Regression Discontinuity with Multiple Running Variables Allowing Partial Effects

Jin Young Choi, Myoung Jae Lee

    Research output: Contribution to journalArticlepeer-review

    11 Citations (Scopus)

    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 languageEnglish
    Pages (from-to)258-274
    Number of pages17
    JournalPolitical Analysis
    Volume26
    Issue number3
    DOIs
    Publication statusPublished - 2018 Jul 1

    Bibliographical note

    Publisher Copyright:
    Copyright © The Author(s) 2018. Published by Cambridge University Press on behalf of the Society for Political Methodology.Â.

    Keywords

    • difference in differences
    • multiple running variables
    • partial effect
    • regression discontinuity

    ASJC Scopus subject areas

    • Sociology and Political Science
    • Political Science and International Relations

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