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

B. van der Klaauw, R.H. Koning

Research output: Working paperAcademic

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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 .
Original languageEnglish
Number of pages41
Publication statusPublished - 2000


  • Autogebruik
  • Waarschijnlijkheidstheorie
  • Schattingstheorie
  • Non-parametrische statistiek
  • 31.73;

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