Cross-sectional data on consumers
Per KrusellIIES, CEPR, NBER
Anthony A. Smith, Jr.Yale University, NBER
March 2015
People are different . . .
. . . in the cross-section, and over time:
I Age (demographics not constant).
I Preference heterogeneity (patience, risk aversion, timeconsistency, effort cost, . . . ): only measured indirectly, basedon theory, or perhaps in lab.
I Earnings, wages; huge literature.
I Wealth (and portfolio composition); less of a huge literature.
I Other elements: health, household composition, . . . .
Here: just a brief review of “main facts” on income and wealth.
I Income in the form of earnings, hours, wages, andconsumption.
I Wealth (but different possible measures).
Empirical studies
I Old subject with early fundamental contributions (Kuznets,Atkinson, etc.).
I New treatments covered here:
I Javier Dıaz-Gimenez et al, “Facts on the Distributions ofEarnings, Income, and Wealth in the United States: 2007Update”, Federal Reserve Bank of Minneapolis QuarterlyReview , 2011.
I Jonathan Heathcote, Fabrizio Perri, and Giovanni L. Violante,“Unequal We Stand: An Empirical Analysis of EconomicInequality in the United States: 1967-2006”, Review ofEconomic Dynamics special issue, 2010.
I Alan Krueger (slide from recent presentation).I Dirk Krueger, Fabrizio Perri, Luigi Pistaferri, and Giovanni L.
Violante, “Introduction to Cross Sectional Facts forMacroeconomists”, introduction to RED special issue, 2010.
I Thomas Piketty, Capital in the Twenty-First Century.
–155250 –120750 –86250 –51750 –17250 17250 51750 86250 120750 155250 189750 224250 258750 293250 327750 362250 396750
3.0
2.5
2.0
1.5
1.0
0.5
0
Figure 1
Histogram of the 2007 Income Distribution (2007 USD)
%
Income
A large majority of the household heads in this group (88 percent) have completed college. Many of them are self-employed (48 percent, which is more than four times the sample average), and almost all of them are
The earnings-rich are still rich along all three dimensions, but appreciably less so than the earnings-richest. Their average earnings, income, and wealth are about three times the sample averages. Their income sources are similar to the sample aver-ages. When compared with the earnings-richest, more
their income comes from labor and less from busi-ness and capital sources. The household heads are still
ing completed college. A very large share of them are
closer look at earnings mobility in Table 28, where we show the transition matrices of those in the 35–45 age
Table 27
Transition Matrices for Earnings, Income,
and Wealth Quintiles, 2001–7
1970 1975 1980 1985 1990 1995 2000 2005
0.2
0.25
0.3
0.35
0.4
0.45
Year
Variance of Log Hourly Wages
1970 1975 1980 1985 1990 1995 2000 2005
0.26
0.28
0.3
0.32
0.34
0.36
0.38
Gini Coefficient of Hourly Wages
Year
1970 1975 1980 1985 1990 1995 2000 20051.7
1.8
1.9
2
2.1
2.2
2.3
2.4
P50−P10 Ratio of Hourly Wages
Year
1970 1975 1980 1985 1990 1995 2000 20051.7
1.8
1.9
2
2.1
2.2
2.3
2.4
Year
P90−P50 Ratio of Hourly Wages
Men
Women
Figure 4: Wage inequality for men and women (CPS)
1970 1975 1980 1985 1990 1995 2000 2005
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Variance of Log Hourly Wages
Year
1970 1975 1980 1985 1990 1995 2000 20050
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4Variance of Log Annual Hours
Year
1970 1975 1980 1985 1990 1995 2000 2005−0.17
−0.12
−0.07
−0.02
0.03
0.08
0.13
0.18
Correl. btw Log Hours and Log Wages
Year
1970 1975 1980 1985 1990 1995 2000 20050.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8Variance of Log Annual Earnings
Year
Men
Women
Figure 6: Inequality in labor supply and earnings of men and women (CPS)
1980 1985 1990 1995 2000 2005
0.25
0.3
0.35
0.4
0.45
0.5
0.55
Variance of Log
Year
1980 1985 1990 1995 2000 2005
0.28
0.3
0.32
0.34
0.36
0.38
0.4Gini Coefficient
Year
1980 1985 1990 1995 2000 20051.8
2
2.2
2.4
2.6
2.8
P50−P10 Ratio
Year
1980 1985 1990 1995 2000 20051.8
2
2.2
2.4
2.6
2.8
P90−P50 Ratio
Year
Equiv. Disp. Inc.
Equiv. ND Cons.
Figure 13: From disposable income to consumption (CEX)
1970 1975 1980 1985 1990 1995 2000 2005
0.2
0.3
0.4
0.5
0.6
Var. of Log Male Hourly Wage
Year
1970 1975 1980 1985 1990 1995 2000 2005
−0.05
0.05
0.15
0.25
0.35Var. of Log Male Hours
Year
1970 1975 1980 1985 1990 1995 2000 2005
0.5
0.6
0.7
0.8
0.9Var. of Log Equiv. Household Earnings
Year
1970 1975 1980 1985 1990 1995 2000 2005
0.25
0.35
0.45
0.55
0.65Var. of Log Equiv. Household Disp. Income
Year
CPS
PSID
CEX
Figure 16: Comparing the evolution of variances across data sets
Table 1: Countries and Contributors
Country Researchers Household Level Data Used
U.S. Heathcote, Perri & Violante CEX, CPS, PSID, SCF
Canada Brzozowski, Gervais, Klein & Suzuki FAMEX, SCF, ADSCF, LAD
U.K Blundell & Etheridge BHPS, FES, FRS, LFS
Germany Fuchs-Schundeln, Krueger & Sommer EVS, GSOEP
Italy Jappelli & Pistaferri SHIW
Spain Pijoan-Mas & Sanchez Marcos ECPF, ECHP, EFF
Sweden Domeij & Floden LINDA, LOUISE, HUT, HINK
Russia Gorodnichenko, Stolyarov & Peter RLMS
Mexico Attanasio & Binelli ENEU, ENIGH
Table 5. Level of Inequality in Year 2000
Bottom (50/10) Top (90/50)Country Disp Inc. Cons. Gap Disp Inc. Cons. Gap
Canada 2.21 1.95 0.26 2.00 1.85 0.15Germany 2.05 1.70 0.35 1.80 1.81 -0.01Italy 2.45 1.91 0.54 1.93 1.88 0.05Mexico 8.00 5.10 2.90 4.75 4.00 0.75Russia 3.02 2.70 0.32 2.60 2.60 0.00Spain∗ 2.04 1.82 0.22 2.00 1.90 0.10Sweden 1.58 1.62 -0.04 1.64 1.73 -0.09UK 2.82 NA NA 2.08 NA NAUSA 2.64 2.00 0.64 2.21 2.0 0.21
Average 2.98 2.35 0.65 2.33 2.22 0.15
* The level for Spain refers to year 1996
Table 6. Long-run Changes in Inequality
Bottom (50/10) Top (90/50)Country Disp. Inc. Cons. Gap Disp. Inc. Cons. Gap Period
Canada 0.38 0.20 0.18 0.10 0.07 0.03 1978-2006Germany 0.35 0.00 0.35 0.15 0.10 0.05 1983-2003Italy 0.22 0.09 0.13 0.05 0.01 0.04 1980-2006Mexico 5.81 0.80 5.01 1.12 1.08 0.04 1989-2002Russia 0.10 0.05 0.05 -0.16 -0.10 -0.06 1994-2005Spain -0.16 -0.13 -0.03 -0.18 0.01 -0.17 1985-1996Sweden 0.13 0.02 0.11 0.21 0.10 0.11 1985-1998UK 0.86 0.58 0.28 0.27 0.12 0.15 1978-2005USA 0.55 0.25 0.30 0.40 0.15 0.25 1980-2006
Average 0.91 0.21 0.71 0.22 0.17 0.05
Higher Income Inequality Associated with Lower Intergenerational Mobility
Denmark
Finland
France
GermanyJapan
New Zealand
Norway
Sweden
United Kingdom
United States
y = 2.2x - 0.27R² = 0.76
0.1
0.2
0.3
0.4
0.5
0.6
0.1
0.2
0.3
0.4
0.5
0.6
0.15 0.20 0.25 0.30 0.35 0.40
Inequality(1985 Gini Coefficient)
Intergenerational earnings elasticity
The Great Gatsby Curve
y = 2.2x - 0.27R² = 0.76
.
Source: Corak (2011), OECD, CEA estimates
g
14June 17, 2014
I C O
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%1810 1830 1850 1870 1890 1910 1930 1950 1970 1990 2010
Sh
are
of
top
dec
ile
or
per
cen
tile
in
to
tal
wea
lth
Top 10% wealth share:Europe
Top 10% wealth share:United States
Top 1% wealth share:Europe
Top 1% wealth share:United States
Figure 10.6. Wealth in e qual ity in Eu rope versus the United States, 1810– 2010
Until the mid- twentieth century, wealth in e qual ity was higher in Eu rope than in the United States.Sources and series: see piketty.pse.ens.fr/capital21c.
T S I
24%
22%
20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Sh
are
of
top
per
cen
tile
in
to
tal
inco
me United States Britain
Canada Australia
Figure 9.2. Income in e qual ity in Anglo- Saxon countries, 1910– 2010
! e share of top percentile in total income rose since the 1970s in all Anglo- Saxon countries, but with di erent magnitudes.Sources and series: see piketty.pse.ens.fr/capital21c.
I L I
24%
22%
20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Shar
e of
top
per
cen
tile
in t
otal
inco
me France Germany
Sweden Japan
Figure 9.3. Income in e qual ity in Continental Eu rope and Japan, 1910– 2010
As compared to Anglo- Saxon countries, the share of top percentile barely increased since the 1970s in Continental Eu rope and Japan.Sources and series: see piketty.pse.ens.fr/capital21c.
T S I
24%
22%
20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Shar
e of
top
per
cen
tile
in t
otal
inco
me France Denmark
SpainItaly
Figure 9.4. Income in e qual ity in Northern and Southern Eu rope, 1910– 2010
As compared to Anglo- Saxon countries, the top percentile income share barely increased in Northern and Southern Eu rope since the 1970s.Sources and series: see piketty.pse.ens.fr/capital21c.
I L I
28%
26%
24%
22%
20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%
Shar
e of
top
per
cen
tile
in t
otal
inco
me
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
IndiaIndonesiaChina Colombia
ArgentinaSouth Africa
Figure 9.9. Income in e qual ity in emerging countries, 1910– 2010
Mea sured by the top percentile income share, income in e qual ity rose in emerging countries since the 1980s, but ranks below the US level in 2000– 2010.Sources and series: see piketty.pse.ens.fr/capital21c.
400%
500%
600%
700%
800%
Ma
rke
t va
lue
of p
riva
te c
ap
ita
l (%
na
tio
na
l in
co
me
)
Germany
France
United Kingdom
100%
200%
300%
1870 1890 1910 1930 1950 1970 1990 2010
Ma
rke
t va
lue
of p
riva
te c
ap
ita
l (%
na
tio
na
l in
co
me
)
Aggregate private wealth was worth about 6-7 years of national income in Europe in 1910, between 2 and 3 years in 1950, and between 4 and 6 years in 2010.
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