arXiv 20 Jun 2026 · Econometrics
arXiv:2606.22035 · PDF · DOI · OpenAlex · Extracted main text
This paper introduces statistical inference procedures for unit-specific coefficients in panel data models, where the coefficients exhibit a latent group structure. The proposed methods achieve efficiency gains by clustering units into a small number of groups, while explicitly accounting for the statistical uncertainty of group assignments. The core idea is to integrate standard inference procedures, such as the $t$-test and Wald tests, with confidence sets for group membership. Two methods are proposed: the first takes the minimum of the test statistics over the confidence set for group membership, and the second corrects for bias caused by possible group misassignment. The former can produce shorter but possibly disconnected sets, while the latter guarantees connected, interpretable intervals at some cost in length. We also develop standard errors that are adjusted for possible group misassignment and valid even with short time periods, which may be of independent interest. Monte Carlo simulations demonstrate that our approach yields narrower confidence sets for units with relatively large error variances than unit-by-unit time-series methods. In contrast, ignoring statistical uncertainty in the group membership estimation leads to distortions in size and coverage. We illustrate the method with an empirical example that estimates the effect of the minimum wage in each U.S. state.
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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 | Su, Liangjun and Shi, Zhentao and Phillips, Peter C. B (2016) Identifying Latent Structures in Panel Data | 1.000 | 7 | 5 | 100% |
| 2 | Andreas Dzemski and Ryo Okui (2021) Convergence rate of estimators of clustered panel models with misclassification self | 1.000 | 6 | 4 | 100% |
| 3 | Bonhomme, Stéphane and Manresa, Elena (2015) Grouped patterns of heterogeneity in panel data | 0.965 | 10 | 4 | 90% |
| 4 | Mehrabani, Ali (2023) Estimation and identification of latent group structures in panel data | 0.928 | 4 | 4 | 100% |
| 5 | Dzemski, Andreas and Okui, Ryo (2024) Confidence set for group membership self | 0.909 | 20 | 8 | 75% |
| 6 | Wuyi Wang and Peter C. B. Phillips and Liangjun Su (2018) Homogeneity pursuit in panel data models: theory and applications | 0.843 | 3 | 3 | 100% |
| 7 | Dube, Arindrajit and Lester, T. William and Reich, Michael (2010) Minimum wage effects across state borders: Estimates using contiguous counties | 0.737 | 3 | 2 | 100% |
| 8 | Wuyi Wang and Peter C. B. Phillips and Liangjun Su (2019) The heterogeneous effects of the minimum wage on employment across states | 0.737 | 3 | 2 | 100% |
| 9 | Berger, Roger L. and Boos, Dennis D (1994) P Values Maximized Over a Confidence Set for the Nuisance Parameter | 0.644 | 2 | 2 | 100% |
| 10 | Dufour, Jean-Marie (1990) Exact Tests and Confidence Sets in Linear Regressions with Autocorrelated Errors | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 41 scored citations.