In regression discontinuity (RD), a running variable (or score) crossing a cutoff determines a treatment that affects the mean-regression function. This paper generalizes this usual one-score mean RD in three ways:Â (i) considering multiple scores, (ii) allowing partial effectsÂ due to each score crossing its own cutoff, not just the full effect with all scores crossing all cutoffs, and (iii) accommodating quantile/mode regressions. This generalization is motivated by (i) many multiple-score RD cases, (ii) the full-effect identification needing the partial effects to be separated, and (iii) informative quantile/mode regression functions. We establish identification for multiple-score RD (MRD), and propose simple estimators that become local difference in differences in case of double scores. We also provide an empirical illustration where partial effects exist.
- difference in differences
- multiple running variables
- partial effect
- regression discontinuity
ASJC Scopus subject areas
- Sociology and Political Science
- Political Science and International Relations