Testing the Normality Assumption in the Sample Selection Model with an Application to Travel Demand
Bas van der Klaauw and
Ruud Koning
Journal of Business & Economic Statistics, 2003, vol. 21, issue 1, 31-42
Abstract:
In 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.
Date: 2003
References: Add references at CitEc
Citations: View citations in EconPapers (28)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Working Paper: Testing the normality assumption in the sample selection model with an application to travel demand (2000) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:21:y:2003:i:1:p:31-42
Ordering information: This journal article can be ordered from
http://www.amstat.org/publications/index.html
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano
More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum ().