Testing the Normality Assumption in the Tobit Model
AbstractThis paper examines a number of statistics that have been proposed to test the normality assumption in the tobit (censored regression) model. It argues that a number of commonly proposed statistics can be interpreted as different versions of the Lagrange multiplier, or score, test for a common null hypothesis. This observation is useful in examining the Monte Carlo results presented in the paper. The Monte Carlo results suggest that the computational convenience of a number of statistics is obtained at the cost of poor finite sample performance under the null hypothesis.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Journal of Applied Statistics.
Volume (Year): 31 (2004)
Issue (Month): 5 ()
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