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This presentation can bedownloaded – in either .docx or .pptx format, from my web page, at:www-personal.umd.umich .edu/~mtwomey
French version, 2013English version, 2014Spanish version, 2014
Sole-authored
Almost 700 pages long. Plus another >200 pages of footnotes, references,further tables, all of whichis available for free on theweb.
Thomas Piketty
Born Paris, 1971Ph.D. 1993, at Paris and LSETaught at MIT in 1993 - 1995 Currently teaches in ParisAlso writes for Libération and Le Monde
EmmanuelSaez
Born 1972Prof at UC Berkeley
(Sir)AnthonyAtkinson
Born 1944
Prof at LSE& Oxford
“Top incomes in Franceduring the 20th century”
Sole authored. 2001.800 pages
Plus, he’s published abouta dozen papers in academic journals.
The major one for us wasin 2003, co-authored with Saez.
Published 2007
Published 2010.
http://topincomes.g-mond.parisschoolofeconomics.eu/#Database:
And it’s all free!
%Inc
AB
Percent of Population, from poorest to richest
B% of population, from poorest to richest
Cum
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of I
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by
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f pop
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Closely related measures of Inequality: Gini Coefficient and Top Income Share
A
The area A reflects inequality.
Gini = A/(A+B)
Top Income Share of the highest z% is the length of the red line.
z
Gini Coefficient of Income Inequality in the U.S.
0.30
0.33
0.35
0.38
0.40
0.43
0.45
0.48
0.50
Gini
Source: US Gov’t http://www.census.gov/hhes/www/income/data/historical/families/index.html
Long U-shaped curve, from before the 1930s Depression. Low point in late 1960s.This pattern is well known; an early analysis was by Simon Kuznets.It has long been known that the source of this data underestimates high incomes.
Source: Atkinson (2007, 20)
The two indicators provide similar stories.
U.S.: Share of the Top 1%, and the Gini Coefficient, 1947-2002
Piketty’s Contributions
Methodological: Use of official tax data to estimate high incomes, Because they are more trustworthy than household surveys Extend coverage farther back in time: France, US, UK, India Incorporates wealth and income data in the same work Focus on Top Income Shares, rather than overall distributionFindings: Experience of US is among most extreme of wealthy countries Concentration of growth at very top: surprising many US academics Emphasis on inheritance as major factor in wealth distributionPolicy Proposal: Proposes a universal wealth tax Emphasis on gains to the top one percent was very timely in terms of the “Occupy Wall St” movement. Perhaps recent US election will keep income distribution close to public consciousness and debate.
Theoretically, why does inequality change?Demographic factors: Ageing of war baby generation Increased labor force participation of womenMacro Forces Short term economic fluctuations, perhaps caused by spending & taxes Anti-poverty programs Social Security, minimum wage, unionization (remember: stagnation in US of wages of non-skilled workers) Tariffs, Immigration Many other government policies Technological change, education
Note that some argue that inequality is good for investment and economic growth. Piketty doesn’t deny that, but he seems against income concentration
Top 10%Top 1%
Gini pre-fisc
Argentina #N/A 26.8 #N/AAustralia 29.3 8.6 46.8Canada 40.4 13.1 43.8Chile #N/A 24.3 53.1China 27.9 5.9 #N/AColombia #N/A 20.3 #N/ADenmark 26.2 6.1 42.9Finland 32.8 8.5 46.7France 33.0 8.8 48.3Germany 34.7 10.9 49.4India #N/A 9.0 #N/AIreland 35.3 10.5 53.7Italy 34.0 9.7 48.8Japan 40.9 9.7 48.8
Netherlan 30.7 6.8 41.7N.Zealand 30.0 8.1 45.5Norway 27.1 7.7 41.0Portugal 38.3 #N/A 52.1Singapore 43.6 15.2 #N/AS. Africa 54.3 17.9 #N/ASpain 32.3 8.6 46.2Sweden 28.1 7.1 42.6Switz. 33.6 11.0 37.2U.K. 41.5 15.4 50.8U.S.A. 46.0 17.9 48.6Uruguay 46.2 13.8 #N/A
Top 10% Top 1%
Gini pre-fisc
Data on Ginis and Top Income Shares, around 2008
1910191119121913191419151916191719181919192019211922192319241925192619271928192919301931193219331934193519361937193819391940194119421943194419451946194719481949195019511952195319541955195619571958195919601961196219631964196519661967196819691970197119721973197419751976197719781979198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201025%
30%
35%
40%
45%
50%
Figure 8.5. Income inequality in the United States, 1910-2010
Share of top decile in total income (incl. capital gains)
Excl. capital gains
The top decile income share rose from less than 35% of total income in the 1970s to almost 50% in the 2000s-2010s. Sources and series: see piketty.pse.ens.fr/capital21c.
Sha
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dec
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ome
Major recovery of top income shares after about 1970. “New Gilded Age.”
191019111912191319141915191619171918191919201921192219231924192519261927192819291930193119321933193419351936193719381939194019411942194319441945194619471948194919501951195219531954195519561957195819591960196119621963196419651966196719681969197019711972197319741975197619771978197919801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008200920100%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
22%
24%
Figure 9.2. Income inequality in Anglo-saxon countries, 1910-2010
U.S. U.K. Canada
Australia
The share of top percentile in total income rose since the 1970s in all Anglo-saxon countries, but with dif-ferent magnitudes. Sources and series: see piketty.pse.ens.fr/capital21c.
Sh
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Share of Top 1%. Experience of Anglo-Saxon countries is different from Europe, Japan (next slide).
U.S.
U.K.
191019111912191319141915191619171918191919201921192219231924192519261927192819291930193119321933193419351936193719381939194019411942194319441945194619471948194919501951195219531954195519561957195819591960196119621963196419651966196719681969197019711972197319741975197619771978197919801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008200920100%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
22%
24%
Figure 9.3. Income inequality: Continental Europe and Japan, 1910-2010
France Germany Sweden
Japan
As compared to Anglo-saxon countries, the share of top percentile barely increased since the 1970s in Continental Europe and Japan. Sources and series: see piketty.pse.ens.fr/capital21c.
Sh
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19791982
19851988
19911994
19972000
20032006
2009-4
-2
0
2
4
6
8
10
12 Lowest Quintile
Second Quintile
Middle Quintile
Fourth Quintile
Highest Quintile
80th to 89th Percentile
Top Ten Percent
90th to 99th Percentiles
Top 1 Percent
US: Percentage Changes in Shares of Household Income, Compared to their Levels in 1980. CBO Data
CBO data confirms Piketty/Saez finding on starkness of US experience of the Top 1% - the ones who gained after 1980, while all other groups stagnated or fell behind. CBO also combined data from IRS and CPS.
Why the more extreme pattern in the U.S.?
1. Piketty rejects an interpretation of current trends as being a result of macro econ fundamentals (in contrast to the post-1920s).
He very explicitly says the current situation is a result of increased income of employees, using the term ‘supermanagers.’ Think hedge fund employees who are given stock options as bonuses. Echoes the “Economics of Superstars” which many economists believe is a market-justified phenomenon.2. He argues that the Anglo Saxon countries were more willing to accept the high levels of inequality resulting from rising incomes of elite employees. Evidently, this is a socio-political judgment, not econ analysis. “Changing social norms regarding inequality and the acceptability of very high wages,” (Piketty and Saez, QJE 2003, p. 35).
3. Distributional impacts of Bush/Obama anti-crisis policies after 2008 are not included. Their inclusion would make things look worse.
Composition of Income of Top Groups in US, 2007
A very high fraction of the Income of people in the top decile comes from ‘wage income’
P90-95 P95-99 P99-99.5 P99.5-99.9 P99.9-99.99 P99.99-100
0%
20%
40%
60%
80%
100%
Graph The composition of top incomes in the U.S., 2007
Labor income
Capital income
Mixed income
Source: Piketty (2014, Figure 8.10). His sources are detailed in: piketty.pse.ens.fr/capi-tal21c.
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Analysis of Wealth in the U.S.
It is well established that wealth is more unequally distributed than income.
Piketty seems to have an implicit model in which business investment depends on returns to capital, which his data suggest is high. Given the concentration of wealth, he projects a long-term vicious circle of concentration of wealth among high income people, which ultimately strangles the growth of economy. He recommends a world-wide tax on wealth above € 1 million/year,
While these findings on rising income shares in the US are accepted, his model of the growth of wealth has been the subject of much criticism by academic economists in the US and elsewhere.Nevertheless, the combination of the already acknowledged strength of the work on income, and the radicalness of the wealth tax proposal, helped increase his impact.
Pre-fiscal/Post-fiscal
Many government programs affect the actual distribution of income (and wealth). We can analyze separately pre-fisc and post fisc. Piketty’s tables report the distribution pre-fiscal policy.
It is well known that many west-European governments re-distribute major shares of income, and that the US does not. But “social norms regarding inequality” probably refer to post-fiscal distribution, so perhaps the analysis of income distribution should also consider post fiscal measures.
[Ginis] OECD data
Pre-Fisc
Post-Fisc Dif.
Pre-Fisc
Post-Fisc Dif.
Chile 52.8 50.6 2.2 49.4 31.7 17.7Korea 34.0 31.1 2.9 Italy 49.8 31.9 18.0Switz. 37.2 29.8 7.4 Norway 42.4 25.5 16.9U.S.A. 49.0 37.4 11.6 Slovak R. 43.6 26.0 17.7Israel 50.3 37.5 12.8 Sweden 43.6 25.8 17.8Canada 44.0 31.9 12.1 Ireland 52.6 31.1 21.5Iceland 37.9 27.2 10.7 France 49.2 29.0 20.2N. Zealand 46.1 32.7 13.3 Denmark 41.5 24.2 17.3Japan 46.4 32.9 13.6 Germany 49.5 28.6 20.9Australia 46.7 32.8 13.9 Czech R. 45.7 25.8 19.8Spain 46.9 32.4 14.5 Austria 47.4 26.5 20.9Netherlnds 42.3 28.6 13.7 Belgium 47.8 26.5 21.3Greece 49.4 33.4 16.0 Slovenia 44.2 24.3 19.9U. Kingdom 50.6 33.8 16.8 Finland 47.6 25.7 21.9
Hungary 28.5 #N/AMexico #NA 47.2 #N/ATurkey #NA 41.7 #N/A
Gini Indexes for the US, Pre-Fisc and Post-Fisc
Latin America: Average Regional Gini Index
of the Distribution of Income, 1980s-2010.
Source: Cornia (2012) page 5.
Top Income Shares in Latin America
Fiscal Redistribution in LAC: Two Data Sources
Measure of Income Redistribution
France SwedenNetherlands
USA
Solt, Frederick. 2014. “The Standardized World Income Inequality Database.” Working paper.
Market Income – Pre-Fisc Net Income - Post-Fisc
Redistribution: Pre-Fisc minus Post-Fisc
Income Redistribution in LAC
Argentina Brazil
Chile Uruguay
Ginis: Pre-fisc minus Post-fisc
Appendix Graph 5. Gini Coefficients, Separating Effects of Fiscal Policy. Six Latin American Countries, Early 2000s
This presentation can be downloaded – in either .pptx or .docx format, from my web page, at:www-personal.umd.umich .edu/~mtwomey
Thank you for your attention!
Any Questions?
Income Composition of Top Groups in US within the Top Decile, 1929 and 2007
A very high fraction of the Income of people in the top decile comes from ‘wage income’
P90-95 P95-99 P99-99.5 P99.5-99.9 P99.9-99.99
P99.99-100
0%
20%
40%
60%
80%
100%
Graph The composition of top incomes in the U.S., 2007
Labor income
Capital income
Mixed income
Source: Piketty (2014, Figure 8.10). His sources are detailed in: piketty.pse.ens.fr/capital21c.
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Will perhaps be another book. Its web version has 250 pages, but a hard-copy, published version would again be several hundred pages.
