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Self-Selection and Subjective Well-Being: Copula Models with an Application to Public and Private Sector Work

Author

Listed:
  • Simon Luechinger
  • Alois Stutzer
  • Rainer Winkelmann

Abstract

We discuss a new approach to specifying and estimating ordered probit models with endogenous switching, or with binary endogenous regressor, based on copula functions. These models provide a framework of analysis for self-selection in economic well-being equations, where assigment of regressors may be choice based, resulting from well-being maximization, rather than random. In an application to public and private sector job satisfaction, and using data on male workers from the German Socio-Economic Panel, we find that a model based on Frank's copula is preferred over two alternative models with independence and normal copula, respectively. The results suggest that public sector workers are negatively selected.

Suggested Citation

  • Simon Luechinger & Alois Stutzer & Rainer Winkelmann, 2008. "Self-Selection and Subjective Well-Being: Copula Models with an Application to Public and Private Sector Work," SOEPpapers on Multidisciplinary Panel Data Research 135, DIW Berlin, The German Socio-Economic Panel (SOEP).
    • Handle: RePEc:diw:diwsop:diw_sp135
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    References listed on IDEAS

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    Cited by:

    1. Lucia Rizzica, 2016. "Why go public? A study of the individual determinants of public sector employment choice," Questioni di Economia e Finanza (Occasional Papers) 343, Bank of Italy, Economic Research and International Relations Area.
    2. Simona Iammarino & Elisabetta Marinelli & Elisabetta Marinelli, 2011. "Is the Grass Greener on the other Side of the Fence? Graduate Mobility and Job Satisfaction in Italy," Environment and Planning A, , vol. 43(11), pages 2761-2777, November.

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    Keywords

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    JEL classification:

    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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