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Empirical Welfare Analysis in Random Utility Models of Labour Supply

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  • Decoster, André

    (KU Leuven)

  • Haan, Peter

    (DIW Berlin)

Abstract

The aim of this paper is to apply recently proposed individual welfare measures in the context of random utility models of labour supply. Contrary to the standard practice of using reference preferences and wages, these measures preserve preference heterogeneity in the normative step of the analysis. They also make the ethical priors, implicit in any interpersonal comparison, more explicit. On the basis of microdata from the Socio Economic Panel (SOEP) for married couples in Germany, we provide empirical evidence about the sensitivity of the welfare orderings to different normative principles embodied in these measures. We retrieve individual and household specific preference heterogeneity, by estimating a structural discrete choice labor supply model. We use this preference information to construct welfare orderings of households according to the different metrics, each embodying different ethical choices concerning the preference heterogeneity in the consumption-leisure space. We then discuss how sensitive the assessment of a hypothetical tax reform is to the choice of metric. The chose tax reform is similar to a subsidy of social security contributions.

Suggested Citation

  • Decoster, André & Haan, Peter, 2010. "Empirical Welfare Analysis in Random Utility Models of Labour Supply," IZA Discussion Papers 5301, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp5301
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    References listed on IDEAS

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    1. Arthur van Soest, 1995. "Structural Models of Family Labor Supply: A Discrete Choice Approach," Journal of Human Resources, University of Wisconsin Press, vol. 30(1), pages 63-88.
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    Cited by:

    1. Stefan Boeters & Luc Savard, 2011. "The Labour Market in CGE Models," Cahiers de recherche 11-20, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    2. Jean-François Carpantier & Christelle Sapata, 2013. "An Ex-Post View of Inequality of Opportunity in France and its Regions," Journal of Labor Research, Springer, vol. 34(3), pages 281-311, September.
    3. Bessho, Shun-ichiro & Hayashi, Masayoshi, 2014. "Intensive margins, extensive margins, and spousal allowances in the Japanese system of personal income taxes: A discrete choice analysis," Journal of the Japanese and International Economies, Elsevier, vol. 34(C), pages 162-178.
    4. Shun-ichiro Bessho & Masayoshi Hayashi, 2015. "Should the Japanese tax system be more progressive? An evaluation using the simulated SMCFs based on the discrete choice model of labor supply," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 22(1), pages 144-175, February.
    5. Olivier Bargain & André Decoster & Mathias Dolls & Dirk Neumann & Andreas Peichl & Sebastian Siegloch, 2013. "Welfare, labor supply and heterogeneous preferences: evidence for Europe and the US," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 41(4), pages 789-817, October.
    6. Olivier Bargain & Mathias Dolls & Dirk Neumann & Andreas Peichl & Sebastian Siegloch, 2011. "Tax-Benefit Systems in Europe and the US: Between Equity and Efficiency," CESifo Working Paper Series 3534, CESifo.
    7. Jean-François Carpantier & Christelle Sapata, 2012. "Unfair inequalities in France: A regional comparison," Working Papers hal-01821150, HAL.
    8. André Decoster & Peter Haan, 2015. "Empirical welfare analysis with preference heterogeneity," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 22(2), pages 224-251, April.
    9. Thor O. Thoresen & Zhiyang Jia & Peter J. Lambert, 2013. "Distributional benchmarking in tax policy evaluations," Discussion Papers 765, Statistics Norway, Research Department.
    10. John Creedy & Nicolas Hérault†, 2011. "Decomposing Inequality and Social Welfare Changes : The Use of Alternative Welfare Metrics," Department of Economics - Working Papers Series 1121, The University of Melbourne.
    11. Jean-François Carpantier & Christelle Sapata, 2016. "Empirical welfare analysis: when preferences matter," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 46(3), pages 521-542, March.
    12. Creedy, John, 2013. "Alternative Distributions for Inequality and Poverty Comparisons," Working Paper Series 18784, Victoria University of Wellington, Chair in Public Finance.
    13. John Creedy, 2013. "Alternative Distributions for Inequality and Poverty Comparisons," Treasury Working Paper Series 13/11, New Zealand Treasury.
    14. John Creedy & Nicolas Hérault†, 2011. "Decomposing Inequality and Social Welfare Changes : The Use of Alternative Welfare Metrics," Department of Economics - Working Papers Series 1121, The University of Melbourne.
    15. Antoine de Mahieu, 2021. "In-work Benefits in Belgium: Effects on Labour Supply and Welfare," International Journal of Microsimulation, International Microsimulation Association, vol. 14(1), pages 43-72.
    16. André Decoster & Peter Haan, 2011. "A Switch from Joint to Individual Taxation Is Welfare Improving," Discussion Papers of DIW Berlin 1175, DIW Berlin, German Institute for Economic Research.
    17. Figari, Francesco, 2011. "From housewives to independent earners: can the tax system help Italian women to work?," ISER Working Paper Series 2011-15, Institute for Social and Economic Research.
    18. Carlotta Balestra & Romina Boarini & Elena Tosetto, 2018. "What Matters Most to People? Evidence from the OECD Better Life Index Users’ Responses," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 907-930, April.
    19. André Decoster & Peter Haan, 2014. "Welfare Effects of a Shift of Joint to Individual Taxation in the German Personal Income Tax," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 70(4), pages 599-624, December.
    20. Boeters, Stefan & Savard, Luc, 2013. "The Labor Market in Computable General Equilibrium Models," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 1645-1718, Elsevier.

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    More about this item

    Keywords

    welfare measures; labour supply; random utility; preference heterogeneity;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • D78 - Microeconomics - - Analysis of Collective Decision-Making - - - Positive Analysis of Policy Formulation and Implementation
    • H24 - Public Economics - - Taxation, Subsidies, and Revenue - - - Personal Income and Other Nonbusiness Taxes and Subsidies
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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