Estimation in nonstationary random coefficient autoregressive models

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dc.creatorBerkes, Istvan
dc.creatorHorvath, Lajos
dc.creatorLing, Shiqing
dc.date2009-02-27
dc.date.accessioned2026-07-07T12:47:54Z
dc.date.available2026-07-07T12:47:54Z
dc.descriptionWe investigate the estimation of parameters in the random coefficient autoregressive model. We consider a nonstationary RCA process and show that the innovation variance parameter cannot be estimated by the quasi-maximum likelihood method. The asymptotic normality of the quasi-maximum likelihood estimator for the remaining model parameters is proven so the unit root problem does not exist in the random coefficient autoregressive model.
dc.description21 pages
dc.identifierhttps://arxiv.org/abs/0903.0022
dc.identifierhttp://arxiv.org/abs/0903.0022
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/221874
dc.subjectMethodology
dc.subjectStatistics Theory
dc.titleEstimation in nonstationary random coefficient autoregressive models
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