The inequality dataset compiled in the 1990s by the World Bank and extended by the UN has been both widely used and strongly criticized. The criticisms raise questions about conclusions drawn from secondary inequality datasets in general. We develop techniques to deal with national and international comparability problems intrinsic to such datasets. The result is a new dataset of consistent inequality series, allowing us to explore problems of measurement error. In addition, the new data allow us to perform parametric non-1inear estimation of Lorenz curves from grouped data. This in turn al1ows us to estimate the entire income distribution; computing alternative inequality indexes and poverty estimates. Finally, we have used our broad1y comparable dataset to examine international patterns of inequality and poverty.

Lorenz curve estimation, income distribution datasets, inequality trends, poverty estimation
Data Collection and Data Estimation Methodology; Computer Programs: General (jel C80), Personal Income, Wealth, and Their Distributions (jel D31), Human Resources; Human Development; Income Distribution; Migration (jel O15)
hdl.handle.net/1765/6856
Tinbergen Institute Discussion Paper Series
Tinbergen Institute

François, J.F, & Rojas-Romagosa, H. (2005). The Construction and Interpretation of Combined Cross-Section and Time-Series Inequality Datasets (No. TI 05-079/2). Tinbergen Institute Discussion Paper Series. Retrieved from http://hdl.handle.net/1765/6856