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Penilaian Polisi Pengimbangan Entropi×Perbezaan-dalam-Perbezaan (Diff-in-Diff)×
BidangInferens KausalEkonometrik
KeluargaRegression modelRegression model
Tahun asal20121994
PengasasJens HainmuellerCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
JenisPreprocessing / reweighting estimatorCausal inference / panel regression
Sumber perintisHainmueller, 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
AliasEntropy Balancing, EB Weighting, Maximum-Entropy Reweighting, Hainmueller Balancingdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Berkaitan45
RingkasanEntropy 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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ScholarGateBandingkan kaedah: Policy Evaluation Entropy Balancing · Difference-in-Differences. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare