arXiv 24 Sep 2021 · Econometrics · publishedJournal of Econometrics (2023) · 13 citations (OpenAlex)
arXiv:2109.11911 · PDF · DOI · OpenAlex · Extracted main text
We study linear panel regression models in which the unobserved error term is an unknown smooth function of two-way unobserved fixed effects. In standard additive or interactive fixed effect models the individual specific and time specific effects are assumed to enter with a known functional form (additive or multiplicative). In this paper, we allow for this functional form to be more general and unknown. We discuss two different estimation approaches that allow consistent estimation of the regression parameters in this setting as the number of individuals and the number of time periods grow to infinity. The first approach uses the interactive fixed effect estimator in Bai (2009), which is still applicable here, as long as the number of factors in the estimation grows asymptotically. The second approach first discretizes the two-way unobserved heterogeneity (similar to what Bonhomme, Lamadon and Manresa 2021 are doing for one-way heterogeneity) and then estimates a simple linear fixed effect model with additive two-way grouped fixed effects. For both estimation methods we obtain asymptotic convergence results, perform Monte Carlo simulations, and employ the estimators in an empirical application to UK house price data.
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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 | Bai, J (2009) Panel data models with interactive fixed effects | 1.000 | 19 | 6 | 100% |
| 2 | Bonhomme, S., T. Lamadon, and E. Manresa (2021) Discretizing unobserved heterogeneity | 1.000 | 12 | 5 | 100% |
| 3 | Moon, H. R. and M. Weidner (2015) Linear regression for panel with unknown number of factors as interactive fixed effects | 0.965 | 10 | 3 | 90% |
| 4 | Griebel, M. and H. Harbrecht (2014) Approximation of bi-variate functions: singular value decomposition versus sparse grids | 0.874 | 6 | 4 | 67% |
| 5 | Pesaran, M. H. (2006, 07) (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure | 0.644 | 2 | 2 | 100% |
| 6 | Ahn, S. C., Y. H. Lee, and P. Schmidt (2001, April) (2001) GMM estimation of linear panel data models with time-varying individual effects | 0.405 | 1 | 1 | 100% |
| 7 | Ahn, S. C., Y. H. Lee, and P. Schmidt (2013) Panel data models with multiple time-varying individual effects | 0.405 | 1 | 1 | 100% |
| 8 | Bai, J. and S. Ng (2002, January) (2002) Determining the number of factors in approximate factor models | 0.405 | 1 | 1 | 100% |
| 9 | Chudik, A., M. H. Pesaran, and E. Tosetti (2011) Weak and strong cross-section dependence and estimation of large panels | 0.405 | 1 | 1 | 100% |
| 10 | Dhaene, G. and K. Jochmans (2015) Split-panel jackknife estimation of fixed-effect models | 0.405 | 1 | 1 | 100% |
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