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

B. van der Klaauw and Ruud Koning

No 00F37, Research Report from University of Groningen, Research Institute SOM (Systems, Organisations and Management)

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 .

Date: 2000
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Journal Article: Testing the Normality Assumption in the Sample Selection Model with an Application to Travel Demand (2003)
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