Ensuring Stability, Accuracy and Meaningfulness in Synthetic Control Methods: The Regularized SHAP-Distance Method

The synthetic control method (SCM) has been increasingly adopted to evaluate causal effects under quasi-experimental designs. However, SCM suffers from sound weaknesses that compromise its accuracy, stability and meaningfulness. The SHAP-distance synthetic control method (SD-SCM) is proposed as solu...

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Bibliographic Details
Published inIDEAS Working Paper Series from RePEc
Main Authors Albalate, Daniel, Bel, Germà, Mazaira-Font, Ferran A
Format Paper
LanguageEnglish
Published St. Louis Federal Reserve Bank of St. Louis 01.01.2020
Subjects
Accuracy
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Summary:The synthetic control method (SCM) has been increasingly adopted to evaluate causal effects under quasi-experimental designs. However, SCM suffers from sound weaknesses that compromise its accuracy, stability and meaningfulness. The SHAP-distance synthetic control method (SD-SCM) is proposed as solution. We evaluate the economic effect of the government formation deadlock in Spain, 2016. The deadlock did not negatively affect economic growth, as the economy grew 1.59% more without full government; standard SCM method overestimates the effect by 0.23 pp. We show that SD-SCM offers higher accuracy and stability, while ensuring the economic meaningfulness of covariates used in building the counterfactual.