随机效应广义空间滞后半参数变系数面板模型的估计

Estimation of Generalized Spatial Lag Semi-parametric Varying-coefficient Panel Model with Random Effects

本文通过构建同时包含因变量和误差项空间滞后的随机效应半参数变系数面板模型,拓展了现有模型的灵活性和适应性;采用截面极大似然估计方法得出了参数和非参数的估计。理论证明发现:在一定的正则条件下,所有估计量具有一致性和渐近正态性。数值模拟显示:估计量具有良好的小样本性质,估计精度随着样本容量的增加而增加;空间权重矩阵的选择对估计量的表现没有产生显著差异,但是在Case权重矩阵下,当样本量相同时,空间相关系数的估计偏差随着空间权重结构复杂度的增加而扩大。

By constructing a semi-parametric varying-coefficient random effect panel model with spatial lag and spatial error,the flexibility and adaptability of the existing models are extended. It uses profile maximum likelihood method to construct both parametric and nonparametric estimators. The theoretical proof shows that all estimators have consistency and asymptotic normality under certain regular conditions. The numerical simulation shows that the estimators have good small sample properties,and the estimation accuracy increases with the increase of the sample capacity. The selection of the spatial weight matrix does not produce significant difference in the performance of the estimator,but under the condition of Case matrix,when the sample quantities are the same,the estimated deviation of spatial correlation coefficients increase with the increase of spatial weight structure complexity.