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Policy Evaluation Entropy Balancing

Entropy 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.

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Sources

  1. Hainmueller, 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: 10.1093/pan/mpr025 ↗
  2. Zhao, Q., & Cooney, D. (2017). Entropy Balancing is Doubly Robust. Journal of Causal Inference, 5(1). DOI: 10.1515/jci-2016-0010 ↗

Related methods

Difference-in-DifferencesInverse Probability WeightingPropensity Score MatchingSynthetic Control Method

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ScholarGate — Policy Evaluation Entropy Balancing (Entropy Balancing for Causal Policy Evaluation). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/policy-evaluation-entropy-balancing