Abstract
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.
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Van Der Klaauw, W. (2010). Regression-Discontinuity Analysis. In: Durlauf, S.N., Blume, L.E. (eds) Microeconometrics. The New Palgrave Economics Collection. Palgrave Macmillan, London. https://doi.org/10.1057/9780230280816_26
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DOI: https://doi.org/10.1057/9780230280816_26
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