On the least squares estimator in a nearly unstable sequence of stationary spatial AR models

Sándor Baran and Gyula Pap

Journal of Multivariate Analysis, 2009, vol. 100, issue 4, 686-698

Abstract: A nearly unstable sequence of stationary spatial autoregressive processes is investigated, when the sum of the absolute values of the autoregressive coefficients tends to one. It is shown that after an appropriate normalization the least squares estimator for these coefficients has a normal limit distribution. If none of the parameters equals zero then the typical rate of convergence is n.

Keywords: primary; 62M10 secondary; 62F12 Autoregressive model Asymptotic normality Martingale central limit theorem (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (2)

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