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Empirical Likelihood for Regression Discontinuity Design

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Abstract

This paper proposes empirical likelihood based inference methods for causal effects identified from regression discontinuity designs. We consider both the sharp and fuzzy regression discontinuity designs and treat the regression functions as nonparametric. The proposed inference procedures do not require asymptotic variance estimation and the confidence sets have natural shapes, unlike the conventional Wald-type method. These features are illustrated by simulations and an empirical example which evaluates the effect of class size on pupils' scholastic achievements. Bandwidth selection methods, higher-order properties, and extensions to incorporate additional covariates and parametric functional forms are also discussed.

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File URL: http://cowles.econ.yale.edu/P/cd/d17b/d1799.pdf
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Bibliographic Info

Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1799.

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Length: 36 pages
Date of creation: May 2011
Date of revision:
Handle: RePEc:cwl:cwldpp:1799

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Web page: http://cowles.econ.yale.edu/
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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

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Keywords: Empirical likelihood; Nonparametric methods; Regression discontinuity design; Treatment effect;

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  1. Chan, Ngai Hang & Peng, Liang & Zhang, Dabao, 2011. "Empirical-Likelihood-Based Confidence Intervals For Conditional Variance In Heteroskedastic Regression Models," Econometric Theory, Cambridge University Press, vol. 27(01), pages 154-177, February.
  2. Whitney Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  3. Horowitz, Joel L. & Savin, N. E., 2000. "Empirically relevant critical values for hypothesis tests: A bootstrap approach," Journal of Econometrics, Elsevier, Elsevier, vol. 95(2), pages 375-389, April.
  4. Imbens, Guido W. & Kalyanaraman, Karthik, 2009. "Optimal Bandwidth Choice for the Regression Discontinuity Estimator," IZA Discussion Papers 3995, Institute for the Study of Labor (IZA).
  5. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, Econometric Society, vol. 68(5), pages 1055-1096, September.
  6. Guido Imbens & Thomas Lemieux, 2007. "Regression Discontinuity Designs: A Guide to Practice," NBER Working Papers 13039, National Bureau of Economic Research, Inc.
  7. Davidson, Russell & MacKinnon, James G., 2006. "The power of bootstrap and asymptotic tests," Journal of Econometrics, Elsevier, Elsevier, vol. 133(2), pages 421-441, August.
  8. Song Xi Chen & Hengjian Cui, 2006. "On Bartlett correction of empirical likelihood in the presence of nuisance parameters," Biometrika, Biometrika Trust, Biometrika Trust, vol. 93(1), pages 215-220, March.
  9. Joshua D. Angrist & Victor Lavy, 1999. "Using Maimonides' Rule To Estimate The Effect Of Class Size On Scholastic Achievement," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 114(2), pages 533-575, May.
  10. Feir, Donna & Lemieux, Thomas & Marmer, Vadim, 2010. "Weak Identification in Fuzzy Regression Discontinuity Designs," Microeconomics.ca working papers, Vancouver School of Economics vadim_marmer-2010-19, Vancouver School of Economics, revised 23 Jan 2014.
  11. Xu, Ke-Li & Phillips, Peter C. B., 2011. "Tilted Nonparametric Estimation of Volatility Functions With Empirical Applications," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 29(4), pages 518-528.
  12. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, Econometric Society, vol. 69(1), pages 201-09, January.
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Cited by:
  1. Feir, Donna & Lemieux, Thomas & Marmer, Vadim, 2010. "Weak Identification in Fuzzy Regression Discontinuity Designs," Microeconomics.ca working papers, Vancouver School of Economics vadim_marmer-2010-19, Vancouver School of Economics, revised 23 Jan 2014.

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