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| Drukker, David M.. |
| Categorical and limited dependent variable models are routinely estimated via maximum likelihood. It is well-known that the ML estimates of the parameters are inconsistent if the distribution or the skedastic component is misspecified. When conditional moment tests were first developed by Newey (1985) and Tauchen (1985), they appeared to offer a wide range of easy-to-compute specification tests for categorical and limited dependent variable models estimated by maximum likelihood. However, subsequent studies found that using the asymptotic critical values produced severe size distortions. This paper presents simulation evidence that the standard conditional moment test for normality after tobit estimation has essentially no size distortion and reasonable... |
| Tipo: Journal Article |
Palavras-chave: Conditional moment tests; Bootstrap; Tobit; Normality; Research Methods/ Statistical Methods. |
| Ano: 2002 |
URL: http://purl.umn.edu/115956 |
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| Drukker, David M.. |
| Because serial correlation in linear panel-data models biases the standard errors and causes the results to be less efficient, researchers need to identify serial correlation in the idiosyncratic error term in a panel-data model. A new test for serial correlation in random- or fixed-effects one-way models derived by Wooldridge (2002) is attractive because it can be applied under general conditions and is easy to implement. This paper presents simulation evidence that the new Wooldridge test has good size and power properties in reasonably sized samples. |
| Tipo: Journal Article |
Palavras-chave: Panel data; Serial correlation; Specification tests; Research Methods/ Statistical Methods. |
| Ano: 2003 |
URL: http://purl.umn.edu/116069 |
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