Research

Radius Matching on the Propensity Score with Bias Adjustment: Tuning Parameters and Finite Sample Behaviour

Martin Huber, Michael Lechner and Andreas Steinmayr

Empirical Economics, 2015, 49(1): 1–31

Article

Abstract

Using a simulation design that is based on empirical data, a recent study by Huber et al. (J Econom 175:1–21, 2013) finds that distance-weighted radius matching with bias adjustment as proposed in Lechner et al. (J Eur Econ Assoc 9:742–784, 2011) is competitive among a broad range of propensity score-based estimators used to correct for mean differences due to observable covariates. In this companion paper, we further investigate the finite sample behaviour of radius matching with respect to various tuning parameters. The results are intended to help the practitioner to choose suitable values of these parameters when using this method, which has been implemented in the software packages GAUSS, STATA and R.

Cite (BibTeX)
@article{Huber2015radius,
  author      = {Huber, Martin and Lechner, Michael and Steinmayr, Andreas},
  title       = {{Radius Matching on the Propensity Score with Bias Adjustment: Tuning Parameters and Finite Sample Behaviour}},
  journal     = {Empirical Economics},
  year        = {2015},
  volume      = {49},
  number      = {1},
  pages       = {1--31},
  doi         = {10.1007/s00181-014-0847-1}
}

All publications as BibTeX

Earlier versions

  • University of St. Gallen Economics Discussion Paper (2012), "Radius Matching on the Propensity Score with Bias Adjustment: Finite Sample Behaviour, Tuning Parameters and Software Implementation"

Software

  • radiusmatch — Stata module to perform distance-weighted radius matching with bias adjustment.