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Testing the normality assumption in the sample selection model with an application to travel demand
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Testing the normality assumption in the sample selection model with an application to travel demand

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  • Klaauw, B. van der
  • Koning, R.H.

    (Groningen University)

Abstract

In this paper we introduce a test for the normality assumption in the sample selection model.The test is based on a generalization of a semi-nonparametric maximum likelihood method.In this estimation method,the distribution of the error erms is approximated by a Hermite series,with normality as a special case.Because all parameters of the model are estimated both under normality and in the more general specification,we can est for normality using the likeli- hood ratio approach.This est has reasonable power as is shown by a simulation study.Finally,we apply the generalized semi-nonparametric maximum likeli- hood estimation method and the normality est o a model of car ownership and car use.The assumption of normal distributed error erms is rejected and we provide estimates of the sample selection model that are consisten .

Suggested Citation

  • Klaauw, B. van der & Koning, R.H., 2000. "Testing the normality assumption in the sample selection model with an application to travel demand," Research Report 00F37, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    • Handle: RePEc:gro:rugsom:00f37
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    References listed on IDEAS

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    1. Phillips, Peter C B, 1983. "ERAs: A New Approach to Small Sample Theory," Econometrica, Econometric Society, vol. 51(5), pages 1505-1525, September.
    2. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-390, March.
    3. Melenberg, B. & van Soest, A.H.O., 1993. "Semi-parametric estimation of the sample selection model," Other publications TiSEM 204da5b1-2a6f-4815-b823-1, Tilburg University, School of Economics and Management.
    4. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
    5. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    6. Cameron, A Colin & Johansson, Per, 1997. "Count Data Regression Using Series Expansions: With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 203-223, May-June.
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