Measuring Income Inequality Across Countries and Over Time: The Standardized World Income Inequality Database

Abstract

Objective. This article documents wide-ranging revisions to the Standardized World Income Inequality Database (SWIID), which seeks to maximize the comparability of income inequality estimates for the broadest possible coverage of countries and years. Methods. Two k-fold crossvalidations, by observation and by country, are used to evaluate the SWIID's success in predicting the Luxembourg Income Study (LIS), recognized in the field as setting the standard for comparability. Results. The cross-validations indicate that the new SWIID's estimates and their uncertainty are even more accurate than previous versions, extending its advantage in comparability over alternate income inequality data sets. Conclusion. Given its superior coverage and comparability, the SWIID remains the optimum source of data for broadly cross-national research on income inequality. From its origins now over a decade ago, the goal of the Standardized World Income Inequality Database (SWIID) has been to provide estimates of income inequality for as many countries and years as possible while ensuring that these estimates are as comparable as the available data allow (see Solt, 2009). That is to say, the SWIID's first priority is breadth of coverage, and its second priority is comparability. The starting point for the SWIID estimates is a data set with the complementary priorities: the Luxembourg Income Study (LIS), which aims to maximize comparability and, given that primary concern, to include as many countries and years as possible. 1 Then, the SWIID routine estimates the relationships between Gini indices based on the LIS and all of the other Ginis available for the same country-years, and it uses these relationships to estimate what the LIS Gini would be in country-years not included in the LIS but available from other sources. This approach has made the SWIID a preferred source of income inequality data for researchers pursuing broadly cross-national work across a wide range of disciplines, including not only economics (e.g., Berg et al.

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