Testing the Normality Assumption in the Sample Selection Model with an Application to Travel Demand

Bas van der Klaauw
Ruud H. Koning

Journal of Business and Economic Statistics 21, 31-42 (2003).

In this paper we introduce a test for the normality assumption in the sample selection model. The test is based on a flexible parametric specification of the density function of the error terms in the model. This specification follows a Hermite series with bivariate normality as a special case. All parameters of the model are estimated both under normality and under the more general flexible parametric specification, which allows to test for normality using a standard likelihood ratio test. If normality is rejected, the flexible parametric specification provides consistent parameter estimates. The test has reasonable power, as is shown by a simulation study. The test also detects some types of ignored heteroskedasticity. Finally, we apply the flexible specification of the density to a travel demand model, and we test for normality in this model.

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(Click here to download the Gauss-code for estimating the sample selection model using the flexible parametric specification discussed in the paper)

Last updated: October, 24, 2001.