Simultaneous Spatial Panel Data Models with Common Shocks
提出了一种同时建模联立效应、空间效应和共同冲击效应的空间面板数据模型，并开发了拟极大似然和迭代广义主成分两种估计方法，通过蒙特卡洛模拟验证了其有限样本性能，最后应用于贸易与GDP关系的跨国面板数据分析。
We consider a simultaneous spatial panel data model, jointly modeling three effects: simultaneous effects, spatial effects and common shock effects. This joint modeling and consideration of cross-sectional heteroscedasticity result in a large number of incidental parameters. We propose two estimation approaches, a quasi-maximum likelihood method and an iterative generalized principal components method. We develop full inferential theories for the estimation approaches and study the tradeoff between the model specifications and their respective asymptotic properties. We further investigate the finite sample performance of both methods using Monte Carlo simulations. We find that both methods perform well and that the simulation results corroborate the inferential theories. Some extensions of the model are considered. Finally, we apply the model to analyze the relationship between trade and gross domestic product using a panel data over time and across countries.