Sensitivity Analysis of SAR Estimators: A Simulation Study

Shuangzhe Liu (), Wolfgang Polasek and Richard Sellner
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Shuangzhe Liu: University of Canberra, Australia

Working Paper series from Rimini Centre for Economic Analysis

Abstract: Spatial autoregressive models come with a variety of estimators and it is interesting and useful to compare the estimators by location and covariance properties. In this paper, we first study the local sensitivity behavior of the main least squares estimator by using matrix derivatives. We then calculate the Taylor approximation of the least squares estimator in the SAR model up to the second order. Also, we compare the estimators of the spatial autoregression (SAR) model in terms of the covariance structure of the least squares estimators and we make efficiency comparisons using Kantorovich inequalities. Finally, we demonstrate our approach by an example for GDP and employment in 239 European NUTS2 regions. We find a quite good approximation behavior of the SAR estimator in the neighborhood of ρ = 0, i.e. a small spatial correlation.

Keywords: Spatial autoregressive models; least-squares estimators; Taylor approximations; Kantorovich inequality (search for similar items in EconPapers)
Date: 2010-01, Revised 2011-11
New Economics Papers: this item is included in nep-ecm, nep-geo and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:rim:rimwps:22_10

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