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Regression modelQuasi-experimental / causal inference

Panel Data Entropy Balancing

Panel data entropy balancing extends Hainmueller's (2012) entropy balancing method to longitudinal settings. It computes unit-level weights for control observations so that their covariate moments exactly match those of the treatment group across panel periods, then plugs these weights into a weighted panel regression to estimate causal treatment effects without requiring a correctly specified propensity score model.

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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. (2019). Covariate balancing propensity score by tailored loss functions. Annals of Statistics, 47(2), 965-993. DOI: 10.1214/18-AOS1698 ↗

Related methods

Entropy BalancingPanel Data Difference-in-DifferencesPanel Data Inverse Probability WeightingPanel Data Propensity Score MatchingPanel Fixed Effects

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ScholarGate — Panel Data Entropy Balancing (Entropy Balancing for Panel Data). Retrieved 2026-06-04 from https://scholargate.app/tr/causal-inference/panel-data-entropy-balancing