1 Top Incomes over 100 years: What can be learned about the determinants of income distribution? A B Atkinson, Nuffield College, Oxford and Paris School of Economics Trevor Swan Distinguished Lecture February 2007

2 1.Framework for Analysis Earnings, Wealth and Income Distribution and Economic Growth Impact of top 1% 2. Empirical Evidence for a Selection of OECD Countries Incomes Earnings Wealth 3.Seeking Explanations Linking Theory and Evidence Disappearance (and re-appearance?) of rentiers Earnings at the top: superstars and managerial pyramids Conclusions: Role of Public Policy

3 Meade Framework Efficiency, Equality and the Ownership of Property (1964) Individual income of person i Y i = W i + r i K i Factor shares Distribution of earnings Distribution of wealth Distribution of rates of return and their correlation with wealth Correlation of earned and investment income

4 Growth and Distribution In Solow/Swan neoclassical growth model Growth of individual capital per head k i dk i /dt = s w w i + s r r i k i – nk i Aggregate growth dk/dt = s w ∑ i w i + s r ∑ i r i k i – nk If r same for all, and s w = s r = s, then steady state implies sr < n (Stiglitz) and hence k i converge to multiple of w i BUT Unequal inheritance: primogeniture → Pareto upper tail Non-linear savings function Stochastic creation of new fortunes

5 Impact of top 1% If S* is share of top 1%, then the Gini coefficient can be approximated by S* + (1-S*) G, where G is the Gini coefficient for the rest of the population. Considering gross incomes, this means that, if the Gini coefficient for the rest of the population is 40%, then a rise of 8 percentage points in the top share causes a rise of 4.8 percentage points in the overall Gini.

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7 1.Framework for Analysis 2. Empirical Evidence for a Selection of OECD Countries Incomes Earnings Wealth 3.Seeking Explanations Conclusions: The Role of Public Policy A B Atkinson, and T Piketty, editors, Top Incomes over the Twentieth Century, Oxford University Press, volume 1 forthcoming 2007.

8 UK US CA AUS NZ Australian results from A B Atkinson and A Leigh “The Distribution of Top Incomes in Australia”, Economic Record, forthcoming 2007.

9 NL DEU CH FRA

10 Share of top 1% = Proportion of earned income x Share of top 1% of earners x Alignment coefficient for earnings + Proportion of investment income x Share of top 1% with investment income x Alignment coefficient for investment income Alignment coefficient = Share in earnings of top 1% of income recipients / Share of top 1% of earners ( ≤ 1)

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12 Decomposition: WEALTH

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14 UK Putting them together for the UK

15 UK Other income

16 MAJOR themes: Decline in concentration of capital Rise in top earnings post 1979 in some countries MINOR themes Decline in top earnings up to 1979 Modest recovery of capital post 1979

17 1.Framework for Analysis 2.Empirical Evidence for a Selection of OECD Countries 3.Seeking Explanations Linking Theory and Evidence Disappearance (and re-appearance?) of rentiers Earnings at the top: superstars and managerial pyramids Conclusions: The Role of Public Policy

18 Linking Theory and Evidence Models of Individual Incomes Micro-data Independent Models of Distributions Moments Percentiles or percentile shares Summary measures (Gini) Pareto coefficient

19 CAMBRIDGE Accumulation Model (Pasinetti / Meade / Stiglitz) Pareto upper tail α = (n+δ) / [sr(1-t) - βn], where n is rate of population growth, δ the rate of decay of fortunes sr(1-t) is the rate of accumulation out of wealth (r is the rate of return and t the tax rate), and βn captures the periodic effect of the division of estates at death.

20 1/alpha LHS scale (1-t) RHS scale

21 Superstar Theory (Alfred Marshall 1890s and Sherwin Rosen 1980s) + Gives role to both technology and trade - No direct link to distribution ? Explain earlier periods when top earnings fell?

22 Log (Earnings/median) Log [1/(1 – F)] Effect of trade and technology in expanding share of rents captured by top performers = fall in α Superstar model generates extreme value distribution with Pareto tail with exponent α Slope = 1/α

23 Managerial Hierarchy Model (Lydall and Simon) β = log e [span of managerial control] divided by log e [1+ increment with promotion ] span increment 25% 5 7.2

24 Log (Earnings/median) Log [1/(1 – F)] Superstar model not enough on its own, since not explain earlier rise in α Hierarchical Salary Model Hierarchical model not enough on its own, since predicted Pareto exponent β too large - +

25 Conclusions: The Role of Public Policy Not just globalisation Progressive taxation Privatisation and pay policy A Return of Incomes Policy?