What determines income distribution and how income distribution might affect growth
What determines income distribution and how income...
Transcript of What determines income distribution and how income...
What determines income distribution and how income
distribution might affect growth
Branko Milanovic World Bank Training Poverty and Inequality Analysis
Course March 5, 2012
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, unionization, 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 3
03
54
04
5
gin
iWY
+g
iniW
in th
at o
rde
r o
f pre
ced
en
ce
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.
30
35
40
45
Gin
i fr
om
my a
llG
ini 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
30
35
40
45
Gin
i fr
om
my a
llG
ini 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
30
35
40
45
gin
iWY
+g
iniW
in th
at o
rde
r o
f pre
ced
en
ce
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
China vs. India (using 2008 household surveys and $PPP)
China
India
456
100
03
65
01
00
00
500
00
inco
me p
er
ca
pita in
dolla
rs p
pp
pe
r ye
ar
0 20 40 60 80 100percentile
Calcul08.do using finla08.dta
The same data but forcing the means to be equal to
consumption per capita from national accounts…
China
India
456
100
03
65
01
00
00
500
00
inco
me p
er
ca
pita in
dolla
rs p
pp
pe
r ye
ar
0 20 40 60 80 100percentile
twoway (scatter inc2 group if group> 1 & contcod=="IDN", yscale(log) ylabel(456 1000 3650 10000 50000) /*
*/ legend(off) yline(456 3650) ytitle(income per capita in dollars ppp per year) xtitle(percentile)) /*
*/ (scatter inc2 group if group>1 & contcod=="CHN", text(20000 98 "China") text(2500 85 "India"))
…or GDI per capita
(should depreciation be counted as part of your income?)
China
India
456
100
03
65
01
00
00
500
00
inco
me p
er
ca
pita in
dolla
rs p
pp
pe
r ye
ar
0 20 40 60 80 100percentile
twoway (scatter inc1 group if group> 1 & contcod=="IDN", yscale(log) ylabel(456 1000 3650 10000 50000) legend(off) yline(456 3650) ytitle(income per capita in
dollars ppp per year) xtitle(percentile)) (scatter inc1 group if group>1 & contcod=="CHN", text(20000 98 "China") text(2500 85 "India"))
Gini and mean income (most recent, 2008 data,
100 countries)
ALB
ARG
ARMAUT
AZE
BEL
BGD
BGRBIH
BLR
BOL
BRA
CAF
CAN
CHL
CHN
CIV
CMR
COL
CRI
CYP
CZE
DEU
DNK
DOMECU
EGY
ESPEST
FIN
FRAGBR
GEOGIN
GRC
GTM
HND
HRV
HUN
IDN
IND
IRL
IRN
IRQ
ISL
ISR
ITA JPN
KAZ
KEN
KGZ
KHM
KOR
KOS
LAO
LBR
LTU
LUX
LVA
MAR
MDA
MDG
MEX
MKD
MNE
MNG
MOZMYS
NER
NIC
NLD
NOR
PAK
PAN
PER
PHL
POL
PRT
PRY
ROM
RUS
SLV
SRB
SVK
SVN
SWE
SWZ
SYR
THA
TJK
TUR
TZA
UGA
UKR
URY
USAVEN
VNM
WBG
YEM
.2.3
.4.5
.6
gin
i
1000 5000 10000 40000mean HS PPP inc, 2008 ICP
Calcul08.do based on final08.dta
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 S
hare
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%
1885
1890
1895
1900
1905
1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
Inco
me S
hare
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%1916
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
Hol1732
India-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
0
share
of to
p 1
%
20 30 40 50 60 70gini2
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
8
sh
are
ga
in in p
erc
en
t
-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 0
24
68
sh
are
ga
in in p
erc
en
t
-1 0 1 2 3share of poorest market decile in percent
01
23
45
sh
are
ga
in in p
erc
en
t
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
0
sh
are
ga
in in p
erc
en
t
20 25 30 35share of poorest market decile in percent
-3-2
-10
sh
are
ga
in in p
erc
en
t
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 (positive value) 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
0
gain
of
the m
iddle
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
Greater inequality reduces
safety of property rights (Keefer & Knack)
Dependent variable:
protection of property rights Cross 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.
Or, the reverse link and the reverse sign:
greater protection of property rights
increases inequality
Dependent 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