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A Structural Labor Supply Model with Nonparametric Preferences

Author

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  • van Soest, A.H.O.

    (Tilburg University, Center For Economic Research)

  • Das, J.W.M.

    (Tilburg University, Center For Economic Research)

  • Gong, X.

    (Tilburg University, Center For Economic Research)

Abstract

Nonparametric techniques are usually seen as a statistic device for data description and exploration, and not as a tool for estimating models with a richer economic structure, which are often required for policy analysis. This paper presents an example where nonparametric flexibility can be attained in a fully structural model. A structural labour supply model with a nonparametric specification of preferences is introduced, which can be used for the analysis of all sorts of (non-linear) tax and benefits changes. Moreover, the model can deal with several other problems in estimation of structural labour supply models, such as non-convex tax rules, benefits, unobserved wages of non-workers, and model coherency. The utility maximization problem is solved by discretizing the budget set and choosing the optimal leisure and income combination from a finite set of alternatives. The direct utility function is approximated with a series expansion. For a given length of the expansion, the model is estimated by smooth simulated maximum likelihood. The wage equation is estimated jointly with the labour supply model, and measurement errors in wage rates are allowed for. The model is estimated with Dutch data on labour supply of married females, for various lengths of the series expansion. Estimates of labour supply elasticities and effects of a proposed tax reform suggest that the results do not change much once the order of the series expansion is extended beyond two, even though the second order model is statistically rejected against higher order models. Monte Carlo simulations are used to show that the estimation strategy has remarkably good finite sample properties for the size of our sample. On the other hand they lead to some concern about the potential bias to measurement error in the hours variable.
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • van Soest, A.H.O. & Das, J.W.M. & Gong, X., 2000. "A Structural Labor Supply Model with Nonparametric Preferences," Discussion Paper 2000-60, Tilburg University, Center for Economic Research.
    • Handle: RePEc:tiu:tiucen:5e6f370d-3e08-48be-8a44-1da8a4f5173b
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    References listed on IDEAS

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    Cited by:

    1. Bargain, Olivier, 2009. "Flexible labor supply models," Economics Letters, Elsevier, vol. 105(1), pages 103-105, October.
    2. Olivier Bargain, 2004. "On modeling household labor supply with taxation," DELTA Working Papers 2004-14, DELTA (Ecole normale supérieure).
    3. Olivier Bargain & Andreas Peichl, 2013. "Steady-State Labor Supply Elasticities: An International Comparison," AMSE Working Papers 1322, Aix-Marseille School of Economics, France.
    4. 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.
    5. Bargain, Olivier & Peichl, Andreas, 2013. "Steady-state labor supply elasticities: A survey," ZEW Discussion Papers 13-084, ZEW - Leibniz Centre for European Economic Research.
    6. Olivier Bargain & Kristian Orsini & Andreas Peichl, 2012. "Comparing Labor Supply Elasticities in Europe and the US: New Results," Working Papers halshs-00805736, HAL.
    7. Anil Kumar, 2012. "Nonparametric estimation of the impact of taxes on female labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(3), pages 415-439, April.
    8. Bargain, Olivier B. & Doorley, Karina, 2013. "Putting Structure on the RD Design: Social Transfers and Youth Inactivity in France," IZA Discussion Papers 7508, Institute of Labor Economics (IZA).

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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure

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