Poisson qmle of count time series models

Ali Ahmad and Christian Francq

MPRA Paper from University Library of Munich, Germany

Abstract: Regularity conditions are given for the consistency of the Poisson quasi-maximum likelihood estimator of the conditional mean parameter of a count time series. The asymptotic distribution of the estimator is studied when the parameter belongs to the interior of the parameter space and when it lies at the boundary. Tests for the significance of the parameters and for constant conditional mean are deduced. Applications to specific INAR and INGARCH models are considered. Numerical illustrations, on Monte Carlo simulations and real data series, are provided.

Keywords: Boundary of the parameter space; Consistency and asymptotic normality; Integer-valued AR and GARCH models; Non-normal asymptotic distribution; Poisson quasi-maximum likelihood estimator; Time series of counts. (search for similar items in EconPapers)
JEL-codes: C12 C13 C22 (search for similar items in EconPapers)
Date: 2014-11
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
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https://mpra.ub.uni-muenchen.de/59804/1/MPRA_paper_59804.pdf original version (application/pdf)

Related works:
Journal Article: Poisson QMLE of Count Time Series Models (2016)
Working Paper: Poisson QMLE of Count Time Series Models (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:59804

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