Regression modelQuasi-experimental / causal inference

Bayesian Matching Estimator

The Bayesian Matching Estimator estimates average treatment effects in observational studies by combining classical nearest-neighbour or kernel matching with a Bayesian posterior over the treatment effect. It inherits matching's covariate-balancing logic while propagating uncertainty through a full posterior distribution rather than relying on asymptotic standard errors, yielding credible intervals that reflect both sampling variability and prior knowledge.

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Sources

  1. Rubin, D. B. (1978). Bayesian inference for causal effects: The role of randomization. The Annals of Statistics, 6(1), 34-58. DOI: 10.1214/aos/1176344064
  2. Heckman, J. J., Ichimura, H., & Todd, P. (1998). Matching as an econometric evaluation estimator. Review of Economic Studies, 65(2), 261-294. DOI: 10.1111/1467-937X.00044

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Referenced by

ScholarGateBayesian Matching Estimator (Bayesian Matching Estimator for Average Treatment Effects). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/bayesian-matching-estimator