Detecting selection bias, using propensity score matching, and estimating treatment effects: an application to the private returns to a master’s degree

Abstract

Most research in the area of higher education is plagued by the problem of endogeneity or self-selection bias. Unlike ordinary least squares (OLS) regression, propensity score matching addresses the issue of self-selection bias and allows for a decomposition of treatment effects on outcomes. Using panel data from a national survey of bachelor’s degree recipients, this approach is illustrated via an analysis of the effect of receiving a master’s degree, in various program areas, on wage earning outcomes. The results of this study reveal that substantial self-selection bias is undetected when using OLS regression techniques. This article also shows that, unlike OLS regression, propensity score matching allows for estimates of the average treatment effect, average treatment on the treated effect, and the average treatment on the untreated effect on student outcomes such as wage earnings.