Asymptotic inference for a nearly unstable sequence of stationary spatial AR models

A nearly unstable sequence of stationary spatial autoregressive processes is investigated, where the autoregressive coefficients are equal, and their sum tends to one. It is shown that the limiting distribution of the least-squares estimator for this coefficient is normal and, in contrast to the doubly geometric process, the typical rate of convergence is n-5/4.

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Year of publication:	2004
Authors:	Baran, Sándor ; Pap, Gyula ; Zuijlen, Martien C. A. van
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 69.2004, 1, p. 53-61
Publisher:	Elsevier
Keywords:	Autoregressive model Asymptotic normality Martingale central limit theorem

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

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005319811