RANDOM COEFFICIENT AUTOREGRESSIVE PROCESSES:A MARKOV CHAIN ANALYSIS OF STATIONARITY AND FINITENESS OF MOMENTS
- 1 January 1985
- journal article
- Published by Wiley in Journal of Time Series Analysis
- Vol. 6 (1) , 1-14
- https://doi.org/10.1111/j.1467-9892.1985.tb00394.x
Abstract
Simple yet practically efficient conditions for the ergodicity of a Markov chain on a general state space have recently been developed. We illustrate their application to non‐linear time series models and, in particular, to random coefficient autoregressive models.As well as ensuring the existence of a unique stationary distribution, geometric rates of convergence to stationarity are ensured. Moreover, sufficient conditions for the existence and convergence of moments can be determined by a closely related method. The latter conditions, in particular, are new.Keywords
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