Sun, Liyang;
Ben-Michael, Eli;
Feller, Avi;
(2025)
Using Multiple Outcomes to Improve the Synthetic Control Method.
Review of Economics and Statistics
(In press).
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Abstract
When there are multiple outcome series of interest, Synthetic Control analyses typically proceed by estimating separate weights for each outcome. In this paper, we instead propose estimating a common set of weights across outcomes, by balancing either a vector of all outcomes or an index or average of them. Under a low-rank factor model, we show that these approaches lead to lower bias bounds than separate weights, and that averaging leads to further gains when the number of outcomes grows. We illustrate this via a re-analysis of the impact of the Flint water crisis on educational outcomes.
| Type: | Article |
|---|---|
| Title: | Using Multiple Outcomes to Improve the Synthetic Control Method |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | linear factor model, synthetic control method, panel data |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10205560 |
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