arXiv 19 Dec 2025 · Econometrics
arXiv:2512.17576 · PDF · DOI · OpenAlex · Extracted main text
Many popular estimation methods in panel data rely on the assumption that the covariates of interest are strictly exogenous. However, this assumption is empirically restrictive in a wide range of settings. In this paper I argue that credible empirical work requires meaningfully relaxing strict exogeneity assumptions. Econometricians have developed methods that allow for sequential exogeneity, which in contrast with strict exogeneity allows for the presence of feedback from past outcomes to future covariates or treatments. I review some of the classic work on linear models with constant coefficients, and then describe some approaches that allow for coefficient heterogeneity in models with feedback. Finally, in the last two parts of the paper I review recent work that allows for sequential exogeneity in nonlinear panel data models, and mention possible extensions to network settings.
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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 | Chamberlain (2022) Feedback in panel data models | 1.000 | 8 | 3 | 100% |
| 2 | Ghanem, Sant'Anna, and Wüthrich (2022) Selection and parallel trends | 0.928 | 4 | 3 | 100% |
| 3 | Alvarez and Arellano (2003) The time series and cross-section asymptotics of dynamic panel data estimators | 0.874 | 8 | 2 | 100% |
| 4 | Bonhomme, Dano, and Graham (2023) Identification in a binary choice panel data model with a predetermined covariate | 0.874 | 7 | 2 | 100% |
| 5 | Arellano and Bond (1991) Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations | 0.874 | 5 | 2 | 100% |
| 6 | Bonhomme (2012) Functional differencing self | 0.874 | 5 | 2 | 100% |
| 7 | Bonhomme, Dano, and Graham (2025) Moment Restrictions for Nonlinear Panel Data Models with Feedback | 0.874 | 5 | 2 | 100% |
| 8 | Arellano (2003) Panel data econometrics | 0.843 | 3 | 3 | 100% |
| 9 | Marx, Tamer, and Tang (2024) Heterogeneous Intertemporal Treatment Effects via Dynamic Panel Data Models | 0.843 | 3 | 3 | 100% |
| 10 | Bonhomme (2025) Unrestricted Heterogeneity in Linear Econometric Models self | 0.811 | 4 | 2 | 100% |
Showing the top 10 of 85 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Causal Graphs for Conditional Parallel Trends | 1.000 | 5 | 3 |
| 2 | Selection and parallel trends | 0.405 | 1 | 1 |
| 3 | Forecasted Treatment Effects with Short Panels | 0.405 | 1 | 1 |
| 4 | Event Studies with Feedback | 0.405 | 1 | 1 |
| 5 | The Projection Solution to the Incidental Parameter Problem | 0.405 | 1 | 1 |
| 6 | Inference for Fixed Effects Estimators when Panels are Unbalanced | 0.405 | 1 | 1 |