29.8 Entropy Balancing

(Hainmueller 2012)

  • Entropy balancing is a method for achieving covariate balance in observational studies with binary treatments.

  • It uses a maximum entropy reweighting scheme to ensure that treatment and control groups are balanced based on sample moments.

  • This method adjusts for inequalities in the covariate distributions, reducing dependence on the model used for estimating treatment effects.

  • Entropy balancing improves balance across all included covariate moments and removes the need for repetitive balance checking and iterative model searching.

References

Hainmueller, Jens. 2012. “Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies.” Political Analysis 20 (1): 25–46.