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A new semiparametric approach to analysing conditional income distributions

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  • Sohn, Alexander
  • Klein, Nadja
  • Kneib, Thomas

Abstract

In this paper we explore the application of Generalised Additive Models of Location, Scale and Shape for the analysis of conditional income distributions in Germany following the reunification. We find that conditional income distributions can generally be modelled using the three parameter Dagum distribution and our results hint at an even more pronounced effect of skill-biased technological change than can be observed by standard mean regression.

Suggested Citation

  • Sohn, Alexander & Klein, Nadja & Kneib, Thomas, 2014. "A new semiparametric approach to analysing conditional income distributions," Center for European, Governance and Economic Development Research Discussion Papers 192, University of Goettingen, Department of Economics.
  • Handle: RePEc:zbw:cegedp:192
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    References listed on IDEAS

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    1. David Card & Jörg Heining & Patrick Kline, 2013. "Workplace Heterogeneity and the Rise of West German Wage Inequality," The Quarterly Journal of Economics, Oxford University Press, vol. 128(3), pages 967-1015.
    2. Sebastian Vollmer & Hajo Holzmann & Florian Ketterer & Stephan Klasen, 2013. "Distribution dynamics of regional GDP per employee in unified Germany," Empirical Economics, Springer, vol. 44(2), pages 491-509, April.
    3. McDonald, James B, 1984. "Some Generalized Functions for the Size Distribution of Income," Econometrica, Econometric Society, vol. 52(3), pages 647-663, May.
    4. Jonathan Morduch & Terry Sicular, 2002. "Rethinking Inequality Decomposition, With Evidence from Rural China," Economic Journal, Royal Economic Society, vol. 112(476), pages 93-106, January.
    5. Martin Biewen & Andos Juhasz, 2012. "Understanding Rising Income Inequality in Germany, 1999/2000–2005/2006," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 58(4), pages 622-647, December.
    6. Nicole M. Fortin & Thomas Lemieux, 1998. "Rank Regressions, Wage Distributions, and the Gender Gap," Journal of Human Resources, University of Wisconsin Press, vol. 33(3), pages 610-643.
    7. Gert Wagner & Jan Göbel & Peter Krause & Rainer Pischner & Ingo Sieber, 2008. "Das Sozio-oekonomische Panel (SOEP): Multidisziplinäres Haushaltspanel und Kohortenstudie für Deutschland – Eine Einführung (für neue Datennutzer) mit einem Ausblick (für erfahrene Anwender)," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 2(4), pages 301-328, December.
    8. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    9. Singh, S K & Maddala, G S, 1976. "A Function for Size Distribution of Incomes," Econometrica, Econometric Society, vol. 44(5), pages 963-970, September.
    10. Stefan Bach & Giacomo Corneo & Viktor Steiner, 2009. "From Bottom To Top: The Entire Income Distribution In Germany, 1992-2003," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(2), pages 303-330, June.
    11. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    12. Martin Biewen & Stephen Jenkins, 2005. "A framework for the decomposition of poverty differences with an application to poverty differences between countries," Empirical Economics, Springer, vol. 30(2), pages 331-358, September.
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    Cited by:

    1. Alexander Sohn, 2015. "Beyond Conventional Wage Discrimination Analysis: Assessing Comprehensive Wage Distributions of Males and Females Using Structured Additive Distributional Regression," SOEPpapers on Multidisciplinary Panel Data Research 802, DIW Berlin, The German Socio-Economic Panel (SOEP).

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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