Checking Model Adequacy for Count Time Series by Using Pearson Residuals

After having fitted a model to a given count time series, one has to check the adequacy of this model fit. The (standardized) Pearson residuals, being easy to compute and interpret, are a popular diagnostic approach for this purpose. But which types of model inadequacy might be uncovered by which st...

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Bibliographic Details
Published in:Journal of time series econometrics 2020-01, Vol.12 (1)
Main Authors: Weiß, Christian, Scherer, Lukas, Aleksandrov, Boris, Feld, Martin
Format: Article
Language:English
Subjects:
count time series
model adequacy
overdispersion
Pearson residuals
serial dependence
Time series
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Summary:After having fitted a model to a given count time series, one has to check the adequacy of this model fit. The (standardized) Pearson residuals, being easy to compute and interpret, are a popular diagnostic approach for this purpose. But which types of model inadequacy might be uncovered by which statistics based on the Pearson residuals? In view of being able to apply such statistics in practice, it is also crucial to ask for the properties of these statistics under model adequacy. We look for answers to these questions by means of a comprehensive simulation study, which considers diverse types of count time series models and inadequacy scenarios. We illustrate our findings with two real-data examples about strikes in the U.S., and about corporate insolvencies in the districts of Rhineland–Palatinate. We conclude with a theoretical discussion of Pearson residuals.
ISSN:1941-1928
1941-1928
2194-6507
DOI:10.1515/jtse-2018-0018