Identifying the Effect of Changing the Policy Threshold in Regression Discontinuity Models
AbstractRegression discontinuity models, where the probability of treatment jumps discretely when a running variable crosses a threshold, are commonly used to nonparametrically identify and estimate a local average treatment effect. We show that the derivative of this treatment effect with respect to the running variable is nonparametrically identified and easily estimated. Then, given a local policy invariance assumption, we show that this derivative equals the change in the treatment effect that would result from a marginal change in the threshold, which we call the marginal threshold treatment effect (MTTE). We apply this result to Manacorda (2012), who estimates a treatment effect of grade retention on school outcomes. Our MTTE identifies how this treatment effect would change if the threshold for retention was raised or lowered, even though no such change in threshold is actually observed.
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Bibliographic InfoPaper provided by Boston College Department of Economics in its series Boston College Working Papers in Economics with number 759.
Date of creation: 01 Aug 2010
Date of revision: 15 Dec 2012
Note: Previously circulated as "Regression Discontinuity Marginal Threshold Treatment Effects"
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regression discontinuity; sharp design; fuzzy design; treatment effects; program evaluation; threshold; running variable; forcing variable; marginal effects.;
Find related papers by JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-09-25 (All new papers)
- NEP-ECM-2010-09-25 (Econometrics)
- NEP-IAS-2010-09-25 (Insurance Economics)
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- Joshua Angrist & Miikka Rokkanen, 2012.
"Wanna Get Away? RD Identification Away from the Cutoff,"
NBER Working Papers
18662, National Bureau of Economic Research, Inc.
- Angrist, Joshua & Rokkanen, Miikka, 2013. "Wanna Get Away? RD Identification Away from the Cutoff," IZA Discussion Papers 7429, Institute for the Study of Labor (IZA).
- Yingying Dong, 2012. "Regression Discontinuity Applications with Rounding Errors in the Running Variable," Working Papers 111206, University of California-Irvine, Department of Economics.
- Yingying Dong, 2011.
"Jumpy or Kinky? Regression Discontinuity without the Discontinuity,"
111207, University of California-Irvine, Department of Economics.
- Dong, Yingying, 2010. "Jumpy or Kinky? Regression Discontinuity without the Discontinuity," MPRA Paper 25461, University Library of Munich, Germany.
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