Tactics for design and inference in synthetic control studies: An applied example using high-dimensional data

Alex Hollingsworth () and Coady Wing

No fc9xt, SocArXiv from Center for Open Science

Abstract: We describe identification assumptions underlying synthetic control studies and offer recommendations for key---and normally ad hoc---implementation decisions, focusing on model selection; model fit; cross-validation; and decision rules for inference. We outline how to implement a Synthetic Control Using Lasso (SCUL). The method---available as an R package---allows for a high-dimensional donor pool; automates model selection; includes donors from a wide range of variable types; and permits both extrapolation and negative weights. In an application, we employ our recommendations and the SCUL strategy to estimate how recreational marijuana legalization affects sales of alcohol and over-the-counter painkillers, finding reductions in alcohol sales.

Date: 2020-05-03
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:fc9xt

DOI: 10.31219/osf.io/fc9xt

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