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| Natural Experiment in Politics× | Regression Discontinuity in Elections× | |
|---|---|---|
| Field | Political Science | Political Science |
| Family | Process / pipeline | Process / pipeline |
| Year of origin≠ | 2012 | 2008 |
| Originator≠ | Dunning (design-based framework); Lee (close-election RD lineage) | David S. Lee (electoral application); broader RD tradition |
| Type≠ | Observational study exploiting as-if random assignment | Quasi-experimental causal design using a vote-share threshold |
| Seminal source≠ | Dunning, T. (2012). Natural Experiments in the Social Sciences: A Design-Based Approach. Cambridge: Cambridge University Press. ISBN: 9781107698000 | Lee, D. S. (2008). Randomized Experiments from Non-random Selection in U.S. House Elections. Journal of Econometrics, 142(2), 675–697. DOI ↗ |
| Aliases | Political natural experiment, As-if random design, Design-based natural experiment, Quasi-experiment with as-if randomization | Close-election RD, Electoral regression discontinuity, Vote-share RD design, Incumbency-advantage RD |
| Related≠ | 4 | 3 |
| Summary≠ | A natural experiment in political science exploits a naturally occurring source of as-if random assignment — close elections, lotteries, arbitrary boundaries, or policy thresholds — to identify causal effects without the researcher manipulating anything. Codified for the social sciences by Thad Dunning's 2012 design-based treatment and exemplified by David Lee's close-election regression-discontinuity analysis of U.S. House races, the approach treats nature, institutions, or chance as if they had run an experiment, recovering credible causal estimates from observational data when randomization is impossible. | 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. |
| ScholarGateDataset ↗ |
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