The construction and interpretation of combined cross-section and time-series inequality datasets

The inequality dataset compiled in the 1990s by the World Bank and extended by the United Nations has been both widely used and strongly criticized. The criticisms raise questions about conclusions drawn from secondary inequality datasets in general. The authors 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 them to explore problems of measurement error. In addition, the new data allow the authors to perform parametric non-linear estimation of Lorenz curves from grouped data. This in turn allows them to estimate the entire income distribution, computing alternative inequality indexes and poverty estimates. Finally, the authors use their broadly comparable dataset to examine international patterns of inequality and poverty.