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Can subjective data improve inequality measurement? A multidimensional index of economic inequality

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  • Philipp Poppitz

    (University of Hamburg, Germany)

Abstract

To measure multidimensional inequality by a univariate index, dimensions of inequality need to be weighted. This work addresses the normative and empirical problems by estimating hedonic weights based on German microdata. In contrast to previous works, individuals’ perception of inequality is used to estimate a weighting scheme including five dimensions. Aggregating outcomes by a generalized Gini and the hedonic weights, annual multidimensional economic inequality (MDEI) is calculated from 2000 to 2016. The results show that the MDEI is significantly higher in the analyzed period compared to the case of equal weights, but lower than income inequality. Over time, multidimensional inequality in Germany increased at the same pace as income inequality until 2006. Since then, the decreasing trend of MDEI is amplified under the assumption of imperfect substitution elasticity. The decomposition analysis reveals that income contributes more than any other dimension to inequality, but the exceptional reduction in unemployment is the major cause for the decline of the MDEI from 2008 onwards.

Suggested Citation

  • Philipp Poppitz, 2017. "Can subjective data improve inequality measurement? A multidimensional index of economic inequality," Working Papers 446, ECINEQ, Society for the Study of Economic Inequality.
    • Handle: RePEc:inq:inqwps:ecineq2017-446
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    Cited by:

    1. Philipp Poppitz, 2019. "Multidimensional Inequality and Divergence: The Eurozone Crisis in Retrospect," Working Papers V-420-19, University of Oldenburg, Department of Economics, revised Feb 2019.

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    More about this item

    Keywords

    inequality; multidimensional index; perception; hedonic weights;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General

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