The Long-Run Determinants of Inequality: What Can We Learn From Top Income Data?

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The Long-Run Determinants of Inequality: What Can We Learn From Top Income Data? Jesper Roine, Jonas Vlachos and Daniel Waldenström (paper at: www.anst.uu.se/danwa175 ) XXIV International Conference of the Giordano Dell Amore Observatory on the relationship between law and economics, October 27, 2011 Waldenström: Long-run 1

The issues Does economic growth benefit everyone? How does trade openness influence inequality? Is it really the poor that mainly gain from financial development or is it the rich? What is the role of the state in all this? Waldenström: Long-run 2

This presentation 1. A long-run perspective New inequality dataset covering most of 20th C. 2. What accounts for changes in inequality? Trade, Finance, Growth, Redistribution? 3. Are patterns same for all? High-income vs Low-income countries 4. Specific issues Role of financial crises Waldenström: Long-run 3

Theories explaining top income shares Economic growth Top incomes closely attached to economy (bonuses) Trade openness Standard story: Capitalists in rich countries gain Superstars gain from globalized labor markets Financial development Typically regarded as pro-poor (reduced barriers) But it can be pro-rich (power, early stages) Redistribution Waldenström: Long-run 4

Top income shares a new source Traditional lack of long-run inequality evidence A solution: historical tax data Available since early 20th C. Long-run series Available in most countries cross-country comp. Primarily observations of the highest incomes We focus on three groups in the distribution: "The Rich" (Top 1 percentile) "The Upper Middle Class" (Top101 percentiles) "The Rest" Waldenström: (Bottom 90 Long-run percentiles) 5

Differences across groups (Sweden 2008) Average income Waldenström: Long-run 6

Top decile share over time: Sweden Waldenström: Long-run 7

Share of income (%) "Upper Middle Class" (Top10-32 28 1%) and "Rich" (Top 1%) in 24 20 16 12 8 Top 1% 4 Sweden Top 10-1% 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Source: Roine and Waldenström (2008, updates) Waldenström: Long-run 8

35 Top 10-1% and Top 1% in the U.S. 30 25 Top 10-1% 20 15 10 Top 1% 5 1900 1920 1940 1960 1980 2000 Source: Piketty and Saez (2003, updates) Waldenström: Long-run 9

Data on income inequality Income data Gross market income bef. most taxes and transfers Includes labor, capital, business income Source: Past studies (cf Atkinson/Piketty 2007, 2010) Computation of top income shares The share of total income that goes to the top 10, 5, 1, 0.1, etc % of all potential income earners. Three variables: Top 1%, Top 10-1%, Bottom 90% Waldenström: Long-run 10

Top 1%: The rich 30 25 Total income share of Top1 (%) 20 15 10 5 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Argentina Australia Canada Finland France Germany India Ireland Japan Netherlands New Zealand Spain Sweden Switzerland United Kingdom United States Waldenström: Long-run 11

35 Top 10-1%: Upper middle class 30 Total income share of Top10-1 (%) 25 20 15 10 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Argentina Australia Canada Finland France Germany India Ireland Japan Netherlands New Zealand Spain Sweden Switzerland United Kingdom United States Waldenström: Long-run 12

Potential determinants GDP/capita and Population Source: Maddison Financial development: Bank deposits + Stock market Sources: Mitchell, IFS, FSD, Bordo, Rajan & Zingales Trade openness: (Exports+Imports)/GDP Sources: Mitchell, López-Córdoba & Meissner, Bordo Robustness: De jure openness (Clemens/Williamson; IMF) Waldenström: Long-run 13

GDP per capita (1990 G-K USD) 30000 25000 20000 15000 10000 5000 Potential inequality GDP/cap determinants 4.5 Total capitalization as share of GDP 4 3.5 3 2.5 2 1.5 1 0.5 Financial development 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Argentina Australia Canada Finland France Germany India Ireland Japan Netherlands New Zealand Spain Sweden Switzerland United Kingdom United States 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Argentina Australia Canada Finland France Germany India Ireland Japan Netherlands New Zealand Spain Sweden Switzerland United Kingdom United States Trade openness (trade share in GDP) 400 350 300 250 200 150 100 50 Trade openness Central government spending as share of GDP 0.50 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 Gov. spending 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Argentina Australia Canada Finland France Germany India Ireland Japan Netherlands New Zealand Spain Sweden Switzerland United Kingdom United States 0.00 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Argentina Australia Canada Finland France Germany India Ireland Japan Netherlands New Zealand Spain Sweden Switzerland United Kingdom United States Waldenström: Long-run 14

Income tax rates (top rates) 100 90 80 Top marginal income tax (%) 70 60 50 40 30 20 10 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Argent ina Australia Canada Finland France Germany India Ireland Japan Netherlands New Zealand Spain Sweden Switzerland United Kingdom United States Waldenström: Long-run 15

Empirical methodology Log-linear regression model: Income shares (Top1, Top10-1,Bot90) are regressed on the potential determinants + controls No firm claims on causal relationships Technicalities: Two estimators: Dynamic first-difference (DFD) First-difference GLS (FDGLS) Control for unobserved time-invariant effects and country-specific trends Waldenström: Long-run 16

Baseline results Top 1% Top 10-1% Bottom 90% Finance 0.98*** 1.27*** 0.17 0.18 0.53 1.87*** Trade 8.80*** 2.31 0.20 0.35 3.15 0.32 Growth 5.81*** 6.56*** 8.82*** 7.02*** 5.53** 1.65 Gov.Spend 5.98 3.62 16.51*** 24.05*** 22.52*** 23.94*** Taxation 4.39*** 3.18** 10.18*** Obs 126 92 99 77 99 77 Controls Yes Yes Yes Yes Yes Yes N countries 14 12 12 10 12 10 Waldenström: Long-run 17

Level of development Top 1% Top 10-1% Bottom 90% Growth Low 5.07*** 9.03*** 4.53 Growth Med 6.41*** 7.34*** 5.98 Growth High 2.62 9.84*** 8.26* Finance Low 1.65* 3.26** 2.08 Finance Med 0.88* 0.33 1.02 Finance High 0.86* 0.40 0.88 F: Low=Med 0.31 0.45 0.52 0.02 0.74 0.18 F: Low=High 0.25 0.42 0.8 0.01 0.45 0.18 F: Med=High 0.07 0.98 0.34 0.94 0.59 0.9 Obs 126 126 99 99 99 99 N countries 14 14 12 12 12 12 Waldenström: Long-run 18

Do financial crises matter? Top 1% Top 10-1% Bank crisis 1.07*** 1.08*** 0.33 0.35 Currency crisis 0.06 0.31 Obs 171 171 132 132 Controls Yes Yes Yes Yes N countries 16 16 14 14 Crisis data from Bordo et al. (2001) and Laeven and Valencia (2008) Waldenström: Long-run 19

Extensions and robustness Extensions Role of democracy (Polity IV - No role) Role of technology (Patents - No role; Share of GDP in agriculture- No role) Robustness We use top shares within the top Ex: Top1/Top10 and Top0.1/Top1 Restrict analysis to postwar period Rules out influence from Great Depression Results in line with main analysis Waldenström: Long-run 20

Conclusions 1. Finance is strongly pro-rich Financial crises associated with reduced top shares 2. Trade openness has no clear impact on inequality 3. Economic growth pos. correlated with top shares; neg. correlated with upper middle class share Extends Dew-Becker & Gordon (2005, 2007) No sign of global labor market for elites Waldenström: Long-run 21

Waldenström: Long-run 22

Main findings in top income literature Similarities across countries (mostly) 1900-1980: Substantially reduced inequality After 1980, Anglo-Saxon and Cont. Eur. Potential determinants: Shocks to capital income/wealth (pre-wwii) Progressive taxation (postwar period) Globalized labor markets (1980-, esp. Anglo- Saxon) 23