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Inequality in Germany: Myths, Facts, and Policy Implications

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Listed:
  • Michele Battisti
  • Gabriel Felbermayr
  • Sybille Lehwald

Abstract

In this paper we try to provide an overview of a series of simple descriptive facts on recent trends in economic inequality in Germany. We believe that it is important to be precise in the way in which we define the inequality measure and the sample we use, to avoid generating vague messages that fail to properly inform policy makers and the public. Using mostly administrative data from the IAB and panel survey data from SOEP, we show that some of the conventional wisdom on recent trends on income inequality in Germany does not seem to find strong support in the data. In particular, we find that current low levels of unemployment are likely to imply higher levels of measured inequality among the employed, but are likely to diminish inequality among the working-age population as a whole. Our paper also discusses the importance to carefully distinguish between inequality at the individual and household levels, and separate the role of the welfare state. Finally, while admitting data limitations we briefly analyse recent trends in wealth inequality in Germany, and discuss the possible role of recent macroeconomic policies on wealth inequality.

Suggested Citation

  • Michele Battisti & Gabriel Felbermayr & Sybille Lehwald, 2016. "Inequality in Germany: Myths, Facts, and Policy Implications," ifo Working Paper Series 217, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  • Handle: RePEc:ces:ifowps:_217
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Gabriel Felbermayr & Michele Battisti & Sybille Lehwald, 2016. "Income Inequality in Germany, Part 2: The Role of Redistribution," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 69(14), pages 22-29, July.
    2. repec:ces:ifodic:v:14:y:2016:i:4:p:19267790 is not listed on IDEAS
    3. Florian Dorn, 2016. "On Data and Trends in Income Inequality around the World," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 14(4), pages 54-64, December.
    4. Geiger, Niels & Prettner, Klaus & Schwarzer, Johannes A., 2018. "Automatisierung, Wachstum und Ungleichheit," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2018, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    5. Gabriel Felbermayr & Michele Battisti & Sybille Lehwald, 2016. "Income Inequality in Germany, Part 1: Is There a Trend Reversal?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 69(13), pages 28-37, July.
    6. Florian Dorn, 2016. "On Data and Trends in Income Inequality around the World," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 14(04), pages 54-64, December.
    7. Amparo Ba'illo & Javier C'arcamo & Carlos Mora-Corral, 2021. "Extremal points of Lorenz curves and applications to inequality analysis," Papers 2103.03286, arXiv.org.

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    More about this item

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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