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Testing for Uncorrelated Residuals in Dynamic Count Models with an Application to Corporate Bankruptcy

Pedro Sant'Anna ()

MPRA Paper from University Library of Munich, Germany

Abstract: This article proposes a new diagnostic test for dynamic count models, which is well suited for risk management. Our test proposal is of the Portmanteau-type test for lack of residual autocorrelation. Unlike previous proposals, the resulting test statistic is asymptotically pivotal when innovations are uncorrelated, but not necessarily iid nor a martingale difference. Moreover, the proposed test is 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 statistic is examined by means of a Monte Carlo experiment. Finally, using a dataset on U.S. corporate bankruptcies, we apply our test proposal to check if common risk models are correctly specified.

Keywords: Time Series of counts; Residual autocorrelation function; Model checking; Credit risk management. (search for similar items in EconPapers)
JEL-codes: C12 C22 C25 G3 G33 (search for similar items in EconPapers)
Date: 2013-05
New Economics Papers: this item is included in nep-ecm and nep-rmg
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https://mpra.ub.uni-muenchen.de/48376/1/MPRA_paper_48376.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/48429/8/MPRA_paper_48429.pdf revised version (application/pdf)

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Journal Article: Testing for Uncorrelated Residuals in Dynamic Count Models With an Application to Corporate Bankruptcy (2017) Downloads
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