Testing the Normality Assumption in the Tobit Model

Darryl Holden

Journal of Applied Statistics, 2004, vol. 31, issue 5, 521-532

Abstract: This 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.

Keywords: Tobit (Censored Regression) And Probit Models; Normality; Language Multiplier (score) Tests; Hours Of Work Equations (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (13)

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DOI: 10.1080/02664760410001681783

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