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How Closely Do Top Income Shares Track Other Measures of Inequality?*

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     This article builds on the work of Facundo Alvaredo, Tony Atkinson, Fabien Dell, Chiaki Moriguchi, Brian Nolan, Thomas Piketty, Jesper Roine, Emmanuel Saez, Wiemer Salverda, Michael Veall, and Daniel Waldenström, who have painstakingly used taxation statistics and other historical data to estimate top income shares for the countries analysed herein. In addition, I am grateful to Tony Atkinson, Ian Irvine, Thomas Piketty, Emmanuel Saez and Daniel Waldenström for valuable comments on earlier drafts. Elena Varganova provided outstanding research assistance. The dataset of top income shares may be downloaded from http://econrsss.anu.edu.au/~aleigh/.

Abstract

In recent years, researchers have used taxation statistics to estimate the share of total income held by the richest groups, such as the top 10% or the top 1%. Compiling a standardised top income shares dataset for 13 developed countries, I find that there is a strong and significant relationship between top income shares and broader inequality measures, such as the Gini coefficient. This suggests that panel data on top income shares may be a useful substitute for other measures of inequality over periods when alternative income distribution measures are of low quality, or unavailable.

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