Regression modelCausal inference

Geographic Regression Discontinuity

Geographic Regression Discontinuity (GRD) is a quasi-experimental design that exploits sharp geographic boundaries—borders, policy boundaries, or natural features—to estimate causal effects. Introduced by Dell (2010) and others, it compares outcomes on either side of a boundary where treatment changes abruptly, leveraging the idea that units on opposite sides of a border are otherwise similar. This approach yields credible causal estimates for spatially localized policies, institutional changes, and natural phenomena.

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Sources

  1. Dell, M. (2018). The persistent effects of Peru's mining mita. Econometrica, 78(6), 1863-1911. DOI: 10.3982/ECTA8121
  2. Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615-635. DOI: 10.1016/j.jeconom.2007.05.001

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Referenced by

ScholarGateGeographic Regression Discontinuity (Geographic Regression Discontinuity Design). Retrieved 2026-06-04 from https://scholargate.app/tr/econometrics/geographic-regression-discontinuity