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Causal Inference The Mixtape - 10 Synthetic Control

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The first appearance of the synthetic control estimator was a 2003 article where it was used to estimate the impact of terrorism on economic activity (Abadie and Gardeazabal 2003). Since that publication, it has become very popular—particularly after the release of an R and Stata package coinciding with Abadie, Diamond, and Hainmueller (2010). A Google Scholar search for the words “synthetic control” and “Abadie” yielded over 3,500 hits at the time of writing. The estimator has been so influential that Athey and Imbens (2017) said it was “arguably the most important innovation in the policy evaluation literature in the last 15 years” (p.3). To understand the reasons you might use synthetic control, let’s back up to the broader idea of the comparative case study. In qualitative case studies, such as Alexis de Tocqueville’s classic Democracy in America, the goal is to reason inductively about the causal effect of events or characteristics of a single unit on some outcome using logic and

10 Synthetic Control – Causal Inference The Mixtape Causal Inference: The Mixtape. Buy the print version today: Buy from Amazon Buy from Yale Press \[ % Define terms \newcommand{\Card}{\text{Card }} \DeclareMathOperator*{\cov}{cov} \DeclareMathOperator*{\var}{var} \DeclareMathOperator{\Var}{Var\,} \DeclareMathOperator{\Cov}{Cov\,} \DeclareMathOperator{\Prob}{Prob} \newcommand{\independent}{\perp \!\!\! \perp} \DeclareMathOperator{\Post}{Post} \DeclareMathOperator{\Pre}{Pre} \DeclareMathOperator{\Mid}{\,\vert\,} \DeclareMa

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Causal Inference The Mixtape - 10 Synthetic Control

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