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Testing a parametric transformation model versus a nonparametric alternative

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  • Arkadiusz Szydlowski

Abstract

Despite an abundance of semiparametric estimators of the transformation model, no procedure has been proposed yet to test the hypothesis that the transformation function belongs to a finite-dimensional parametric family against a nonparametric alternative. In this paper we introduce a bootstrap test based on integrated squared distance between a nonparametric estimator and a parametric null. As a special case, our procedure can be used to test the parametric specification of the integrated baseline hazard in a semiparametric mixed proportional hazard (MPH) model. We investigate the finite sample performance of our test in a Monte Carlo study. Finally, we apply the proposed test to Kennan’s strike durations data.

Suggested Citation

  • Arkadiusz Szydlowski, 2017. "Testing a parametric transformation model versus a nonparametric alternative," Discussion Papers in Economics 17/15, Division of Economics, School of Business, University of Leicester.
    • Handle: RePEc:lec:leecon:17/15
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    References listed on IDEAS

    as
    1. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
    2. Gorgens, Tue & Horowitz, Joel L., 1999. "Semiparametric estimation of a censored regression model with an unknown transformation of the dependent variable," Journal of Econometrics, Elsevier, vol. 90(2), pages 155-191, June.
    3. Jochmans, Koen, 2012. "The variance of a rank estimator of transformation models," Economics Letters, Elsevier, vol. 117(1), pages 168-169.
    4. Richard Blundell & Joel L. Horowitz, 2007. "A Non-Parametric Test of Exogeneity," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1035-1058.
    5. Han, Aaron K., 1987. "A non-parametric analysis of transformations," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 191-209, July.
    6. Roger W. Klein & Robert P. Sherman, 2002. "Shift Restrictions and Semiparametric Estimation in Ordered Response Models," Econometrica, Econometric Society, vol. 70(2), pages 663-691, March.
    7. Horowitz, Joel L, 1996. "Semiparametric Estimation of a Regression Model with an Unknown Transformation of the Dependent Variable," Econometrica, Econometric Society, vol. 64(1), pages 103-137, January.
    8. Foster A. M. & Tian L. & Wei L. J., 2001. "Estimation for the Box-Cox Transformation Model Without Assuming Parametric Error Distribution," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1097-1101, September.
    9. Joel L. Horowitz, 1999. "Semiparametric Estimation of a Proportional Hazard Model with Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 67(5), pages 1001-1028, September.
    10. Subbotin, Viktor, 2007. "Asymptotic and bootstrap properties of rank regressions," MPRA Paper 9030, University Library of Munich, Germany, revised 20 Mar 2008.
    11. Joel L. Horowitz, 2006. "Testing a Parametric Model Against a Nonparametric Alternative with Identification Through Instrumental Variables," Econometrica, Econometric Society, vol. 74(2), pages 521-538, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Specification testing; Transformation model; Duration model; Bootstrap; Rank estimation;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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