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ValdkondÖkonomeetriaÖkonomeetria
PerekondRegression modelRegression model
Tekkeaasta20212005
LoojaArkhangelsky, Athey, Hirshberg, Imbens, and WagerOscar Jorda
TüüpTreatment-effect estimationMulti-horizon regression
AlgallikasArkhangelsky, D., Athey, S., Hirshberg, D. A., Imbens, G. W., & Wager, S. (2021). Synthetic difference-in-differences. American Economic Review, 111(12), 4088-4118. DOI ↗Jorda, O. (2005). Estimation and inference of impulse responses by local projections. American Economic Review, 95(1), 161-182. DOI ↗
RööpnimetusedSynthetic DID, SDIDLP-IR, Multi-horizon regression
Seotud33
KokkuvõteSynthetic Difference-in-Differences (SDID) combines synthetic control and difference-in-differences approaches to estimate treatment effects when a policy or intervention affects one unit (country, firm) at a point in time. Introduced by Arkhangelsky et al. (2021), it improves upon both methods alone by using weighted combinations of controls to match treated units' pre-treatment trends and levels. This yields more precise and robust estimates than classical DiD or synthetic control.Local Projections (LP) is a semi-parametric method for estimating impulse responses directly via multi-horizon regressions, bypassing VAR-model specification. Introduced by Jorda (2005), it projects outcomes h periods ahead onto current shocks and lags, producing impulse-response functions without assuming a particular lag structure or VAR order. This flexibility has made it the dominant approach in applied macroeconomics for measuring policy effects and shock transmission.
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ScholarGateVõrdle meetodeid: Synthetic Difference-in-Differences · Local Projections. Loetud 2026-06-17 aadressilt https://scholargate.app/et/compare