空间计量经济学中的空间自回归模型

This paper provides an overall view on the SAR model, which generalizes the autoregessive time series model to a spatial setting. It is the most popular model in spatial econometrics with broad applications in empirical economics as it captures interactions and spilled over effects across economic agents. We first provide some economic justification of such a model in an complete information static game setting, of which observed outcomes are Nash equilibria. Comparative statics analysis in economics provides economic implications on direct and indirect effects and multiplier effect on outcomes. The traditional ML estimation and its extension in terms of QML estimation are discussed. Recent developments on concavity of its log likelihood function are established, and alternative estimation methods, GMM and GEL, are presented. The construction of best GMM estimation with linear-quadratic moments is feasible. The GEL approach on estimation and testing for the SAR model can be robust against unknown heteroskedasticity.