Testing for Uncorrelated Residuals in Dynamic Count Models With an Application to Corporate Bankruptcy
Pedro H. C. Sant’Anna
Authors registered in the RePEc Author Service: Pedro H. C. Sant'Anna ()
Journal of Business & Economic Statistics, 2017, vol. 35, issue 3, 349-358
This article proposes new model checks for dynamic count models. Both portmanteau and omnibus-type tests for lack of residual autocorrelation are considered. The resulting test statistics are asymptotically pivotal when innovations are uncorrelated but possibly exhibit higher order serial dependence. Moreover, the tests are able to detect local alternatives converging to the null at the parametric rate T− 1/2, with T the sample size. The finite sample performance of the test statistics are examined by means of Monte Carlo experiments. Using a dataset on U.S. corporate bankruptcies, the proposed tests are applied to check if different risk models are correctly specified. Supplementary materials for this article are available online.
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
Working Paper: Testing for Uncorrelated Residuals in Dynamic Count Models with an Application to Corporate Bankruptcy (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:35:y:2017:i:3:p:349-358
Ordering information: This journal article can be ordered from
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan
More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().