Efficient Estimation of Spatial Autoregressive Models

Théophile Azomahou

Working Papers of BETA from Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg

Abstract: This paper considers estimating general spatial autoregressive models using the generalized method of moments (GMM). I propose nonparametric estimates of the optimal instruments based on conditional second moment restrictions. I show that these instruments are optimal over all possible instruments, especially over those usually suggested in a spatial context. I provide a nonparametric estimator of sample autocovariances function for irregularly spaced spatial processes, and I show that this estimator converges in probability. I then derive the consistency in norm L_2 of the resulting asymptotic variance matrix estimator. Finally, the asymptotic distribution of the GMM estimator is stated.

Keywords: Instrumental variables; Spatial dependence; Nonparametric estimation (search for similar items in EconPapers)
JEL-codes: C13 C14 C50 (search for similar items in EconPapers)
Date: 2001
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:ulp:sbbeta:2001-05

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