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Social Indicators Research

, Volume 146, Issue 3, pp 511–531 | Cite as

Can Subjective Data Improve the Measurement of Inequality? A Multidimensional Index of Economic Inequality

  • Philipp PoppitzEmail author
Original Research
  • 155 Downloads

Abstract

Measuring multidimensional inequality by means of a univariate index requires weighting the dimensions of inequality. This paper explores the normative and empirical problems involved in measuring inequality by estimating hedonic weights on the basis of German microdata. In contrast to previous works, the perception of inequality, derived from subjective social status, has been used to estimate a weighting scheme that includes five dimensions. By aggregating outcomes using a generalized Gini and the hedonic weights, annual multidimensional economic inequality (MDEI) was calculated for the period from 2000 to 2016. The results show that during this period MDEI is significantly higher than when equal weights are used, but lower than income inequality. Until 2006, multidimensional inequality in Germany increased at the same pace as income inequality, but since 2008, the trend of MDEI points downwards if one assumes imperfect substitution between dimensions. The counterfactual decomposition reveals that income contributes to inequality more than any other dimension, but the exceptional reduction in unemployment is the major cause of the decline by the MDEI.

Keywords

Inequality Composite index Hedonic weights Perception Social status 

JEL Classification

D31 C43 I30 

Notes

Acknowledgements

The author would like to thank Ulrich Fritsche, Ingrid Größl, Koen Decancq as well as the participants of the ECINEQ Winter School on Inequality and Social Welfare Theory 2017, the \(7{\mathrm{th}}\) ECINEQ conference and the Verein für Sozialpolitik annual conference for useful comments and suggestions. All remaining errors and ambiguities are the author’s responsibility.

Supplementary material

11205_2019_2141_MOESM1_ESM.pdf (273 kb)
Supplementary material 1 (pdf 272 KB)

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Carl von Ossietzky University OldenburgOldenburgGermany

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