误差合成空间固定系数模型的多阶段广义最小二乘估计

Fixed Coefficient Spatial Panel Data Model with Error Components:Multi-Stage Estimation Based on FGLS

本文对时变系数的空间面板数据模型进行了研究,所研究的模型利用扰动项中的空间个体成分将不同时期的方程联系起来,同时,自变量系数和空间自回归系数是时变的,但不会随着观测个体的变动而变动。本文利用基于可行的广义最小二乘估计的多阶段方法对模型参数进行了估计,研究了估计量的大样本性质,并利用Monte Carlo方法模拟了其小样本性质。模拟结果表明,估计量的渐近性质随着样本容量的增加而改善。对中国省级地区间财税策略互动行为的实证案例也体现了本文理论模型的应用价值。

This paper researches the time-varying coefficient spatial panel data model with error compo- nents. This model combines the equations in different time by the individual factors of error disturbance, and allows the independent coefficients and the spatial autoregressive coefficients changing over time. However, the independent coefficients and the spatial autoregressive coefficients are fixed in each time. This paper estimates the coefficients by a multi-stage estimation based on FGLS and proves the asymp- totic consistence and simulates the small sample properties by Monte Carlo. The simulation reveals that the small sample properties of estimators. The simulation output reveals that the asymptotic property improved with the increase of sample size. The empirical research of China＇s provincial fiscal expenditure reaction strategy also reflects the application value of the model.