Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies

@inproceedings{Hainmueller2012EntropyBF,
  title={Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies},
  author={Jens Hainmueller},
  year={2012}
}
This paper proposes entropy balancing, a data preprocessing method to achieve covariate balance in observational studies with binary treatments. Entropy balancing relies on a maximum entropy reweighting scheme that calibrates unit weights so that the reweighted treatment and control group satisfy a potentially large set of prespecified balance conditions that incorporate information about known sample moments. Entropy balancing thereby exactly adjusts inequalities in representation with respect… CONTINUE READING

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Alternative balance metrics for bias reduction in matching methods for causal inference

  • J. 35634–72. Sekhon
  • Unpublished manuscript, Department of of…
  • 2006
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