William Torous, Florian Gunsilius, Philippe Rigollet
arXiv 12 Aug 2021 · Statistics — Methodology · publishedJournal of Causal Inference (2024) · 8 citations (OpenAlex)
arXiv:2108.05858 · PDF · DOI · OpenAlex · Extracted main text
We propose a nonlinear difference-in-differences method to estimate multivariate counterfactual distributions in classical treatment and control study designs with observational data. Our approach sheds a new light on existing approaches like the changes-in-changes and the classical semiparametric difference-in-differences estimator and generalizes them to settings with multivariate heterogeneity in the outcomes. The main benefit of this extension is that it allows for arbitrary dependence and heterogeneity in the joint outcomes. We demonstrate its utility both on synthetic and real data. In particular, we revisit the classical Card & Krueger dataset, examining the effect of a minimum wage increase on employment in fast food restaurants; a reanalysis with our method reveals that restaurants tend to substitute full-time with part-time labor after a minimum wage increase at a faster pace. A previous version of this work was entitled "An optimal transport approach to causal inference.
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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 | Susan Athey and Guido W Imbens (2006) Identification and inference in nonlinear difference-in-differences models | 1.000 | 16 | 4 | 100% |
| 2 | David Card and Alan B Krueger (1994) Minimum wages and employment: A case study of the fast-food industry in New Jersey and Pennsylvania | 0.737 | 3 | 2 | 100% |
| 3 | David Neumark and William Wascher (2000) Minimum wages and employment: A case study of the fast-food industry in New jersey and Pennsylvania: Comment | 0.693 | 5 | 1 | 100% |
| 4 | Alberto Abadie (2005) Semiparametric difference-in-differences estimators | 0.644 | 4 | 1 | 100% |
| 5 | Jonathan Roth and Pedro HC Sant'Anna (2020) When is parallel trends sensitive to functional form? | 0.644 | 2 | 2 | 100% |
| 6 | Tudor Manole and Jonathan Niles-Weed (2021) Sharp Convergence Rates for Empirical Optimal Transport with Smooth Costs | 0.511 | 2 | 2 | 50% |
| 7 | Gabriel Peyré and Marco Cuturi (2019) Computational optimal transport | 0.511 | 2 | 2 | 50% |
| 8 | Ralph Tyrell Rockafellar (1997) Convex analysis | 0.511 | 2 | 2 | 50% |
| 9 | Yann Brenier (1991) Polar factorization and monotone rearrangement of vector-valued functions | 0.511 | 2 | 1 | 100% |
| 10 | Victor Chernozhukov, Alfred Galichon, Marc Henry, and Brendan Pass (2021) Identification of hedonic equilibrium and nonseparable simultaneous equations | 0.511 | 2 | 1 | 100% |
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arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.