International inequality (Concepts 1 and 2) Milanovic, “Global inequality and its implications” Lectures 3-5

Definitions

Three concepts of inequality defined Concept 1 inequality Concept 2 inequality Concept 3 (global) inequalty

Definitions Different types of inequality

What world inequality are we talking about? Comparison between the three concepts of inequality

Concept 1 inequality, 1950-2002

Inequality between countries coverage: countries and population

About 140 countries included; about 6200 country/year GDPs almost 100 percent of world population and world GDP (in current dollars) current countries projected backward (NEW)  SIMA World Bank data used to get benchmark 1995 $PPP GDP per capita; then these GDP per capita projected backward and forward using countries’ real growth rates (78% of data from WB sources; others mostly from national SYs; some from PennWorld Tables, UN sources)

Inequality, 1950-2005: The mother of all inequality disputes 0.7 Global inequality (Concept 3) 0.6 Gini coefficient Weighted international inequalty (Concept 2) Weighted international inequality without China 0.5 Unweighted international inequality (Concept 1) 0.4 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004

Unweighted inter-national inequality, 1950 to 2000 According to Concept 1, countries' performances have diverged over the last two decades   Unweighted inter-national inequality, 1950 to 2000

And it is not only because Africa is falling behind

Regional convergence and divergence (Gini and Theil index) Africa Asia Latin America, Caribbean Eastern Europe and former USSR

WENAO Note: Theil Index is always shown by the lower line. The definition of the Theil entropy index is where yi = income of i-th country, μ=mean income, and n=-sample size.

Concept 1 inequality in historical perspective: Convergence/divergence during different economic regimes

Relationship between Gini and ln GDI per capita, 2002

Convergence and growth theory

Convergence and divergence Unconditional or σ convergence (original studies by Baumol for OECD countries based on Maddison data). All countries end up with the same steady-state equilibirum level (NCGT). Slower growth of richer countries as MPK falls and they get closer to technological frontier (technology is freely available to all) Conditional or β convergence (Barro with human capital only on the RHS instead of K and L). Growth regressions; based also on endogeneous (“new”) growth theory; each country ends with its own steady-state equilibrium

Relationship between δ and β convergence Sigma (or any other inequality measure) convergence: direct judgment about dispersal of income levels Beta convergence: indirect (regression-based) regularity; thus not very useful except that it allows us to retrieve a structural parameter in a growth model β does not imply δ convergence; but δ convergence implies β convergence (Wodon and Yitzhaki 2006 Economic Letters).

Endogeneous growth in response to increasing returns to scale (no ↓ MPs), monopolistic competition (no free competition), and no free diffusion of technology (all key neoclassical assumptions abandoned), role of policies and institutions important Noted: Lucas paradox: capital flows from rich to rich countries; mean country incomes diverge But β convergence compatible with greater dispersal of growth rates and incomes Often meaningless: if Ethiopia had education level and institutions of the US, it would grow faster than the US! (These factors are concommitant with high income, not independent of it.)

State steady income Depends on A = initial technology but also resource endowment, climate, institutions etc, g = rate of technological progress, s = savings (investment) rate, n = population or labor growth rate, δ = depreciation, α = share of capital in total output. y* = income per effective unit of labor. In unconditional convergence, all economies the same, β<0 even if no other RHS variable Or economies differ only if one or more of these parameters differ. Some of the parameters to be included on the RHS. And find out if β is negative then. But do not forget about A!

Endogenous growth: Romer’s key points Technological change propels growth Technological change endogenous (responds to incentives) Technological change (knowledge) is a non-rival but partially excludable good (non-rival: can be used by many; excludable: you can exclude some people from using it) Excludability (intellectual property rights) is crucial to cover fixed costs of research and leads to increasing economies of scale (and hence to divergence in incomes) (Romer: The origins of endogenous growth, JEP, 1994)

Panel approach : heterogeneity of countries Allow for country-fixed effect (contained in A); large differences in technology (A): variables like institutions, climate etc. which are in country fixed effect influence income level (not sufficient to use K, L) Instrument for A; since A is “kitchen-sink” variable, it can be instrumented by almost any variable If both A and g differ, no convergence If parameter heterogeneity (Pasaran & Binder); no sense to talk about cross-country regressions which constrain the parameters (even in panels)

The bottom line σ convergence among rich countries since WW2 and possibly earlier; at least in terms of wage-rates (Williamson), and even during the Inter-war years (Milanovic, Restat) σ divergence for the world recently, but also historically, since the Industrial revolution σ or unconditional divergence is the same as increase in Concept 1 inequality (Gini instead of st. deviation of logs) The world of increasing returns to scale PF is a world of high income and very high inequality (examples of Sylicon valley, soccer)

Link between HOS trade, growth convergence and global income distribution Factor price equalization theory depends on openness (not necessarily trade); HOS affects factor prices Under full openness, factor prices will be equal across countries Yet per capita incomes may differ, since per capita income = Σ wi (factor prices) where weights (w) depend on factor endowments which are not equal across countries So trade may affect within-national distributions, and growth rates of poor and rich countries => determining global income distribution T

The two periods, 1960-1978 and 1978-2000

Focus first on inequality between countries: Discontinuity in development trends around 1978-80 The watershed years (Bairoch) Tripling of oil prices Increase in real interest rates (from –1% to +5% in the USA and the world) Debt crisis China’s responsibility system introduced Latin American begins its “lost decade”, E. Europe/USSR “stagnate”

But also discontinuity in inequality trends Within-country inequalities have been rising during the last two decades (US, UK, China, India) Inequalities between countries are rising since 1978 Population weighted inequality between countries decreasing since 1978 thanks to growth in China and India (Caveat: acc. to Maddison Concept 2 inequality is almost stable) Inequality among people in the world is very high (Gini between 62 and 66) but its direction of change is not clear

The outcome: Middle income countries declined (Latin America, EEurope/former USSR) China and India pulled ahead Africa’s position deteriorated further Developed world pulled ahead World growth rate decreased by about 1 % (compared to the 1960-78 period)

Different way to look at world growth rates 1960-1980 1980-2000 Unweighted (each country counts the same) 2.9 0.8 Percentage negative 23 33 China 2.7 8.2 India 1.2 3.6 Population-weighted 3.0 3.2 World 2.6 1.6

Annual per capita growth rates 1980-2002 Mean Median Percentage negative “Old OECD” 1.9 2.0 17 Middle income countries 1.0 1.8 33 LLDC 0.1 0.8 43

Growth over 1980-2002 period as function of initial (1980) income

Distribution of population (in %; year 2000) according to how country did over 1980-2000 Africa Asia WENAO LLDC Big time winners (>58%) 13 90 7 26 Winners 34 93 27 Losers 44 3 38 Big time losers (>20%) 9 Total 100

The Four Worlds

Define four worlds: First World: The West and its offshoots Take the poorest country of the First World (e.g. Portugal) Second world (the contenders): all those less than 1/3 poorer than Portugal. Third world: all those 1/3 and 2/3 of the poorest rich country. Fourth world: more than 2/3 below Portugal.

The border countries and their GDP per capita levels (in $PPP, 1995 prices)

Overall upward and downward mobility 1960-78 and 1978-2000

Four Worlds in 1960

Four Worlds in 2003

Four worlds in 1960 and 2003 1960 2003 First 41 26 27 16 Second 22 12 Number of countries % of population First 41 26 27 16 Second 22 12 7 2 Third 39 13 29 37 Fourth 25 49 72 46

Poorer than during Carter Parts of Africa where 2000 GDI per capita is less than in 1980 (350m people ) US GDI per capita in the meantime increased 50%

Poorer than during J.F. Kennedy Parts of Africa where 2000 GDI per capita is less than in 1963 (180m people ) US GDI per capita in the meantime doubled

Why Concept 1 inequality matters Are poor countries catching up as we would expect from theory? Are similar policies producing the same effects or not? (Rodrik: convergence of policies, divergence of outcomes). Why? Migration issues Countries are not only interchangeable individuals (random assortments of individuals); they are cultures. Divergence in outcomes is elimination of some cultures. Perhaps it’s good, perhaps not.

Transition countries: continued output divergence despite policy convergence twoway (line EBRD_sd year) (line gdpppp_sd year, yaxis(2)), legend(off) text(6.2 1997 "standard deviation of all > EBRD indicators") text(3.5 2000 "standard deviation of GDI per capita")

LAC countries: continued output divergence despite policy convergence

The key borders today First to fourth world: Greece vs. Macedonia and Albania; Spain vs. Morocco (25km) First to third world: US vs. Mexico; Germany vs. Poland; Austria vs. Hungary In 1960, the only key borders were Argentina and Uruguay (first) vs. Brazil, Paraguay and Bolivia (third world), and Australia (first) vs. Indonesia (fourth)

Ratio of real GDI per capita Year 2002 Year 1960 Approximate % of foreign workers in labor force Ratio of real GDI per capita Greece (Albanians) 7.5 4 to 1 2.2 to 1 Spain (Moroccans) 12.0 4.5 to 1 2.3 to 1 United States (Mexicans) >10.0 4.3 to 1 3.6 to 1 Austria (former Yugoslavs) 10.0 2.7 to 1 2.6 to 1 Malaysia (Indonesians) >14.0 5.3 to 1 1.5 to 1

The two periods of international growth Mean (unweighted) incomes: “Rest against West” Regional homogeneity 1960-1978 Rest catching up Strong divergence in Asia & Africa; divergence in EEurope/FSU; mild convergence in WENAO and LAC 1978-2000 All falling behind except Asia Continued strong divergence in Africa, joined by EEurope; mild divergence in Asia & LAC; continued convergence in WENAO only

Concept 2 inequality, 1950-2000

Moving to Concept 2: its relevance and irrelevance Once we have Concepts 1 & 3, Concept 2 is redundant. But we have imperfect grasp of Concept 3 inequality => Concept 2 provides a check on “true” inequality (its lower bound) We use it to approximate “true” inequality. Think, at the limit, of each individual being a country

Population according to income of country where they live (2000) India, Nigeria China Brazil, Russia Mexico WEur, Japan USA histogram gdpppp [w=popu] if year==2000 & gdpppp<32000 & Dcont==1, bin(20) percent ylabel(0(10)40)

Inequality between population-weighted countries According to Concept 2, there is convergence among countries…

...or maybe there is not

Alternative Concept 2 calculations Alternative growth rates for China (official-World Bank, Maddison, Penn World Tables) Breaking China, India, US, Indonesia and Brazil into states/provinces (but redistribution within nations) Breaking China into rural and urban parts (Kanbur-Zhang data set) What PPP to use (Geary-Khamis, EKS, Afriat)

Implied China’s GDP per capita in different years According to different sources PWT 6.1 Maddison World Bank 1952 568 627 262 1960 662 785 497 1966 773 879 534 1978 899 1142 754 1988 1703 2119 1676 1999 3319 3803 3867 2000 3642 na 4144

Concept 2 inequality based on different data and partitions 0.600 WB with regions and China rural/urban WB data with 0.550 regions Maddison 0.500 World Bank PWT6.1 0.450 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Concept 2 inequality based on different data and partitions

How much has Concept 2 inequality changed (Gini points; 1985-2000)?

Distribution of people according to income of country where they live (ln GDPPPP pc; countries/provinces/states/R-U China, 1980-00 1980 2000 twoway (kdensity lngdp [w=popu] if Dgrand2==1 & year==1980 & lngdp<11)

From one to two poles? Concept 2 inequality in 1955 and 2000 twoway (kdensity lngdp [w=popu] if Dcont==1 & year==1955 & lngdp<11) (kdensity

Concept 2 between 1980 and 2000 Contributes to decline (equilibrating factors) Inclusion of provinces/states of China, India, Brazil, Indonesia, US (even if many within themselves are diverging!) 0.5 point Reverses decline (disequilibrating factors) Higher (old) income level in China (Maddison) 1.5 points Inclusion of rural/urban break up of China 0.5 points Result: we shave off half of the Concept 2 decline