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A smoothed maximum score estimator for the binary choice panel data model with individual fixed effects and applications to labour force participation

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  • Charlier, G.W.P.

    (Tilburg University, Center for Economic Research)

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    Abstract

    In a binary choice panel data model with individual effects and two time periods, Manski proposed the maximum score estimator, based on a discontinuous objective function, and proved its consistency under weak distributional assumptions. However, the rate of convergence of this estimator is low (N) and its limit distribution cannot be used for making inference. This paper overcomes this problem by applying the idea of Horowitz to smooth Manski's objective function. The paper extends the resulting smoothed maximum score estimator to the case of more than two time periods and to unbalanced panels (assuming away selectivity effects). Under weak assumptions the estimator is consistent and asymptotically normal with a rate of convergence that is at least N 2/5 and can be made arbitrarily close to N1/2, depending on the strength of the smoothness assumptions imposed. Statistical inferences can be made. The estimator is applied to an equation for labour force participation of married Dutch.

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    Bibliographic Info

    Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1994-81.

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    Date of creation: 1994
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    Handle: RePEc:dgr:kubcen:199481

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    Web page: http://center.uvt.nl

    Related research

    Keywords: Estimation; Labour Supply; Panel Data; Labour Participation; smoothing; statistics;

    References

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    1. Ruud, Paul A., 1984. "Tests of Specification in Econometrics," Department of Economics, Working Paper Series qt4kq8m0hf, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    2. repec:att:wimass:9001 is not listed on IDEAS
    3. G. S. Maddala, 1987. "Limited Dependent Variable Models Using Panel Data," Journal of Human Resources, University of Wisconsin Press, vol. 22(3), pages 307-338.
    4. Avery, Robert B & Hansen, Lars Peter & Hotz, V Joseph, 1983. "Multiperiod Probit Models and Orthogonality Condition Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(1), pages 21-35, February.
    5. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    6. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Incomplete panels and selection bias: A survey," Discussion Paper 1992-7, Tilburg University, Center for Economic Research.
    7. Horowitz, Joel L., 1993. "Semiparametric estimation of a work-trip mode choice model," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 49-70, July.
    8. Newey, Whitney K, 1985. "Maximum Likelihood Specification Testing and Conditional Moment Tests," Econometrica, Econometric Society, vol. 53(5), pages 1047-70, September.
    9. Newey, Whitney K & Powell, James L & Walker, James R, 1990. "Semiparametric Estimation of Selection Models: Some Empirical Results," American Economic Review, American Economic Association, vol. 80(2), pages 324-28, May.
    10. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
    11. Gourieroux, Christian & Monfort, Alain, 1993. "Simulation-based inference : A survey with special reference to panel data models," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 5-33, September.
    12. Manski, Charles F, 1987. "Semiparametric Analysis of Random Effects Linear Models from Binary Panel Data," Econometrica, Econometric Society, vol. 55(2), pages 357-62, March.
    13. Manski, Charles F., 1985. "Semiparametric analysis of discrete response : Asymptotic properties of the maximum score estimator," Journal of Econometrics, Elsevier, vol. 27(3), pages 313-333, March.
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