Upward and Downward Bias When Measuring Inequality of Opportunity

33 Pages Posted: 2 Apr 2018

See all articles by Paolo Brunori

Paolo Brunori

University of Bari - Faculty of Economics

Vito Peragine

Università di Bari

Laura Serlenga

Università degli Studi di Bari; Institute for the Study of Labor (IZA)

Multiple version iconThere are 2 versions of this paper

Abstract

Estimates of the level of inequality of opportunity have traditionally been interpreted as lower bounds due to the downward bias resulting from the partial observability of circumstances that affect individual outcome. We show that such estimates may also suffer from upward bias as a consequence of sampling variance. The magnitude of the latter distortion depends on both the empirical strategy used and the observed sample. We suggest that, although neglected in empirical contributions, the upward bias may be significant and challenge the interpretation of inequality of opportunity estimates as lower bounds. We propose a simple criterion to select the best specification that balances the two sources of bias.Our method is based on cross-validation and can easily be implemented with survey data.To show how this method can improve the reliability of inequality of opportunity measurement, we provide an empirical illustration based on income data from 31 European countries. Our evidence shows that estimates of inequality of opportunity are sensitive to model selection. Alternative specifications lead to significant differences in the absolute level of inequality of opportunity and to the re-ranking of a number of countries. This confirms the need for an objective criterion to select the best econometric model when measuring inequality of opportunity.

Keywords: inequality of opportunity, model selection, cross-validation, variance-bias trade-off

JEL Classification: C52, D3, D63

Suggested Citation

Brunori, Paolo and Peragine, Vitorocco and Serlenga, Laura, Upward and Downward Bias When Measuring Inequality of Opportunity. IZA Discussion Paper No. 11405. Available at SSRN: https://ssrn.com/abstract=3153369

Paolo Brunori (Contact Author)

University of Bari - Faculty of Economics ( email )

Piazza Cesare Battisti 1
Bari, Taranto 70121
Italy

Vitorocco Peragine

Università di Bari ( email )

Piazza Cesare Battisti 1
Bari, Taranto 70121
Italy

Laura Serlenga

Università degli Studi di Bari ( email )

Piazza Umberto I
Bari, 70121
Italy

Institute for the Study of Labor (IZA) ( email )

P.O. Box 7240
Bonn, D-53072
Germany

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