia*
1980-1984
8.70
1985-1989
8.88
1990-1994
8.82
1995-1999
8.22
2000-2004
7.95
* Indicate population-weighted averages.
Source: WIDER (2005) and World Bank (2006).
Top
Quintile
Ratio, Top
to Bottom
Quintile
14.29
13.36
13.51
12.02
12.50
17.90
16.96
17.24
15.65
15.90
22.25
21.63
21.99
20.84
21.20
35.84
38.60
37.91
42.78
41.30
3.69
4.08
4.05
4.91
4.59
12.70
12.50
12.50
11.60
11.39
16.50
16.30
16.20
15.00
15.24
21.70
21.30
21.40
19.30
21.45
40.50
41.00
41.10
46.00
44.27
4.71
4.61
4.67
5.68
5.78
12.90
16.70
21.80
39.50
4.34
11.50
9.00
15.10
12.40
21.00
18.00
44.80
54.60
5.89
9.10
12.51
12.22
12.90
12.46
13.00
16.29
16.07
16.90
15.86
16.30
21.35
21.28
22.20
20.64
21.10
41.27
42.08
39.20
42.29
40.30
4.81
5.04
4.67
4.83
4.33
17.51
11.60
13.10
11.80
12.49
17.45
15.45
16.90
15.80
15.98
20.36
21.19
21.70
21.50
20.98
36.82
44.12
39.30
42.80
42.22
4.68
5.78
4.42
5.35
5.07
12.92
12.54
12.66
11.73
11.64
16.63
16.33
16.40
15.16
15.38
21.70
21.33
21.55
19.65
21.32
40.04
40.91
40.57
45.24
43.71
4.61
4.61
4.60
5.52
5.56
39
Table 10
Non-Income Measures of Living Condition
Year and Category Bangladesh
India
Nepal
Human Development Index
1980
0.348
0.431
0.328
1985
0.381
0.470
0.369
1990
0.412
0.510
0.414
1995
0.445
0.545
0.453
2000
0.478
0.577
0.490
2004
0.530
0.611
0.527
Adult Literacy rate (% of people ages 15 and above)
1980
28.93
41.03
22.41
1985
31.52
45.20
26.50
1990
34.22
49.32
30.45
1995
37.08
53.27
35.98
2000
39.99
57.24
41.70
2004
61.00
48.60
Life expectancy at birth (years)
1982
49.81
55.05
49.12
1987
52.91
57.60
52.02
1992
56.00
60.15
54.61
1997
59.84
62.24
57.36
2002
62.09
63.38
59.86
2004
63.30
63.30
62.10
Under-Five Mortality rate (per 1,000)
1980
205
173
195
1990
144
123
145
1995
116
104
120
2000
82
94
95
2004
77
85
76
* Indicate population-weighted averages.
Source: UNDP (HDR various years) and World Bank (2006)
Pakistan
Sri Lanka South Asia*
0.383
0.420
0.462
0.473
0.499
0.539
0.648
0.676
0.699
0.719
0.741
0.755
0.42
0.46
0.50
0.53
0.56
0.60
27.82
31.35
35.38
39.31
49.90
85.29
87.10
88.72
90.24
91.63
90.70
39.02
42.94
46.87
50.69
55.72
60.15
56.23
58.24
59.67
61.68
63.82
63.40
68.25
69.49
70.73
71.78
73.80
74.30
54.77
57.31
59.78
62.03
63.41
63.47
156
138
125
108
101
48
32
25
20
14
172.84
125.34
106.13
92.98
84.44
40
Figures
Figure 1
GDP Per Capita in 2000 US$
200
400
600
800 1000
GDP Per Capita
1980
1985
1990
Year
1995
GDP Per Capita in 2000 PPP International $
1000
2000
3000
4000
Bangladesh
Nepal
Sri Lanka
2000
2005
India
Pakistan
South Asia
Figure 2
GDP Per Capita PPP
1980
1985
1990
Year
Bangladesh
Nepal
Sri Lanka
1995
2000
2005
India
Pakistan
South Asia
41