TY  - RPRT
        AU  - Augurzky, Boris
AU  - Kluve, Jochen
        TI  - Assessing the Performance of Matching Algorithms When Selection into Treatment Is Strong
        PY  - 2004/Sep/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 1301
        UR  - https://www.iza.org/publications/dp1301
        AB  - This paper investigates the method of matching regarding two crucial implementation choices, the distance measure and the type of algorithm. We implement optimal full matching – a fully efficient algorithm – and present a framework for statistical inference. The implementation uses data from the NLSY79 to study the effect of college education on earnings. We find that decisions regarding the matching algorithm depend on the structure of the data: In the case of strong selection into treatment and treatment effect heterogeneity a full matching seems preferable. If heterogeneity is weak, pair matching suffices.
        KW  - optimal full matching
KW  - selection into treatment
KW  - matching algorithms
        ER  -