A Primer for Applying Propensity-Score Matching

The use of microeconometric techniques to estimate the effects of development policies has become a common approach not only for scholars, but also for policy-makers engaged in designing, implementing and evaluating projects in different fields. Among these techniques, Propensity-Score Matching (PSM) is increasingly applied in the policy evaluation community. This technical note provides a guide to the key aspects of implementing PSM methodology for an audience of practitioners interested in understanding its applicability to specific evaluation problems. The note summarizes the basic conditions under which PSM can be used to estimate the impact of a program and the data required. It explains how the Conditional Independence Assumption, combined with the Overlap Condition, reduces selection bias when participation in a program is determined by observable characteristics. It also describes different matching algorithms and some tests to assess the quality of the matching. Case studies are used throughout to illustrate important concepts in impact evaluation and PSM. In the annexes, the note provides an outline of the main technical aspects and a list of statistical and econometric software for implementing PSM.