What determines income distribution and how income
distribution might affect growth
Branko MilanovicWorld Bank Training Poverty and Inequality Analysis
CourseMarch 3, 2011
A. From Kuznets to Piketty: determinants of income
distribution
1. Relationship between income and inequality: the rise and fall of
the Kuznets hypothesis
Kuznets inverted U-shaped curve (defined in 1955)
• As income increases, inequality at first goes up and then declines
• “It seems plausible to assume that in the process of growth, the earlier periods are characterized by…forces that may have widened the inequality…for a while because of the rapid growth of the non-A [non-agricultural] sector and wider inequality within it.
• It is even more plausible to argue that the recent narrowing in income inequality observed in the developed countries was due to a combination of • the narrowing inter-sectoral inequalities in product per worker, • the decline in the share of property incomes in total incomes of households, and • the institutional changes that reflect decisions concerning social security and full employment."
Kuznets curve: history• Evidence for Kuznets curve in cross-sectional
data analyzed in the 1970s, 1980s (Paukert, Lecaillon, Koeble & Thomas)
• More than 90% of pooled time-series and cross-sectional Gini variability is due to differences between countries => factors that determine country inequality are stable (Li, Squire, Zhou)
• Elusive evidence in time-series (Oshima)• Strong historical evidence for Western Europe
before and during Industrial revolution (Lindert and Willianson, van Zanden, Prados)
• Modifications of the Kuznets curve: “strong” and “weak” formulations
The same idea; Tocqueville 120 years earlier
• If one looks closely at what has happened to the world since the beginning of society, it is easy to see that equality is prevalent only at the historical poles of civilization. Savages are equal because they are equally weak and ignorant. Very civilized men can all become equal because they all have at their disposal similar means of attaining comfort and happiness. Between these two extremes is found inequality of condition, wealth, knowledge-the power of the few, the poverty, ignorance, and weakness of all the rest. (Memoir on pauperism, 1835).
• General formulation (used by Ahluwalia 1976)
• We expect β1>0 and β2<0
• Control variables include socialist dummy, government transfers, share of state sector employment, openness, age structure of population (Milanovic 1994; Williamson and Higgins 1999)
itt
k
ikititoit eZYYGini 221 )(lnln
Relationship between Gini and GDP per capita; (about 1100 Ginis between 1970 and 2005)
twoway (scatter Giniall lngdpppp if Giniall<65) (qfit Giniall lngdpppp, yline(20 60, lpattern(dash))), legend(off) xtitle(ln of GDP per capita in international dollars) ytitle(Gini)From global_new2.dta
Kuznets curve
20
30
40
50
60
Gin
i
6 7 8 9 10 11ln of GDP per capita in international dollars
• No controls; a weak inverted U relationship (more than 1300 Gini obs)
• Huge variability in inequality; R2 only 0.11• The upward sloping part of the curve
generally hard to discern• Turning point quite unstable; here about
$PPP 4,000 (level of Sri Lanka or Paraguay in 2008)
• Some disenchantment with the hypothesis: hard to see inverted U in time-series for a single country
No downward portion plotted against time or income: example of the USA
3035
4045
gini
WY+
gini
W in
that
ord
er o
f pre
cede
nce
1950 1960 1970 1980 1990 2000year when the survey was conducted
twoway scatter Giniall year if contcod=="USA", connect(l) ylabel(30(5)45)From allginis.dta.
3035
4045
Gin
i fro
m m
y al
lGin
i file
25000 30000 35000 40000 45000constant 2005 ppp, based on icp05
twoway scatter Giniall gdpppp if contcod=="USA", connect(l) ylabel(30(5)45)From global_new2
Example of China
3035
4045
Gin
i fro
m m
y al
lGin
i file
0 1000 2000 3000 4000constant 2005 ppp, based on icp05
Against income, 1970-2004
twoway scatter Giniall gdpppp if contcod=="CHN" & year<2005, connect(l) ylabel(30(5)45)From global_new2.dta
3035
4045
gini
WY+
gini
W in
that
ord
er o
f pre
cede
nce
1950 1960 1970 1980 1990 2000year when the survey was conducted
Against time, 1950-2004
twoway scatter Giniall year if contcod=="CHN" & year<2005, connect(l) ylabel(30(5)45)Based on giniall.dta
2. Credit market imperfections theory : “pull yourself by your
bootstraps”
Credit market imperfections• Poor households do not invest in human K even
if the returns are high; they invest in subsistence-related types of investment
• Indivisibilities: minimum threshold of K needed for investment; convex returns
• Societies with these problems both more unequal and wasteful in terms of human and capital resources
• Example of win-win strategy (inequality&growth)• Solutions: asset redistribution, no school fees,
deeper capital markets, micro finance
Credit constraint, education, democracy (Li, Squire & Zhou)
pooled IV formulation
Schooling 1960 -4.6** -4.4**
Democracy 1.6** 1.5**
Land Gini 60 0.16** 0.15**
Financial depth (M2/GDP)
-7.7** -10.1**
R2 0.62
No. of obs. 166 166
3. Political theory of income distribution
Methodologically, move from household survey data to fiscal
data
Long-run studies using income and inheritance tax data (Picketty et al.): France 1901-98
• Secular decline in inequality• Due to the declining share of top 1%• Due to the decreasing importance of large
capital income• Due to progressive taxation and
progressive (and high) inheritance taxes• Produces no effect on average K stock but
truncates large K holdings (lower concentration of capital income)
Story for the US (Piketty & Sanz)• Top K incomes decreased during the
Depression and WW2 and never recovered (top estates still lower in real terms than around 1900)
• Total K income did not decrease; its concentration did
• Change in factoral income composition among the top 1%; no longer mostly capitalists but salaried workers. Δ more pronounced in the US than in France
• Conclusion: No spontaneous decline in inequality. Role of depression, wars and progressive taxation. Policy and politics matter the most. A political theory of income distribution
Explanation by E. Saez in “Striking it richer”
The labor market has been creating much more inequality over the last thirty years, with the very top earners capturing a large fraction of macroeconomic productivity gains. A number of factors may help explain this increase in inequality, not only •underlying technological changes but also the retreat of institutions developed during the New Deal and World War II - such as • progressive tax policies, • powerful unions, • corporate provision of health and retirement benefits, and • changing social norms regarding pay inequality.
Recent findings
• A number of similar studies for developed countries reaches the same conclusion: a U-shaped inequality in the 20th century in English-speaking countries (UK: Atkinson 03; Netherlands: Atkinson & Salvedra 03; Italy: Brandolini)
• But also for India: Banerji and Piketty 2005• Long L shaped curve for the rest of
developed countries
A. Top 0.1% incomne share in English Speaking Countries
0%
2%
4%
6%
8%
10%
12%
1913
1918
1923
1928
1933
1938
1943
1948
1953
1958
1963
1968
1973
1978
1983
1988
1993
1998
Inco
me
Sha
re
United States United Kingdom Canada
Source: Piketty and Saez (2006)
Fig 5. Top 0.1% income share in Germany and Japan
0%
2%
4%
6%
8%
10%
12%18
8518
9018
9519
0019
0519
1019
1519
2019
2519
3019
3519
4019
4519
5019
5519
6019
6519
7019
7519
8019
8519
9019
9520
00
Inco
me
Sha
re
Japan Germany
Source: Piketty and Saez (2006)
Fig 3: Share and Composition of top 0.01% in the US
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%19
16
1921
1926
1931
1936
1941
1946
1951
1956
1961
1966
1971
1976
1981
1986
1991
1996
Salaries Business Income Capital Income Capital Gains
Source: Piketty and Saez (2006)
But this finding crucially depends on strong ρ btw. Gini and top income share; while true among
recent data, not true historically!
twoway scatter top_percent gini2 if Dancient==1, msize(vlarge) mlabel( country) xlabel(20(10)70)
Source: Milanovic, Williamson and Lindert (2009)
Roman Empire
Byzantium
Eng1290Florence
South Serbia
Levant
Eng1688
Hol1732India-Moghul
Old Castiille
Eng1759
France
Nueva España
Eng1801
Bihar
Netherlands
Kingdom of Naples
Chile
Brazil
Peru
Maghreb
China
Java1880
Japan
Kenya
Java1924
Kenya
Siam
India-British
01
02
03
0sh
are
of to
p 1
%
20 30 40 50 60 70gini2
B. How inequality might affect growth
Channel 1: The median voter hypothesis (Meltzer-Richard)
Political mechanism• Greater inequality in
factor income=>• Relatively poor μ
voter=>• Chooses relatively
high tax rate
Economic mechanism• High redistribution
and distorsionary effect of taxes =>
• Lower growth rate
Extent of redistribution = = fct (inequality in market income)
• Hypothesis 1. More market-unequal countries redistribute more (using two definitions of market income, without and with government pensions)
• Hypothesis 2. An increase in market share of a given decile is associated with a lower sharegain
• Question. If countries do redistribute more, is the mechanism through which it happens, the median voter hypothesis?
Redistribution is greater if market income share of the poor is less
Source: Milanovic 2000, 2009
02
46
8sh
areg
ain
in p
erce
nt
-1 0 1 2 3share of poorest market decile in percent
From figure.do based on data_voter_checked.dta
It holds for all deciles: if a decile is better-off in terms of marketP income distribution, it loses more through the redistribution
02
46
8sh
areg
ain
in p
erce
nt
-1 0 1 2 3share of poorest market decile in percent
01
23
45
shar
egai
n in
per
cent
1 2 3 4 5share of poorest market decile in percent
Bottom (first) decile Second decile
Richest (top) decile Second richest decile
-8-6
-4-2
0sh
areg
ain
in p
erce
nt
20 25 30 35share of poorest market decile in percent
-3-2
-10
shar
egai
n in
per
cent
15 16 17 18share of poorest market decile in percent
More market unequal states of the world associated with greater Gini reduction through redistribution
Without controls With controls
Gini of marketP income +0.438**(8.9)
+0.473**(8.2)
Openness +0.002(0.9)
GDP per capita (in logs) -0.004(-0.6)
Constant -0.010**(-5.3)
-0.070(0.3)
R2 (within) 0.47 0.54
Number of observations 110 100
Dependent variable: Gini reduction through redistribution. Country fixed effects regression. Source: Milanovic (2009)
But we cannot show that the middle deciles gains more if market inequality high
-8-6
-4-2
0ga
in o
f the
mid
dle
36 38 40 42 44 46share of the middle in market income
Source: Milanovic 2000
Sharegain of the very poor, 1973-2005 (using market income)
USA
Germany
24
68
10
Dis
trib
utio
na
l ga
in o
f th
e b
ottom
de
cile
1970 1980 1990 2000 2010year
twoway (scatter gain3 year if contcod=="DEU" & decile==1, connect(l)) (scatter gain3 year if contcod=="USA" & decile==1, connect(l)), legend(off) text(4 2000 "USA") text(7 2000 "Germany") ytitle(Distributional gain of the bottom decile) Based on data_voter_checked.dta
Channel 2: Inequality and property rights
Political mechanism• Greater inequality
creates cleavages =>• They are particularly
strong if coincide with ethnic differences (high horizontal inequality)=>
• Insecure property rights
Economic mechanism• Insecure property
rights =>• Lower growth rate
Inequality and property rights (Keefer & Knack)
Dependent variable:
protection of property rightsCross section
Ln GDP per capita 1985 7.61**
Ethnic tensions -0.933**
Income Gini circa 1985 -0.196**
Land Gini 1985 -0.097**
R2 0.80
No. of obs. 64
Dependent variable: Property rights: ICRG measure 1986-95. Ranges from 0 to 50.
Excursus: the reverse link and the reverse sign: greater protection of property rights
increases inequalityDependent Gini Gini (time-dummies
included on the RHS)
Property rights 0.929** 0.709*
Financial development (M2/GDI)
-0.064** -0.07**
Education 0.026 -0.016
Land inequality -0.016 -0.02
Democracy 0.438** 0.323**
Prop. Rights x Democracy
-0.056** -0.046**
R2 within (N) 0.26 (203) 0.35 (203)
• Greater protection of property rights increases inequality
• The rich elite is also politically powerful and protects its economic assets
• The effect is mitigated by the introduction of democracy
• => The negative effect of property rights protection is particularly strong in low-democracy environments
• But the regression does not include an income term
(results based on Savoia and Easaw, 2007; World Development, Feb. 2010)
Channel 3. Inequality caused by “morally irrelevant” characteristics
• Inequalities which are independent of individual effort, entrepreneurship or luck
• “Wasteful” (vs. instrumental or “useful”) inequalities
• Examples: education, health, opportunity to better oneself economically, to have a political voice
• Horizontal inequalities between ethnic/religious groups, education levels, socio-economic categories, geographical areas
Assumed ρ’s for different parts of the world
Base case Optrimistic (high mobility)
Pessimistic (low
mobility)
Average Gini (year 2002)
Nordic 0.2 0.15 0.3 27.5
Rest WENAO
0.4 0.3 0.5 33.7
E. Europe 0.4 0.3 0.5 30.6
Asia 0.5 0.4 0.6 37.6
LAC 0.66 0.5 0.9 53.8
Africa 0.66 0.5 0.9 42.6
Also a super-optimistic: ρ=0.2 for all; and super-pessimistic: ρ=0.9 for all. ρ’s based on literature review.
How one’s income depends on circumstances:(dependent variable: own household per capita income, in $PPP, logs)
Eq.
Mean per capita country income (in ln)
Gini index (in %)
Parents’ estimated income class (ventile)
Constant
Number of observations
R2 adjusted
Number of countries
6 (Pessimistic)
0.991
(0)
-0.019
(0.00)
0.109
(0.00)
-0.582
(0.00)
232,000
0.83
116
4 (Base)
0.986
(0.00)
-0.019
(0.00)
0.105
(0.00)
-0.513
(0.00)
232,000
0.81
116
5 (Optimistic)
0.987
(0)
-0.019
(0.00)
0.100
(0.00)
-0.462
(0.00)
232,000
0.80
116
• Circumstances at one’s birth (country + parents’ income class) explain between 83 percent (if world is fairly income-mobile within countries) and 85 percent (if there is less social mobility) of variability in income globally
• => thus, only a very small portion of global income differences can be due to effort
• Coefficient on country mean income remains 1; coefficient on parental income 0.1 (each notch is worth 10% increase in children’s income); coeff. slightly higher if there is less social mobility
• As a proxy, WDR06 looks at the contribution of horizontal inequalities to total inequality, or total “feasible between- inequality” (total Y of country=given; number and sizes of groups=given; ‘pecking order’ by group mean incomes= given; => find new group mean incomes that maximize the between component)
• Up to 40-45% of “feasible between inequality” explained by education differences
• Inequality traps and the interaction between political and economic power