
空间计量经济学中的空间自回归模型
The Spatial Autoregression Model in Spatial Econometrics
本文对SAR模型进行了综述,将自回归时间序列模型推广到空间的设定.这是空间计量经济学中最受欢迎的模型,在经济学实证研究中有着广泛的应用,因为它捕捉了经济主体之间的相互作用和溢出效应.本文首先给出了在完全信息静态博弈设定下的纳什均衡模型的经济解释.比较静态经济比较分析提供了对结果有直接和间接影响以及乘数效应的经济解释.本文讨论了传统的ML估计及其在QML估计方面的扩展.我们也阐述了近来对数似然函数凹性方面的最新研究,和其他的估计方法,包括GMM和GEL.利用线性二阶矩构造最优GMM估计方法是可行的.对SAR模型进行估计和检验的GEL方法对未知异方差具有较好的稳健性.
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.
空间自回归 / 交互作用 / 溢出效应 / 完全信息博弈 / 纳什均衡 / QML / GMM / GEL / QMLE的唯一性 / 最优线性二次矩 / 未知异方差 {{custom_keyword}} /
spatial autoregression / interactions / spill-over effects / complete information game / Nash equilibrium / QML / GMM / GEL / uniqueness of QMLE / best linear-quadratic moment / unknown heteroskedasticity {{custom_keyword}} /
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感谢孙玉莹、许杏柏及包皓文、白云、崔如鸿、陶睿的翻译及校对.
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