Testing for the mixture hypothesis of geometric distributions

Jin Seo Cho, Chirok Han

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Use of the likelihood ratio (LR) statistic is examined to test for the mixture assumption of geometric distributions. As the asymptotic null distribution of the LR statistic is not a standard chi-square due to the fact that there are a boundary parameter problem and a nuisance parameter not identified under the null, we derive it separately and also provide a method to obtain the asymptotic critical values. Further, the finite sample properties of the LR test are evaluated by Monte Carlo simulations by examining the levels and powers of the LR test. Finally, using Kennan's (1985) strike data in labor economics, we conclude that unobserved heterogeneity is present in the data, which cannot be captured by specifying a geometric distribution.

Original languageEnglish
Pages (from-to)31-55
Number of pages25
JournalJournal of Economic Theory and Econometrics
Volume20
Issue number3
Publication statusPublished - 2009 Sep 1

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Testing
Geometric distribution
Likelihood ratio statistic
Likelihood ratio test
Nuisance parameter
Monte Carlo simulation
Critical value
Asymptotic distribution
Labor economics
Finite sample properties
Unobserved heterogeneity

Keywords

  • Geometric distribution
  • Likelihood ratio statistic
  • Mixture
  • Strike data
  • Unobserved heterogeneity

ASJC Scopus subject areas

  • Economics and Econometrics

Cite this

Testing for the mixture hypothesis of geometric distributions. / Cho, Jin Seo; Han, Chirok.

In: Journal of Economic Theory and Econometrics, Vol. 20, No. 3, 01.09.2009, p. 31-55.

Research output: Contribution to journalArticle

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