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Cited by 391Advanced Causal Inference TechniquesElectoral Systems and Political ParticipationSpatial and Panel Data Analysis

Geographic Boundaries as Regression Discontinuities

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Keele, Luke J., Titiunik, Rocío·2015·Political Analysis
DOI 10.1093/pan/mpu014
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Abstract

Political scientists often turn to natural experiments to draw causal inferences with observational data. Recently, the regression discontinuity design (RD) has become a popular type of natural experiment due to its relatively weak assumptions. We study a special type of regression discontinuity design where the discontinuity in treatment assignment is geographic. In this design, which we call the Geographic Regression Discontinuity (GRD) design, a geographic or administrative boundary splits units into treated and control areas, and analysts make the case that the division into treated and control areas occurs in an as-if random fashion. We show how this design is equivalent to a standard RD with two running variables, but we also clarify several methodological differences that arise in geographical contexts. We also offer a method for estimation of geographically located treatment effects that can also be used to validate the identification assumptions using observable pretreatment characteristics. We illustrate our methodological framework with a re-examination of the effects of political advertisements on voter turnout during a presidential campaign, exploiting the exogenous variation in the volume of presidential ads that is created by media market boundaries.

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  • In a geographic context, position alongside a border matters; two locations with equal distance to a long border are not comparable if they have very different north-south, east-west, or altitude positions along the border.

    “As Keele and Titiunik 90 pointed out, the position alongside a border matters in a geographic context, as two locations with equal distance to a long border are not comparable if they have very different north and south, east and west, or high and low altitude positions along the border.”

    From Health benefits of reduced deforestation in the Brazilian Amazon (2024) · cites this paper as [90]

    Section 4.2, “Naive Distance” (page unavailable), says that equal perpendicular distances can conceal substantial separation along a long border, supporting the claim about position along it. The paper describes location in two dimensions, however, and does not address differences in altitude. (LLM, conf=0.86)

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Cited by

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Authors
Keele, L. J., & Titiunik, R.
Affiliations
  • Pennsylvania State University (US)
  • University of Michigan (US)
Corresponding author
Titiunik, Rocío
ORCID
Venue
Political Analysis
Publisher
Cambridge University Press (CUP)
Published
2015
Volume
23
Issue
1
Pages
127-155
ISSN
  • 1047-1987 (ISSN-L)
  • 1476-4989
DOI
10.1093/pan/mpu014
OpenAlex
W2133561901
Cited by
391
References
3
Citations by year
2026: 41 · 2025: 49 · 2024: 45 · 2023: 29 · 2022: 46 · 2021: 37 · 2020: 24 · 2019: 31 · 2018: 24 · 2017: 26 · 2016: 18 · 2015: 11 · 2014: 8 · 2012: 1
FWCI
21.93
Type
journal article
Language
en
Open access
Licence
www.cambridge.org/core/terms (unspecified, 734 d)
Locations
  • Political Analysis (publishedVersion)
  • SSRN Electronic Journal (submittedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • National Science Foundation (1357561)
  • University of Cambridge
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
Keywords
regression discontinuity design, natural experiment, causal inference, administrative boundaries, treatment effect estimation, identification assumptions, political advertising, voter turnout, presidential campaigns

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