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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 Individuals in: Countries World The usual within-country distributions (e.g. inequality in the US is greater than in Sweden) Global income distribution: distribution of persons in the world (comparable prices) Countries in: ----- Distribution of countries’ GDP per capita (rich vs. poor countries; are the poor countries catching up or not; the convergence literature) (comparable prices) What world inequality are we talking about? Comparison between the three concepts of inequality Main source of data Unit of observation Welfare concept National currency conversion Within-country distribution (inequality) Concept 1: unweighted inter-national inequality National accounts Country GDP or GNP per capita Concept 2: weighted international inequality National accounts Country (weighted by its population) GDP or GNP per capita Concept 3: “true” world inequality Household surveys Individual Mean per capita disposable income or expenditures Market exchange rate or PPP exchange rate (but different PPP concepts used) Ignored Ignored Included Concept 1 inequality, 1950-2000 Inequality between countries Coverage: number of countries and share of world population 160 Number of countries or coverage of world population 140 Number of countries included 120 Coverage of world population (in %) 100 80 60 40 20 0 19 50 19 52 19 54 19 56 19 58 19 60 2 6 19 19 64 19 66 19 68 19 70 19 72 74 19 19 Year 76 19 78 19 80 2 8 19 19 84 19 86 19 88 19 90 19 92 19 94 19 96 8 9 19 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) 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). Growth regressions; based also on endogeneous (“new”) growth theory; each country ends with its own steady-state equilibrium • Endogeneous growth in response 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 level of income y* Ae gt [ s /( n g • Depends on A = initial technology but also resource enbdowment, clisate, institutions etc, g = technological progress, s = savings (investment) rate, n = population or labor growth rate, g = rate of technological progress, δ = depreciation, α = share of labor in total output • 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! 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 countrty fixed effect influence income level (not sufficient to use K, L) • Instrument for A; since A is “kitchen-sink” variable 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 crss-country regressions which constrain the parameters (even in panelds) The bottom line • σ convergence among rich countries since WW2 and possibly earlier; at least in terms of wagerates (Williamson), and even during the Interwar yesrs (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) Going back to the 1978-2000 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 LLDC 1.0 1.8 33 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%) Winners 13 90 7 26 34 7 93 27 Losers 44 3 0 38 Big time losers (>20%) 9 0 0 9 100 100 100 100 Total 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) 1960 1978 2000 Greece (13821) Barbados (13297) Malaysia (9887) Slovak (8595) Egypt (4630) Bulgaria (4313) First to second Portugal (3205) Croatia (3085) Second to third Haiti (2139) Malaysia (2120) Portugal (7993) Puerto Rico (7662) Armenia (5294) Fiji (5156) Third to fourth Nigeria (1080) Madagascar (1031) Guyana (2728) Cote d’Ivoire (2649) Overall upward and downward mobility 1960-78 and 1978-2000 1978-2000 1960-78 Four Worlds 1960 Four Worlds 2003 Four worlds in 1960 and 2003 1960 2003 Number of % of Number of % of countries population countries 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. 3500 Transition countries: continued output divergence despite policy convergence 4 3000 5 st dev. of gdpppp per capita 6 standard deviation of all EBRD indicators 2500 2 2000 3 standard deviation of GDI per capita 1990 1995 2000 Year... 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") 2005 LAC countries: continued output divergence despite policy convergence 8.00 4 St deviation of the Lora reform indexindicator 7.00 3.9 6.00 3.8 5.00 3.7 4.00 3.6 St. deviation of GDI per capita 3.00 3.5 2.00 3.4 1.00 3.3 0.00 3.2 1985-1988 1988-1991 1992-1994 1995-1997 1998-1999 The two periods of international growth Period 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 Year 20 00 19 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 19 80 19 78 19 76 19 74 19 72 19 70 19 68 19 66 19 64 19 62 19 60 19 58 19 56 19 54 19 52 19 50 Gini index The mother of all inequality disputes 0.700 Global inequality 0.600 Populationweighted 0.500 Unweighted 0.400 How are Concepts 2 and 3 related? • In Gini terms: n n 1 i1 Gi pii i n y y ) p p L j i i j j i • where Gi=individual country Gini, π=income share, yi = country income, pi = popul. share, μ=overall mean income, n = number of countries • In Theil: n n p Ti p ln i i 1 i i yi Inequality between population-weighted countries According to Concept 2, there is convergence among countries… 0.780 0.740 0.700 Theil 0.660 0.620 0.580 Gini 0.540 19 50 19 52 19 54 19 56 19 58 19 60 19 62 19 64 19 66 19 68 19 70 19 72 19 74 19 76 19 78 19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 0.500 19 50 19 52 19 54 19 56 19 58 19 60 19 62 19 64 19 66 19 68 19 70 19 72 19 74 19 76 19 78 19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 Gini coefficient ...or maybe there is not 0.600 World 0.560 World without China 0.520 0.480 World without India and China 0.440 0.400 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 1952 568 627 World Bank 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 for different versions of China’s GDP per capita 0.5800 World Bank 0.5600 Penn World Tables Maddison 0.5200 0.5000 0.4800 98 96 94 92 90 88 86 84 82 80 00 20 19 19 19 19 19 19 19 19 19 78 Years 19 74 72 70 68 66 64 62 60 58 56 54 52 76 19 19 19 19 19 19 19 19 19 19 19 19 19 19 50 0.4600 19 Gini 0.5400 …and breaking China and India into their provinces/states. Inter-national population-weighted inequality: with China and India replaced by their provinces and states 65.0 60.0 Countries and regions of China (R/U) and India Countries and regions of China and India Gini index 55.0 Countries only 50.0 45.0 40.0 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Year How much has Concept 2 inequality changed (Gini points; 1985-00)? Whole countries ChIIBus by states + whole countries R/U for China World Bank data -3.3 Maddison data -1.9 -4.0 -2.3 -3.3 -1.9 .4 Distribution of people according to income of country where they live (ln GDPPPP pc; countries/provinces/states/R-U China, 1980-00 1980 .2 0 .1 kdensity lngdp .3 2000 6 7 8 9 10 x kdensity lngdp kdensity lngdp twoway (kdensity lngdp [w=popu] if Dgrand2==1 & year==1980 & lngdp<11) 11 .0001 0 .00005 kdensity gdpppp .00015 Distribution of people according to income of country where they live (GDPPPP pc; countries only 1980-2000 0 10000 20000 30000 40000 x kdensity gdpppp kdensity gdpppp 50000 .3 .2 .1 0 kdensitylngdp .4 .5 From one to two poles? Concept 2 inequality in 1955 and 2000 6 7 8 x kdensity lngdp 9 10 11 kdensity lngdp twoway (kdensity lngdp [w=popu] if Dcont==1 & year==1955 & lngdp<11) (kdensity Concept 2 between 1980 and 2000 Contributes to decline Reverses decline (equilibrating factors) (disequilibrating factors) • Inclusion of provinces/states of • Higher (old) income China, India, Brazil, level in China Indonesia, US (even if (Maddison) 1.5 points many within • Inclusion of themselves are rural/urban break up diverging!) 0.5 point of China 0.5 points Result: we shave off half of the Concept 2 decline