Jushan Bai, Jesse Chieh Chen
arXiv 23 Aug 2026 · Econometrics
arXiv:2608.22499 · PDF · Extracted main text
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.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Fogli, Alessandra and Veldkamp, Laura Nature or nurture? Learning and the geography of female labor force participation | 1.000 | 8 | 3 | 100% |
| 2 | Li, Liyao and Yang, Zhenlin Spatial dynamic panel data models with correlated random effects | 0.941 | 6 | 5 | 83% |
| 3 | Tziolas, Ioanna and Elhorst, J. Paul The rise and spread of female labour force participation at the US county level | 0.874 | 11 | 2 | 100% |
| 4 | Anselin, Luc Spatial Econometrics: Methods and Models | 0.644 | 2 | 2 | 100% |
| 5 | Bai, Jushan and Li, Kunpeng Dynamic spatial panel data models with common shocks self | 0.644 | 2 | 2 | 100% |
| 6 | Elhorst, J. Paul Spatial Econometrics: From Cross-Sectional Data to Spatial Panels | 0.644 | 2 | 2 | 100% |
| 7 | Shi, Wei and Lee, Lung-Fei Spatial Dynamic Panel Data Models with Interactive Fixed Effects | 0.644 | 2 | 2 | 100% |
| 8 | Bai, Jushan Panel Data Models with Interactive Fixed Effects self | 0.405 | 1 | 1 | 100% |
| 9 | Bai, Jushan Fixed-Effects Dynamic Panel Models, a Factor Analytical Method self | 0.405 | 1 | 1 | 100% |
| 10 | Bai, Jushan Likelihood approach to dynamic panel models with interactive effects self | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 24 scored citations.