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Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

Diferencë-në-diferencë (DiD) e përmirësuar me mësimin makinor (ML-DiD)×Metoda e Kontrollit Sintetik (SCM)×
FushaInferenca kauzaleInferenca kauzale
FamiljaRegression modelRegression model
Viti i origjinës2018-20202003–2010
KrijuesiChernozhukov et al. (double/debiased ML framework); Sant'Anna & Zhao (2020) for DR-DiDAlberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
LlojiCausal inference / semiparametricQuasi-experimental causal inference
Burimi themeluesChernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C., Newey, W., & Robins, J. (2018). Double/debiased machine learning for treatment and structural parameters. The Econometrics Journal, 21(1), C1-C68. DOI ↗Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505. DOI ↗
Emërtime të tjeraML-DiD, double/debiased ML DiD, DML difference-in-differences, augmented DiDSCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Të lidhura64
PërmbledhjaMachine learning-augmented DiD combines the classic difference-in-differences identification strategy with flexible ML estimators for nuisance functions — the propensity score and the outcome regression — to obtain valid causal estimates even when treatment selection and outcome dynamics are complex, high-dimensional, or nonlinear. The approach, rooted in double/debiased machine learning (Chernozhukov et al., 2018) and doubly-robust DiD (Sant'Anna & Zhao, 2020), guards against misspecification bias while preserving the core DiD logic of before-after, treated-versus-control comparisons.The Synthetic Control Method estimates the causal effect of a treatment or policy on a single treated unit by constructing a weighted combination of untreated units — the synthetic control — that closely resembles the treated unit before the intervention. The gap between the treated unit and its synthetic counterpart after the intervention is the estimated treatment effect.
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  2. 2 Burimet
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  1. v1
  2. 2 Burimet
  3. PUBLISHED

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ScholarGateKrahasoni metodat: Machine learning-augmented difference-in-differences · Synthetic Control Method. Marrë më 2026-06-15 nga https://scholargate.app/sq/compare