Testing the normality assumption in the Tobit model

D.R. Holden

Research output: Contribution to journalArticle

13 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)521-532
Number of pages11
JournalJournal of Applied Statistics
Volume31
Issue number5
DOIs
Publication statusPublished - 2004

Keywords

  • tobit models
  • normality
  • statistics
  • econometrics
  • business mathematics

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