Regression Discontinuity in Elections
Regression discontinuity in elections is a quasi-experimental design that exploits the sharp winning threshold in electoral contests to estimate causal effects of holding office. Just above the threshold a candidate or party wins; just below, it loses. In very close races, which side ends up just over the line is plausibly as good as random, so comparing the later outcomes of bare winners and bare losers identifies the causal effect of winning — most famously the incumbency advantage — without confounding by candidate or district quality.
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Sources
- Lee, D. S. (2008). Randomized Experiments from Non-random Selection in U.S. House Elections. Journal of Econometrics, 142(2), 675–697. DOI: 10.1016/j.jeconom.2007.05.004 ↗
- Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281–355. DOI: 10.1257/jel.48.2.281 ↗
- Eggers, A. C., Fowler, A., Hainmueller, J., Hall, A. B., & Snyder, J. M. (2015). On the Validity of the Regression Discontinuity Design for Estimating Electoral Effects: New Evidence from Over 40,000 Close Races. American Journal of Political Science, 59(1), 259–274. DOI: 10.1111/ajps.12127 ↗
How to cite this page
ScholarGate. (2026, June 22). Regression Discontinuity Design in Close Elections. ScholarGate. https://scholargate.app/en/political-science/regression-discontinuity-in-elections
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