Genuinely unbalanced spatial panel data models with fixed effects: M-estimation and inference with an application to FDI inflows
研究了因部分空间单元在某些时期缺失导致的真正非平衡空间面板数据模型，提出了M估计和推断方法，并应用于中国省级外商直接投资流入，发现正确处理非平衡性可揭示被掩盖的正向空间溢出效应。
We consider spatial panel data models with genuine unbalancedness arising from the non-presence of some spatial units in certain time periods. General M-estimation methods are proposed for model estimation, which take into account the estimation of the incidental fixed effects parameters and allow for spatiotemporal heteroskedasticity and high-order time-varying spatial effects. Corrected plug-in methods are proposed for standard error estimation. The proposed estimation and inference methods are rigorously studied for their asymptotic properties and finite sample performance. An application to China’s provincial FDI inflows shows that properly accounting for genuine unbalancedness uncovers significant positive spatial spillovers that are masked when the data are artificially treated as balanced.