Dong, Yingying (2010): Jumpy or Kinky? Regression Discontinuity without the Discontinuity.
Preview |
PDF
MPRA_paper_25427.pdf Download (300kB) | Preview |
Abstract
Regression Discontinuity (RD) models identify local treatment effects by associating a discrete change in an outcome with a corresponding discrete change in the probability of treatment at a known threshold of a running variable. This paper shows that it is possible to identify RD model treatment effects without a discontinuity. The intuition is that identification can come from a slope change (a kink) instead of a discrete level change (a jump) in the treatment probability. Formally this can be shown using L'hopital's rule. I also interpret the identification results intuitively using instrumental variable models. Estimators are proposed that can be applied in the presence or absence of a discontinuity, by exploiting either a jump or a kink.
Item Type: | MPRA Paper |
---|---|
Original Title: | Jumpy or Kinky? Regression Discontinuity without the Discontinuity |
Language: | English |
Keywords: | Regression Discontinuity, Fuzzy design, Average treatment effect, Identification, Jump, Kink, Threshold |
Subjects: | C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C25 - Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions ; Probabilities |
Item ID: | 25427 |
Depositing User: | Yingying Dong |
Date Deposited: | 26 Sep 2010 01:02 |
Last Modified: | 06 Oct 2019 03:34 |
References: | Angrist, J. D. and J.-S. Pischke (2008) Mostly Harmless Econometrics: An Empiricist's Companion, Princeton University Press. Hahn, J., P. E. Todd, and W. Van der Klaauw (2001), "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, 69, 201--09. Card, D., C. Dobkin, and N. Maestas, (2008), "The Impact of Nearly Universal Insurance Coverage on Health Care Utilization: Evidence from Medicare," American Economic Review, 98, 2242--2258. Carneiro, P., J. J. Heckman, and E. Vytlacil, (2010), "Evaluating Marginal Policy Changes and the Average Effect of Treatment for Individuals at the Margin," Econometrica, 78, 377--394. Heckman, J. J. (2010), "Building Bridges Between Structural and Program Evaluation Approaches to Evaluating Policy," Journal of Economic Literature, 48, 356-398. Imbens, G. W. and K. Kalyanaraman (2009), "Optimal Bandwidth Choice for the Regression Discontinuity Estimator," NBER working paper number 14726. Imbens, G. W. and T. Lemieux (2008), "Regression Discontinuity Designs: A Guide to Practice," Journal of Econometrics, 142, 615--35. Imbens, G. W. and J. M. Wooldridge (2009), "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature 47, 5--86. Jacob, B. A., and L. Lefgren, (2004) "Remedial Education and Student Achievement: A Regression-Discontinuity Analysis," Review of Economics and Statistics, 86, 226--244. Lee, D. S. and T. Lemieux (2010), "Regression Discontinuity Designs in Economics," Journal of Economic Literature 48, 281--355. Porter, J. R. (2003) "Estimation in the Regression Discontinuity Model," Unpublished Manuscript. Rubin, D. B. (1974) "Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies," Journal of Educational Psychology, 66, 688--701. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/25427 |