Inequality in the very long run: inferring inequality from data on social groups
- 447 Downloads
This paper presents a new method for calculating Gini coefficients from tabulations of the mean income of social classes. Income distribution data from before the Industrial Revolution usually come in the form of such tabulations, called social tables. Inequality indices generated from social tables are frequently calculated without adjusting for within-group income dispersion, leading to a systematic downward bias in the reporting of pre-industrial inequality. The correction method presented in this paper is applied to an existing collection of twenty-five social tables, from Rome in AD 1 to India in 1947. The corrections, using a variety of assumptions on within-group dispersion, lead to substantial increases in the Gini coefficients.
KeywordsPre-industrial inequality Social tables Kuznets curve History
Unable to display preview. Download preview PDF.
- 1.Aitchison, J., Brown, J.A.C.: The Lognormal Distribution, with special reference to its uses in economics. 1st edn. Cambridge University Press (1957)Google Scholar
- 3.Clark, G.: A Farewell to Alms: A Brief Economic History of the World. Princeton University Press (2008)Google Scholar
- 4.Crow, E.L., Shimizu, K.: Lognormal distributions: theory and applications. 1 edn. CRC Press (1987)Google Scholar
- 8.Kakwani, N.: Income inequality and poverty: methods of estimation and policy applications. A World Bank Research Publication (1980)Google Scholar
- 9.Kuznets, S.: Economic Growth and Income Inequality. Am. Econ. Rev. 45(1), 1–28 (1955)Google Scholar
- 14.Milanovic, B., Lindert, P.H., Williamson, J.G.: Measuring ancient inequality. National Bureau of Economic Research Working Paper Series, 13550 (2007)Google Scholar
- 16.Minnesota Population Center: Integrated Public Use Microdata Series, International: Version 6.0 [Machine-readable database]Google Scholar
- 19.Young, A.: The Gini coefficient for a mixture of ln-normal populations. Mimeo, London School of Economics (2011)Google Scholar