arXiv 18 Dec 2022 · Econometrics · publishedJournal of Econometrics (2024) · 2 citations (OpenAlex)
arXiv:2212.09193 · PDF · DOI · OpenAlex · Extracted main text
We develop a general framework for the identification of counterfactual parameters in a class of nonlinear semiparametric panel models with fixed effects and time effects. Our method applies to models for discrete outcomes (e.g., two-way fixed effects binary choice) or continuous outcomes (e.g., censored regression), with discrete or continuous regressors. Our results do not require parametric assumptions on the error terms or time-homogeneity on the outcome equation. Our main results focus on static models, with a set of results applying to models without any exogeneity conditions. We show that the survival distribution of counterfactual outcomes is identified (point or partial) in this class of models. This parameter is a building block for most partial and marginal effects of interest in applied practice that are based on the average structural function as defined by Blundell and Powell (2003, 2004). To the best of our knowledge, ours are the first results on average partial and marginal effects for binary choice and ordered choice models with two-way fixed effects and non-logistic errors.
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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 | Chernozhukov, V., I. Fernández-Val, S. Hoderlein, H. Holzmann, and W… (2015) Nonparametric Identification in Panels Using Quantiles | 0.928 | 5 | 3 | 80% |
| 2 | Honoré, B (1992) Trimmed LAD and Least Squares Estimation of Truncated and Censored Regression Models with Fixed Effects | 0.843 | 3 | 3 | 100% |
| 3 | Hoderlein, S. and H. White (2012) Nonparametric Identification in Nonseparable Panel Data Models with Generalized Fixed Effects | 0.811 | 4 | 2 | 100% |
| 4 | Chernozhukov, V., I. Fernández-Val, J. Hahn, and W. K. Newey (2013) Average and Quantile Effects in Nonseparable Panel Models | 0.794 | 14 | 5 | 50% |
| 5 | Botosaru, I., C. Muris, and K. Pendakur (2021) Identification of Time-Varying Transformation Models with Fixed Effects, with an Application to Unobserved Heterogeneity in Reso… self | 0.737 | 3 | 2 | 100% |
| 6 | Blundell, R. W. and J. L. Powell (2003) Endogeneity in Nonparametric and Semiparametric Regression Models | 0.644 | 2 | 2 | 100% |
| 7 | Blundell, R. W. and J. L. Powell (2004) Endogeneity in Semiparametric Binary Response Models | 0.644 | 2 | 2 | 100% |
| 8 | Botosaru, I. and C. Muris (2017) Binarization for Panel Models with Fixed Effects self | 0.644 | 2 | 2 | 100% |
| 9 | Botosaru, I., C. Muris, and S. Sokullu (2022) Partial Effects in Time-Varying Linear Transformation Panel Models with Endogeneity self | 0.644 | 2 | 2 | 100% |
| 10 | Chen, S., S. Khan, and X. Tang (2019) Exclusion Restrictions in Dynamic Binary Choice Panel Data Models: Comment on Semiparametric Binary Choice Panel Data Models Wit… | 0.644 | 2 | 2 | 100% |
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