Testing the Normality Assumption in the Sample Selection Model with an Application to Travel Demand
AbstractIn this article 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 enables testing for normality using a standard likelihood ratio test. If normality is rejected, then 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 heteroscedasticity. Finally, we apply the flexible specification of the density to a travel demand model and test for normality in this model.
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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 21 (2003)
Issue (Month): 1 (January)
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Web page: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main
Other versions of this item:
- 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).
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- Melenberg, B. & Van Soest, A., 1993. "Semi-Parametric Estimation on the Sample Selection Model," Papers 9334, Tilburg - Center for Economic Research.
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