Constructing Long and Dense Time-Series of Inequality Using the Theil Index

Levy Economics Institute Working Paper No. 259

29 Pages Posted: 10 Jun 1999

See all articles by Pedro Conceicao

Pedro Conceicao

United Nations - Human Development Report Office

James K. Galbraith

University of Texas at Austin - Lyndon B. Johnson School of Public Affairs; Levy Economics Institute of Bard College

Date Written: December 1998

Abstract

Year-to-year economy-wide measures of income distribution, such as the Gini coefficient, are rarely available for long periods except in a few developed countries, and as a result few analyses of year-to-year changes in inequality exist. But wage and earnings data by industrial sectors are readily available for many countries over long time frames. This paper proposes the application of the between-group component of the Theil index to data on wages, earnings and employment by industrial classification, in order to measure the evolution of wage or earnings inequality through time. We provide formal criteria under which such a between-group Theil statistic can reasonably be assumed to give results that also track the (unobserved) evolution of inequality within industries. While the evolution of inequality in manufacturing earnings cannot be taken as per se indicating the larger movements of inequality in household incomes, including those outside the manufacturing sector, we argue on theoretical grounds that the two will rarely move in opposite directions. We conclude with an empirical application to the case of Brazil, an important developing country for which economy-wide Gini coefficients are scarce, but for which a between-industries Theil statistic may be computed on a monthly basis as far back as 1976.

JEL Classification: J31

Suggested Citation

Conceicao, Pedro and Galbraith, James K., Constructing Long and Dense Time-Series of Inequality Using the Theil Index (December 1998). Levy Economics Institute Working Paper No. 259, Available at SSRN: https://ssrn.com/abstract=148008 or http://dx.doi.org/10.2139/ssrn.148008

Pedro Conceicao (Contact Author)

United Nations - Human Development Report Office ( email )

304 E 45th Street, FF-1262
New York, NY 10017
United States

James K. Galbraith

University of Texas at Austin - Lyndon B. Johnson School of Public Affairs ( email )

2300 Red River St., Stop E2700
PO Box Y
Austin, TX 78713
United States
512-471-1244 (Phone)

Levy Economics Institute of Bard College

Blithewood
Annandale-on-Hudson, NY 12504
United States
845-758-7700 (Phone)
845-758-1149 (Fax)