Juan M. Rodriguez-Poo, Alexandra Soberon, Stefan Sperlich
arXiv 12 Jun 2025 · Econometrics · publishedEconometrics and Statistics (2026)
arXiv:2506.10690 · PDF · DOI · OpenAlex · Extracted main text
We consider identification, inference and validation of linear panel data models when both factors and factor loadings are accounted for by a nonparametric function. This general specification encompasses rather popular models such as the two-way fixed effects and the interactive fixed effects ones. By applying a conditional mean independence assumption between unobserved heterogeneity and the covariates, we obtain consistent estimators of the parameters of interest at the optimal rate of convergence, for fixed and large $T$. We also provide a specification test for the modeling assumption based on the methodology of conditional moment tests and nonparametric estimation techniques. Using degenerate and nondegenerate theories of U-statistics we show its convergence and asymptotic distribution under the null, and that it diverges under the alternative at a rate arbitrarily close to $\sqrt{NT}$. Finite sample inference is based on bootstrap. Simulations reveal an excellent performance of our methods and an empirical application is conducted.
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| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Pesaran, M. H (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure | 1.000 | 5 | 3 | 100% |
| 2 | Bai, J (2009) Panel data models with interactive fixed effects | 0.928 | 4 | 3 | 100% |
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| 9 | Chudik, A. and H. Pesaran (2015, 01) (2015) 3large panel data models with cross-sectional dependence: A survey | 0.405 | 1 | 1 | 100% |
| 10 | Chudik, A., K. Mohaddes, M. Pesaran, and M. Raissi (2017) Is there a debt-threshold effect on output growth? | 0.405 | 1 | 1 | 100% |
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