Model identification for infinite variance autoregressive processes

Beth Andrews and Richard A. Davis

Journal of Econometrics, 2013, vol. 172, issue 2, 222-234

Abstract: We consider model identification for infinite variance autoregressive time series processes. It is shown that a consistent estimate of autoregressive model order can be obtained by minimizing Akaike’s information criterion, and we use all-pass models to identify noncausal autoregressive processes and estimate the order of noncausality (the number of roots of the autoregressive polynomial inside the unit circle in the complex plane). We examine the performance of the order selection procedures for finite samples via simulation, and use the techniques to fit a noncausal autoregressive model to stock market trading volume data.

Keywords: Akaike’s information criterion; All-pass models; Autoregressive processes; Infinite variance; Noncausal (search for similar items in EconPapers)
JEL-codes: C13 C22 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:172:y:2013:i:2:p:222-234

DOI: 10.1016/j.jeconom.2012.08.009

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