AI 中文总结
本研究针对大N、固定T框架下的动态空间面板模型，提出结合空间增强随机载荷（SERL）设定的块坐标算法，模拟及美国县女性劳动力参与率应用验证了方法的有效性。
AI 中文摘要
我们在大N、固定T的框架下研究了带有观测到的回归元、交互式效应以及同期和滞后依赖的动态空间面板模型。该空间模型构成了一个N维联立方程系统，在N个方程的视角下，交互式效应引入了N个单位特定的载荷向量。当T固定时单独估计这些载荷向量会产生Nickell偏差背后的附带参数问题。我们利用N个方程的视角通过空间雅可比来处理空间 simultaneity。然而关键的是，我们将同一模型视为具有N个观测值的T个方程系统。结合空间增强随机载荷（SERL）设定，这种T个方程的视角产生了无单位特定附带参数的拟似然。我们提出了一种计算上易处理的块坐标算法。模拟显示估计误差较小，且通常接近名义覆盖概率。将该方法应用于美国县女性劳动力参与率，我们发现存在显著的动态和空间依赖，且教育在解释女性劳动力参与率上升方面发挥了重要作用。
英文摘要
We study a dynamic spatial panel model with observed regressors, interactive effects, and contemporaneous and lagged dependence in a large-$N$, fixed-$T$ framework. The spatial model constitutes an $N$-dimensional simultaneous-equations system. In this $N$-equation view, the interactive effects introduce $N$ unit-specific loading vectors. Estimating them individually when $T$ is fixed creates the type of incidental-parameters problem underlying Nickell bias. We use the $N$-equation view to account for spatial simultaneity through the spatial Jacobian. Crucially, however, we view the same model as a $T$-equation system with $N$ observations. Together with a spatially enriched random-loadings (SERL) specification, this $T$-equation view yields a quasi-likelihood without unit-specific incidental parameters. We propose a computationally tractable block-coordinate algorithm. Simulations show small estimation errors and generally near-nominal coverage probabilities. Applying the method to U.S. county female labor-force participation, we find substantial dynamic and spatial dependence and an important role for education in explaining the rise in female labor-force participation.
