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<p>Geographic Regression Discontinuity Designs (GRDDs) are used to estimate long-run historical effects, despite well-established results showing that RDD requires a discontinuous assignment rule rather than merely plausibly exogenous spatial variation. This article evaluates Henn et al.’s (Comparative Political Studies. 10.1177/00104140251369335, 2025) study in <i>Comparative Political Studies,</i> which treats Catholic diocesan boundaries as quasi-random cutoffs. Archival church records indicate that these boundaries were endogenous to colonial infrastructure, disease ecology, settler geography, and ecclesiastical administration. Spatial-econometric simulations demonstrate that standard GRDD specifications produce statistically significant effects in 64–71% of placebo tests when no true effect exists. The implication is methodological rather than case-specific: designs lacking discontinuous assignment can transform spatial noise into apparent causal effects.</p>

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The Devil is in the Geography: the Persistent Misuse of Geographic Regression Discontinuity Design (GRDD) in Political Science

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  • 出版模式：

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  • 发表日期：

    2026年3月13日

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  • Dwayne Woods

摘要

Geographic Regression Discontinuity Designs (GRDDs) are used to estimate long-run historical effects, despite well-established results showing that RDD requires a discontinuous assignment rule rather than merely plausibly exogenous spatial variation. This article evaluates Henn et al.’s (Comparative Political Studies. 10.1177/00104140251369335, 2025) study in Comparative Political Studies, which treats Catholic diocesan boundaries as quasi-random cutoffs. Archival church records indicate that these boundaries were endogenous to colonial infrastructure, disease ecology, settler geography, and ecclesiastical administration. Spatial-econometric simulations demonstrate that standard GRDD specifications produce statistically significant effects in 64–71% of placebo tests when no true effect exists. The implication is methodological rather than case-specific: designs lacking discontinuous assignment can transform spatial noise into apparent causal effects.