TY  - RPRT
        AU  - Lechner, Michael
AU  - Strittmatter, Anthony
        TI  - Practical Procedures to Deal with Common Support Problems in Matching Estimation
        PY  - 2017/Jan/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 10532
        UR  - https://www.iza.org/publications/dp10532
        AB  - This paper assesses the performance of common estimators adjusting for differences in covariates, such as matching and regression, when faced with 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 (RMSE) 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.
        KW  - common support
KW  - regression
KW  - matching estimation
KW  - Empirical Monte Carlo Study
KW  - outlier
KW  - small sample performance
        ER  -