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Entropy Balancing×Diferència en Diferències (Diff-in-Diff)×
CampInferència causalEconometria
FamíliaRegression modelRegression model
Any d'origen20121994
Autor originalJens HainmuellerCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipusPreprocessing / reweighting estimatorCausal inference / panel regression
Font seminalHainmueller, J. (2012). Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies. Political Analysis, 20(1), 25-46. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
ÀliesEntropy Balancing, EB Weighting, Maximum-Entropy Reweighting, Hainmueller Balancingdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Relacionats45
ResumEntropy balancing is a maximum-entropy reweighting method that assigns weights to control-group units so that their weighted covariate moments exactly match those of the treated group. Introduced by Hainmueller (2012), it provides exact balance on specified moments without iterative propensity-score trimming, making it a powerful preprocessing tool for causal policy evaluation in observational studies.Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.
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ScholarGateCompara mètodes: Policy Evaluation Entropy Balancing · Difference-in-Differences. Recuperat el 2026-06-15 de https://scholargate.app/ca/compare