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Testing for unobserved heterogeneity in exponential and Weibull duration models by Jin Seo Cho; Halbert White is a Economics, Econometrics and Finance article available to read on EtoBox.

What is Testing for unobserved heterogeneity in exponential and Weibull duration models about?

We examine the use of the likelihood ratio (LR) statistic to test for unobserved heterogeneity in duration models, based on mixtures of exponential or Weibull distributions. We consider both the uncensored and censored duration cases. The asymptotic null distribution of the LR test statistic is not the standard chisquare, as the standard regularity conditions do not hold. Instead, there is a nuisance parameter identified only under the alternative, and a null parameter value on the boundary of the parameter space, as in Cho and White (2007a). We accommodate these and provide methods delivering consistent asymptotic critical values. We conduct a number of Monte Carlo simulations, comparing the level and power of the LR test statistic to an information matrix (IM) test due to and Lagrange multiplier (LM) tests of and . Our simulations show that the LR test statistic generally outperforms the IM and LM tests. We also revisit the work of van den Berg and Ridder (1998) on unemployment durations and of on interarrival times between stock trades, and, as it turns out, affirm their original informal inferences.

Who reads Testing for unobserved heterogeneity in exponential and Weibull duration models?

Author

Jin Seo Cho; Halbert White

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0304-4076)

Published

2010

Language

EN

Field

Economics, Econometrics and Finance (Social Sciences)