An Assessment of Propensity Score Matching as a Nonexperimental Impact Estimator
利用墨西哥PROGRESA项目的社会实验数据，检验倾向得分匹配在非实验环境下的可靠性，发现该方法在结果测量一致且控制变量丰富时表现良好，但测量差异会导致偏差。
Not all policy questions can be addressed by social experiments. Nonexperimental evaluation methods provide an alternative to experimental designs but their results depend on untestable assumptions. This paper presents evidence on the reliability of propensity score matching (PSM), which estimates treatment effects under the assumption of selection on observables, using a social experiment designed to evaluate the PROGRESA program in Mexico. We find that PSM performs well for outcomes that are measured comparably across survey instruments and when a rich set of control variables is available. However, even small differences in the way outcomes are measured can lead to bias in the technique.