Synthetic Control Method (SCM)

The synthetic control method estimates the effect of an intervention on a single treated unit by constructing a weighted combination of untreated donor units that reproduces the treated unit's pre-intervention outcome path.

합성통제법은 처치 이전 결과 경로를 재현하도록 처치받지 않은 비교단위들을 가중 결합하여 하나의 처치단위에 대한 개입 효과를 추정하는 방법입니다.

How do I estimate the effect of a policy that affected only one region or country?

한 지역이나 국가에만 적용된 정책의 효과는 어떻게 추정하나요?

The synthetic control method builds a counterfactual for one treated unit, such as a state or city, from a weighted average of untreated units chosen to match its outcomes before the intervention, and the post-intervention gap estimates the effect. It fits aggregate panel data with a long pre-intervention period and a pool of comparable untreated units, with inference based on placebo tests.

When to use Synthetic Control Method (SCM)

• One region, country, or organization exposed to a policy or event
• Long series of outcomes before the intervention
• Several untreated units that can serve as donors

When to use something else

• Many treated units: use difference-in-differences or an event study design
• Short pre-intervention period or poor pre-treatment fit: use difference-in-differences with careful trend checks

Assumptions and requirements

• Good pre-intervention fit between treated and synthetic units
• Donor units unaffected by the intervention (no spillovers)
• No other major shocks to the treated unit at the same time
• Treated unit's outcomes within the range spanned by the donors

What the analysis reports

• Donor weights
• Predictor balance between treated and synthetic units
• Treated versus synthetic outcome plot and gap plot
• Pre-intervention RMSPE
• Placebo-in-space tests and permutation p-value

How to report it

Relative to its synthetic control (pre-intervention RMSPE = [value]), [treated unit]'s [outcome] was on average [value] lower after [intervention], with a placebo-based p-value of [value].

Related methods

• Difference-in-Differences
• Synthetic Difference-in-Differences
• Interrupted Time Series

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