Onil Boussim
arXiv 18 Jul 2026 · Econometrics
arXiv:2607.16991 · PDF · Extracted main text
This paper develops a synthetic control estimator for compositional outcomes, vectors of shares generated by an underlying categorical process. Derived from a random utility model with interactive fixed effects on relative systematic utilities, the estimator maps compositions to log-odds, where the standard convex hull condition identifies the counterfactual as a convex combination of donor log-odds. Equivalently, it recovers the Fréchet barycenter under the Aitchison metric, the canonical geometry of the simplex (the non-linear space of shares) using a single set of weights across all categories. I also developed a placebo inference procedure based on the Aitchison distance. An application to Pennsylvania's electricity generation mix following the Alternative Energy Portfolio Standard uncovers a large and persistent compositional shift: natural gas exceeds its counterfactual by nearly 60 percentage points by 2022, while renewables lose relative ground.
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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 | Abadie, Alberto and Diamond, Alexis and Hainmueller, Jens (2010) Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program | 1.000 | 5 | 4 | 100% |
| 2 | Sun, Liyang and Ben-Michael, Eli and Feller, Avi (2025) Using multiple outcomes to improve the synthetic control method | 0.961 | 9 | 4 | 89% |
| 3 | Aitchison, John (1982) The statistical analysis of compositional data | 0.843 | 3 | 3 | 100% |
| 4 | Chernozhukov, Victor and Wüthrich, Kaspar and Yinchu Zhu (2018) Exact and robust conformal inference methods for predictive machine learning with dependent data | 0.843 | 3 | 3 | 100% |
| 5 | Egozcue, Juan José and Pawlowsky-Glahn, Vera and Mateu-Figueras, Glò… (2003) Isometric logratio transformations for compositional data analysis | 0.644 | 2 | 2 | 100% |
| 6 | Abadie, Alberto and Gardeazabal, Javier (2003) The economic costs of conflict: A case study of the Basque Country | 0.511 | 2 | 1 | 100% |
| 7 | Tian, Wei and Lee, Seojeong and Panchenko, Valentyn (2023) Synthetic controls with multiple outcomes: Estimating the effects of non-pharmaceutical interventions in the COVID-19 pandemic | 0.511 | 2 | 1 | 100% |
| 8 | Abadie, A and L'Hour, J (2017) A penalized synthetic control estimator for disaggregated data | 0.405 | 1 | 1 | 100% |
| 9 | Athey, Susan and Bayati, Mohsen and Doudchenko, Nikolay and Imbens,… (2018) Matrix completion methods for causal panel data models | 0.405 | 1 | 1 | 100% |
| 10 | Doudchenko, Nikolay and Imbens, Guido W (2016) Balancing, regression, difference-in-differences and synthetic control methods: A synthesis | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 16 scored citations.