Abstract
Model misspecifcation is a serious issue since misspecifcation generally renders statistical inference invalid. However, specifcation testing of discrete choice models is rarely applied. This paper describes a nonparametric test procedure which uses a combination of smoothed residual plots and a test statistic able to detect general misspecifcation. Nonparametric methods require large datasets when the number of independent variables is more than a few. A way to circumvent this problem is indicated, increasing the usefulness of the approach also with limited datasets.
Originalsprog | Engelsk |
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Tidsskrift | Journal of Choice Modelling |
Vol/bind | 1 |
Udgave nummer | 1 |
Sider (fra-til) | 26-39 |
Antal sider | 14 |
ISSN | 1755-5345 |
DOI | |
Status | Udgivet - 1 jan. 2008 |