SPATIAL SEMIPARAMETRIC MODEL WITH ENDOGENOUS REGRESSORS
提出了一种半参数广义矩估计方法，用于处理含内生空间依赖回归元的局部参数空间模型，证明了估计量的一致性和渐近正态性，并构建了空间异方差和自相关一致协方差估计量。
This paper proposes a semiparametric generalized method of moments estimator (GMM) estimator for a partially parametric spatial model with endogenous spatially dependent regressors. The finite-dimensional estimator is shown to be consistent and root-n asymptotically normal under some reasonable conditions. A spatial heteroscedasticity and autocorrelation consistent covariance estimator is constructed for the GMM estimator. The leading application is nonlinear spatial autoregressions, which arise in a wide range of strategic interaction models. To derive the asymptotic properties of the estimator, the paper also establishes a stochastic equicontinuity criterion and functional central limit theorem for near-epoch dependent random fields.