arXiv 8 Jun 2026 · Econometrics
arXiv:2606.09625 · PDF · DOI · OpenAlex · Extracted main text
This paper proposes a synthetic control (SC) framework for the estimation of conditional distributional treatment effects. Identification rests on a parallel trends condition formulated in the parameter space of the semiparametric distribution regression (DR) model, which keeps the counterfactual conditional distribution within the model class. The weights solve a least-squares problem subject to an adding-up constraint, yielding a closed-form estimator. We derive the asymptotic distribution of the counterfactual estimator, with DR estimation error and weight estimation error contributing at the same rate to the asymptotic variance. Moreover, we propose a supremum test for the null of no treatment effect, whose limit is the supremum of a Gaussian process. Simulations illustrate that conditioning on covariates can reveal effects being difficult to detect from the unconditional distribution alone. An application to the 1992 New Jersey minimum wage increase using CPS data finds effects concentrated in the minimum-wage corridor for low-education, low-experience workers.
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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., Fernández-Val, I., and Melly, B (2013) Inference on counterfactual distributions | 0.928 | 5 | 4 | 80% |
| 2 | Autor, D. H., Manning, A., and Smith, C. L (2016) The contribution of the minimum wage to US wage inequality over three decades: A reassessment | 0.737 | 3 | 2 | 100% |
| 3 | Abadie, A (2021) Using synthetic controls: Feasibility, data requirements, and methodological aspects | 0.644 | 2 | 2 | 100% |
| 4 | Ben-Michael, E., Feller, A., and Rothstein, J (2021) The augmented synthetic control method | 0.644 | 2 | 2 | 100% |
| 5 | Doudchenko, N. and Imbens, G. W (2016) Balancing, regression, difference-in-differences and synthetic control methods: A synthesis | 0.644 | 2 | 2 | 100% |
| 6 | Gunsilius, F. F (2023) Distributional synthetic controls | 0.644 | 2 | 2 | 100% |
| 7 | Wied, D (2024) Semiparametric distribution regression with instruments and monotonicity self | 0.644 | 2 | 2 | 100% |
| 8 | Abadie, A., Diamond, A., and Hainmueller, J (2010) Synthetic control methods for comparative case studies: Estimating the effect of California's tobacco control program | 0.511 | 2 | 1 | 100% |
| 9 | Card, D. and Krueger, A. B (1994) Minimum wages and employment: A case study of the fast-food industry in new jersey and pennsylvania | 0.511 | 2 | 1 | 100% |
| 10 | Abadie, A. and Gardeazabal, J (2003) The economic costs of conflict: A case study of the Basque country | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 37 scored citations.