Balancing, regression, difference-in-differences and synthetic control methods¶
Doudchenko, N., & Imbens, G. (2016). Balancing, regression, difference-in-differences and synthetic control methods: A synthesis. NBER Working Paper 22791.
Cited by¶
1 citation across 1 artifact.
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Primes¶
- Blocking (In Experimental Design)
- T1 — Known-heterogeneity benefit versus design-constraint cost. Blocking pays off to the extent that the blocking variable is correlated with outcomes; when correlation is strong, blocking can cut required sample size by 20–50%
This sourceSynthesizes balancing/weighting and pre-treatment-outcome matching methods, formalizing how correlation between covariates/blocking variables and outcomes drives precision gains.
- T1 — Known-heterogeneity benefit versus design-constraint cost. Blocking pays off to the extent that the blocking variable is correlated with outcomes; when correlation is strong, blocking can cut required sample size by 20–50%
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