Regression-Discontinuity Analysis

The regression discontinuity (RD) data design is a quasi-experimental evaluation design first introduced by Thistlethwaite and Campbell (1960) as an alternative approach to evaluating social programmes. The design is characterized by a treatment assignment or selection rule which involves the use of a known cut-off point with respect to a continuous variable, generating a discontinuity in the probability of treatment receipt at that point. Under certain comparability conditions, a comparison of average outcomes for observations just left and right of the cut-off can be used to estimate a meaningful causal impact. While interest in the design had previously been mainly limited to evaluation research methodologists (Cook and Campbell, 1979; Trochim, 1984), the design is currently experiencing a renaissance among econometricians and empirical economists (Hahn, Todd and van der Klaauw, 1999; 2001; Angrist and Krueger, 1999; Porter, 2003). Among the main econometric contributions have been the formal derivation of identification conditions for causal inference and the introduction of semiparametric estimation procedures for the design. At the same time, a large and rapidly growing number of empirical applications are providing new insights into the applicability of the design, which have led to the development of several sensitivity and validity tests.