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GMM Estimation of Partially Linear Single-index Spatial Autoregressive Model

Abstract

This paper studies the generalized method of moment (GMM) estimation of partially linear single-index spatial autoregressive model (PLSISARM). The asymptotic normality of the estimators for unknown parameters and link function is derived under some regular conditions. Monte Carlo simulations indicate our estimators perform well in finite samples. Meanwhile, the proposed method is used to illustrate the Boston housing data.

(It is a joint work with Suli Chen & Xuan Liu)