Abstract
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: (i) considering multiple scores, (ii) allowing partial effects 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.
Original language | English |
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Pages (from-to) | 258-274 |
Number of pages | 17 |
Journal | Political Analysis |
Volume | 26 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Jul 2018 |
Externally published | Yes |
Keywords
- difference in differences
- multiple running variables
- partial effect
- regression discontinuity
ASJC Scopus subject areas
- Sociology and Political Science
- Political Science and International Relations