Ergodicity and existence of moments for local mixtures of linear autoregressions

We consider a class of nonlinear time series expressed as a local mixture of a finite number of linear autoregressions. The mixing weights are continuous functions of lagged observations while the densities of the innovation terms in each autoregression can be very general and are only assumed to possess finite moments of some order. We focus on the probabilistic properties of the model and provide mild sufficient conditions for geometric ergodicity and existence of moments.

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Year of publication:	2005
Authors:	Carvalho, Alexandre ; Skoulakis, Georgios
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 71.2005, 4, p. 313-322
Publisher:	Elsevier
Keywords:	Nonlinear time series Autoregressions Mixture models Markov chains Geometric ergodic Uniformly geometric ergodic Invariant measure

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005223307