Poisson QMLE of Count Time Series Models

Ali Ahmad () and Christian Francq
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Ali Ahmad: LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique

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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 model. 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 integer-valued autoregressive (INAR) and integer-valued generalized autoregressive conditional heteroscedasticity (INGARCH) models are considered. Numerical illustrations, 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)
Date: 2015-11
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Published in Journal of Time Series Analysis, 2015, 37 (3), pp.291--314. ⟨10.1111/jtsa.12167⟩

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Related works:
Journal Article: Poisson QMLE of Count Time Series Models (2016)
Working Paper: Poisson qmle of count time series models (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01533548

DOI: 10.1111/jtsa.12167

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