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Resurgent AsiaDiversity in Development$

Deepak Nayyar

Print publication date: 2019

Print ISBN-13: 9780198849513

Published to Oxford Scholarship Online: November 2019

DOI: 10.1093/oso/9780198849513.001.0001

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Unequal outcomes for countries and people

Unequal outcomes for countries and people

Chapter:
(p.178) 7 Unequal outcomes for countries and people
Source:
Resurgent Asia
Author(s):

Deepak Nayyar

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198849513.003.0007

Abstract and Keywords

Rapid economic growth in Asia was associated with an unequal distribution of its benefits among countries and between people. There was, in fact, a widening gap in per capita income levels within the Asian-14, while the gap between the richest and poorest countries in Asia was awesome. Much of the income inequality between countries in Asia was attributable to inequality between, rather than within, countries. Yet, there was also a significant increase in inequality between people within countries, just as there was a marked increase in inequality between regions within countries, both of which were more pronounced in countries that experienced rapid growth. Even so, rapid growth did lead to a substantial reduction in absolute poverty. However, the scale of absolute poverty that persists, despite unprecedented growth, is just as striking as the sharp reduction therein. The poverty reduction could have been much greater, were it not for the rising inequality.

Keywords:   absolute poverty, convergence and divergence, growth–poverty–inequality, inequality between countries, inequality between people, regional economic disparities, social development, unequal income distribution, unequal opportunities, well-being of people

During the past fifty years, economic growth in Asia has been impressive compared with developing economies elsewhere and the industrialized countries. It was also much faster than growth in Western Europe and North America during their Industrial Revolutions. And it was clearly far better than its own performance in the preceding century. This led to a significant increase in its share of world GDP even if convergence in levels of income per capita was modest and uneven. However, these aggregates are deceptive. The distribution was unequal among its constituent sub-regions and between countries. It was just as unequal between people and among regions within countries.

The object of this chapter is to analyse unequal outcomes in development and emerging divergences in incomes during this era of rapid economic growth in Asia. In doing so, it seeks to focus on uneven development across countries and on unequal distribution among people within countries. Section 1 examines whether per capita income in Asia converged towards, or diverged from, per capita income in industrialized countries, to situate these outcomes in the context of hypotheses in economics about convergence. Section 2 outlines the contours of inequality between countries in Asia, disaggregated by country-groups and countries, mirrored in divergences in per capita income over time, to underline its significance. Section 3 discusses the rising economic inequality within countries in Asia, reflected not only in a worsening of income distribution between people but also in growing regional disparities. Section 4 considers the extent to which rapid economic growth has helped the poor by bringing about a reduction of absolute poverty in Asia, while highlighting how much, and where, poverty persists. Section 5 analyses the impact of economic transformations in countries at a macro-level on the well-being of people at the micro-level, not only because it is the essential purpose of development but also because opportunities for people shape outcomes in development.

1. Convergence and divergence

The rapid economic growth in Asia, without precedent in history, led to an increase in its share of world GDP, in current prices at market exchange rates, (p.179) from less than one-tenth in 1970 to almost three-tenths in 2016. Consequently, GDP per capita in in Asia, as a proportion of GDP per capita in the world economy rose from less than one-sixth to more than one-half. However, as a proportion of GDP per capita in the industrialized countries it rose only from one-twentieth to one-twelfth (Table 2.3). It would seem that convergence was significant relative to the world average but modest in comparison with industrialized countries.1

Such comparisons are obviously more meaningful at the level of countries rather than the continent. Figures 7.1 and 7.2 compare levels of GDP per capita in the Asian-14, divided into two groups, with levels of GDP per capita in the industrialized countries, in current prices at market exchange rates (in the top panel) and in 1990 international PPP dollars (in the bottom panel), both based on time-series data for 1970–2016. There are two sets of figures, which divide the fourteen countries into two groups, essentially because so many plotted lines in one figure would have been too cluttered for readers to discern the trends.

Figure 7.1 outlines the trends for the three East Asian and four South Asian countries in the Asian-14. At market exchange rates, there was a rapid convergence for South Korea and Taiwan. There was a significant convergence for China and a modest convergence for Sri Lanka beginning around 2000. India, Pakistan, and Bangladesh experienced a slight divergence until 2000 followed by a slight convergence thereafter, so that in 2016 they remained where they were in 1970, with India doing a shade better. In PPP terms, the trends are smoother and clearer. There was a complete convergence for South Korea and Taiwan. There was a significant convergence for China, somewhat less for Sri Lanka, from 2000. India also witnessed a modest convergence starting round 2000, while Pakistan and Bangladesh did not and were at lower levels. The trends over time were similar, though PPP figures smoothen out the fluctuations. The real difference between the two sets of statistics is in the levels. As a proportion of GDP per capita in industrialized countries, the levels of GDP per capita in each of these countries were much higher in PPP terms than at market exchange rates. For example, in 2016, at market exchange rates, GDP per capita in South Korea as a proportion of that in industrialized countries was 66 per cent, whereas in PPP terms, it was close to 100 per cent; the same proportions were 19 per cent and 37 per cent respectively in China, 9 per cent and 29 per cent respectively in Sri Lanka, or 4 per cent and 17 per cent respectively in India.

Unequal outcomes for countries and people

Figure 7.1 GDP per capita for the Asian-14 in East Asia and South Asia: convergence and divergence: 1970–2016 (as a percentage of GDP per capita in industrialized countries)

Source: Author’s calculations from UN National Accounts Statistics and GGDC Online Maddison Project Database. See Appendix.

Figure 7.2 outlines the trends for the six Southeast Asian countries and Turkey in the Asian-14. At market exchange rates, there was a rapid convergence for Singapore, interrupted for some years by the Asian financial crisis, where income per capita exceeded that in industrialized countries from 2010. The convergence was significant for Malaysia and modest for Thailand. There was a slight convergence for Indonesia and Vietnam from around 2005, but almost none for the Philippines. Turkey, at higher income per capita levels, experienced a significant (p.180) (p.181) divergence in the 1980s, from which it recovered after 2000, but did not return to its peak levels of the late 1970s, even in 2016. The trends are clearer in PPP terms. There was more than complete convergence for Singapore. There was significant convergence for Malaysia, Thailand, and Turkey, a modest convergence for Indonesia and Vietnam, but very little for Philippines. Once again, as a proportion of GDP per capita in industrialized countries, the levels of GDP per capita in each (p.182) of these countries were much higher in PPP terms than at market exchange rates, except in Singapore where the two were almost the same. In 2016, at market exchange rates, GDP per capita in Malaysia as a proportion of that in industrialized countries was 22 per cent, whereas in PPP terms, it was 47 per cent; the same proportions were 14 per cent and 42 per cent respectively in Thailand, 8 per cent and 23 per cent respectively in Indonesia, or 5 per cent and 15 per cent respectively in Vietnam, while these proportions were 26 per cent and 34 per cent respectively in Turkey.

Unequal outcomes for countries and people

Figure 7.2 GDP per capita for the Asian-14 in Southeast Asia and Turkey: beginnings of convergence: 1970–2016 (as a percentage of GDP per capita in industrialized countries)

Source: Author’s calculations from UN National Accounts Statistics and GGDC Online, Maddison Project Database. See Appendix.

This evidence at country-level for the Asian-14 shows that, in comparison with industrialized countries, during 1970–2016, there was a rapid convergence in South Korea, Taiwan, and Singapore, with a significant convergence in China and Malaysia, also there in Thailand and Sri Lanka but somewhat less. Since 2000, there are beginnings of a modest convergence in Indonesia, and a very slight convergence in India with similar trends in Vietnam and Bangladesh starting from lower income levels. Philippines and Pakistan witnessed a divergence starting 1980 followed by a convergence after 2004, but their situation in 2016 was not quite back to 1980 levels. Turkey, at much higher levels of income than most of the Asian-14, except Singapore, South Korea, and Taiwan, has witnessed some divergence followed by convergence to stay roughly where it was.

It is worth situating these outcomes in the context of hypotheses about convergence in economics. The idea that latecomers to industrialization would, over time, catch up with countries that are leaders in the process of development does exist in the literature on the subject, but in two somewhat different strands. There is one school of thought in unconventional economic history and there is another school of thought in orthodox economic theory.

In economic history, this idea of countries that are followers catching up with leaders can be traced back to Veblen (1915) in his writing about Germany following in the footsteps of England. For the latter, it was characterized as the ‘penalty of taking the lead’. This notion was conceptualized further by Gerschenkron (1962), as the ‘advantages of relative economic backwardness’, to consider the experience of Russia as a latecomer that was subsequently extended to include France, Italy, and Austria.

The essential hypothesis can be summed up as follows. Economic backwardness, relative to others, creates a tension between the actual stagnation and the potential prosperity. The gap provides the economic incentive to catch up, while the political process drives institutional innovation. Wider gaps create stronger incentives to leap forward. State intervention, then, creates the missing initial conditions for growth, to compensate for the scarcities of capital, skilled labour, entrepreneurship and technological capabilities. Greater backwardness needs greater intervention. The mobilization of savings for investment is critical. In Russia, this was done by the State, whereas in Germany the same role was (p.183) performed by the creation of a banking system that financed industrialization. The greater degree of backwardness in Russia required an emphasis on producer goods rather than consumer goods, larger firms rather than small firms, and capital-intensive rather than labour-intensive technologies. There are benefits to be derived by learning from the mistakes of predecessors, so that economic growth for latecomers is characterized by spurts with periods of high, sometimes exceptional, growth rates. Obviously, the model has limitations, but its generalizations from history, particularly the industrialization experience in Russia, provide analytical insights into how a mix of ideology and institutions, or economics and politics, might foster success in countries that are latecomers to industrialization.

It is no surprise that the Gerschenkron mode of thinking influenced studies in the economic history of other countries, such as Japan.2 It also led to a quantitative assessment of historical analysis across countries. Abramovitz (1986) tested the hypothesis that productivity growth rates are inversely related to productivity levels so that there is a tendency for convergence over time, to find that there was such a catch up in Western Europe with productivity levels in the United States during the quarter century that followed the Second World War. However, it is recognized that catching up is a function not only of technological opportunities but also of social capabilities, which have institutional dimensions that are slow to develop in economies, firms, and individuals. Hence, every country may not be able to realize its potential for catching up since that depends on its social history and initial conditions. In the long term, convergence is, at best, a tendency that emerges from the average experience of a group of countries, which cannot be oversimplified into generalized outcomes.3

In economic theory, modern theorizing about growth in the neoclassical tradition has spawned a large literature on the idea of convergence. This draws inspiration largely from the original contribution of Solow (1956), where the prediction of convergence is at the core of the model. It makes a distinction between unconditional convergence and conditional convergence. In the former, income differences between countries must wither away in the long run, if there is no tendency for countries to have differences in technical progress, savings rates, population growth, and even capital depreciation. In this world, initial conditions do not matter. Indeed, nor does history. Countries converge to their steady states. And these steady states are the same everywhere. Available evidence provides no support for this notion of unconditional, or absolute, convergence.4 The weaker version of the hypothesis, conditional convergence, argues that countries converge to their own steady states but that these steady states can differ between countries, so that it is possible to control for differences in cross-country parameters such as differences in savings rates or population growth. The essential proposition remains the same. Convergence means a negative relationship between growth rates and initial levels of income per capita. The evidence on this latter formulation is less contrary but not sufficient to sustain any generalization. What is more, (p.184) it provides no explanation about why the controlled parameters for which the statistical exercises make adjustments in fact differ across countries. It would seem that this orthodox literature reduces the complexity of the growth process to the simplicity of abstract models. It is no surprise that the notion is contradicted by stylized facts about development.

What does experience during the second half of the twentieth century suggest?5 There are studies that focus on the industrialized countries, the original twenty-one members of OECD, which show that countries with lower levels of GDP per capita in 1950 have typically recorded higher growth rates in GDP per capita until 2000. However, if this sample is enlarged beyond the OECD to seventy countries, including countries from Asia and Africa, evidence for the period from 1960 to 2000 shows that there is no clear relationship between the level of GDP per capita in 1960 and the growth rate in GDP per capita until 2000.6

There are also attempts to support the convergence hypothesis by going back to the nineteenth century (Baumol, 1986) and going forward to the twenty-first century (Lucas, 2000), both of which are characterized by the limitations stressed above. The Baumol study of sixteen countries, the richest in the world at the time, from 1870 to 1979, shows a negative relationship between the initial level of GDP per capita and the growth in GDP per capita over the period. But another study for the same period from 1870 to 1979, that added just seven countries to this set of countries, all of which had higher levels of GDP per capita than Japan and Finland, which were at the bottom in the original sample of sixteen countries in 1870, reveals that the negative relationship between the initial level and growth of GDP per capita vanishes (De Long, 1988). It needs to be said that a selective focus on the rich countries that succeeded is an exercise that validates itself through its choice of countries because there were several other countries with higher levels of GDP per capita than Japan in 1870, which were not included possibly because that would have refuted the convergence hypothesis. These exercises could be described as almost tautological.7 Clearly, studies in retrospect, when the facts about the present are known, should not be used to support generalizations that predict outcomes.

It is clear that hypothesizing about observed outcomes is one thing, but predicting future outcomes is quite another. In reality, there is nothing automatic about convergence, just as there is nothing automatic about growth. Convergence and divergence are often simultaneous. What is more, convergence is often uneven across space and over time. This may be reflected in differences between countries in rates of growth of GDP and GDP per capita but it is also important to analyse the underlying factors.

Therefore, it would be reasonable to ask whether we can learn something about this issue of convergence from the experience of the Asian-14 over the past fifty years. It does not quite validate the convergence hypothesis. In 1970, GDP per capita was among the lowest in China, India, Indonesia, Pakistan, Bangladesh, and (p.185) Vietnam. During 1970–2016, the rate of growth of GDP per capita was the highest in China, but it was among the lowest in Pakistan and Bangladesh, while it was in the medium range in India, Indonesia, and Vietnam. In 1970, the level of GDP per capita in South Korea, Taiwan, Malaysia, Philippines, Thailand, and Sri Lanka was in the middle range among the Asian-14. Yet, during 1970–2016, the rate of growth of GDP per capita was high in South Korea and Taiwan, medium in Malaysia, Thailand, and Sri Lanka, and low in Philippines. In 1970, Singapore and Turkey had the highest levels of GDP per capita among the Asian-14. However, the rate of growth of GDP per capita was close to the highest in Singapore and low in Turkey.8 Clearly, there was no consistent relationship between the initial level of GDP per capita and the subsequent rate of growth of GDP per capita.

2. Inequality between countries

The pace of economic growth in Asia over the past fifty years was uneven across its sub-regions, country-groups and countries. It is no surprise that, over time, this led to an increasing inequality in output shares and a growing divergence in income levels within Asia.

The distribution of GDP between its constituent sub-regions became distinctly more unequal. In the total GDP of Asia, between 1970 and 2016, the share of East Asia rose from less than two-fifths to three-fifths, the share of South Asia fell from almost three-tenths to one-eighth, and the share of West Asia diminished from around one-fifth to one-eighth, while the share of Southeast Asia remained unchanged at about one-eighth (Table 2.3). Consequently, this period witnessed a growing divergence in per capita income levels between East Asia, on the one hand, and Southeast Asia, South Asia, and Asia as a whole, on the other. Of course, per capita income levels remained the highest in West Asia essentially attributable to oil-exporting countries but fluctuated with world oil prices (Figure 2.2).9

The discussion in the preceding chapters has sought to focus on the Asian-14, which is a group made up of economies from different constituent sub-regions of Asia. These countries accounted for more than four-fifths of Asia’s GDP in both 1970 and 2016 (Table 2.10). Given the overwhelming significance of the Asian-14 in the continent, it is possible to examine divergences in per capita incomes at two levels: in comparison with other country-groups in Asia, and between countries in the Asian-14.

For this purpose, Asia is divided into four country-groups: the Asian-14, the West Asian oil-exporting countries (the high-income countries), the Asian least developed countries (LDCs, the poorest countries) and the residual of other Asian developing countries.10 Figure 7.3 plots the trends in GDP per capita for each of these country-groups, as a percentage of GDP per capita in the world economy (perhaps the most appropriate denominator to normalize absolute values, (p.186) spanning a wide range, for a meaningful comparison), based on time-series data for the period 1970–2016. It shows that the West Asian oil-exporting countries had the highest per capita income levels throughout, which fluctuated widely, presumably with world oil prices, but there was no systematic upward or downward trend. There was a clear upward trend with a significant convergence for the Asian-14. However, the LDCs experienced a clear divergence as the income gap between them and the rest widened progressively over time.11 In contrast, per capita income in the Asian-14, which was distinctly lower than in other Asian developing countries in 1970, converged to their level by 2003 and increased the gap progressively thereafter. It is worth noting that, in 1970, per capita income levels for the Asian-14 and the LDCs were not far apart.

Unequal outcomes for countries and people

Figure 7.3 GDP per capita of selected country-groups in Asia as a percentage of GDP per capita in the world economy: 1970–2016

Note: The percentages have been calculated from data on GDP per capita in current prices at market exchange rates.

Source: Author’s calculations from UN National Accounts Statistics.

It is just as instructive to compare trends in GDP per capita among the Asian-14. Figure 7.4 plots GDP per capita, in constant 2010 dollars, for each of these fourteen countries, using time-series data, during the period 1970–2016. The emerging divergences are striking. Singapore, South Korea, and Taiwan simply pulled away far ahead of the rest. Turkey and Malaysia, at lower levels, followed to widen the gap vis-à-vis the rest. Thailand, from the mid-1980s, and China, from the mid-2000s, were some distance behind these leaders. Indonesia and Sri Lanka were just slightly better than India and Philippines barely visible at the bottom, (p.187) followed by Vietnam, Bangladesh, and Pakistan that brought up the rear. The widening gaps in per capita income levels among the Asian-14 are clear.

Unequal outcomes for countries and people

Figure 7.4 Trends in GDP per capita for the Asian-14: 1970–2016 (in constant 2010 US dollars)

Source: Author’s calculations from UN National Accounts Statistics.

The gap between countries at the top and countries at the bottom in terms of per capita income levels in Asia was far wider than it was among the Asian-14. The ratio of GDP per capita in the richest country to GDP per capita in the poorest country in Asia, in current prices at market exchange rates, was 112:1 in 1970 and 102:1 in 2016.12 This ratio fell slightly. Yet, it was more than 100:1 almost five decades later. The ratio of GDP per capita in the richest country to the (p.188) poorest country in Asia, in 1990 international (Geary–Khamis) PPP dollars, was 61:1 in 1970 and 56:1 in 2016.13 In PPP terms, the difference was less, but the gap was still enormous. It is only to be expected that the absolute differences between countries at the top and at the bottom in income per capita, expressed as multiples, diminish as the numeraire is changed from current dollars to PPP dollars. And end points in such a wide range make the difference seem that much larger. Even so, the enormous gap in levels, which are in fact arithmetic averages, is awesome.

There is another dimension to income inequality between countries. Inequality for all countries in Asia can be disaggregated into two components—inequality between countries and inequality within countries—by using the Theil index, which can be decomposed to separate the contribution of within-country and between-country inequality to overall inequality between countries.14 It also has the useful property that the two components are perfectly additive so that there is no residual. Such an exercise in a study on Asia, during the period 1965–2014, shows that between-countries inequality dominated total inequality in Asia, which rose from 1965 to 2005 with dips during 1980–1985 and 1995–2000, to decline a little thereafter. This trend in inequality over time was almost completely driven by the between-countries component.15 The same study estimated the Theil index, during 1965–2014, for three constituent sub-regions of Asia. It shows that sub-regional inequality was the highest in East Asia and was primarily attributable to the between-countries component, whereas sub-regional inequality, in South Asia (the lowest), and in Southeast Asia (the middle-range), was dominated by the within-countries component.16 Clearly, much of the income inequality between countries in Asia was attributable to inequality between, rather than within, countries.

3. Inequality within countries

There are two dimensions of inequality within countries: income distribution between people and economic disparities between regions. This section will focus on the former, while the latter will be considered briefly.

It is exceedingly difficult to find systematic or complete evidence on changes in income distribution, particularly in developing countries. Asia is no exception. The problem lies partly in statistics at the national level, which makes international comparisons that much more difficult. Yet, it is important to sketch a picture, even if it is a rough approximation, of what happened to income inequality within countries in Asia. Table 7.1 puts together evidence on changes in income distribution, measured in terms of Gini coefficients,17 in the Asian-14, for selected years during the period from 1970 to 2015. It needs to be said that the estimates for China, Malaysia, Singapore, South Korea, Taiwan, and Turkey are based on disposable income, while the estimates for Indonesia, Philippines, Thailand, Vietnam, India, Pakistan, Bangladesh, and Sri Lanka are based on (p.189) consumption expenditure. Consumption inequality is always lower than income inequality because the rich save and the poor do not, which is relevant for any interpretation of the data in the table.

Table 7.1 Income distribution changes in the Asian-14: 1970–2015 (Gini Coefficients)

c.1970

c.1980

c.1990

c.2000

c.2010

c.2015

China

27.9

31.0

34.9

43.8

48.1

46.2

South Korea

31.3

30.7

29.5

32.1

31.0

29.5

Taiwan

29.4

26.7

27.2

28.9

31.7

30.8

Indonesia

34.6

35.6

32.0

31.0

38.0

39.5

Malaysia

50.5

48.6

46.2

49.2

46.3

40.1

Philippines

46.0

41.0

43.8

42.8

41.8

40.1

Singapore

40.0

40.7

43.6

48.1

47.2

46.3

Thailand

42.6

45.2

45.3

42.8

39.4

37.9

Vietnam

35.7

37.0

39.3

34.8

Bangladesh

29.0

25.9

27.6

33.4

32.1

India

30.4

32.1

29.7

31.7

35.2

Pakistan

31.5

32.3

33.3

30.4

29.8

30.7

Sri Lanka

31.2

37.0

32.5

41.0

37.0

41.0

Turkey

56.8

51.0

44.1

46.0

40.2

39.7

Notes: See Appendix.

Source: UNU-WIDER World Income Inequality Database.

It is possible to distinguish between the following sets of countries. In Malaysia, Philippines, and Thailand, income inequality was high until circa 2000 and diminished somewhat thereafter, while in Turkey income inequality, the highest in 1970, diminished steadily throughout. Yet, in these countries inequality was high even in 2015, when the Gini coefficient was around 40. In fact, in Philippines and Thailand, income inequality would have been higher than what these figures, based on consumption inequality, suggest. In Singapore, inequality was high to start with and increased further over time. China, Indonesia, India, Sri Lanka, and Bangladesh, were characterized by low or moderate income inequality in 1970. Inequality increased most rapidly in China, where the Gini coefficient rose from 28 in 1970 to 48 in 2010, even if it dropped a little to 46 in 2015. During this period, India, Indonesia, Bangladesh, and Sri Lanka experienced a significant increase in inequality, more than the data suggest because the Gini coefficients for these countries relate to the distribution of consumption rather than income. In South Korea and Taiwan, income inequality was relatively low and changed little during 1970–2015, partly because of land reforms that made the initial distribution more equal. In Pakistan, income inequality must have been higher than the moderate consumption inequality that remained unchanged, but its level is puzzling given the most unequal distribution of land. In Vietnam, even consumption inequality was not low, so that its income inequality was on the high side, despite its land reform and communist politics, which is surprising.

(p.190) For another perspective on inequality within countries, using the same data sources, Table 7.2 traces the changes in the income shares of the top 10 per cent and bottom 50 per cent of the population in each of the Asian-14 for selected years during 1970–2015. Once again, these figures measure income inequality in six countries and consumption inequality in eight countries as specified above. In Malaysia, Philippines, Thailand, and Turkey, the share of the top 10 per cent was far more than the share of the poorest 50 per cent. It was probably the same in China, Indonesia, and Singapore, but the evidence is incomplete. For each of these three countries, there is only one observation during the entire period, which shows that the share of the top 10 per cent was significantly higher than that of the bottom 50 per cent, and the difference was large at 13 percentage points in China. (p.191) The shares were close together for Vietnam only in 2015 and for Sri Lanka until 2000, apart from which the share of the top 10 per cent exceeded that of the bottom 50 per cent. In India and Pakistan, the shares of the top 10 per cent and bottom 50 per cent were close for most of the years. It was only in South Korea, Taiwan, and Bangladesh that the share of the top 10 per cent was consistently less than the share of the bottom 50 per cent.

Table 7.2 Share of top 10 per cent and bottom 50 per cent in the income of the Asian-14

(in percentages)

1970

1980

1990

2000

2010

2015

Top 10 per cent

China

32.0

South Korea

23.0

25.7

24.1

24.3

23.8

Taiwan

22.4

24.3

24.2

24.9

25.9

25.2

Indonesia

31.9

Malaysia

39.8

38.5

36.4

38.4

34.6

Philippines

38.8

32.7

34.7

34.1

32.7

31.3

Singapore

33.2

28.0

Thailand

34.8

35.5

36.4

33.7

30.7

29.2

Vietnam

28.6

29.9

30.9

26.8

Bangladesh

21.9

24.6

27.9

26.9

26.8

India

28.9

25.8

29.8

Pakistan

33.6

27.1

28.5

25.8

26.1

Sri Lanka

26.4

27.5

33.2

29.9

32.9

Turkey

44.7

35.1

31.9

29.3

33.5

Bottom 50 per cent

China

19.0

South Korea

29.5

26.7

28.2

27.9

28.4

Taiwan

30.5

29.8

29.8

29.0

27.6

28.8

Indonesia

24.2

Malaysia

18.1

18.8

20.1

18.2

19.3

Philippines

19.9

23.2

21.4

22.2

22.5

23.4

Singapore

23.6

Thailand

21.8

20.5

20.9

22.0

23.8

24.6

Vietnam

26.4

25.6

24.2

26.7

Bangladesh

32.5

30.8

28.1

28.8

28.6

India

26.1

30.4

27.3

Pakistan

23.1

27.9

28.6

30.4

29.8

Sri Lanka

28.3

28.8

23.5

26.3

24.4

Turkey

14.2

22.1

26.2

24.2

22.0

Note: See Appendix.

Source: UNU-WIDER World Income Inequality Database.

The two measures of inequality (Tables 7.1 and 7.2) reveal similar trends, reinforcing each other. There are, however, two points worth noting. In terms of the shares of the top 10 and bottom 50 per cent, Bangladesh was much the same as South Korea and Taiwan. This is misleading, because consumption distribution data underestimate the share of the top 10 per cent in income, who do much of the saving that is not included. In India and Pakistan as well, the roughly equal shares of the top 10 and bottom 50 per cent could be deceptive for the same reason.

It is reasonable to infer that, in most of the Asian-14, income inequality increased in many countries where it was low to start with, and remained at high levels in other countries even if it decreased from higher initial levels. The only exceptions were South Korea and Taiwan where inequality was low to begin with and remained almost unchanged over the entire period. It needs to be stressed that the Asian-14 were neither exceptions nor unusual in this era, as income inequality was driven up by markets and globalization across the world. In fact, there is an extensive literature on the subject which suggests that, even if inequality levels differ across countries, there is a global trend of rising income inequality among people almost everywhere.18 In a study on income distribution in 135 countries, Palma (2011) finds that the share of the top 10 per cent in national income has risen and the share of the bottom 40 per cent has fallen, while the share of the middle 50 per cent is relatively stable. In a simple metaphor, the rich have become richer and the poor have become poorer.

Given the space constraint, a meaningful discussion on the underlying reasons is not possible here. Suffice it to suggest a few plausible hypotheses. In the earlier stages of development, rapid economic growth led to rising income inequalities. But there was more in this era of markets and globalization. As a consequence of privatization and deregulation, capital gained at the expense of labour everywhere as profit shares rose while wage shares fell. The mobility of capital and the immobility of labour changed the nature of the employment relationship. Structural reforms, which cut tax rates and brought flexibility to labour markets, reinforced this trend. The object of managing inflation was transformed into a near-obsession by the sensitivity of international financial markets, so that governments adopted deflationary macroeconomic policies that squeezed employment. Financial liberalization, which meant a rapid expansion of public as well as private debt, was associated with the mergence of a new rentier class. And the inevitable concentration in the ownership of financial assets probably contributed to a worsening of income distribution.19

(p.192) The other manifestation of rising inequality within countries in Asia was the increase in economic disparities between regions. Economic theory suggests that increasing returns to scale and advantages associated with agglomeration of capital and knowledge could perpetuate, even increase, spatial inequalities.20 This phenomenon is neither surprising nor altogether new. It is in the logic of markets, accentuated by economic liberalization, which tend to widen regional disparities because there is a cumulative causation that creates market driven virtuous circles or vicious circles. Regions that are better endowed with natural resources, physical infrastructure, skilled labour, or educated people, experience a rapid growth. Like magnets, they attract resources and people from elsewhere. In contrast, disadvantaged regions tend to lag behind and become even more disadvantaged. Over time, the gap widens through such cumulative causation.

This has happened in most countries that have experienced rapid growth. Asia is no exception. There are two dimensions of increasing spatial inequalities: the widening urban–rural income gap and the growing disparities between geographical regions within countries. Almost every country in Asia has experienced the former. Rapid economic growth has also been associated with rising inequality between regions or provinces, particularly in large countries such as China, India, and Indonesia, but also elsewhere. In China, as the focus of reforms shifted to the urban sector, regional inequality rose from the mid-1980s largely due to the widening urban–rural gap, while economic disparities between coastal China in the east and the hinterland in the west mounted from the mid-1990s, largely due to rapid industrialization in coastal areas, supported by government policies, driven by markets and globalization.21 In India, the urban–rural gap has widened rapidly.22 Economic reforms led to faster growth in states, mostly in the west and the south, whereas the poorer states in the eastern and central parts of India experienced slow growth.23 The divide was mostly but not entirely regional. The ratio of per capita income, at constant prices, in the eleven richer states, in comparison with the remaining poorer states, increased from 160:100 in 1980–1981 to 231:100 in 2013–2014.24 In Indonesia, the economic gap between Java and the other islands was always there. This gap has widened as manufacturing is concentrated around Jakarta and Surabaya in Java.25 The other islands are still heavily dependent on production and exports of commodities, so that world commodity prices determine incomes.26 These examples can be multiplied across other Asian countries, where rapid economic growth has been associated with rising regional disparities.

4. Absolute poverty in Asia

In the early post-colonial era, Asia was the poorest continent in the developing world. Even in 1970, its GDP per capita in current prices at market exchange rates (p.193) was one-fourth that of Latin America and three-fifths that of Africa (Nayyar, 2013). It was also home to an overwhelming proportion of the world’s poor outside Sub-Saharan Africa. During 1970–1990, the share of Asia in world GDP registered a modest increase and the divergence in per capita incomes came to an end. This process gathered momentum thereafter, as the share of Asia in world GDP increased rapidly and the beginnings of a modest convergence in per capita incomes became discernible. Did its remarkable economic transformation change the lives of poor people in Asia? The answer to this question is critical and depends upon whether absolute poverty in Asia was reduced significantly in this era of transformations.

It needs to be said that the measurement of poverty poses problems because there are conceptual alternatives, methodological difficulties, and data constraints (Atkinson, 1987). There are three conceptual alternatives.27 The simplest is the headcount measure, which estimates the proportion of the population or the number of people below a specified poverty line defined in terms of critical minimum needs so that anyone below it lives in absolute poverty. The poverty gap index comes next, which estimates the mean distance below the poverty line as a proportion of the line, so that it determines the proportion of national income that would be needed to lift everyone out of absolute poverty. There is a set of more complex measures, such as the Sen P measure, which uses the Gini coefficient to measure inequality among those below the poverty line (Sen, 1976). Simply put, as the complexity of the poverty measure increases, the data constraints are more while the methodological difficulties are less. Needless to add, international comparisons make the task more difficult.28

The headcount measure is the most widely used because it is the simplest to estimate and to understand. Of course, the methodological difficulties associated with it are considerable, which range from choosing poverty lines, through finding appropriate price indices for adjusting poverty lines to inflation over time, to using sample data on household consumer expenditure or family incomes from surveys for estimates at a macro-level. Each is a source of endless debates. Such exercises, which count the poor, are either national estimates or World Bank estimates. There can be little doubt that national estimates are better and more robust in terms of their methodology and database although even these are often much debated on points of disagreement or controversy. World Bank estimates are simply not as good in terms of their methodology or statistical foundations. Some question their method of estimation (Pogge and Reddy, 2010). Others argue that the World Bank underestimates poverty (Kaplinsky, 2005). A few even argue that the World Bank overestimates poverty (Sala-i-Martin, 2006). Of the three arguments, the first is the most convincing, the second is perfectly plausible (as the weight assigned to food and necessities in the consumption basket needs to be larger), while the third is far-fetched.29 However, World Bank estimates are the only possible source for inter-country comparisons over (p.194) time and are used here to sketch the contours of a global picture. It must be stressed that the evidence needs to be interpreted with caution.30

The latest World Bank estimates use two poverty lines, which are $1.90 per person per day and $3.20 per person per day in 2011 PPP dollars. The first is the mean of the poverty lines in terms of consumption per capita in the poorest fifteen countries of the world, whereas the second is the median poverty line for thirty-two lower-middle-income countries.31 The usual methodological difficulties that characterize national estimates are also present here. But the object of international comparisons introduces another insofar as national poverty lines are first converted into a common currency using PPP exchange rates and then the international poverty line is converted into the national currency for measuring poverty using the same PPP exchange rates. This problem is accentuated because the changed methodology of World Bank PPP estimates has led to large, sometimes inexplicable, increases in income for some countries.32

Table 7.3 presents estimates, in terms of the proportion of population and the number of people below the two poverty lines, for each of the Asian-14 as well as Asia, for three selected years 1984, 1996, and 2012, to keep the data within manageable limits. It shows that most of the poor in Asia lived in the Asian-14, and that absolute poverty was concentrated in countries with large populations—China, India, and Indonesia—although the numbers were also significant in Vietnam, Bangladesh, and Pakistan. There was virtually no absolute poverty in Singapore, South Korea, and Taiwan, while it was negligible in Turkey.

Table 7.3 Proportion and number of poor in the Asian-14: 1984–2012

Below PPP $1.90 per day

Below PPP $3.20 per day

1984

1996

2012

1984

1996

2012

(percentage of population)

China

75.8

42.1

6.5

96.4

73.1

20.2

Indonesia

71.4

47.4

11.7

91.7

79.8

43.5

Philippines

28.1

17.7

12.1

57.6

43.3

38.7

Thailand

19.6

2.3

0.1

43.1

15.2

1.5

Vietnam

52.9

35.5

2.8

80.0

71.2

13.4

Bangladesh

29.9

35.7

14.8

76.7

75.3

52.9

India

54.8

45.9

21.2

85.5

81.1

60.4

Pakistan

62.2

15.9

7.9

87.9

63.4

46.4

Sri Lanka

13.3

8.9

1.9

45.4

41.5

16.1

Turkey

1.7

2.6

0.3

10.9

10.7

3.4

Asia

58.4

37.9

11.4

82.4

68.8

36.2

Below PPP $1.90 per day

Below PPP $3.20 per day

1984

1996

2012

1984

1996

2012

(in millions)

China

785

512

87

1000

890

272

Indonesia

115

95

29

148

159

108

Philippines

15

13

12

31

32

38

Thailand

9

1

0

21

9

1

Vietnam

37

27

2

56

55

12

Bangladesh

27

43

24

70

91

86

India

409

432

268

638

764

763

Pakistan

61

20

14

86

80

82

Sri Lanka

2

2

0

7

8

3

Turkey

1

1

0

6

6

3

Asia

1563

1293

474

2205

2347

1504

Notes: The number and proportion of poor in South Korea, Singapore, and Malaysia are not included in the table as the estimates are either insignificant or zero. World Bank estimates of poverty do not include Taiwan.

Source: PovcalNet, World Bank, available at http://iresearch.worldbank.org/PovcalNet/.

Between 1984 and 2012, the proportion of the population below the poverty line of PPP$1.90 per day declined sharply by 70 percentage points in China, 60 percentage points in Indonesia, 34 percentage points in India, and 50 percentage points in Vietnam and Pakistan. By 2012, this percentage was double-digit only in India, Bangladesh, Indonesia, and Philippines, while it was almost negligible in Thailand, Vietnam, and Sri Lanka. The progress was almost as impressive in terms of reducing the number of poor people. China reduced this number by 700 million and Indonesia by 85 million. India was the exception, even though it reduced this number by 140 million because, in 2012, as many as 268 million people were still below this poverty line. In 1984, of all the people in Asia below the poverty line of PPP$1.90 per day, one-half lived in China and one-fourth lived in India, whereas in 2012, one-fifth lived in China and more than one-half lived in India.

However, it is clear that progress was far slower in terms of reducing the proportion of population and the number of people living below the poverty line of PPP$3.20 per day. It is not as if these proportions and numbers did not drop. They did. Yet, in 2012, as much as 36 per cent of the population and 1.5 billion people in Asia lived below this higher poverty line. Of these, 1.14 billion people lived in China, India, and Indonesia. But progress in India was far slower than in China, as this number rose. In 1984, of all the people in Asia below the poverty line of PPP$3.20 per day, 45 per cent lived in China and 29 per cent (p.195) lived in India, whereas in 2012, 18 per cent lived in China and 50 per cent lived in India.33

There is another dimension to this problem. Those who lived below the poverty line of PPP$1.90 per day were the perennial poor who were probably unable to reach the critical minimum even in terms of nutrition. Those who lived below the poverty line of PPP$3.20 per day were the vulnerable poor who might have been able to reach the critical minimum in terms of food and clothing plus some basic needs but not appropriate shelter or adequate healthcare and education. Clearly, the population between the two poverty lines was vulnerable, as any shock such as a bad harvest, high inflation, employment cuts, or an illness in the family, could (p.196) have pushed them down further into poverty. In fact, this number of the vulnerable poor in Asia rose from 640 million in 1984 to 1030 million in 2012.

The reduction of absolute poverty in Asia in less than three decades is impressive by historical standards. It was fast growth that lifted people out of poverty.34 Yet, it is striking that poverty persisted as much as it did in Asia despite its rapid economic growth and rising share of world income. Of the total number of people in Asia below both poverty lines, China and India, taken together, accounted for about four-fifths in 1984 and in 2012, even if the distribution of this number between the two Asian giants was reversed. This was despite unprecedented growth rates that were phenomenal in China and impressive in India.

There is a triangular relationship between growth, inequality and poverty, which could provide an explanation. The extent to which economic growth, for any given rate of growth, translates into poverty reduction depends upon what happens to economic inequality. If there is no change in economic inequality, increments in output or income accrue to different segments or fractile groups of the population in exactly the same proportion as the initial income distribution. Thus, a much larger proportion of the increment in income accrues to the rich who are a relatively small proportion of the population, while a much smaller proportion of the increment in income accrues to the poor who are a relatively large proportion of the population. It follows that economic growth translates into a less than proportionate poverty reduction. It is only if economic growth is associated with a reduction in economic inequality that it would translate into a more than proportionate poverty reduction; indeed, reduced inequality could also reduce poverty in the future if it stimulates growth. Of course, the reality was the opposite. Since higher rates of economic growth in Asia were associated with an increase in economic inequality, the poverty reduction must have been less than proportionate. This would explain the persistence of absolute poverty in Asia, although there were substantial reductions in proportions below both the poverty lines, despite the unprecedented rates of economic growth.

5. Well-being of people

The preceding discussion suggests that the remarkable transformation of Asia over the past fifty years led to a significant reduction in absolute poverty. It was also associated with rising economic inequality within countries, except in South Korea and Taiwan. In this context, the fundamental question that arises is whether economic development in countries meant social progress for their peoples. In searching for an answer, it must be recognized that economic growth, while necessary, is transformed into meaningful development if, and only if, it improves the well-being of people, which is both constitutive of, and instrumental in, development.35

(p.197) The well-being of people is constitutive of development as an end in itself, because the welfare of humankind is the essence of development. The well-being of a person depends upon a livelihood that yields income opportunities to provide for food, clothing, and shelter, just as it depends upon good health and basic literacy, which are essential aspects of decent living conditions. This is not only about meeting basic human needs. It is also about the quality of life, which imparts a sense of dignity to people as individuals. Livelihoods yield an income to support private consumption. For the poor, such incomes might suffice for their necessities, but need to be supplemented by public provision of basic health and education services as social consumption.

The well-being of people is instrumental in development, because employment, healthcare, and education are crucial as means to the end. Employment creation can both mobilize and create resources for development. It mobilizes the most abundant yet underutilized resource, people, for development. It creates resources insofar as it increases the productivity of labour. The same people who constitute resources on the supply-side provide markets on the demand-side in the process of development since wages are incomes. This interactive causation is a potential source of economic growth.36 Similarly, healthcare, which ensures the physical well-being of people, and education which creates capabilities in people, ensure that productivity of labour is higher than it would otherwise be, thus contributing to economic growth. It is for this reason that Myrdal (1968) emphasized health and education, described as ‘investment in man’, also characterized by some economists as human capital, as necessary means in the quest for development.37 In fact, over fifty years, the spread of education in society and the provision of healthcare have been at the foundation of success at development in Asia.38

For the continent as a whole, its economic transformation was indeed associated with a social transformation. In Asia, between 1965 and 2016, the infant mortality rate dropped from 160 to twenty-three per 1000 live births, life expectancy at birth increased from forty-nine to seventy-two years, while literacy rates rose from 43 to 82 per cent. There were, of course, differences between constituent sub-regions, as these indicators of social progress improved the most in East Asia and the least in South Asia, with West Asia slightly better than Southeast Asia somewhere in between (Table 2.1). Given the diversity of Asia, however, it is necessary to consider such outcomes at the country level.

Table 7.4 Economic and social indicators of development for the Asian-14: 1970–2016

GDP per capita (in constant 2010 USD)

Infant Mortality Rate (per 1000 live births)

Life Expectancy at Birth (in years)

Adult Literacy Rate (in percentages)

1970

1990

2016

1970

1990

2016

1970

1990

2016

1970

1990

2016a

China

226

705

6773

79

42

9

59

69

76

61

78

95

South Korea

1817

8454

25686

47

13

3

62

72

82

76

92

97

Taiwan

1775

7636

21803

27

5

4

69

74

79

76

91

98

Indonesia

659

1653

3974

113

62

22

55

63

69

55

82

95

Malaysia

1731

4535

11032

42

14

7

64

71

75

64

83

93

Philippines

1257

1526

2753

55

41

23

61

65

69

85

94

96

Singapore

6514

22430

52458

22

6

2

68

75

83

66

89

97

Thailand

923

2463

5963

71

30

9

59

70

75

75

93

93

Vietnam

266

424

1735

54

37

17

60

71

76

69

88

94

Bangladesh

402

389

1023

148

100

28

48

58

73

22

35

73

India

354

533

1855

142

89

34

48

58

69

34

48

69

Pakistan

465

729

1162

144

106

63

53

60

67

20

43

57

Sri Lanka

711

1128

3832

54

18

8

65

70

75

83

91

91

Turkey

4216

6750

14117

127

55

11

52

64

76

45

79

96

Sources and Notes: See Appendix. The figures on adult literacy rates in the column for 2016, which are the latest available for each of the countries, relate to different years during the period 2010–2015.

Table 7.4 presents compiled evidence on these social indicators of development for each of the Asian-14, in 1970, 1990, and 2016, along with their levels of GDP per capita in real terms for reference and comparison. In this context, it is essential to remember that income per capita is an arithmetic mean while social indicators are also statistical averages, so that neither captures the actual living conditions of people, particularly the vulnerable and the poor. All the same, the evidence in the table shows significant progress in terms of social development. Infant mortality rates plummeted in all countries, although the 2016 levels were still on the high (p.198) (p.199) side in some. Life expectancy rose by 10–25 years, to reach a level of 70–80 years in most countries. Adult literacy rates increased by 30–50 percentage points, to a range of 90–95 per cent in all except three countries.

There are, inevitably, differences between economies. By 2016, in Singapore, South Korea, Taiwan, Turkey, Malaysia, and China (in descending order of real GDP per capita), infant mortality rates were single-digit, life expectancy was in the range of 75–83 years, and adult literacy rates were 95 per cent or more. Thailand and Sri Lanka came close to the best performers, despite lower income levels. Indonesia and Philippines, at similar income levels, did not make as much progress, except in adult literacy rates. Vietnam at a distinctly lower income level fared better. India, Bangladesh, and Pakistan were the laggards in terms of all three social indicators, with Pakistan doing the worst among the Asian-14. Income per capita levels were important underlying factors, but China, Sri Lanka, and Vietnam—as also Kerala in India—demonstrate that social development is possible even at lower income levels. Even so, there is a connection between the economic and social aspects of development, where the causation runs in both directions. Rising, or higher, per capita income levels are associated with improving, or better, social indicators, and vice-versa.

There is a cumulative causation in the interaction between human well-being and economic development, as the constitutive and the instrumental complement each other through positive feedback mechanisms. Improvements in the well-being of people and the process of economic development reinforce each other, dispensing with the need to mediate between economic growth and social development, creating a virtuous circle that makes for success at development. The opposite is also possible. If the process of economic development does not improve the well-being of people, it might create a vicious circle in which neither growth nor development are sustainable, because the feedback mechanisms between the constitutive and the instrumental are absent or negative. Unequal opportunities for people in terms of access to healthcare and education through public provision can only lead to unequal outcomes in terms of incomes and well-being. Such inequality of outcomes can, in turn, accentuate inequality of opportunities. A relative deprivation in the space of opportunities, and the capabilities that such opportunities create or foster, could lead to an absolute deprivation in the space of outcomes, whether employment, incomes, or assets. Similarly, a relative deprivation in the space of outcomes could also lead to an absolute deprivation in the space of opportunities, and hence the capabilities required for engaging with markets. It should be recognized that unequal opportunities and unequal outcomes could also accentuate each other over time across generations.

(p.200)

Notes:

(1.) For an analysis of the share of Asia in world GDP and its GDP per capita as a proportion of that in industrialized countries, during 1970–2016, see Chapter 2.

(2.) See Okhawa and Rosovsky (1973).

(p.258) (3.) The central Gerschenkron idea was also formalized in several models. See, for example, Nelson and Phelps (1966), Gomulka (1970), and Findlay (1976).

(4.) See, for example, De Long (1988). There is, however, a study by Rodrik (2013) which finds unconditional convergence when the sample is restricted to the manufacturing sector.

(5.) There are empirical studies, for selected countries, which focus on this period to suggest that growth in GDP per capita is negatively related to the initial level of GDP per capita. See, for instance, Barro (1991) and Islam (1995). However, these results depend partly on the choice of countries and of periods.

(6.) Blanchard (2011) provides a detailed discussion.

(7.) See De Long (1988) and Pritchett (1997).

(8.) For average annual rates of growth of GDP per capita, during 1970–2016, see Table 3.2, and for the distinction between high (more than 5 per cent), medium (3.5 to 5 per cent) and low (less than 3.5 per cent) growth rates, see Table 3.3. For initial levels of GDP per capita, see Table 7.4.

(9.) For an analysis of changes in the distribution of Asia’s GDP between each of it constituent sub-regions, and their respective GDP per capita as a proportion of that in industrialized countries, during 1970–2016, see Chapter 2.

(10.) The West Asian oil-exporting countries are Bahrain, Iran, Iraq, Kuwait, Oman, Qatar, Saudi Arabia, and United Arab Emirates. The LDCs are Afghanistan, Bangladesh, Bhutan, Cambodia, Laos, Myanmar, Nepal, and Timore-Leste. The group of other Asian developing countries includes Brunei Darussalam, Maldives, Mongolia, North Korea, Jordan, Lebanon, Palestine, and Syria. The Central Asian countries—Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan—are not included in this residual group because national accounts statistics for these countries are available starting only in 1992.

(11.) It is worth noting that Bangladesh is among the group of Least Developed Countries in Asia. However, it is also included in the Asian-14. If Bangladesh were excluded from the LDCs country-group, the divergence experienced by LDCs would be even greater.

(12.) In terms of GDP per capita, for 1970 and 2016 both, the richest country was Qatar (US$4,921 and US$59,324), while the poorest countries were Laos (US$44) and Afghanistan (US$584), respectively. See UN National Accounts Statistics.

(13.) In 1970, the richest and poorest countries were Qatar (PPP$32,573) and Laos (PPP$533) respectively. In 2016, the richest and poorest countries were Singapore (PPP$32,708) and Afghanistan (PPP$585). See GGDC Maddison online database.

(14.) The Theil index is a measure of inequality based on information theory. If all countries in a continent (or in the world) have exactly the same per capita income, the Theil coefficient would have a value of zero. If all the income in a continent (or in the world) accrues to just one country, the Theil coefficient would have a value of log N where N is the number of countries.

(15.) For an analysis, with supporting evidence, see Wan and Wang (2019).

(16.) For a discussion on trends over time in these sub-regions, see Wan and Wang (2019).

(17.) The Gini coefficient is a measure of inequality that is used by economists. It is best explained with a simple example. If all persons in an economy have the same, equal, (p.259) income, it has a value of zero. If all the income in an economy accrues to just one person, it has a value of 100.

(18.) See, for example, Bourguignon and Morrisson (2002), Cornia (2004), Milanovic (2005), Atkinson and Piketty (2010), Atkinson et al. (2010), Milanovic (2011), Palma (2011), Piketty (2014), Atkinson (2015), and Bourguignon (2015).

(19.) For a more detailed discussion, see Nayyar (2006 and 2013).

(20.) This is highlighted in the literature on endogenous growth theory and new economic geography. See, for example, Romer (1986) and Krugman and Venables (1995).

(21.) For an analysis, with supporting evidence, see Wan (2007) and Wan et al. (2007).

(22.) Between 1992–1993 and 2012–2013, GDP per capita in the agricultural sector as a proportion of GDP per capita in the non-agricultural sector dropped from 14 per cent to 10 per cent (calculated from national accounts statistics and population statistics of India). See also Nayyar (2019a).

(23.) On economic growth and regional inequality in India, see Cherodian and Thirlwall (2015) and Lolayekar and Mukhopadhyay (2017). On the widening gap between the north and the south, see Paul and Sridhar (2015).

(24.) The eleven richer states were Andhra Pradesh, Karnataka, Kerala, and Tamil Nadu from the south, Gujarat, Maharashtra and Goa from the west, and Delhi, Haryana, Himachal Pradesh, and Punjab from the north. The poorer states (the rest), included Assam, Bihar, Jammu and Kashmir, Madhya Pradesh, Odisha, Rajasthan, Uttar Pradesh, and West Bengal, plus the smaller states in the north-east and a few union territories. The states of Chhattisgarh, Telangana, and Uttarakhand, which were created after 1980–1981, are included in the group of their erstwhile state. For the richer states taken together, their per capita income, as compared to that of India was 114:100 in 1980–1981 and 147:100 in 2013–2014. For the poorer states, these ratios were 71:100 and 64:100 respectively. Per capita income refers to per capita GDP at factor cost in 2004–2005 prices. Author’s calculations from EPWRF India Time Series, www.epwrfits.in, based on India’s national accounts statistics.

(25.) For an analysis of regional economic inequality in Indonesia, during 1983–2004, see Akita et al. (2011), who show that as the share of mining has decreased the spatial distribution of manufacturing has played a more important role in shaping regional inequality, while the primacy of Jakarta with its urbanization economies, facilitated by globalization and trade, has determined much of overall regional inequality in Indonesia.

(26.) These are petroleum, coal, and palm oil from Kalimantan, copper, coffee, and cocoa from Sulawesi and agricultural commodities, including timber from Sumatra. But the poor on these islands do not benefit from booms in commodity prices.

(27.) For a detailed discussion, see Rohini Nayyar (1991).

(28.) On the complexity of international comparisons, see Atkinson and Bourguignon (2001) and Deaton (2005).

(29.) This issue is discussed at greater length in Nayyar (2013).

(30.) It might be worthwhile for the interested reader to compare World Bank estimates of poverty with another set of estimates of absolute poverty in Asia that adopt the same poverty lines, for the period 1965–2014, using data on household consumption from the Penn World Tables and statistics on inequality from the UNU-WIDER World (p.260) Income Inequality Database, for its constituent sub-regions and selected countries. See Wan and Wang (2019) in the companion volume.

(31.) The database is provided by 1600 surveys for thirty-six countries in Asia.

(32.) For a critical evaluation, see Chang (2010).

(33.) Using the same poverty lines of PPP$1.90 per day and PPP$3.20 per day, Wan and Wang (2019) show that there was a similar rapid decline in absolute poverty in Asia as well as these selected countries. However, the proportion of the population, and the number of the poor, below both poverty lines is significantly higher in the World Bank estimates than in the Wan and Wang estimates.

(34.) For a systematic analysis of the factors underlying the reduction of absolute poverty in Asia, in which rapid growth was the most important, see Wan and Wang (2019).

(35.) Sen (1999) develops a similar idea in a different context to argue that freedoms are both constitutive of, and instrumental in, development.

(36.) For an analysis of, and discussion on, why employment should be the primary objective of macroeconomic policies for development, see Nayyar (2014).

(37.) In fact, Part Seven of Asian Drama, Volume III, titled ‘Population Quality’ sought to focus on education and health (pp. 1533–1828).

(38.) For a systematic analysis of education and health in the context of economic development in Asia during the past fifty years, see Mundle (2019).