1. Income Inequality II

2. References
Gabriel Zucman, and Emmanuel Saez “Wealth Inequality in the United States since 1913: Evidence from Capitalized Income Tax Data”, Quarterly Journal of Economics, 2016, 131(2):
Gabriel Zucman, Thomas Piketty and Li Yang “Capital Accumulation, Private Property and Rising Inequality in China, ”, forthcoming, American Economic Review.
Facundo Alvaredo, Gabriel Zucman, Lucas Chancel, Thomas Piketty and Emmanuel Saez “The Elephant Curve of Global Inequality and Growth”, American Economic Association P&P, 2018, 108:

3. References
台灣貧富差距的真相 (
Inequality.org (
World Inequality Report 2018 (

4. Roadmap Why do we study inequality? Income inequality
Wealth inequality
Global inequality
Why does inequality grow?

5. Measuring Inequality
Inequality matters because the public cares about it
⇒ Need to provide transparent inequality measures
Goals: Understand drivers of inequality trends and the effects of public policy on inequality

6. Income and Wealth Income is a flow = Labor income + Capital income
Capital income is the return on Wealth
Wealth is a stock accumulated from savings and inheritances

7. WORLDWIDE INCOME INEQUALITY
Income inequality is growing within most countries
But large emerging countries (China, India) are catching up with advanced economies
Is global income inequality increasing or decreasing?
Hard question to answer due
lack of comparable data across countries
difficulty of measuring top incomes in surveys
In this paper, we use new consistent data from World Inequality Database (WID) to generate world inequality estimates since 1980

8. WORLD INEQUALITY DATABASE
WID.world is the most extensive database on the historical evolution of income and wealth distribution (100+ researchers)
100% transparent, open source, reproducible
Website started in 2011 with historical top income share series using tax data
New WID.world website launched 1/2017.

10. WID.WORLD KEY NOVELTIES
We cover full distribution (not just the top), we use individual adult unit (with equal split of income among couples)
We distribute total National Income (not just fiscal income) ⇒ Brings together analysis of growth and inequality
Emerging countries added (China, India, Brazil, Russia)

11. Constantly expanding database on the historical evolution of income and wealth with global coverage goal
Open access, multi-lingual website and visualization tools
Stata and R packages: access our data from Stata command “wid”

12. Top Income Shares
Simple way to measure inequality: what share of total pre-tax market income goes to the top 10% families, to 1%, etc.
Individual income tax statistics are the only source
covering long-time periods
capturing well top incomes
25 countries have been analyzed in the on-going World Top Incomes Database
Caveats: Income concept used is narrower than National Income and focus is solely on pre-tax, pre-transfer income

13. Income Inequality

17. Drop in Inequality in 1st Half of 20th Century
All advanced countries had very high income concentration one century ago (explains pessimism of Piketty 2014)
All countries experience sharp reduction in income concentration during the first part of the 20th century
This is primarily a capital income phenomenon
War and depression shocks hit top capital earners (drop follows each country specific history)
Government police responses-regulations and progressive income and inheritance taxation-make this drop permanent

18. Recent Surge in Inequality
Driven by surge in top labor incomes which then fuels wealth inequality
Difference across countries rules out technical change and globalization as the unique explanations
Policies play a key role in shaping inequality (tax and transfer policies, regulations, education)
Key debate: do gains of the top 1% reflect productivity or do they come at the expense of the 99%?

31. Wealth Inequality
Wealth inequality is always much higher than income inequality (bottom 50% families own about zero wealth)
Us government taxes 1/3 of market incomes to fund transfers and public goods: disposable income inequality lower than market income inequality

41. Global Inequality

42. Top 10% income shares across the world, 2016

43. Top 10% income shares across the world, 1980‒2016

44. Top 10% income shares across the world, 1980‒2016

45. Top 1% income shares across the world, 1980-2016

46. Bottom 50% income shares across the world, 1980‒2016

60. Why does inequality grow?

61. Global income growth and inequality, 1980‒2016

62. Share of growth captured by income groups, 1980‒2016

63. KEY RESULTS
Inequality is increasing everywhere but at different speeds
In rich countries, US inequality increases much faster than in Europe (contrast US vs. France)
Inequality shifts clearly follow policy changes (Reagan in US, transitions in China/Russia, deregulation in India)
⇒ Globalization and technological progress cannot explain fully pre-tax incomne inequality: Institutions and policies matter

64. None of large emerging countries studied meets new Sustainable Development Goal target of bottom 40% growing faster than average

65. Top 1% and Bottom 50% Income Shares in US

66. Top 1% and Bottom 50% Income Shares in US and France

67. WORLD INEQUALITY ESTIMATES
We follow a step-by-step approach towards a consistent global distribution of income and wealth
1) We start with countries for which we have Distributional National Income series (2/3 of the world population)
2) For other countries, we use information on average national income per adult and assume distribution within country is the same as other countries in same region
E.g.: we assume that national income in Argentina, Mexico, etc. is distributed as in Brazil

68. 3) For sub-Saharan Africa, we use World Bank surveys with correction at the top using fiscal data and National Accounts
4) We pool country distributions using PPP exchange rates (not market exchange rates)

69. Total income growth by percentile in US-Canada and Western Europe, 1980-2016

70. Total income growth by percentile in China, India, US-Canada, and Western Europe

71. Total income growth by percentile across all world regions, 1980-2016

72. Global top 1% and bottom 50% income shares, 1980‒2016

73. Global top 1% and bottom 50% income shares: PPP versus market exchange rates

74. Global top 10% income share: between versus within-country inequality

75. GLOBAL INEQUALITY PROJECTIONS
(a) Growth: UN and OECD produce long-term population and economic growth forecasts
(b) Distribution: We assume that economic growth per adult from will be distributed across percentiles as in : “business as usual” scenario (1)
⇒ Can simulate dynamics of global inequality and growth

76. We consider two alternative scenarios:
(2) Very unequal growth in every country as the US
(3) Pretty equal growth in every country as the EU
⇒ Inequality has a huge long-term impact on future incomes of bottom 50%

77. Top 1% and bottom 50% shares of global income, 1980–2050

78. Global average income versus global 50% average, 1980–2050

79. Global bottom 50% average income, 1980–2050

80. Economic Effects of Taxing the Top 1%
Strong empirical evidence that pre-tax top incomes are affected by top tax rates
3 potential scenarios with very different policy consequences
Supply-Side: Top earners work less and earn less when top tax rate increases ⇒ Top tax rates should not be too high
Tax Avoidance/Evasion: Top earners avoid/evade more when top tax rate increases
⇒ a) Eliminate loopholes, b) Then increase top tax rates
Rent-seeking: Top earners extract more pay (at the expense of the 99%) when top tax rates are low ⇒ High top tax rates are desirable

81. Real changes vs. tax Avoidance?
Test using charitable giving behavior of top income earners
Because charitable is tax deductible, incentives to give are stronger when tax rates are higher
Under the tax avoidance scenario, reported incomes and reported charitable giving should move in opposite directions
Empirically, charitable giving of top income earners has grown in close tandem with top incomes
⇒ incomes at the top have grown for real

82. Supply-Side or Rent-seeking
Under rent-seeking scenario, growth in top 1% incomes should come at the expense of bottom 99% (and conversely)
US Evidence: Top 1% incomes grow slowly from 1933 to 1975 and fast afterwards. Bottom 99% incomes grow fast from 1933 to 1975 and slowly afterwards
International evidence: Hard to find an effect of top rate cuts on economic growth
⇒ Consistent with rent-seeking effects
More research needed on this critical question

83. Policy Conclusions
US historical evidence and international evidence shows that tax policy plays a key role in the shaping inequality
High top tax rates reduce the pre-tax income gap without visible effect on economic growth
Public will favor more progressive taxation only if it is convinced that top income gains are detrimental to the 99%
In globalized world, progressive taxation will require international coordination to keep tax avoidance/evasion low

84. CONCLUSIONS
WID.world aims at constructing systematic series on inequality in all countries for research and policy debate use
Our preliminary estimates show that global top 1% captured twice as much growth as bottom 50% since 1980
Under Business as usual and even with optimistic growth assumptions in the emerging world, global inequality will continue to rise
Rising inequality is not inevitable: policies can promote equitable growth pathways in the coming decades

85. Inequality and Health