Stéphane Bonhomme, Kevin Dano, Bryan S. Graham
arXiv 13 Jan 2023 · Econometrics · publishedSERIEs (2023) · 6 citations (OpenAlex)
arXiv:2301.05733 · PDF · DOI · OpenAlex · Extracted main text
We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a covariate sequentially exogenous conditional on lagged outcomes and covariates). The choice model is indexed by a scalar parameter $\theta$, whereas the distribution of unit-specific heterogeneity, as well as the feedback process that maps lagged outcomes into future covariate realizations, are left unrestricted. We provide a simple condition under which $\theta$ is never point-identified, no matter the number of time periods available. This condition is satisfied in most models, including the logit one. We also characterize the identified set of $\theta$ and show how to compute it using linear programming techniques. While $\theta$ is not generally point-identified, its identified set is informative in the examples we analyze numerically, suggesting that meaningful learning about $\theta$ may be possible even in short panels with feedback. As a complement, we report calculations of identified sets for an average partial effect, and find informative sets in this case as well.
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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 | Honoré, B. E. and Tamer, E (2006) Bounds on parameters in panel dynamic discrete choice models | 0.874 | 8 | 2 | 100% |
| 2 | Chamberlain, G (1993) Feedback in panel data models | 0.843 | 3 | 3 | 100% |
| 3 | Andersen, E. B (1970) Asymptotic properties of conditional maximum-likelihood estimators | 0.843 | 3 | 3 | 100% |
| 4 | Chamberlain, G (1985) Heterogeneity, duration dependence and omitted variable bias | 0.843 | 3 | 3 | 100% |
| 5 | Rasch, G (1960) Studies in mathematical psychology: I. Probabilistic models for some intelligence and attainment tests | 0.843 | 3 | 3 | 100% |
| 6 | Bekker, P. and Wansbeek, T (2001) Identification in parametric models | 0.737 | 4 | 3 | 50% |
| 7 | Al-Sadoon, M. M., Li, T., and Pesaran, H (2017) Exponential class of dynamic binary choice panel data models with fixed effects | 0.644 | 2 | 2 | 100% |
| 8 | Bonhomme, S., Dano, K., and Graham, B (2022) Sequential moment restrictions in nonlinear panel data models self | 0.644 | 2 | 2 | 100% |
| 9 | Chamberlain, G (2022) Feedback in panel data models | 0.644 | 2 | 2 | 100% |
| 10 | Honoré, B. E. and Kyriazidou, E (2000) Panel data discrete choice models with lagged dependent variables | 0.644 | 2 | 2 | 100% |
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