Transcript Comments on Income and Wealth Concentration in a

Comments on Income and
Wealth Concentration in a
Historical and International
Perspective
Berkeley Symposium on Poverty,
the Distribution of Income, and
Public Policy
In the Last Two Years…
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Nine studies on income or wealth shares held
by the top percentiles of their distributions
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Income: Canada, France, Netherlands,
Switzerland, UK, and US.
Wealth: France, Switzerland, and US.
Fascinating work
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Long time series can help shed light on the effects
of taxation, business cycles, and other factors
influencing income and wealth distributions.
Cross-country differences can further be used to
consider the importance of alternative tax systems
and institutional environments.
Three Quibbles About
Emmanuel’s Paper
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Tax evasion is minimal on wages?
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Erard and Ho (2001, JPubE) on “ghosts.”
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15% ($11b) as large as the filer tax gap ($73b) in 1988.
60% of the ghosts income is W&S.
Most audit studies suggest that tax evasion
has declined over time?
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$232b in taxes were due in 1998 but not
collected, 31% more in real dollars than 1988.
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“The health of the federal tax administration system is on
a serious long-term downtrend” (C. Rossotti).
Likelihood of face-to-face audit: 2% in 1977,
0.1% in 2001.
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Criminal cases have plummeted.
Three Concerns, continued…
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There’s been only a very modest increase in
top wealth shares in the US and UK over the
last 25 years?
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Consistent with SCFs – wealth share of top 1
percent was 31.6% in 1962 and 32.3% in 2001.
But…
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95/50 ratio increased to 15.3 from 9.8
99/50 ratio increased to 68.8 from 35.8.
Figure 4: Net Worth Ratios Relative the the Median, 1962-2001, SCF Data
120
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90/50 net worth ratio
95/50 net worth ratio
98/50 net worth ratio
99/50 net worth ratio
99.5/50 net worth ratio
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0
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Net Worth to Median Ratio
100
Figure 3: Net Worth at Each Fractile of the Net Worth Distribution, 1962-2001 SCFS, 2001 dollars
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25th percentile
50th percentile
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90th percentile
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99th percentile
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99.5th percentile
Figure 7: Median Net Worth of Cohorts, Full Population (2001 dollars)
200000
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0
32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86
Age
25-39 in 1962
25-39 in 1983
25-39 in 1992
40-54 in 1962
40-54 in 1983
40-54 in 1992
Emmanuel and Gene
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Are linked by an interest in similar questions.
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Gene and colleagues were the first (to my
knowledge) to highlight a very important stylized
fact in the growth and inequality debate.
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In the ‘80s inequality and growth were positively
correlated: a trend that appears to have continued in
the ‘90s.
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Female labor supply and inequality of property income
accounted for the 1980s patterns (focusing on top 10%).
Learning from Gene:
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Don’t devise a Gini measure to account for shifts
in the age distribution of the population, or you
too can have the following said about your work…
Emmanuel and Gene, cont.
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Emmanuel extended income and wealth
inequality series for the US back to the
introduction of the income and estate taxes.
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Gene extended US poverty statistics, which
Census had calculated beginning in 1959, back to
1939 and 1949.
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It is noteworthy how sharply poverty rates fell over this
period (earnings poverty from 68.1% in 1939, 53.2, 35.8,
26.9, and it went up to 28.9% in 1979).
Among other factors correlated with the
increase in 1979 poverty rates, Gene started
directing IRP.
Where Emmanuel (and Gene)
Might Take This Research
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Two puzzles
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The sharp increase in US income inequality did not
lead to sharp increases in wealth inequality. Why?
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Concentration of capital income not fully convincing
Explosion in wage and salaries in English-speaking
countries but not elsewhere.
It is hard, but try to go further in
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Relating time series to behavioral hypotheses
about the level and structure of taxation.
What other factors affect inequality and how do
these vary cross countries and over time.
Can this tell us anything about arguments that
inequality erodes social “cohesion” and growth?
Emmanuel and Gene’s
Ongoing Research
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Explain why you care (and others should
care) about inequality.
Perhaps wealth inequality increases demand, and
consequently prices for goods like education that
have high wealth elasticities.
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Perhaps changing wealth inequality may lead to
errors in expectations about future events.
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This could exacerbate existing differences in IG education
transfers for education due to wealth differences.
Perhaps leading to life-cycle planning failures.
Wealth and political participation:
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Long-standing issue in the interest group, lobbying, and civic
participation literatures in political science.
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Lit focuses on income, would be nice to document effects of
wealth.