Statistics and Computing

, Volume 15, Issue 3, pp 197–215

Matching estimators and optimal bandwidth choice

Article

DOI: 10.1007/s11222-005-1309-6

Cite this article as:
Frölich, M. Stat Comput (2005) 15: 197. doi:10.1007/s11222-005-1309-6

Abstract

Optimal bandwidth choice for matching estimators and their finite sample properties are examined. An approximation to their MSE is derived, as a basis for a plug-in bandwidth selector. In small samples, this approximation is not very accurate, though. Alternatively, conventional cross-validation bandwidth selection is considered and performs rather well in simulation studies: Compared to standard pair-matching, kernel and ridge matching achieve reductions in MSE of about 25 to 40%. Local linear matching and weighting perform poorly. Furthermore, the scope for developing better bandwidth selectors seems to be limited for ridge matching, but non-negligible for kernel and local linear matching.

Keywords

covariate adjustment nonparametric regression propensity score missing data counterfactual treatment effect 

Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  1. 1.University College London and University of St. GallenSt. GallenSwitzerland
  2. 2.Institute for the Study of Labor (IZA)Bonn