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Spatial Regression Discontinuity Design/Evidence
Method evidence record

Spatial Regression Discontinuity Design

Spatial Regression Discontinuity Design uses a geographic or administrative boundary as the threshold that assigns units to treatment. Observations just inside one side of the boundary are compared with those just outside it, exploiting the near-random variation in treatment status near the cutoff to recover a local causal effect. The approach is widely used in economics, political science, and public health when policies or institutions change sharply at a border.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Spatial Regression Discontinuity Design
Taxonomic method record · regression-model / causal-inference
  • Dell, M. (2010). The Persistent Effects of Peru's Mining Mita. Econometrica, 78(6), 1863-1903. · DOI 10.3982/ECTA8121
  • Keele, L., & Titiunik, R. (2015). Geographic Boundaries as Regression Discontinuities. Political Analysis, 23(1), 127-155. · DOI 10.1093/pan/mpu014
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Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyDifference-in-Differencesmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketFuzzy Regression Discontinuitymachine-suggested · Relational suggestion, not evidence.See alsoInstrumental Variables in Health Researchmachine-suggested · Relational suggestion, not evidence.See alsoPropensity Score Matchingmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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