arXiv 13 Jan 2026 · Econometrics
arXiv:2601.08281 · PDF · DOI · OpenAlex · Extracted main text
This paper proposes a novel approach for estimating treatment effects in panel data settings, addressing key limitations of the standard difference-in-differences (DID) approach. The standard approach relies on the parallel trends assumption, implicitly requiring that unobservable factors correlated with treatment assignment be unidimensional, time-invariant, and affect untreated potential outcomes in an additively separable manner. This paper introduces a more flexible framework that allows for multidimensional unobservables and non-additive separability, and provides sufficient conditions for identifying the average treatment effect on the treated. An empirical application to job displacement reveals substantially smaller long-run earnings losses compared to the standard DID approach, demonstrating the framework's ability to account for unobserved heterogeneity that manifests as differential outcome trajectories between treated and control groups.
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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 | Hu and Schennach (2008) Instrumental variable treatment of nonclassical measurement error models | 1.000 | 9 | 3 | 100% |
| 2 | Sant'Anna and Zhao (2020) Doubly robust difference-in-differences estimators | 0.737 | 5 | 2 | 60% |
| 3 | Jacobson, LaLonde and Sullivan (1993) Earnings losses of displaced workers | 0.737 | 3 | 2 | 100% |
| 4 | Freyberger (2018) Non-parametric panel data models with interactive fixed effects | 0.644 | 4 | 1 | 100% |
| 5 | Athey and Imbens (2006) Identification and inference in nonlinear difference-in-differences models | 0.644 | 2 | 2 | 100% |
| 6 | Heckman, Ichimura and Todd (1998) Matching as an econometric evaluation estimator | 0.644 | 2 | 2 | 100% |
| 7 | Jarosch (2023) Searching for job security and the consequences of job loss | 0.585 | 3 | 1 | 100% |
| 8 | Dauth and Eppelsheimer (2020) Preparing the sample of integrated labour market biographies (SIAB) for scientific analysis: a guide | 0.511 | 2 | 2 | 50% |
| 9 | Arellano, Blundell and Bonhomme (2017) Earnings and consumption dynamics: a nonlinear panel data framework | 0.511 | 2 | 1 | 100% |
| 10 | Hu (2017) The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor econo… | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 38 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Event-Study Designs for Discrete Outcomes under Transition Independence | 0.405 | 1 | 1 |
| 2 | MSE-Optimal Difference-in-Differences Estimator | 0.405 | 1 | 1 |