Construct · 1 fields · 3 citations

regression discontinuity: a standalone construct

One name. One construct. A landmark on the map.

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regressiondiscontinuity1 CONSTRUCTRD designTHISTLETHWAITE · CUTOFF

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Econometrics

A design that estimates a treatment effect at a cutoff on a running variable

Donald Thistlethwaite and Donald Campbell introduced the regression-discontinuity design in 1960 as an alternative to the after-the-fact comparison study, examining students who fell just above and just below a scholarship award cutoff. The idea is that when a treatment is assigned by whether a continuous score, the running variable, crosses a fixed threshold, the units landing just on either side of that threshold are alike in almost every other respect, so a jump in the outcome right at the cutoff can be attributed to the treatment. Jinyong Hahn, Petra Todd, and Wilbert van der Klaauw formalized the method in 2001, stating the assumptions under which it identifies a causal effect and linking it to nonparametric estimation, and Guido Imbens and Thomas Lemieux's 2008 guide set out the now-standard practice for choosing the estimation window and probing the design. What makes it a landmark is that it recovers a credible causal estimate from an ordinary administrative rule, a cutoff on a test score, income, age, or vote share, without a randomized experiment, while the estimate it yields applies only to units near the threshold.[1][2][3]

Unit
A local treatment effect at the cutoff, expressed in the outcome's own units (for example test points, dollars, or a probability)
Recovery means
Not applicable
Measured by
Identified by comparing outcomes just above and just below the threshold, commonly through local linear regression fitted within a chosen window of the running variable

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Nearby constructs

regression4 fields · 5 citationsjingle · one word, four constructsidentification6 fields · 9 citationsjingle · one word, six constructsselection4 fields · 5 citationsjingle · one word, four constructs

References

  1. Thistlethwaite, D. L., & Campbell, D. T. (1960). Regression-discontinuity analysis: An alternative to the ex post facto experiment. Journal of Educational Psychology, 51(6), 309–317. https://doi.org/10.1037/h0044319
  2. Hahn, J., Todd, P., & van der Klaauw, W. (2001). Identification and estimation of treatment effects with a regression-discontinuity design. Econometrica, 69(1), 201–209. https://doi.org/10.1111/1468-0262.00183
  3. Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615–635. https://doi.org/10.1016/j.jeconom.2007.05.001

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