Geographic Boundaries as Regression Discontinuities

By Luke Keele, R. Titiunik. Political Analysis, 2015

379 citations recorded by the source corpus.

Subfields: Education, Political Science and International Relations, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/5512e7591e86963e89a39984e770b0656fa2b0e2

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Citations in the corpus

Regression Discontinuity Designs Based on Population Thresholds: Pitfalls and Solutions (2015, background): “Our main contribution here is to show conclusive evidence of manipulative sorting in official population numbers in 1See Keele and Titiunik (2015) for a discussion of compound treatment in RDDs based on geographical boundaries.”
Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs (2018, methodology): “We also discuss extensions to fuzzy, geographic, multi-score, and multi-cutoff RD designs (Hahn, Todd and van der Klaauw, 2001; Papay, Willett and Murnane, 2011; Keele and Titiunik, 2015; Cattaneo, Keele, Titiunik and Vazquez-Bare, 2016), as well as to”
Inference in Regression Discontinuity Designs under Local Randomization (2016, methodology): “An alternative approach to analyzing RD designs relies on the idea of local randomization, which postulates that treatment assignment may be regarded as (or at least approximated by) a known randomization mechanism near the RD cutoff (Lee 2008). In other words, in this approach, the units closest to”
Randomization Inference in the Regression Discontinuity Design: An Application to Party Advantages in the U.S. Senate (2015, background): “, Keele and Titiunik [36] and references therein).”
Interpreting Regression Discontinuity Designs with Multiple Cutoffs (2016, background): “Cattaneo, Vazquez-Bare, Keele and Titiunik (2016) investigate different approaches in a multi-cutoff RD design to achieve identification of E[Y1i − Y0i|Xi = x] for values of x ∈ C under substantially weaker conditions than Assumption 5.”
Econometric Methods for Program Evaluation (2018, background): “Multi-Score and Geographic RD designs are settings where the treatment assignment rule depends on more than one score variable (see Papay et al., 2011; Keele and Titiunik, 2015).”