Practical procedures to deal with common support problems in matching estimation
Michael Lechner and
Anthony Strittmatter ()
Econometric Reviews, 2019, vol. 38, issue 2, 193-207
This paper assesses the performance of common estimators adjusting for differences in covariates, such as matching and regression, when faced with the so-called common support problems. It also shows how different procedures suggested in the literature affect the properties of such estimators. Based on an empirical Monte Carlo simulation design, a lack of common support is found to increase the root-mean-squared error of all investigated parametric and semiparametric estimators. Dropping observations that are off support usually improves their performance, although the magnitude of the improvement depends on the particular method used.
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Working Paper: Practical Procedures to Deal with Common Support Problems in Matching Estimation (2017)
Working Paper: Practical Procedures to Deal with Common Support Problems in Matching Estimation (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:taf:emetrv:v:38:y:2019:i:2:p:193-207
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