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The Construction and Interpretation of Combined Cross-Section and Time-Series Inequality Datasets

Joseph Francois and Hugo Rojas-Romagosa ()

No 5214, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: 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 linear estimation of Lorenz curves from grouped data. This in turn allows us to estimate the entire income distribution, computing alternative inequality indexes and poverty estimates. Finally, we have used our broadly comparable dataset to examine international patterns of inequality and poverty.

Keywords: income distribution datasets; inequality trends; Lorenz curve estimation; poverty estimation (search for similar items in EconPapers)
JEL-codes: C80 D31 O15 (search for similar items in EconPapers)
Date: 2005-09
New Economics Papers: this item is included in nep-dev
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Related works:
Working Paper: The Construction and Interpretation of Combined Cross-Section and Time-Series Inequality Datasets (2007) Downloads
Working Paper: The Construction and Interpretation of Combined Cross-Section and Time-Series Inequality Datasets (2005) Downloads
Working Paper: The construction and interpretation of combined cross-section and time-series inequality datasets (2005) Downloads
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