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Economic &
Social Affairs
DESA Working Paper No. 27
ST/ESA/2006/DWP/27
September 2006
Riding the Elephants: The Evolution of World
Economic Growth and Income Distribution at
the End of the Twentieth Century (1980-2000)
Albert Berry and John Serieux
Abstract
is paper presents estimates of world economic growth for 1970-2000, and changes in the
intercountry and interpersonal distribution of world income between 1980 and 2000. ese
estimates suggest that, while the rate of growth of the world economy slowed in the 1980-2000
period, and average within-country inequality worsened, the distribution of world income among
individuals, nevertheless, improved a little. However, that result was wholly due to the exceptional
economic performances of China and India. Outside these two countries, the slowdown in world
growth was even more dramatic, the distribution of world income unequivocally worsened, and
poverty rates remained largely unchanged.
JEL Classifi cation: FO, 13, 04
Keywords: world inequality trends; international income distribution, convergence,
world poverty trends
Albert Berry is Professor Emeritus of Economics at the University of Toronto.
E-mail: berry2@chass.utoronto.ca.
John Serieux is Assistant Professor of Economics at the University of Manitoba.
E-mail: serieuxj@shaw.ca.
Comments should be addressed by email to the authors.
UN/DESA Working Papers are preliminary
documents circulated in a limited number of
copies and posted on the DESA website at
http://www.un.org/esa/desa/papers to stimulate
discussion and critical comment. e views
and opinions expressed herein are those of the
author and do not necessarily refl ect those of
the United Nations Secretariat. e designations
and terminology employed may not conform to
United Nations practice and do not imply the
expression of any opinion whatsoever on the part
of the Organization.
Typesetter: Valerian Monteiro
United Nations
Department of Economic and Social Aff airs
2 United Nations Plaza, Room DC2-1428
New York, N.Y. 10017, USA
Tel: (1-212) 963-4761 • Fax: (1-212) 963-4444
e-mail: esa@un.org
http://www.un.org/esa/desa/papers
Contents
e world since 1980 ...................................................................................................................... 1
Growth trends and changes in the intercountry distribution of income ........................................... 4
e distribution of world income among persons ............................................................................ 7
Major caveats ............................................................................................................................. 15
A clarifi cation with respect to studies showing increasing inequality of world distribution ............... 18
Poverty trends and patterns ............................................................................................................. 19
Summary and conclusions ............................................................................................................... 21
References ............................................................................................................................. 23
Appendix A ............................................................................................................................. 25
Appendix B ............................................................................................................................. 29
Appendix C ............................................................................................................................. 30
Appendix D ............................................................................................................................. 34
Riding the Elephants: The Evolution of World Economic Growth and
Income Distribution at the End of the Twentieth Century (1980-2000)
Albert Berry and John Serieux
e huge gap between the world’s rich and its poor1 has made trends in world inequality a matter of much
interest. at gap appears to have widened markedly during a period beginning in the early nineteenth
century at the latest2 and continuing until at least the middle of the twentieth. Since about 1950 it has been
possible to follow the evolution of inequality with much more precision, given the availability of national
accounts in all major countries and of intracountry inequality measures in an increasing share of them. Most
prior studies have underscored three main points. First, the distribution of world income is highly unequal,
considerably more so than that of any but the most inegalitarian countries (Whalley, 1979; Berry, Bourgui-
gnon and Morrisson, 1983; 1991); this is a natural result of the fact that both intracountry and intercountry
inequalities contribute signifi cantly to world inequality. Second, when the measure of income is absolute
purchasing power (in international prices) the bulk of world inequality comes from intercountry income
diff erences rather than from intracountry diff erences. Finally, the level of world inequality did not change
markedly, in either direction, between 1950 and the mid-1980s (Berry, Bourguignon and Morrisson, 1991;
Bourguignon and Morrisson, 2002; Peacock, Hoover and Killian, 1988; Schultz, 1998).
Updated and wider-ranging analysis of recent patterns and trends of world inequality is warranted,
partly because the period since about 1980 has brought a wave of historic changes in several regions of the
world and in the character of the world economy, and partly because a variety of theories and pieces of fac-
tual information suggest that past distributional patterns might be changing. eories of economic conver-
gence, which have received much attention in recent years, tend to support the presumption that globaliza-
tion, with its increasing economic integration among countries, would strengthen the forces of convergence
and lower world inequality (Barro, 1991; Barro and Sala-i-Martin, 1992; Ben-David, 1993). On the other
hand, many countries have suff ered signifi cant increases in internal inequality over the last couple of decades,
with some authors suggesting that this trend is causally related to globalization and market-friendly econom-
ic reforms (Wood, 1994; Robbins, 1996). Has this intracountry pattern of increasing inequality been strong
enough to off set the eff ects of any impulse toward intercountry convergence, if indeed both of these eff ects
can be shown to exist?
With slower world economic growth since the 1970s, any serious increase in inequality might mean
a derailment of the process of poverty reduction that had been fairly continuous over the post-war period.
Concern on this point has been fuelled by two studies from the World Bank (Milanovic, 2002; Dikhanov
and Ward, 2001), referring to the period 1988-1993 and reporting signifi cant increases in inequality (of 3-4
percentage points in the Gini coeffi cient) over that period.3 If this result were accurate, and if the trend were
1 Poverty is defi ned here by per capita income of the family to which a person belongs, with the income data for each
country converted to a common base (international dollars) in such a way as to imply that the poverty line involves
the same ‘purchasing power’ in each country. e many methodological and data diffi culties confronted in trying to
achieve this goal are discussed below.
2 Estimates by Bourguignon and Morrisson (2002) go only as far back as 1820, though Lindert and Williamson (2001)
suspect that the widening may have been occurring for some time before that point.
3 Later calculations by Milanovic (2005) suggest that this ‘spike’ in inequality was not reproduced (in similar magnitude)
for the 1988-1998 period.
2 DESA Working Paper No. 27
to continue at anything close to the rate they estimate, the world could be in for an increase in inequality
strong enough to imply an end to a long period of gradual reduction in the incidence of poverty.
With such issues in mind, this paper examines the evolution of world income and its distribution
across regions, countries and individuals over the period 1980-2000. e aim is to identify the main trends,
to determine whether they support common perceptions about regional and country performances, and to
see how important these trends have been in the overall pattern of changing world inequality during that
period. To that end, the next section examines the theoretical approaches to the issue of global income dis-
tribution since 1980 and the degree to which they inform current concerns. e following section presents
estimates of the weighted average growth of the world economies from 1970 to 2000 and measures of the
intercountry distribution of world income. e next three sections present estimates of the distribution of
world income between persons (based on a methodology outlined in Appendix C) followed by caveats and
clarifi cations related to those estimates. e penultimate section presents data on changes in world poverty
during the 1980-2000 period. e paper concludes with a brief review of the issues, results and implications.
The world since 1980
e 1980s and 1990s have seen several profound changes both in the nature of economic interaction
between countries and in the economic and political fortunes of certain regions and countries. Prominent
among these changes have been:
the break-up of the Soviet bloc and the transition of its former members toward the market
system;
accelerated growth and an increasing role of the market in the Chinese economy;
a long-awaited period of good growth in India;
the fi rst prolonged slump for the Japanese economy in the post-war period, suggesting that its
period as the only fast growing high-income country has come to an end;
the international debt crisis of the 1980s, that made this a ‘lost decade’ in South and Central
America;
a severe regional crisis in sub-Saharan Africa due not only to the extended crisis of heavily
indebted poor countries (HIPCs)––most of which are in sub-Saharan Africa––but also to an un-
derlying failure of agriculture to grow at a satisfactory rate, rapid population growth and, more
recently, the traumatic incursion of AIDS;
the ‘information revolution’ featuring the arrival en masse of computer technology;
a general policy shift in nearly all countries towards a greater use of the market in resource al-
location; and fi nally
‘globalization’––the increasingly tight interaction among national economies, to the point where
the economic raison d’être of the national state is increasingly called into question.
Viewing these changes along more ‘systemic’ lines, a number of authors have argued that the years around
1980 have constituted a ‘watershed’ between a previous relatively successful phase of ird World growth
during which per capita output rose at a healthy rate (by about 2.2 per cent from the end of World War II
until 1978), in Bairoch’s periodization (Bairoch, 1997, vol. 3: 997-1000), that allowed some narrowing of
the (intercountry per capita income) gap with the rich industrial world, and a subsequent period of slow and
erratic growth, during which most of the ird World lost ground to the rich countries of the West. Ar-
righi (2002) attributes the transition to the fact that the United States of America, previously a major capital
•
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•
•
•
•
•
Riding the Elephants: The Evolution of World Economic Growth ... 3
exporter, became a major importer of capital, leading directly to the debt crisis of the 1980s and to the rise
in real interest rates, a shift to which many authors give great weight in explaining subsequent problems
(Easterly, 2001; Galbraith, 2002). While a few developing countries did manage to achieve sustained growth
over this period, it is often seen as one of bifurcation within the ird World, with the majority of countries
doing badly in this most recent phase (Easterly, 2001; Milanovic, 2005).
Opinions vary widely on the anticipated eff ects of some of these events and trends. One prominent
view, derived in part from trade theory, is that national economies which interact increasingly with each
other will converge (Barro, 1991; Barro and Sala-i-Martin, 1992; Ben-David, 1993), either through a ten-
dency for such interaction to equalize the returns to factors of production across countries and/or through
technological diff usion, which suggests important advantages to being a follower, rather than a leader, and
thus being able to borrow abroad to invest and to have low-cost access to the technological innovations made
elsewhere. Much of the vast literature that relates overall economic growth in developing countries to export
performance may be considered to fall broadly into this latter category (see the reviews in Bliss, 1989, and
Evans, 1989). Similarly, the neoclassical growth model predicts convergence in per capita incomes among
countries because poorer countries with higher marginal rates of return to capital will grow faster than (and
attract capital from) richer countries with lower marginal rates of return (Solow, 1956). Allowing for diff er-
ent steady states or augmenting the neoclassical model with human capital, and some specifi cations of new
growth models, predict less strong or conditional convergence, which maintains the expected higher growth
rate for poorer countries but allows for persistent diff erences due to varying rates of physical and human
capital accumulation and population growth between countries (Mankiw, Romer and Weil, 1992).4
Counterpoised against these theories is the idea that there are powerful centrifugal forces in the
world economy, ranging from the extreme case in which rich countries straightforwardly control and exploit
the weaker through the use of power, to less directly power-related mechanisms, as in the core-periphery
model, that nonetheless produce a similar outcome. Beyond these propositions, the majority of new growth
models predict either sustained inequality in country incomes or outright divergence. Several empirical stud-
ies have concluded that, at the world level, divergence among mean country incomes has been the prevailing
pattern (Pritchett, 1995; UNCTAD, 1997) and hence that the world distribution of income has become
substantially more unequal over the last few decades (Korzeniewicz and Moran, 1997; UNDP, 1999).
Dramatic conditions at the two ends of the world distribution persuade many people that inequality
must have risen. e Forbes 1999 survey of the world’s richest put Bill Gates well ahead of the pack of 465
billionaires with a wealth of 90 billion, and reported that this group had a total wealth of around 1.5 tril-
lion dollars (Dolan, 1999). In 1997 the low-income countries, with just over 2 billion people, had a com-
bined gross national product (GNP) of just half this amount when converted to US dollars at the countries’
exchange rates, or about twice that level when converted at purchasing power parity (PPP)(World Bank,
1999: 191). In a similar vein, the United Nations Development Programme’s Human Development Report
1999 (UNDP, 1999) reported that the three richest people in the world have more than the combined GNP
of all (43) least developed countries and their 600 million people. Meanwhile, conditions at the bottom
end remain abysmal, not only in income terms per se but also in other respects. Bales (1999) estimated that
27 million people around the world remain in ‘violent economic bondage’, from prostitutes in ailand to
bonded farmers in India and child workers in many countries. Chen and Ravallion (2004) reported that 1.1
4 A more technical interpretation is that countries with diff erent rates of accumulation are evolving to diff erent steady
states, and thus, convergence is conditioned on the steady state.
4 DESA Working Paper No. 27
billion people (or 21 per cent of the world’s population) were living on less than one 1993 international dol-
lar a day in 2001, and that that number had remained essentially unchanged since 1996.
Whether the sources of convergence or of divergence have, on balance, been the stronger, the pat-
tern is unlikely to have been a very simple one. During much of the twentieth century there was a partial
convergence in the sense that the fastest growing countries were neither those at the top nor those at the bot-
tom of the income hierarchy, but rather a subset of middle-income ‘follower’ countries, among which Japan
and the Soviet Union were, for much of the period, the most prominent. While these countries were gaining
on the leaders, the group of low-income countries below them was not. is pattern has changed since the
late 1970s when China, a (then) low-income country with about a fi fth of the world’s population, began to
register fast growth, thereby contributing to the equalization of world distribution. Since the early 1980s,
India’s growth has also accelerated, albeit less dramatically than China’s. Two other large low-income coun-
tries, Indonesia and Pakistan, have (until recently) put in relatively strong growth performances. e poorer
performing countries of Africa, a region yet to achieve a strong take-off and still experiencing rapid, though
now falling, population growth, are home to an increasing share of the world’s poor.
ere is little overlap between theories that address the question of convergence among countries
in per capita income and those which focus on intracountry distribution although, naturally, some of the
same aspects of economic life are assumed to be at work in both cases (e.g., international trade, technologi-
cal change). e benchmark theory with respect to intracountry distribution is Kuznets’ (1955) idea that the
level of inequality would fi rst rise, then fall, over the course of development. at view has lost currency over
the last few decades, and similar results could be expected from the combined implications of the dual econ-
omy model and the effi ciency wage theory or the Harris-Todaro models of development economics.5 But
any current consensus on the long term changes in internal distribution is probably limited to a few rather
obvious points, e.g., that an equalization over time in the distribution of such important assets as agricultural
land and human capital will tend to produce a more equitable distribution of income.
Whatever the expectations may have been for the pattern of intracountry distribution, the overall
experience of the 1980s and 1990s is generally recognized to have been negative, in both developed and
developing countries (Corry and Glyn, 1994; Berry and Stewart, 1997; Cornia, 2004). Increases in interna-
tional trade and technological change have been cited as possible causes of the frequent episodes of increas-
ing inequality within both developed and developing countries. In the United States they are the main
candidates discussed (Wood, 1994; Bound and Johnson, 1992). In developing countries the analysis is less
far advanced but these phenomena are again among the suspects. Both are discussed in the context of the in-
creasing earnings gaps between more and less skilled workers that have been observed in many less developed
countries (Robbins, 1996).
Growth trends and changes in the intercountry distribution of income
is paper presents evidence on the world distribution of income among persons over the period 1980-
2000, and notes some of the more obvious possible links to the monumental events of the last two decades.
5 e predictions of these models combined would suggest that, at the very earliest stages of development, the
distribution of income in the dominant traditional sector would tend to determine overall inequality. However, as the
high-wage modern sector grows at the expense of the low-wage traditional sector, intersectoral inequality would add to
intrasectoral inequality to cause overall inequality to increase. Eventually, as the modern sector begins to dominate the
economy, intrasectoral inequality (this time in the modern sector) would again become the dominant contributor to
overall inequality as intersectoral inequality fades in importance with the disappearing traditional sector.
Riding the Elephants: The Evolution of World Economic Growth ... 5
Of particular interest is the question of whether or not the impact of economic integration has been closer to
the hopeful predictions of the optimists or the worrisome prognoses of the pessimists.
e period 1980-2000 was punctuated by economic crisis in many countries of the ird World,
especially those of South and Central America, sub-Saharan Africa, and most of the former Soviet bloc.
However, this was also a period of continuing fast growth for most of East Asia (including China at an
impressive 6-9 per cent per year),6 and of a stronger performance by the Indian subcontinent than had been
the case during most of the post-colonial period, especially by India itself with a rate of nearly 6 per cent per
year. e developed countries of Europe and North America grew at 2 to 3 per cent per year (see table 1),
Japan decelerated substantially to a low of 1.6 per cent in the 1990s, and the former Soviet bloc countries
underwent marked economic contractions in the early 1990s.
e 1980s saw a slowdown in the weighted average rate of growth of the world’s economies to 2.9
per cent from the 3.8 per cent achieved in the 1970s. is deceleration was the net result of three divergent
patterns among the various regions (table 1). South Asia joined East Asia as a high-growth region; Western
Europe and North America experienced moderate slowdowns; and all the other regions (sub-Saharan Africa,
South and Central America, Eastern Europe, and the Middle East) suff ered sharp declines in growth.
e 1990s brought modest changes to most regions. In particular, a moderate slowdown in East Asia
(the combined result of the slowdown in the Japanese economy and the East Asian crisis), a moderate decline
in Western Europe, a moderate increase in North America, continued brisk growth in South Asia, and slow
growth in sub-Saharan Africa. e exceptions were South and Central America and the Middle East with
marked accelerations, and the dramatic collapse of the former Soviet bloc (Eastern Europe and Central Asia).
e net eff ect was a further deceleration in world economic growth to just 2.5 per cent.7
At the income-group level, the pattern of world growth was similarly complex (table 2). Africa’s
weak performance notwithstanding, the per capita income in the poorest countries as a group (i.e., the
6 Several authors have argued that the offi cial fi gures overestimate the actual growth of the Chinese economy,
though the exact degree of overestimation is not clear. Reasonable accuracy is especially important in light of the
size of that country. We conclude that, even with the most extreme assumptions, the growth rate would almost
certainly fall between 6 per cent and 9 per cent per annum. Wu (1998), after examining offi cial and alternative
estimates, concluded that China’s offi cial fi gures underestimated output up until the late 1980s and that the
growth rate was overestimated by at least 2 per cent since the late 1970s. Using these presumptions and the range
of alternative estimates provided by various authors (Keidel, 1992; Maddison, 1999; Ren, 1997; Wu, 1998) we
recalculated China’s output levels (in international dollars) for the 1979-2000 period based on an assumption
of a 10 per cent underestimate of (World Bank-reported) GDP (in domestic currency) in 1987, and a consistent
overestimate of growth of 2.5 per cent. Fortunately, though these adjustments to the offi cial data lower both the
estimated average growth of the world economy and the degree of improvement in the distribution of world
income, the impact is not overly sensitive to the size of the adjustments themselves. In effect, any combination of
adjustments within the range suggested by Keidel (1992), Wu (1998) and Maddison (1999) leads to similar results.
Appendix table B1 compares our output estimates for various years with the offi cial estimates. Appendix table
B2 reports the sensitivity of world distribution to the choice of assumptions about the level of underestimation of
1987 GDP and the overestimation of the GDP growth rate. While acceptance of the offi cial Chinese data implies a
more positive trend in global income inequality and slightly faster world income growth than does the use of our
adjusted fi gures, the general pattern of change is the same.
7 Estimates of world economic growth rates vary according to the details of the methodology, including such factors as
the base years chosen at which to make PPP conversions to a standard currency. But there seems to be no disagreement
that world growth did slow down since about 1980. Milanovic (2005: 57), for example, gives per capita GDP growth
rates of 3.3 per cent over 1960-1978 and 1.6 per cent over 1978-2000, somewhat higher than ours for similar but not
identical periods, but showing about the same amount of deceleration.
6 DESA Working Paper No. 27
Table 1.
Average annual rate of output growth by region and sub-period, 1970-2000a
Weighted country averagesb
Real GDP Real per capita GDP
Region 1970-1980 1980-1990 1990-2000 1970-1980 1980-1990 1990-2000
Sub-Saharan Africa 3.16 1.97 2.01 0.29 -0.96 -0.62
East Asia 4.63 4.98 4.06 2.75 3.50 2.92
South Asia 3.31 5.65 5.53 0.90 3.42 3.67
Central and South America 5.56 1.24 3.11 3.21 -0.77 1.44
Middle East 6.04 2.21 3.38 3.19 -0.79 1.35
Eastern Europe 5.17 1.70 -3.47 4.31 0.98 -3.40
Western Europe 2.99 2.48 2.06 2.38 1.97 1.57
North America 3.16 2.55 3.15 1.73 1.34 1.84
Industrial countries 3.14 2.75 2.41 2.35 2.16 1.74
Transitional economies 5.17 1.70 -3.41 4.31 0.98 -3.40
Developing countries 4.75 3.59 4.63 2.47 1.53 2.94
World 3.81 2.86 2.46 1.94 1.16 1.06
Sources: Authors’ calculations using data from the WDI (online), UN Common Database (UN) and the Penn World Tables --
Mark 5.6 (CIC).
a. e sample used for the construction of this table consists of 136 countries, a smaller sample than that used for income
distribution estimates. is is largely because of the extension of coverage to the 1970s (a time during which many of the countries
did not yet exist, were at war, or had poor statistical data). Also, because no data on the former Soviet Republics is available for the
1970s, for comparison purposes the Soviet Union is treated as a single (lower middle-income) country through to 2000.
b. e regional and world growth rates are the output-weighted sums of the individual country growth rates. ese (average
annual) country growth rates were estimated from constant price measures of output in local currency then, to ensure
comparability (in purchasing power values of output) growth estimates were weighted by current international dollar (PPP)
estimates of GDP at the beginning of each decade.
Table 2.
Average annual rates of output growth by country income group (1970-2000)
Weighted country averages
Real GDP (Domestic currency) Real per capita GDP (Domestic currency)
Country income categories 1970-1980 1980-1990 1990-2000 1970-1980 1980-1990 1990-2000
Low-income 3.58 4.87 4.66 1.08 2.49 2.59
Lower middle-income 4.87 3.42 1.32 3.05 1.85 0.23
Upper middle-income 5.94 1.52 3.27 3.81 -0.31 1.87
High-income 3.14 2.75 2.42 2.35 2.16 1.74
Low-income without India 4.18 3.90 3.39 1.46 1.28 1.06
Lower middle-income without China 5.23 2.55 -1.10 3.44 0.83 -2.23
China and India 3.74 6.32 6.85 1.72 4.57 5.46
World without China 3.78 2.69 2.14 1.91 0.92 0.63
World without China and India 3.82 2.58 1.96 2.05 0.91 0.53
World without Eastern Europe 3.64 3.03 3.18 1.68 1.24 1.67
World without China and Eastern Europe 3.60 2.84 2.86 1.59 0.94 1.20
World without China, India and E. Europe 3.63 2.71 2.70 1.71 0.90 1.08
World 3.81 2.86 2.47 1.94 1.16 1.06
Sources: Authors’ calculations using data from the WDI (online), UN Common Database (UN) and the Penn World Tables --
Mark 5.6 (CIC).
Riding the Elephants: The Evolution of World Economic Growth ... 7
World Bank’s ‘low income’ category) grew faster than in the rich ones during both the 1980s and the 1990s,
with an average gap of 0.6 per cent over the two decades. is diff erential would have been even wider, and
contributed to a greater reduction in world inequality, had demographic trends been similar between these
country groupings. With both the substantially faster population growth in the low-income countries taken
into account and India excluded from that group, the result is slower per capita growth than in the high-in-
come countries, creating a source of income divergence. India’s presence in the low-income group of coun-
tries can, therefore, be thought of as the source of convergence of that category towards the higher ones.8
In a departure from the pattern of the 1970s, when the middle-income countries as a whole substan-
tially outgrew both the low-income and the high-income groups, this category suff ered serious deceleration
in the 1980s and 1990s (table 2). In the 1980s it was the upper middle-income countries that suff ered the
largest drop in output growth (from 5.9 to 1.5 per cent) as per capita growth became negative––a refl ection
of the crises in South and Central American economies. In the 1990s the lower middle-income group met
this fate. Even with the impressive performance of China, that category showed almost zero growth in per
capita income (0.23 per cent). Excluding China, the average decline in per capita income was a dramatic 2.2
per cent per year—refl ecting the economic implosion that occurred in Eastern Europe and Central Asia.
e crucial role of China and India in determining changes in the intercountry pattern of distribu-
tion of world output since 1980, suggested by tables 1 and 2, is confi rmed by the conventional measures
of income inequality. e Gini, eil, and three Atkinson measures reported in table 3 all indicate a mod-
erate improvement in world intercountry inequality in each decade between 1980 and 2000.9 However,
when China and India are excluded the pattern is reversed, with all measures indicating deterioration in the
distribution of world income, often of roughly comparable magnitude to the improvement that occurs when
they are included. e exclusion of India alone does not reverse the trend. e exclusion of China alone
does so for the Gini coeffi cient and to a lesser extent the eil and Atkinson (0.5) measures as well, but the
Atkinson (1) suggests no change and the Atkinson (2), which gives most weight to changes at the bottom of
the income ladder, continues to suggest an improvement––an eff ect of the improving situation in India. e
exclusion of Eastern Europe alone generally reinforces the overall trend of improvement. (Figure 1 presents
the changes in Gini coeffi cient values depending on which countries are excluded).
e dramatic eff ect of the growth performance of China and India on measures of intercountry
income inequality is perhaps best illustrated by a disaggregation of the eil coeffi cient, presented at the bot-
tom of table 3. In 1980, over a quarter of estimated intercountry income inequality could be attributed to
the low income levels of China and India. In 2000, however, these countries’ contribution to world inequal-
ity was negative, i.e., their presence made the intercountry distribution of world income more equal!
The distribution of world income among persons
Although prior analyses concur on the conclusion that, at the world level, most of the inequality among per-
sons is the result of diff erences in average incomes across countries, intracountry inequality is also signifi cant
and changes therein could have an important impact on the level of world inequality among people. e fact
8 ough China was also a low-income country through most of that period, it had graduated to the lower middle-
income category by 2000 and is thus included in that group for these calculations.
9 e Atkinson coeffi cients are implied welfare-based measures of inequality. As the number shown in brackets increases,
income transfers near the bottom of the distribution have a stronger eff ect on the inequality measure. See Appendix C
for a more detailed description of these measures.
8 DESA Working Paper No. 27
Table 3.
Intercountry income inequality measures
Country group Year Gini Theil Atkinson (0.5) Atkinson (1) Atkinson (2)
All countries 1980 0.585 0.700 0.288 0.503 0.695
1990 0.578 0.636 0.275 0.471 0.654
2000 0.553 0.559 0.251 0.428 0.623
World without China 1980 0.537 0.622 0.247 0.463 0.695
1990 0.558 0.629 0.258 0.467 0.688
2000 0.567 0.630 0.264 0.467 0.685
World without India 1980 0.560 0.674 0.268 0.490 0.709
1990 0.564 0.631 0.263 0.468 0.678
2000 0.547 0.574 0.246 0.436 0.658
World without China and India 1980 0.473 0.512 0.198 0.401 0.680
1990 0.510 0.572 0.224 0.436 0.706
2000 0.541 0.634 0.249 0.469 0.730
World without Eastern Europe 1980 0.606 0.751 0.313 0.528 0.702
1990 0.593 0.678 0.296 0.492 0.662
2000 0.563 0.591 0.263 0.446 0.637
Contribution of China and India to world inequality (Theil coeffi cient-based analysis)
1980 1990 2000
China’s contribution to international inequality 11.1% 1.0% -12.6%
India’s contribution to international inequality 3.7% 0.8% -2.6%
The combined contributions of China and India 26.9% 10.0% -13.3%
Sources: Authors’ calculations using data from the WDI (online), UN Common Database (UN) and the Penn World Tables
– Mark 5.6 (CIC).
Note: Because this analysis is based on country per capita GNP fi gures, the eff ect of changes in intracountry distributions of
income is absent. e above results, therefore, overstate the positive contribution of rapid growth in China to distribution of world
income among persons because the distribution of income within China was deteriorating during these periods. However, as is
seen in table 6 below, when intracountry distribution is included the eff ect remains positive (though less pronounced).
Figure 1:
Evolution of between country inequality (Gini coefficient values)
0.450
0.470
0.490
0.510
0.530
0.550
0.570
0.590
0.610
0.630
0.650
1980 1990 2000
Without Eastern Europe
All countries
Without China
Without China and India
Source: Table 3.
Riding the Elephants: The Evolution of World Economic Growth ... 9
that many developing and most major developed countries suff ered worsening income distribution during
the 1980s (known, especially in the United States, as the ‘greed decade’) or the 1990s, makes this a possibil-
ity to be reckoned with.
Among the 25 large countries10 for which reasonably comparable Gini coeffi cient estimates from
the beginning and end of the 1980s are available (from the WIDER World Income Inequality Database and
the 2001 World Development Indicators), 14 recorded increases in the Gini coeffi cient11 (i.e., a worsening
distribution of income) while 10 recorded decreases (i.e., improved distribution) and one saw no change.12
In the 1990s, the general deterioration of intracountry income distribution appears to have been even more
acute. Of 27 countries for which comparable Gini coeffi cient estimates were available, 18 suff ered increas-
ing inequality and only eight recorded an improvement. In the 1990s, as they attempted the transition to
capitalism, the great majority of the Eastern European and Central Asian countries with available data expe-
rienced worsening inequality. China, while going much less far along the path of economic reform than the
former Soviet bloc countries, also appears to have experienced the negative eff ects of growing market forces
on distribution.
To include within-country income in our estimates of the distribution of world income, all large
countries were divided into fi ve, ten or forty income groups based on estimates of the distribution of income
among persons for the relevant years (1980, 1990 and 2000). us, the world of 163 countries (used for
estimating intercountry inequality) was decomposed into one of 383 income groups, of which 255 were sub-
national income groups with an identifi able range of income.13 ese income groups accounted for 85 per
cent of the population of the countries represented and 81 per cent of total world population in 2000. is
methodology is detailed further in Appendix C.
With both intra and intercountry income diff erences taken into account, our best estimate of the
1980 decile distribution of world income among individuals (ranked by per capita household income, and
converted to current international dollars using PPP rates) implies a Gini coeffi cient of 0.651, a eil coef-
fi cient of 0.891 and a ratio of 73.7-fold between the average income of the top decile and that of the bottom
one (table 4).14
Between 1980 and 1990, all of the indicators we use suggest that the overall level of world inequal-
ity declined at least slightly. e Gini coeffi cient fell to 0.648 (from 0.651) and each of the various Atkinson
coeffi cients dropped a little (table 4). e eil coeffi cient fell more noticeably, from 0.891 to 0.845. Between
1990 and 2000 all of the indicators fell again, some by a bit more than in the 1980s and some by a bit less.
10 By our defi nition, large countries are those with populations of over 25 million.
11 Gini coeffi cient estimates are considered comparable if they derive from similar enumeration and measurement
approaches. us, income distribution estimates that use households as the enumeration and income as the
measurement unit are not compatible with those that use persons as the enumeration unit or those that use
expenditure as the measurement unit.
12 Since very few countries have annual measurements of income inequality, the end/beginning of decade inequality
measures had to be approximated in most instances from years close to the beginning or end of the decade. us, the
1980 distribution was often approximated by an estimate from the period 1978-1983; the 1990 distribution from
measures from the period 1988-1992; and the 2000 estimate from the latest distribution beyond 1995.
13 is means, of course, that 128 small countries are still treated as single income groups, but sensitivity analyses indicate
that, because they represent only 15 per cent of the total population, further subdivision of these countries (into
income groups) would add little to the accuracy of the inequality estimates.
14 See Appendix C for a description of the method used in estimating the distribution of world income among persons or,
more precisely, among sub-country income groups.
10 DESA Working Paper No. 27
e ratio of average top decile income to average bottom decile income fell from 73.7 in 1980 to 69.0 in
1990 and to 66.7 in 2000. ough all of the inequality measures we use indicate at least a mild improvement
in the distribution of world income over the two decades, the 2000 distribution does not Lorenz dominate ei-
ther the 1990 or 1980 distributions, nor does the 1990 distribution Lorenz dominate the 1980 distribution.15
All of the bottom six deciles gained in income share in both decades; the six combined moved up
markedly from a share of 11.3 per cent in 1980 to 12.6 per cent in 1990 and 14.0 per cent in 2000. e los-
ing deciles were 7, 8 and 9, their share falling sharply from 42.1 per cent in 1980 to 36.7 per cent in 2000,
while the top decile gained over two percentage points, from 46.6 per cent in 1980 to 49.3 per cent in 2000.
Much of the gain achieved by the bottom deciles refl ects the fast growth in China and India. e fact that
the deciles near the top were unable to hold onto their share was the combined result of poor growth of per
capita income in the upper middle-income countries (South and Central America in the 1980s and Eastern
Europe in the 1990s) and the widening income gaps within the high-income countries.16 e world’s poorest
were, generally speaking, substantially better off in 2000 than in 1980. e bottom 20 per cent (40 per cent)
enjoyed an income increase of 50 per cent (59 per cent) over the 20-year period. e temporal and geo-
graphic nature of that improvement will be discussed in the next section.
15 One distribution is said to Lorenz dominate another one if the Lorenz curve corresponding to the former lies nowhere
below and is at least sometimes above the Lorenz curve corresponding to the other distribution.
16 In eff ect, these income groups consist largely of small upper middle-income countries and the middle classes of the
large upper middle-income countries, together with the lower-income groups of the large wealthy countries.
Table 4.
Decile distribution of world income among persons, and associated inequality measures
Income shares by decile of world population (%)
Change in
share of total
world income
Annual income growth (1985
PPP value of income)
1980 1990 2000
1980-
2000 1980-1990 1990-2000
Decile 1 0.63 0.71 0.74 0.11 2.4% 1.8%
Decile 2 1.09 1.29 1.32 0.23 3.0% 1.6%
Decile 3 1.45 1.69 1.90 0.44 2.8% 2.5%
Decile 4 1.90 2.12 2.46 0.56 2.4% 2.9%
Decile 5 2.51 2.75 3.18 0.67 2.2% 2.8%
Decile 6 3.71 4.07 4.39 0.68 2.2% 2.1%
Decile 7 6.73 6.23 6.41 -0.32 0.5% 1.6%
Decile 8 12.34 10.89 10.19 -2.16 0.0% 0.7%
Decile 9 23.06 21.61 20.13 -2.93 0.6% 0.6%
Decile 10 46.57 48.64 49.28 2.71 1.7% 1.5%
World 100.00 100.00 100.00
Measures of inequality 20-year change in inequality measure
Gini coeffi cient 0.651 0.648 0.639 -0.012
Theil coeffi cient 0.891 0.845 0.802 -0.089
Atkinson (0.5) 0.349 0.343 0.332 -0.017
Atkinson (1) 0.590 0.570 0.552 -0.038
Atkinson (2) 0.792 0.773 0.763 -0.029
Ratio of top to bottom decile incomes 73.7 69.0 66.7
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database (UN), Penn World Tables – Mark
5.6 (CIC) and WIID (WIDER).
Riding the Elephants: The Evolution of World Economic Growth ... 11
What is perhaps most intriguing, and at fi rst glance paradoxical, about the outcome for 1980-2000
is that, though no previous post-war period seems to have been characterized by as general a pattern of
intracountry worsening of distribution as this one, the overall level of inequality has moved in the opposite
direction, again in contrast to the previous tendency of near constancy over the preceding decades (Berry,
Bourguignon and Morrisson, 1991: 73; Bourguignon and Morrisson, 2002: Table 1).
Among other studies using the same methodology (conversion among currencies by International
Comparison Programme (ICP) indices of the United Nations Statistics Division and the University of Penn-
sylvania, and national accounts-based fi gures for average income of each country), the fi nding of constancy
or decline in global inequality over the past couple of decades appears to be the norm. Studies diff er more in
the absolute level of inequality that they report. is is not surprising because most methodological diff er-
ences are likely to lead to fairly systematic diff erences over time between any two studies. Judged by the Gini
coeffi cients, whereas our fi gures indicate a very small decrease in inequality (from 0.651 in 1980 to 0.639
in 2000), Bhalla (2002: 84) fi nds a somewhat greater decline from a higher level (0.687 in 1979 to 0.676
in 1989 and 0.660 in 1999) while Sala-i-Martin (2002: 60) reports a decline from 0.638 in 1980 to 0.630
in 1990 and 0.609 in 1998. Perhaps the faster fall in inequality reported by these two studies than ours is
substantially due to the fact that we adjusted the offi cial Chinese data and they did not. When we used the
unadjusted offi cial fi gures, our Gini estimates also fell by one percentage point in the 1980s and two in the
1990s (table B2).17 If we include Bourguignon and Morrisson (2002) data for 1980 to 1992 (Ginis of 0.657
and 0.663, respectively) as approximating the story of the 1980s, all four studies come up with minimal
change in the Gini coeffi cient over that decade (one percentage point or less), but Bhalla (2002) and Sala-
i-Martin (2002) fi nd larger declines of a couple of percentage points in the 1990s compared to our 0.9
percentage point. Milanovic (2005: 118) reports a decline of 0.6 over the slightly diff erent period 1988-1998
for a common sample of countries, a decline that might be a little bigger had he converted to a common cur-
rency only in one year, as we did. Overall then, in light of a variety of diff erences in details of the methodol-
ogy, adjustment of offi cial data made or not made, and decisions with respect to which source of intracoun-
try inequality to accept, these modest diff erences in estimates and in trends are reassuring.
As noted, world inequality refl ects, in large part, the huge diff erences in average income levels
across countries. Expressed in terms of the eil index, which has the advantage of being decomposable in a
straightforward way, this factor accounted for over three-quarters (75.8 per cent) of overall world inequality
in 1980, while just 24.2 per cent refl ected intracountry inequality (table 5). ese proportions had changed
to 66.1 per cent and 33.9 per cent respectively by 2000, refl ecting the general deterioration of intracoun-
try distribution evidenced by the rising Gini coeffi cients mentioned earlier, as well as the rapid decline of
the intraregional between-country component of overall inequality over the period. Diff erences in average
incomes across the six regions by themselves accounted for around 45 per cent of total inequality in all three
decades (though the Gini coeffi cient refl ecting the actual level of inequality fell from 0.426 in 1980 to 0.370
in 2000). e average level of intraregional between-country inequality (i.e., the weighted mean of inter-
country income diff erences within a region) fell by nearly one third (from 0.274 in 1980 to 0.189 in 2000)
leading to a rapid contraction in its share of overall inequality (from three-fi fths to only slightly more than
two-fi fths).
17 Another source of diff erence with Bhalla’s study is that his distribution data for India show no net change over the
decades (Bhalla, 2002: 46) whereas our estimate is of an increase from 0.417 to 0.445. (Our estimate is higher in
absolute terms since we have adjusted the expenditure Ginis to the income concept in order to make them comparable
to the data for other countries).
12 DESA Working Paper No. 27
With its large share of world population, China’s economic evolution is obviously important to what
happens at the world level. Since its growth performance has substantially outpaced other countries’ in the
period under discussion, and since its economic system has unique features, it is also of interest to ask what
happened to distribution (and to growth) in the world outside China over these years. With China excluded,
the Gini coeffi cient rises by about three percentage points, the eil coeffi cient by about four points and the
Atkinson (0.5) by nearly three points, while the other two Atkinson indices show less or no signifi cant change.
Noticeably, the indices that do not rise are those more sensitive to what happens at the bottom of the distribu-
tion. is is because, even without China, the bottom deciles did better than those in the upper-middle part
of the distribution (table 6). us the presence of China signifi cantly changes our estimated outcome over this
twenty-year period from a modest, but clear, decrease in inequality to a worsening––at least as judged by most
of the indicators. Interestingly, the pattern of change varies less than do the summary measures. Even with
China excluded, the bottom deciles gain in income share though now only the bottom four instead of six,
and by a more modest amount (from 4.9 per cent of total income to 5.4 per cent). Meanwhile, the top decile
records a dramatic gain of over 6 percentage points, while the second highest decile almost holds its own and
deciles 5-8 suff er a sharp net loss of share from 31.8 per cent to 25.5 per cent. With gains by the top and
bottom at the expense of the middle, the ratio of the income of the top decile to that of the bottom one rises
from about 76 in 1980 to 80 in 2000. It is noteworthy that to a considerable degree the same trends charac-
terized both the 1980s and the 1990s, despite the markedly diff erent events taking place in each.
e major redistribution of income within the top two-thirds of the (China excluded) world
distribution refl ects both diff erential growth (e.g., the poor performance of the former Soviet Union) and
increases in intracountry inequality in the higher income countries. Since the growth of the world without
Table 5:
Sources of world income inequality
(Based on the additive separability property of the Theil coeffi cient)
Theil inequality measures 1980 % 1990 % 2000 %
As measured (with only large-country inequality considered)
Interregional inequality 0.426 47.8 0.393 46.6 0.370 46.1
Average intraregional (intercountry) inequality 0.274 30.8 0.243 28.7 0.189 23.6
Total intercountry inequality 0.700 78.6 0.636 75.3 0.559 69.7
Average intracountry inequality
(when limited to large countries) 0.191 21.4 0.209 24.7 0.243 30.3
World income inequality (as measured in this paper) 0.891 100.0 0.845 100.0 0.802 100.0
Including small-country inequality
Interregional inequality 0.426 46.1 0.393 44.6 0.370 43.7
Average intraregional (intercountry) inequality 0.274 29.7 0.243 27.6 0.189 22.4
Total intercountry inequality 0.700 75.8 0.636 72.2 0.559 66.1
Average intracountry inequality
(when extrapolated to all countries) 0.223 24.2 0.245 27.8 0.287 33.9
World income inequality (implied) 0.923 100.0 0.881 100.0 0.846 100.0
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database (UN), Penn World Tables – Mark
5.6 (CIC) and WIID (WIDER).
Notes: e fi rst part of the table presents inequality estimates (and percentage measures) derived directly from the data where
large countries (those with populations of over 25 million) have been disaggregated into income groups but small countries have
not and are thus not included (see Appendix C for the methodology). In the second part of the table, intracountry inequality
is extrapolated to all countries (i.e., small countries are assumed to have average levels of inequality similar to those of large
countries).
Riding the Elephants: The Evolution of World Economic Growth ... 13
China has been slower than that of the world with it (just 2.7 per cent and 2.1 per cent a year for the 1980s
and 1990s respectively), it is not surprising that the falling income shares of middle deciles 6, 7 and 8 also
meant that they lost ground in absolute as well as relative terms, with overall negative growth in their (1995
international dollar equivalent) per capita income (table 6).18
e inequality trend is aff ected further if India is excluded along with China (table 7). For the
remaining 62 per cent of the world population there was a clear worsening of the distribution of income,
as the Gini coeffi cient rose sharply from 0.559 to 0.621 between 1980 and 2000 and the ratio of average
income of the top decile to that of the bottom rose from 61.5 to 85.2. With two of the fastest growing coun-
tries (as well as the two largest) excluded, average income per capita for the rest of the world grew at only 0.9
per cent per year between 1980 and 1990, and 0.5 per cent per year during the 1990s (table 2).
Although the bottom three deciles still recorded marginal income growth, the next four all lost in
absolute terms; only the top two showed substantial income increases, with the share of the top decile rising
sharply from 36.1 per cent in 1980 to 42.9 per cent in 2000 (about the same amount as in the case where
only China is excluded). ough the biggest losers are in the middle deciles, the fall in the income shares of
the bottom deciles, as well, exposes and highlights the fact that growth in China and India off set the poor
economic performance of other low-income countries, particularly those in Africa.
18 e rates of decile income growth in the last two columns of table 6 (or table 4) do not average the rates of growth
in table 2 because the latter are a weighted average of domestic growth rates while the former are direct estimates of
growth after translating all income to 1985 PPP equivalents.
Table 6.
Decile distribution of world income among persons when China is excluded
Income shares by decile of world population (%)
Change in
share of total
world income
Annual income growth (1985
PPP value of income)
1980 1990 2000 1980-2000 1980-1990 1990-2000
Decile 1 0.54 0.58 0.59 0.05 1.9% 1.0%
Decile 2 1.01 1.12 1.09 0.08 2.2% 0.6%
Decile 3 1.38 1.49 1.63 0.25 1.9% 1.8%
Decile 4 2.03 1.97 2.12 0.09 0.8% 1.6%
Decile 5 3.22 2.95 2.83 -0.39 0.2% 0.5%
Decile 6 5.50 4.71 4.32 -1.18 -0.5% 0.0%
Decile 7 8.88 7.95 6.88 -2.00 -0.1% -0.5%
Decile 8 14.19 13.00 11.45 -2.73 0.2% -0.4%
Decile 9 22.40 22.25 22.15 -0.26 1.0% 0.9%
Decile 10 40.86 43.98 46.95 6.09 1.8% 1.6%
World 100.00 100.00 100.00
Measures of inequality 20-year change in inequality measure
Gini coeffi cient 0.612 0.630 0.644 0.033
Theil coeffi cient 0.826 0.842 0.865 0.039
Atkinson (0.5) 0.313 0.328 0.341 0.028
Atkinson (1) 0.562 0.569 0.579 0.017
Atkinson (2) 0.801 0.798 0.800 -0.001
Ratio of top to bottom decile incomes 76.2 75.8 80.0
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database (UN), Penn World Tables – Mark
5.6 (CIC) and WIID (WIDER).
14 DESA Working Paper No. 27
e deterioration in the distribution of world income when China and India are excluded is more
unequivocal than both the improvement when these countries are included and the deterioration when only
China is excluded. ere is no Lorenz dominance in either of the latter two cases but, when both India and
China are excluded, the 1980 distribution of world income Lorenz dominates both the 1990 and 2000 dis-
tributions and the 1990 distribution Lorenz dominates that for 2000.
Given the dramatic events befalling the former Soviet bloc, it is also of interest to see what eff ect
they had on the trajectory of growth and inequality (table A4, Appendix A). During the 1990s the world
economy grew at just 2.5 per cent while the world outside the former Soviet bloc grew at 3.2 per cent,
highlighting the major impact of its collapse on world growth. However, the signifi cant increase in inequal-
ity reported for most countries of the bloc, even when combined with the eff ect of their falling income on
intercountry inequality, contributes only modestly to the pattern of world income distribution. Excluding
the countries of the former Soviet bloc leads to a moderate exaggeration of the pattern of decreasing overall
inequality. In the world outside the former Soviet bloc the Gini coeffi cient fell by 0.017 points; with that
bloc included, the decline was of 0.009 points. e world eil coeffi cient fell by 0.043 points, while that
of the world outside the former Soviet bloc fell by 0.055 points. Qualitatively similar stories emerge for the
other indicators of inequality. Exclusion of this part of the world, however, does not lead to Lorenz domi-
nance by later distributions over earlier ones.
Table 7.
Decile distribution of world income among persons when both China and India are excluded
Income shares by decile of world population (%)
Change in
share of total
world income
Annual income growth (1985
PPP value of income)
1980 1990 2000 1980-2000 1980-1990 1990-2000
Decile 1 0.59 0.54 0.50 -0.08 0.2% 0.1%
Decile 2 1.07 1.06 0.99 -0.08 0.9% 0.2%
Decile 3 1.78 1.56 1.52 -0.26 -0.3% 0.5%
Decile 4 2.83 2.46 2.21 -0.62 -0.4% -0.2%
Decile 5 4.65 3.84 3.33 -1.31 -0.9% -0.6%
Decile 6 7.05 6.16 5.13 -1.92 -0.3% -1.0%
Decile 7 10.13 9.21 7.89 -2.25 0.1% -0.7%
Decile 8 14.77 14.11 13.60 -1.17 0.6% 0.4%
Decile 9 21.00 21.45 21.92 0.92 1.3% 1.0%
Decile 10 36.13 39.62 42.90 6.77 2.0% 1.6%
World 100.00 100.00 100.00
Measures of inequality 20-year change in inequality measure
Gini coeffi cient 0.559 0.591 0.621 0.062
Theil coeffi cient 0.692 0.768 0.840 0.148
Atkinson (0.5) 0.264 0.293 0.321 0.057
Atkinson (1) 0.499 0.536 0.568 0.069
Atkinson (2) 0.775 0.804 0.818 0.043
Ratio of top-to-bottom decile income 61.5 73.2 85.2
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database (UN), Penn World Tables – Mark
5.6 (CIC) and WIID (WIDER).
Riding the Elephants: The Evolution of World Economic Growth ... 15
Major caveats
Given the number of data problems and possible methodological fl aws in calculations like those reported
above, it is a foregone conclusion that the results are, at best, approximations to the true reality. It is almost
certain that the country-level fi gures in most developing counties understate inequality, mainly because of
the incomplete reporting of capital incomes (especially large ones) relative to labour incomes,19 but also
because of the exclusion of income from asset appreciation. is creates a presumption that the estimates of
world inequality are also downward biased, but since the methodological fl aws involved in merging the data
for diff erent countries can create either upward or downward biases, this is less certain.20
Our main concern here, however, is with possible biases in the estimated trends in inequality.21
ese are far too numerous to list; much additional research will be required to sort out their impacts and
their relative importance.22 Probably the two phenomena most capable of leading to signifi cant bias are
changes in the degree of the under-coverage of capital incomes, already mentioned, and diff erences in the
price trends for diff erent income groups within countries. e latter relates to the fact that each datum on
inequality is based on current prices. If, in a given country, prices rise faster for some income groups than for
others, the changes in the distribution of purchasing power will be misestimated by the change in current
price inequality. Under many circumstances there may be no reason to expect income-group-specifi c price
indices to move very diff erently over time, but in the context of major freeing of markets and the attendant,
sometimes substantial, changes in relative prices, such an assumption is not so defensible. For example,
countries of Eastern Europe which saw a reduction of the rationing systems and freeing of prices of staples
may well have undergone diff erential price changes by group. e same goes for countries that have opened
up quickly to international trade; in most developing countries this has led to declines in the relative prices
of a number of luxury goods (such as cars), which may mean that the relative cost of the market basket con-
sumed by the rich has fallen vis-à-vis that of the poor.23
Another concern, which may technically be viewed as a special case of the previous one, involves
public consumption goods. All of the country distribution data used here refer only to private income;
though everyone recognizes the need to take account of the distribution of public good consumption, the
practical diffi culties have precluded it as a general practice.24 Given the widespread decline in public expen-
diture in recent years, it is probable that distributional trends would look somewhat diff erent, and very likely
19 Altimir (1987) re-estimated inequality in several Latin American countries using plausible assumptions about the level
and distribution of capital income; the adjusted Gini coeffi cients were typically 2-6 Gini points higher.
20 It is also the case that the bias due to under-coverage of capital incomes in individual countries might have very little
refl ection at the global level if the problem mainly characterized middle-income countries—not impossible since data
accuracy is generally higher in rich countries and the capital share itself may be lower in poor countries in which case
the biasing impact of its being underreported would also be muted.
21 e fact that the available fi gures assume away all intra-family inequality appears to create only a small downward bias
in measured inequality, as demonstrated by Haddad and Kanbur (1993).
22 e list would include the possibility that inclusion of public goods would change the observed patterns of inequality
change, that improvements to household surveys are making them more accurate as time goes on and that this leads
to observed trends being diff erent from actual trends, changes in the distorting eff ects of the way PPP conversion is
carried out, and so on.
23 Both of these scenarios would tend to mean that a common price assumption would lead to a downward bias in the
estimation of changes in inequality.
24 Early important case studies were those of Selowsky (1979) for Colombia and Meerman (1977) for Malaysia. For
no country, to our knowledge, has an attempt been made to include public goods in the estimates of inequality on a
continuing basis such as to allow one to see how their inclusion aff ects trends in inequality.
16 DESA Working Paper No. 27
more negative, were public consumption included in the data, though the increase in targeting of certain
services may have had a suffi ciently strong positive eff ect to prevent this outcome or even reverse it.25 26
e above biases involve the estimation of inequality at the country level as opposed to the merg-
ing of country data for the world-level estimate. In both cases there is a reasonable theoretical presumption
(related to the processes of liberalization and globalization) that the bias will have risen since 1980, and a
modest amount of empirical evidence has been brought forward in support of that conclusion (e.g., de Fer-
ranti and others, 2004: 235). Overall, these limitations suggest that, for the period in question, the available
(conventional) measures of income inequality are more likely to err on the side of undue optimism (i.e., to
overestimate improvements in the distribution of income or to underestimate deteriorations). us any pic-
ture painted by the data is unlikely to be overly pessimistic. Allowing for these possible (or probable) biases
might suggest a ‘best guess’ that the level of world inequality, instead of falling a little from 1980-2000, was
very close to staying constant, or might even have risen a little. It is worth emphasizing that, although there
has been a considerable convergence of results around the ‘modest decline in world inequality’ conclusion
for at least the last two decades of the twentieth century, most of the major remaining possible biases in the
estimates (especially the most glaring ones noted above) are common to all of the studies. us it is quite
possible that all of them are signifi cantly off the mark in the same direction.
Milanovic (2002: 72), relying exclusively on household survey data for both mean income and its
distribution, estimated that between 1988 and 1993, the Gini coeffi cient for the world income distribution
had risen from 0.628 to 0.660 for a common sample of countries. is suggested that, if his methodology
was indeed the correct one, not only was world inequality increasing, it was doing so very rapidly. e mes-
sage contrasted signifi cantly with that of the other available and comparable studies that, as noted above,
pointed to a smallish decrease since 1980. In fact, the diff erence between the two approaches turns out to
have been much less than fi rst met the eye since, when Milanovic added 1998 estimates, these showed an in-
equality decline between 1993 and 1998 and hence a more modest increase from 1988 to 1998 of 1.8 Gini
percentage points, from 0.623 to 0.641 (Milanovic, 2005: 118). From 1990 to 2000, our estimated Gini
coeffi cient fell from 0.648 to 0.639 (table 4). Milanovic also undertook estimates using national accounts-
25 Another source of imprecision lies in the fact that the ICP (International Comparisons Project of the Center for
International Comparisons) conversion indices used here do not provide fully accurate translation of per capita income
levels between countries; whereas use of nominal exchange rates tends to exaggerate income diff erences between richer
and poorer countries, the ICP indices tend to understate them (Dowrick and Quiggin, 1997). Dowrick and Quiggin
(1997) derive an alternative index with desirable properties which, in the Organisation for Economic Cooperation
and Development (OECD) context, implies that income convergence occurred between 1980 and 1990 whereas the
ICP indices yielded no clear results. But Quiggin (2002) reports that the opposite appears to be true when a sample
including poor countries is used, and that there is no general presumption that the use of this index would lead to
more frequent fi ndings of convergence.
26 Although intracountry trends do not usually have a major impact on world trends unless they are dramatic, they may
have been playing a role here. us, Bhalla (2002: 39) reports signifi cant declines in inequality in both Mexico and
Brazil between 1980 and 1999; the general view among specialists is that inequality has risen markedly in Mexico since
1984; prior to that the comparability of surveys was weak, making it diffi cult to judge trends. In Brazil, most sources
(including ourselves) indicate a smaller decrease in inequality than does Bhalla––his Gini falls by six percentage points
between 1980 and 1999 while ours falls by one percentage point over 1980-2000. It would require a very detailed and
careful comparison to sort out which diff erences show up in the mildly diff erent estimates of world distribution trends.
Almost all developing countries still suff er major problems and ambiguities in their data on distribution. Much of the
statistical error and the non-comparability across surveys at diff erent points of time are likely to be fairly random, such
that it might not aff ect estimates of inequality trends much. e major possible sources of error in estimation of the
time trend, in particular the inaccurate reporting of capital incomes, are present in all studies undertaken thus far. It
would be useful to undertake simulation exercises to test for the sensitivity of trend estimates to plausible errors in this
aspect of intracountry inequality.
Riding the Elephants: The Evolution of World Economic Growth ... 17
based fi gures for mean per capita income of each country, and in that case found the Gini coeffi cient to fall
from 0.641 in 1988 to 0.635 in 1998, fi gures almost identical to our own for 1990-2000. is suggests that
the main diff erence between his preferred result and ours refl ects the use of diff erent fi gures for mean per
capita income of countries (survey-based incomes in his case and national account-based incomes in our
case) rather than a number of other diff erences of methodological detail or the fact that the end years are
a little diff erent. is leaves us with two interesting questions arising from Milanovic’s results, where they
contrast with others.
First, was there, in fact, a rather sudden increase in world inequality between 1988 and 1993 as
his fi gures show (albeit less markedly in his 2005 publication than in that of 2002)? Sorting out this ques-
tion would require an analysis of the statistical sources of that increase to discern whether they more likely
refl ected true trends or statistical error and is well beyond the scope of this study.
Second, what can be said about the relative merits of using household survey-based estimates of per
capita income in each country versus national accounts-based estimates? is is also a complicated mat-
ter that cannot currently be resolved on the basis either of theory or available empirical evidence. All ap-
proaches have to use distribution data from household surveys so the weaknesses of that information show
up in all estimates. e diff erence between the two is the choice of the mean income measures. Milanovic’s
approach uses the mean per capita income measure derived directly from household surveys with its likely
underestimation of true mean income (mainly because of the underreporting of capital income) while our
method uses national accounts-based per capita income fi gures (which is not without its own measurement
problems). However, it is not accuracy of measurement that is the critical issue here. e main argument for
using national accounts estimates of per capita income is that the methodology is likely to produce less vari-
ability in the errors of observation over time than the household survey data. Given the underreporting of
capital incomes in survey data it is unclear how this eff ect plays out over time with respect to the distribution
of global income. Capital incomes do vary over time and, at this point, our knowledge of the distribution of
capital income in developing countries is too limited to allow more than conjecture as to patterns of change
and consequent eff ects on income measures.
It should be emphasized that which methodology is best and which sources of bias are the most seri-
ous depends on exactly what one wants to learn from the data. One methodology may be better at approxi-
mating true inequality at a point of time but worse at identifying trends—our main interest here. One may
be better at approximating the distribution of consumption expenditures and the other at approximating
the distribution of income. If the former is one’s main interest, household surveys (when there are enough
of them and they are comparable enough) are likely to provide the better approach, since the capital income
reporting problem becomes close to irrelevant. Meanwhile, studies of changing inequality in given countries
do not confront many of the challenges involved in dealing with world inequality.
Our focus here is the direction of changes in world inequality among persons. For that purpose, we
suspect that the use of national accounts-based per capita income measures is superior to the use of house-
hold survey-based fi gures. However, accepting that this is, nevertheless, debatable, it is somewhat reassuring
that the apparent impact of that methodological choice is less than it appeared to be when Milanovic (2002)
was published. Over 1988 to1998, the diff erence in change in the Gini coeffi cient, according to Milanovic’s
(2005: 118) calculations is 2.4 percentage points—a 1.8 percentage point increase using the survey-based
means and a 0.6 point decrease using the national accounts-based means.
18 DESA Working Paper No. 27
A clarifi cation with respect to studies showing increasing inequality of world distribution
Most of the confusion and ambiguity as to what has been happening to world inequality has been due, not
to the methodological issues discussed in this paper, but to two others: whether the individual person or the
country is the unit of comparison and whether per capital incomes are converted to a common base using
offi cial or market exchange rates or using PPP conversion rates. All of the studies previously referred to in
this paper, with the exception of Korzeniewicz and Moran (1997), share with us the practice of converting
national data to a ‘common’ base using PPP conversion ratios and using the individual as the basic unit of
observation.
When the country rather than the individual is the unit of observation, one is, in eff ect, giving equal
weight to each country; China with several hundred times more people than Costa Rica, is given the same
weight as that country. is treatment inevitably means that what happens in the many small or relatively
small countries becomes the main determinant of ‘world inequality’. China and India, with between them
around 40 per cent of the world’s population, have only between 1 and 2 per cent of the weight in these cal-
culations. If most countries fell in about the same size range, it would not matter much whether one weight-
ed by population or did not; but in fact, countries vary enormously in size, as the just-cited fi gures indicate.
Hence, it does matter. Among those who have focused on this ‘unweighted’ measure of world inequality is
Castells (1993). e very widespread view that global inequality has been rising has been supported by these
simple comparisons of growth rate in richer versus poorer countries and, ironically, has often been fuelled by
statements coming from such establishment institutions as the World Bank and the International Monetary
Fund (IMF).27 Milanovic (2005: 39-44) presents a time series covering 1950-2000 that shows a modest
increase in unweighted intercountry inequality from a Gini coeffi cient of 0.44 in 1950 to about 0.47 around
1980, followed by a very sharp increase to about 0.54 at the end of the century. Over the fi fty years as a
whole, most of the increase comes from what happens in Africa (as one might guess from the fact that there
are so many small countries there and they have done relatively badly compared to other developing coun-
tries), but the concentrated increase since 1980 does not have that origin, it is, instead, due mainly to events
in Latin America and in the middle-income countries of Eastern Europe and the former Soviet Union.
Conclusions about world inequality trends are also very sensitive to whether conversion of national
data to an international ‘currency’ takes the PPP route or uses offi cial exchange rates.28 e United Nations
Conference on Trade and Development (UNCTAD) was one of the institutions, along with the UNDP (1999)
to report a major increase in inequality at some point in the last few decades, with the Gini coeffi cient rising
from 0.66 in 1965 to 0.74 in 1990 and the ratio of the richest quintile to the poorest rising dramatically from
31.1 to 60.1 (UNCTAD 1997: 81). e report drew on Korzeniewicz and Moran (1997). e authors were
aware that the choice between market exchange rate conversion and PPP conversion matters. ey judged that
the latter was the more appropriate way to gauge relative welfare conditions but followed Arrighi (1991: 22-23)
to the conclusion that exchange rates provide a better “indicator of the command that diff erent countries have
over the human and natural resources”. However, most users of these estimates are basically concerned with the
distribution of welfare and, by implication, access to locally available resources at domestic prices—suggesting
the use of PPP exchange rates. us, as Firebaugh (2003: 37) puts it, “virtually all recent studies of between-
nation or global income inequality use income data adjusted for purchasing power parity diff erences”.
27 us “ e average income in the richest 20 countries is 37 times the average in the poorest 20-a gap that has doubled
in the past 40 years” (International Monetary Fund, 2000: 50, cited in Firebaugh, 2003: 18).
28 Although there are tricky issues within the broad PPP approach (see Milanovic, 2005; Dowrick and Akmal, 2003;
Dowrick and Quiggin, 1997; and others) these appear to matter much less to most results than does the choice of any
variant of this general approach as opposed to offi cial exchange rates.
Riding the Elephants: The Evolution of World Economic Growth ... 19
Poverty trends and patterns
Trends in the incidence of poverty naturally depend on where the poverty line is drawn. Rather than choos-
ing one line, inevitably somewhat arbitrary, we estimate poverty incidence for three diff erent levels, 500,
1000, and 1500 1985 international dollars (annually).29 We diverge from the standard $1 and $2-a-day pov-
erty lines partly because ours are income-based poverty lines, in contrast to the consumption-based approach
used by the World Bank and United Nations. Given average national levels of private consumption relative
to total income, the $1-a-day (or $365-a-year) consumption based poverty line is likely to be fairly close
to our $500 income poverty line.30 In eff ect, then, our $500 and $1,000 poverty lines can be considered
roughly comparable to those $1 and $2-a-day consumption lines. Persons with income below $500 can be
reasonably considered extremely poor, those with income of $500 or greater but less than $1,000, very poor,
and those with income of $1,000 or greater but less than $1,500, moderately poor.
For the world as a whole, it is noteworthy that poverty, when measured by the 500-international-
dollar poverty line, continued to decline rapidly during the 1980s but the pace slackened markedly in the
1990s (table 8). During the 1980s, the share of people below this line fell sharply in East Asia, mainly
refl ecting the growth of China and also in South Asia, while remaining about constant in Africa (table 9).
29 e use of international dollars as measures of growth and income distribution is designed to ensure uniformity of
purchasing power across countries. In eff ect, anyone with an income of 500 international dollars should have the same
purchasing power regardless of which country they live in.
30 Direct translation from consumption to income using the national average ratio between these two variables gives
about $540 per year, but this would be an overestimate because people with lower incomes generally tend to consume
more of their income than do those with higher incomes.
Table 8.
World poverty incidence (Alternative poverty lines, 1980-2000)
The world
International poverty lines
(in fi xed 1985 international dollars) Per cent of total world population
1980 1990 2000
Income groups with average income of < $500 25.7 14.6 12.1
Income groups with average income of < $1000 53.8 43.6 28.5
Income groups with average income of < $1500 60.5 54.1 44.8
The world without China
Income groups with average income of < $500 18.6 12.6 12.2
Income groups with average income of < $1000 40.4 35.9 27.1
Income groups with average income of < $1500 46.9 45.8 42.2
The world without China and India
Income groups with average income of < $500 12.1 9.0 10.1
Income groups with average income of < $1000 26.7 24.4 20.2
Income groups with average income of < $1500 32.8 32.3 31.4
The world without Eastern Europe
Income groups with average income of < $500 27.4 15.4 12.8
Income groups with average income of < $1000 57.3 46.2 29.7
Income groups with average income of < $1500 64.5 57.3 46.9
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database (UN), Penn World Tables – Mark
5.6 (CIC) and WIID (WIDER).
20 DESA Working Paper No. 27
In the 1990s, though it had already been lowered considerably, poverty by this defi nition was again roughly
halved in East Asia. However, the rate of improvement fell sharply in South Asia due to increasing inequal-
ity in India (although per capita income growth increased slightly) and the fact that income groups were
much less clustered close to that line than previously.31 Poverty incidence again held about constant in
sub-Saharan Africa. us, these two decades saw modest poverty reduction (by this defi nition) in the world
outside China, and very little indeed in the world outside China and India––from 12.1 in 1980 to 10.1 in
2000. In both these latter two cases there was some reduction in the 1980s followed by a loss of ground in
the 1990s.
e distinction between the 1980s and the 1990s is dramatically diff erent when the poverty line
is set at $1000. For the world as a whole and for the world minus China, the percentage point decline was
greater in the 1990s and substantial in absolute terms (table 8). For the world outside China and India, there
was only a very marginal decline in each decade. is refl ects the fact that in South Asia (and, more particu-
larly, India), the worsening distribution of income that muted the eff ect of rising overall income for the low-
est income groups had a less dramatic eff ect in this intermediate range as well as the fact that fewer income
classes were located near that poverty line in 1980 than in 1990.32 rough both decades, the Middle East
continued to record moderate declines in poverty, but in South and Central America, the retrogression of the
1980s was not erased in the 1990s (table 9).
At the higher poverty line of $1500, the pattern is again diff erent. Poverty, by that defi nition, de-
clines only moderately for the world as a whole, a little when China is excluded and marginally over the two
decades when both India and China are excluded. In terms of the regional distribution, only East Asia and
31 In fact, in 1980, 10 per cent of the total South Asian population had incomes between 400 and 500 international
dollars. In 1990 only 2 per cent lay in that range.
32 Essentially because some of the income groups in the upper part of this range in 1990 were less adversely aff ected by
the worsening income distribution.
Table 9.
Rates of poverty by region
Regions
Poverty lines (in 1985 international dollars)
$500 $1000 $1500
1980 1990 2000 1980 1990 2000 1980 1990 2000
Sub-Saharan Africa 56.9 57.5 58.0 74.8 75.3 71.4 85.2 85.8 80.8
East Asia 36.8 15.3 7.6 73.8 53.3 27.6 82.6 66.4 46.9
Eastern Europe and
Central Asia .. .. .. .. .. 4.2 .. .. 4.2
Middle East 3.3 3.1 .. 30.2 20.0 13.2 40.4 29.8 23.1
North America .. .. .. 4.2 4.6 .. 4.2 4.6 4.8
South Asia 36.1 21.3 20.0 80.0 67.5 46.0 88.0 81.0 72.1
South and Central America .. .. .. 15.4 17.3 17.3 21.8 31.6 32.8
Western Europe .. .. .. 2.7 .. .. 5.4 3.2 ..
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database (UN), Penn World Tables – Mark
5.6 (CIC) and WIID (WIDER).
Notes: Because the estimation produced is based on population units, some of which are large in relation to the less populated
regions, the estimates are approximations. ough direction of change should almost certainly be correctly indicated, both
absolute levels and degree of change can be biased.
.. e approximation procedure produced a fi gure of zero in these cases, i.e., there was a downward bias due to the fact that the
average income of the lowest income group used in the calculation was above the poverty line in question.
Riding the Elephants: The Evolution of World Economic Growth ... 21
the Middle East record large declines in poverty defi ned by this line, while South Asia recorded a moderate
decline and Africa, surprisingly, a modest decline as well. However, increasing proportions of the Eastern
European, and the South and Central American populations fell below that level over the two decades.
e area for concern, then, with respect to world poverty trends involves the bottom decile or so of
world population, who are still below or close to the $500 line and who have been climbing above this line
at a slower rate than higher deciles historically did. As has been widely noted, this new challenge has a strong
regional component. As of 1980, the average income of the poorest quintile of the population was strikingly
similar across South Asia, sub-Saharan Africa and East Asia (table 10). e succeeding two decades have
seen a remarkable divergence in the fates of these groups, with average incomes rising rapidly in East Asia
and moderately in South Asia but falling slightly in sub-Saharan Africa. By 2000, the average income of East
Asia’s bottom quintile was 50 per cent above that of the corresponding quintile of South Asia and over three
times that of the bottom sub-Saharan African quintile. e extent of the collapse of incomes in sub-Saharan
Africa is further illustrated by the fact that that bottom quintile was earning a higher proportion of total
income in 2000 than it was in 1980, but the purchasing power of its income had dropped!
e two regions with the largest populations in poverty have been reducing poverty rapidly, while
the third one has been going in the opposite direction. But the net positive outcome—a signifi cant decline
in world poverty incidence—seems to have run out in the 1990s. An improvement on the performance of
that decade, in particular in sub-Saharan Africa, and more equitable growth in South Asia will be necessary
for poverty reduction to regain the momentum of the earlier decades.
Summary and conclusions
In the light of divergent income trends across other regions, rapid and sustained expansion of the Chinese
economy, and the more moderate, but consistent growth in India, were critical to the modest expansion
of the world economy during the 1980s and 1990s. World inequality among persons fell during both the
1980s and the 1990s, according to all of our indicators—marginally according to some (including the Gini
coeffi cient) and more markedly according to others (including the eil coeffi cient). Income share was
transferred from deciles seven to nine to the bottom six deciles and to the top decile. is outcome can be
seen as the net result of two off setting trends: falling intercountry inequality and rising intracountry inequal-
Table 10.
Fortunes of the bottom quintile by regions
Regions
Average income (in 1985 international dollars) Proportion of total income
1980 1990 2000 1980 1990 2000
Sub-Saharan Africa 207 177 190 3.3 3.0 3.5
East Asia 265 396 609 2.8 3.0 3.4
Eastern Europe and Central Asia 2,664 2,847 1,872 9.1 8.8 7.8
Middle East 759 892 1,136 4.2 5.1 5.7
North America 2,465 2,374 2,927 3.8 3.1 3.1
South Asia 234 346 418 5.9 6.3 5.4
South and Central America 1,044 757 882 4.8 3.9 3.9
Western Europe 3,265 3,832 4,260 6.6 6.4 6.0
World 326 431 507 1.7 2.0 2.1
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database (UN), Penn World Tables – Mark
5.6 (CIC) and WIID (WIDER).
22 DESA Working Paper No. 27
ity in wealthier countries and some of the developing ones (most prominently China). In fact, the observed
improvement in the distribution of world income can be attributed entirely to the fact that the lessening
of income gaps between countries was suffi cient to off set the rising inequality within countries. As a result,
the world’s poor were, generally speaking, substantially better off in 2000 than in 1980 and, accordingly,
world poverty incidence continued its long downward trend. e rate of poverty reduction (in the world
as a whole) was brisk in the 1980s, continuing the pattern of the 1960s and 1970s, as East and South Asia
(the home of the majority of the world’s poor) expanded at a signifi cantly faster rate than the rest of the
world. However, despite continued growth in these regions in the 1990s, we see that increasing intracountry
inequality (particularly in China and India) and the fact the most of the remaining poor had incomes well
below the poverty line, combined with increasing poverty in Africa, led to a near cessation in the reduction
of extreme poverty globally.
It might be argued that the overall pattern of world income distribution over the period 1980-2000
was one of convergence; but with such a fi nding resting largely on the performance of a single country
(China), its meaning would be open to question. When India is excluded along with China, the pattern
is unmistakably one of divergence. In the world outside those two countries, overall per capita economic
growth fell by close to 50 per cent in each successive decade after the 1970s, the distribution of income
became markedly more unequal and poverty levels were roughly unchanged. us, the two decades span-
ning the period 1980 to 2000 can be described as manifesting strong pressures towards divergence, off set
plus a little by the rapid growth of the two largest low-income countries. In short, these two countries can be
considered to have rescued the world from a dismal overall performance, on the equality front, in the closing
decades of the twentieth century.
Riding the Elephants: The Evolution of World Economic Growth ... 23
References
Altimir, Oscar (1987). Income distribution statistics in Latin America and their reliability. Review of Income and Wealth
33 (2): 111-155.
Arrighi, Giovanni (1991). World income inequalities and the future of socialism. New Left Review 189: 39-65.
Arrighi, Giovanni (2002). e African Crisis: World Systemic and Regional Aspects. New Left Review 15 (May-June): 5-36.
Bales, Kevin (1999). Disposable People: New Slavery in the Global Economy. University of California Press, Berkeley.
Bairoch, Paul (1997). Victoires et déboires. Histoire économique et sociale du monde de XVIè siècle à nos jours, 3 volumes. Folio Histoire
Gallimard, Paris.
Barro, Robert (1991). Economic growth in a cross section of countries. Quarterly Journal of Economics 106: 407-443.
Barro, Robert, and Xavier Sala-i-Martin (1992). Convergence. Journal of Political Economy 100: 223-251.
Ben-David, Dan (1993). Equalizing exchange: Trade liberalization and convergence. Quarterly Journal of Economics 108: 653-679.
Berry, Albert, Francois Bourguignon and Christian Morrisson (1983). Changes in the World Distribution of Income Between 1950
and 1977. Economic Journal 93 (37): 331-350.
Berry, Albert, Francois Bourguignon and Christian Morrisson (1991). Global Economic Inequality and its Trends Since 1950. In
Lars Osberg (ed.). Readings on Economic Inequality. M.E. Sharpe, New York.
Berry, Albert, and Frances Stewart (1997). Market Liberalization and Income Distribution: the Experience of the 1980s. In Roy
Culpeper, Albert Berry and Frances Stewart (eds). Bretton-Woods: 50 Years Later. Macmillan, London.
Bhalla, Surjit (2002). Imagine there’s no country: Globalization and its Consequences for Poverty, Inequality and Growth. Institute for
International Economics, Washington, DC.
Bliss, Christopher (1989). Trade and Development. In Hollis Chenery and T.N. Srinivasan (eds). Handbook of Development
Economics, Volume 2. North Holland, Amsterdam.
Bound, John, and George Johnson (1992). Changes in the Structure of Wages in the 1980s: An Evaluation and Alternative
Explanations. American Economic Review 82 (3): 371-392.
Bourguignon, Francois, and Christian Morrisson (2002). Inequality Among World Citizens, 1820-1992. American Economic Review
92 (4): 727-744.
Castells, Manuel (1993). e informational economy and the new international division of labor. In Martin Carnoy, Manuel
Castells, Stephen S. Cohen and Jorge Enrique Cardoso (eds). e new global economy in the information age. Pennsylvania
State University, University Park.
Chen, Shaohua, and Martin Ravallion (2004). How Have the World’s Poorest Fared since the Early 1980s? e World Bank Research
Observer 19 (2): 141-169.
Cornia, Giovanni Andrea (ed.) (2004). Inequality, growth, and poverty in an era of liberalization and globalization. Oxford University
Press, New York.
Corry, Dan, and Andrew Glyn (1994). Macroeconomics of equality, stability and growth. In Andrew Glyn and David Miliband
(eds). Paying for Inequality: e Economic Cost of Social Injustice. IPPR/Rivers Oram Press, London: 1-23.
de Ferranti, David, Guillermo Perry, Francisco H. G. Ferreira and Michael Walton. (2004). Inequality in Latin America: Breaking
with history? Latin American and Caribbean Studies, World Bank, Washington DC.
Dikhanov, Yuri, and Michael Ward (2001). Measuring the Distribution of Global Income. World Bank, Washington, DC.
Dolan, Kerry A. (1999). e World’s Working Rich: A Decade of Wealth, Forbes, 164(1), (July 05): 154-55.
Dowrick, Steve, and Muhammed Akmal (2003). Contradictory Trends in Global Income Inequality: A Tale of Two Biases, Review of
Income and Wealth 51(2): 201-29.
Dowrick, Steve, and John Quiggin (1997). True measures of GDP and convergence. American Economic Review 87 (1): 332–341.
Easterly, William (2001). e Lost Decades: Developing Countries’ Stagnation in Spite of Policy Reform, 1980-98. Journal of
Economic Growth 6 (2): 135-157.
Evans, David (1989). Alternative Perspectives on Trade and Development. In Hollis Chenery and T.N. Srinivasan (eds). Handbook of
Development Economics,Volume 2, North Holland, Amsterdam: 1241-1304.
Firebaugh, Glenn (2003). e New Geography of Global Income Inequality. Harvard University Press, Cambridge, MA.
Galbraith, James K. (2002). A Perfect Crime: Inequality in the Age of Globalization. Daedalus (Winter): 11-25.
Haddad, Louis, and Ravi Kanbur (1993). How serious is the neglect of intra-household inequality. Economic Journal
100 (402): 866-881.
24 DESA Working Paper No. 27
International Monetary Fund (2000). How we can help the poor: Introduction. Finance and Development 37 (4): 2.
Keidel, Albert. (1992). How Badly Do China’s National Accounts Underestimate China’s GNP? Working Paper E-8042, Rock Creek
Research Inc., Washington, DC.
Korzeniewicz, Roberto Patricio, and Timothy Moran (1997). World Economic Trends in the Distribution of Income, 1965-1992.
American Journal of Sociology 102 (4): 1000-1039.
Kuznets, Simon (1955). Economic Growth and Income Inequality. e American Economic Review 45 (1): 1-28.
Lindert, Peter, and Jeff rey Williamson (2001). Does Globalization Make the World More Unequal. NBER Working Paper no. 8228,
National Bureau of Economic Research, Cambridge, MA.
Mankiw, Gregory, David Romer and David Weil (1992). A Contribution to the Empirics of Economic Growth. Quarterly Journal of
Economics 107 (2): 407-437.
Maddison, Angus (1999). Chinese Economic Performance in the Long Run. OECD Development Centre, Paris.
Meerman, Jacob (1977). e distribution of public expenditure for education and agriculture in Malaysia: Methodological issues and a
new approach. Oxford University Press, New York, for the World Bank, Washington, DC.
Milanovic, Branko (2002). True world income distribution, 1988 and 1993: First calculations based on household surveys alone.
Economic Journal 112 (476): 51-92.
Milanovic, Branko (2005). Worlds Apart. Princeton University Press, Princeton, NJ.
Peacock, Walter G., Greg A. Hoover and Charles D. Killian (1988). Divergence and Convergence in International Development: A
Decomposition Analysis of Inequality in the World System. American Sociological Review 53: 838-852.
Penn World Tables (PWT) Mark 5.6, University of Pennsylvania, Philadelphia PA: Center of International Comparisons
Pritchett, Lant (1995). Divergence Big Time. Policy Research Working Paper, no. 1522, World Bank, Washington, DC.
Quiggin, John (2002). Analyzing inequality: Changing patterns of resource distribution within the global system, Australian
National University, draft.
Ren, Ruoen (1997). China’s Economic Performance in an International Perspective. OECD Development Centre, Paris.
Robbins, Donald (1996). Evidence on Trade and Wages in the Developing World. Technical Paper, no. 119, December, OECD
Development Centre, Paris.
Sala-i-Martin, Xavier (2002). e Disturbing ‘Rise’ of Global Income Inequality. NBER Working Paper, no. 8904, National Bureau of
Economic Research, Cambridge, MA.
Schultz, T. Paul (1998). Inequality in the distribution of personal income in the world: How is it changing and why? Journal of
Population Economics 11 (3): 307-344.
Selowsky, Marcelo (1979). Who benefi ts from government expenditure? A case study of Colombia. Oxford University Press, New York,
for the World Bank, Washington, DC.
Solow, Robert (1956). A Contribution to the eory of Economic Growth. Quarterly Journal of Economics 70: 65-94.
United Nations common database (UNCDB), New York, NY: United Nations Statistics Division.
http://unstats.un.org/unsd/cdb/cdb_help/cdb_quick_start.asp
UNCTAD (1997). Trade and Development Report 1997: Globalisation, Distribution and Growth. United Nations Conference on
Trade and Development, Geneva.
UNDP (1999). Human Development Report 1999. Oxford University Press, New York, for United Nations Development
Programme, New York.
Whalley, John (1979). e Worldwide Income Distributions: Some Speculative Calculations, Review of Income and Wealth
25 (3): 261-276.
WIDER, World Income Inequality Database (WIID), Helsinki: United Nations University, World Institute for Development
Economics Research, URL: http://www.wider.unu.edu/wiid/wiid.htm.
Wood, Adrian (1994). North-South Trade, Employment and Inequality. Oxford; Clarendon Press.
World Bank, World Development Indicators (WDI)-Online Version. Washington DC.
http://publications.worldbank.org/register/WDI
Wu, Harry X. (1998). How Rich is China and How Fast Has the Economy Grown? Statistical Controversies. China Economy
Papers, Asia Pacifi c Press 1998/3, Canberra.
Riding the Elephants: The Evolution of World Economic Growth ... 25
Appendix A
Table A1. World and regional per capita incomes (GNP) and regional rankings
1980 1990 2000
Per capita income Per capita income Per capita income
Regions
Current
int.
dollars
1985
int.
dollars
R
A
N
K
Current
int.
dollars
1985
int.
dollars
R
A
N
K
Current
int.
dollars
1985
int.
dollars
R
A
N
K
North America 11,078 13,050 1 19,135 15,495 1 27,656 18,716 1
Western Europe 8,672 9,987 2 15,380 12,047 2 21,346 14,141 2
Eastern Europe 4,812 5,865 3 7,603 6,457 3 6,699 4,820 3
Latin America 3,639 4,390 4 4,785 3,845 4 6,676 4,480 4
Middle East 3,161 3,630 5 4,222 3,478 5 5,800 3,981 5
East Asia 1,653 1,876 6 3,387 2,654 6 5,544 3,586 6
Sub-Saharan Africa 1,112 1,269 7 1,426 1,168 7 1,603 1,096 8
South Asia 668 789 8 1,356 1,095
8 2,272 1,548 7
World 3,247 3,792 5,375 4,312 7,351 4,918
Sources: World Bank, World Development Indicators (online edition); UN Common Database (Online edition).
Table A2. Measures of interregional income inequality
Inequality measure 1980 1990 2000
Gini 0.486 0.471 0.450
Theil 0.426 0.393 0.370
Atkinson (0.5) 0.192 0.182 0.175
Atkinson (1.0) 0.347 0.325 0.309
Atkinson (2.0) 0.535 0.499 0.479
Ratio of highest to lowest (average) regional
incomes 16.6 14.1 17.3
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database
(UN), Penn World Tables - Mark 5.6 (CIC) and WIID (WIDER).
26 DESA Working Paper No. 27
Table A3. Measures of intraregional income inequality
(as distributed among persons)
Region Year Gini Theil Atkinson (0.5) Atkinson (1) Atkinson (2)
1980 0.565 0.578 0.291 0.439 0.603
1990 0.571 0.607 0.297 0.455 0.642
Sub-Saharan Africa
2000 0.579 0.610 0.303 0.457 0.627
1980 0.647 0.763 0.349 0.534 0.683
1990 0.625 0.698 0.322 0.503 0.662
East Asia
2000 0.575 0.575 0.266 0.437 0.611
1980 0.270 0.123 0.058 0.115 0.225
1990 0.283 0.134 0.064 0.125 0.237
Eastern Europe
and
Central Asia 2000 0.365 0.229 0.106 0.205 0.372
1980 0.308 0.200 0.084 0.181 0.433
1990 0.313 0.195 0.084 0.177 0.387
Western Europe
2000 0.320 0.203 0.088 0.184 0.390
1980 0.466 0.379 0.175 0.315 0.506
1990 0.481 0.418 0.189 0.342 0.547
South and
Central America
2000 0.489 0.429 0.192 0.349 0.557
1980 0.509 0.456 0.207 0.366 0.560
1990 0.443 0.342 0.156 0.290 0.475
Middle East
and
North Africa 2000 0.419 0.302 0.138 0.260 0.446
1980 0.407 0.340 0.142 0.289 0.555
1990 0.448 0.428 0.172 0.348 0.648
North America
2000 0.460 0.430 0.179 0.350 0.627
1980 0.395 0.261 0.125 0.230 0.388
1990 0.391 0.252 0.123 0.223 0.368
South Asia
2000 0.429 0.307 0.148 0.265 0.428
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database
(UN), Penn World Tables - Mark 5.6 (CIC) and WIID (WIDER).
Riding the Elephants: The Evolution of World Economic Growth ... 27
Table A4. Distribution of world income without Eastern Europe and Central Asia
Income shares by decile of world population (%) Change in prop.
of
total world
income
Annual income growth
(1985 PPP value
of income)
1980 1990 2000 1980-2000 1980-
1990
1990-
2000
Decile 1 0.64 0.71 0.72 0.08 2.5% 1.9%
Decile 2 1.09 1.28 1.25 0.16 3.0% 1.5%
Decile 3 1.43 1.67 1.81 0.38 3.0% 2.6%
Decile 4 1.85 2.07 2.31 0.46 2.5% 2.9%
Decile 5 2.34 2.54 2.96 0.62 2.2% 3.3%
Decile 6 3.15 3.60 4.05 0.90 2.7% 3.0%
Decile 7 4.97 5.09 5.90 0.93 1.6% 3.3%
Decile 8 10.33 9.12 9.84 -0.49 0.1% 2.6%
Decile 9 23.91 22.14 20.79 -3.12 0.6% 1.1%
Decile 10 50.28 51.77 50.37 0.09 1.7% 1.5%
World 100.00 100.00 100.00
Measures of inequality 20-year change
Gini coefficient 0.675 0.669 0.652 -0.023
Theil coefficient 0.954 0.899 0.844 -0.110
Atkinson (0.5) 0.377 0.367 0.347 -0.030
Atkinson (1) 0.615 0.593 0.570 -0.045
Atkinson (2) 0.798 0.780 0.774 -0.024
Ratio of top to bottom decile
incomes 78.8 73.0 70.3
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database (UN),
Penn World Tables - Mark 5.6 (CIC) and WIID (WIDER).
28 DESA Working Paper No. 27
Chart A1. Evolution of world income inequality
(Gini coefficient Values)
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database (UN),
Penn World Tables - Mark 5.6 (CIC) and WIID (WIDER).
0.500
0.520
0.540
0.560
0.580
0.600
0.620
0.640
0.660
0.680
0.700
1980 1990 2000
All
Countries
Without
China
Without
China and
India
Without
Eastern
Europe
Riding the Elephants: The Evolution of World Economic Growth ... 29
Appendix B
Table B1. World Bank and adjusted estimates of Chinese GDP
Year World Bank estimates of GNP
(Trillions of current international dollars)
Our estimates of GNP
(Trillions of current international dollars)
1980 455,826 588,547
1990 1,586,011 1,624,306
2000 4,965,740 4,041,983
Source: World Development Indicators (World Bank).
Table B2. Sensitivity analysis (of world inequality and output measures) with respect to output and growth assumptions for China
World inequality measures
using official (World Bank) data
Change in inequality coefficients between 1980 and 2000
Assumptions/
measures 1980 1990 2000
Change
(1980-
2000)
(1) (2) (3) (4) Workin g
assumption (6) (7) (8) (9)
(a) Percent official undervaluation of 1987 GNP
(b) Percentage points overestimation of GNP growth
5
2.0
5
2.5
5
3.0
10
2.0
10
2.5
10
3.0
15
2.0
15
2.5
15
3.0
Gini 0.660 0.649 0.630 -0.029 -0.015 -0.011 -0.008 -0.015 -0.012 -0.008 -0.016 -0.012 -0.008
Theil 0.940 0.849 0.779 -0.161 -0.105 -0.092 -0.078 -0.102 -0.089 -0.075 -0.099 -0.086 -0.072
Atkinson (0.5) 0.361 0.344 0.323 -0.038 -0.021 -0.017 -0.012 -0.021 -0.017 -0.012 -0.021 -0.017 -0.012
Atkinson (1) 0.609 0.572 0.541 -0.068 -0.045 -0.039 -0.033 -0.044 -0.038 -0.032 -0.043 -0.037 -0.031
Atkinson (2) 0.810 0.775 0.759 -0.051 -0.035 -0.031 -0.027 -0.033 -0.029 -0.026 -0.031 -0.028 -0.024
1980---
1990
1990---
2000
Average Output growth, 1980-2000
World output growth 2.91 2.60 2.76 2.68 2.65 2.63 2.69 2.66 2.64 2.7 2.67 2.65
Per capita output growth 1.21 1.20 1.20 1.12 1.10 1.08 1.14 1.11 1.09 1.15 1.12 1.10
Sources: Authors’ calculations using data from the WDI (World Bank), UN Common Database (UN), Penn World Tables - Mark 5.6 (CIC) and
WIID (WIDER).
30 DESA Working Paper No. 27
Appendix C
Selection criteria, data sources and sample size
Inclusion:
A. Estimates of output growth (tables 1 and 2)
All countries with output data in both domestic currency and current international dollars
(PPP) for the period 1970 to 2000.
B. Inequality measures and poverty lines
All countries with income data in both domestic and current international dollars from
1980, 1990 and 2000 (or sufficiently close to allow estimation).
Number of countries in the sample used for this paper:
136 countries for tables 1 and 2 (measuring output growth) and 163 countries for the
remaining tables (measuring income distribution).
Main data sources:
World Development Indicators (online edition), The World Bank;
UN Common Database (online edition), The United Nations;
The Penn World Tables (The Mark 5.6 Database), University of Pennsylvania;
Coverage:
1980 1990 2000
Total population of countries included (millions) 4,259.0 5,043.5 5,801.2
Percent of world population 95.5 96.0 95.8
Percent in countries of over 25 million33 85.6 85.2 84.7
Countries of substantial size (in terms of population) missing from the sample, due to
insufficient data, and their estimated 2000 population (in millions):
Afghanistan (26.6)
Iraq (23.3)
Myanmar (45.6)
North Korea (23.6)
Methodology for estimating the distribution of world income between persons
Based on the best estimates of the distribution of income among persons in 1980, 1990 and 2000,
all countries with populations of 25 million or greater in 2000 were subdivided into sub-national
(or intracountry) income groups. The exception was the Democratic Republic of Congo (for
which there was no relevant distribution data). Countries with population between 25 million and
200 million (a total of 31) were divided into population quintiles. Countries with populations
above 200 million but less than one billion (Indonesia and the United States) were subdivided
into population deciles. China and India, with populations of over a billion, were each
subdivided into forty groups of equal population but varying average incomes. The income
Riding the Elephants: The Evolution of World Economic Growth ... 31
proportions for the forty population groups were estimated through interpolation. Basically,
beginning with a decile distribution, income is subdivided (into forty equal population groups) in
a manner that reproduces the same Gini coefficient of the original distribution.
Using this method, 35 large countries were mapped to 255 sub-national income groups
covering approximately 85 per cent of the total sample population in each year. The remaining
small countries (128 in all) were treated as single income groups. Though this created a
heterogeneous mix of data points (referencing both income-based, sub-national groups and
whole countries) our sensitivity analyses indicate that further subdivision (of countries) would
have had little discernible effect on distribution measures (for the world and regions) but would
greatly increase data demands.
The distribution estimates used for translating country incomes (GNP or GNI) into the
income of sub-national income groups were measures of the division of GNI by quintile or decile
(or more) of persons. Thus, for example, a country with a quintile distribution of income of 6 per
cent, 12 per cent, 19 per cent 26 per cent and 37 per cent for a particular year, could be divided
into five sub-national groups, each consisting of 20 per cent of the country’s population but with
6 per cent, 12 per cent, 19 per cent, 26 per cent and 37 per cent of the national income
respectively.
However, the available distribution data was not always in the form of income per
person. A significant proportion of distribution data is expenditure based and/or uses households
(rather than persons) as the enumeration unit. There is no fixed derivable conversion factor
between those various measurement methods because of the variation in spending patterns and
average household sizes across countries and income groups. However, it is not a great stretch to
assume that the relationship between those measures would not change radically from year to
year within a single country, and that it would be similar for countries with similar social and
economic structures. We, therefore, used implied conversion factors (i.e., we assumed that the
relationship between different distribution measures was roughly constant across time within the
same country and similar across countries that are alike in terms of income and geographic
location or structure). Thus, for example, the (computed) relationship between estimates of the
distribution of household expenditure by quintile of households and the distribution of income by
quintile of persons, both measured in 1988 for France, could be used to convert a 1980 estimate
of the distribution of expenditure by quintile of households to an approximate distribution of
income by quintile of persons for France in that same year. That same implied conversion matrix
can be credibly used to convert a similar measure for Germany in 1990, though not for a clearly
dissimilar country, such as Iran, or even for Germany in 2000.
Data was also limited in terms of available years. Distribution data was not always
available for the exact years of 1980, 1990 or 2000. More often, data would be for other years
close to those years (e.g., 1981, 1992, etc). We worked on the assumption that data for one to
three years from 1980, 1990 or 2000 could serve as proxies for those years (e.g., 1982 for 1980).
In a few cases, where compatible measures bracketed the year in question (e.g., 1978 and 1982),
the desired distribution was derived by interpolation.
32 DESA Working Paper No. 27
Data limitations also meant that, for some countries, available data was not sufficient to
indicate distribution changes for both of the sub-periods (1980-1990 and 1990-2000). Where such
data was not available, we assumed no change in the distribution of income. Though this
assumption is necessarily somewhat incorrect, it avoids the imposition of an arbitrary judgment
on how inequality may have changed. Since the evidence from intracountry Gini coefficient
changes strongly suggest that income distribution worsened in a majority of countries, the
assumption of no change almost certainly biases estimates of changes in world intracountry income
distribution downwards.
Though many sources were used for distribution estimates, the main sources were the
UNDP-WIDER Income Inequality Database and the 2001 World Bank World Development
Indicators.
The Atkinson coefficients
The Atkinson coefficient is not a single measure but a class of measures individually
differentiated by the degree of aversion to inequality (or implied welfare cost of inequality)
represented by the parameter e. The e term can also be treated as an inequality sensitivity index.
The measures can be defined as one minus the ratio of an equity sensitive estimate of
mean income over the arithmetic mean income.
u
y
eA e)(
1)( −=
The equity sensitive mean income is defined by the equation:
∑⋅−
=−
)( 11
1
)( yi
pi
ey ee
where pi is the population weight for income group i and yi is the average income for income
group i. Thus the direct formula for the index is:
()
1,0lnexp1
1,0
)(
1
1
)(
1
1
)(
=≥
⎥
⎦
⎤
⎢
⎣
⎡∑
−=
≠≥
∑
−
⋅−= ⎥
⎦
⎤
⎢
⎣
⎡−
ee
yi
pi
A
ee
yie
pi
A
e
e
e
μ
μ
The weight attached to a marginal increase in the income of the highest income group relative to
the same increase in income for the lowest income group is determined by the weighting factor
(x) that is related to the sensitivity parameter e by the formula:
z
1
e
x=
where z is the ratio of the income of the richest group to that of the poorest. Thus, given z, as e
increases, the equity sensitive mean income, and thus the Atkinson index, becomes increasingly
Riding the Elephants: The Evolution of World Economic Growth ... 33
sensitive to income changes at the bottom end of the distribution. By the same token, as e
increases, the equity sensitive mean income is less and less responsive to income increases at the
top end of the distribution but, because the arithmetic mean remains just as sensitive, the
Atkinson index is also increasingly sensitive to such changes.
For e=0 (meaning that x=1) no additional weight is attached to the income of the poorest (or any)
group (the equity sensitive mean income is identical to the arithmetic mean). Absolute income
inequality is acceptable since the Atkinson (0) is always equal to 0. At the other extreme, if e=∞
then all weight is attached to the income of the poorest group and thus the equity sensitive mean
is always essentially zero and the Atkinson (∞) is always 1. All inequality is extreme (or, put
differently, no price is too high to pay for income equality).
More reasonably, if e=0.5 and z=10 (meaning x=0.316), then, a marginal increase in the income
of the highest income group causes the equity sensitive mean to increase by roughly one-third
(31.6 per cent) of the amount by which it would have increased if that same (marginal) income
had gone to the lowest income group. But since the arithmetic mean does not differentiate, the
increase at the top end causes the inequality measure to increase (the second term in the A(e)
equation above gets smaller) while the increase in income at the lower end causes it to decrease.
Put differently, if a marginal dollar were to be transferred from the highest income group to the
lowest income group, but 68.4 cents (i.e., 100-31.6) of that income was lost in the act of transfer,
then the equity sensitive mean income would be identical before and after transfer!
If e=2 and z=10, then x=0.01. This means that a marginal increase in the income of the highest
income group would increase the equity sensitive mean income by only 1 per cent (one one-
hundredth) of an identical (absolute) increase in the income of the lowest income group. In fact,
put in dollar terms, the equity sensitive mean would respond equivalently to a $1 increase in the
income of the lowest income group and a $100 increase in the income of the highest income
group!
Thus, the A(2) is much more sensitive to income inequality than is the A(0.5). The A(1), of
course, is between those two extremes and its values tend to be close, in terms of both magnitude
and sensitivity, to those of the Theil indices.
34 DESA Working Paper No. 27
Appendix D
Regional grouping of the countries included in the sample
Sub-
Saharan
Africa
East Asia South
Asia
South and
Central
America
Middle
East and
North
Africa
Eastern
Europe
and Central
Asia
Western
Europe
North
America
B
enin
B
otswana
B
urkina Faso
B
urundi
C
ameroon
C
entral
African
Rep.
C
had
C
omoros
C
ongo, Dem.
Rep.
C
ongo, Rep.
C
ote d'Ivoire
E
thiopia
G
abon
G
ambia
G
hana
G
uinea-
Bissau
K
enya
L
esotho
M
adagasca
r
M
alawi
M
ali
M
auritania
M
auritius
M
ozambique
N
amibia
N
ige
r
N
igeria
R
wanda
S
enegal
S
ierra Leone
S
outh Africa
S
waziland
T
ogo
U
ganda
Z
ambia
Z
imbabwe
A
ustralia
C
hina
F
iji
H
ong
Kong,
China
I
ndonesia
J
apan
K
orea,
Rep.
M
alaysia
N
ew
Zealand
P
apua New
Guinea
P
hilippines
S
ingapore
S
olomon
Islands
T
hailand
B
angladesh
I
ndia
N
epal
P
akistan
S
ri Lanka
A
ntigua and
Barbuda
A
rgentina
B
arbados
B
elize
B
olivia
B
razil
C
hile
C
olombia
C
osta Rica
D
ominica
D
ominican
Republic
E
cuado
r
E
l Salvado
r
G
renada
G
uatemala
G
uyana
H
aiti
H
onduras
J
amaica
N
icaragua
P
anama
P
araguay
P
eru
St
Kitts,
Nevis
St
Vincent
and the
Grenadines
S
uriname
T
rinidad and
Tobago
U
ruguay
V
enezuela
A
lgeria
B
ahrain
E
gyp
t
I
ran
I
srael
J
ordan
M
orocco
O
man
Q
ata
r
S
audi
Arabia
S
yria
T
unisia
U
nited
Arab
Emirates
B
ulgaria
C
zechoslovakia
H
ungary
P
oland
R
omania
C
ountries of
the former
Soviet Union
A
ustria
B
elgiu
m
C
yprus
D
enmar
k
F
inland
F
rance
G
ermany
G
reece
I
celand
I
reland
I
taly
L
uxembourg
M
alta
N
etherlands
N
orway
P
ortugal
S
pain
S
weden
S
witzerland
T
urkey
U
nited
Kingdom
B
ahamas
C
anada
M
exico
U
SA
