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Why High-order Polynomials Should not be Used in Regression Discontinuity Designs

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  • Andrew Gelman
  • Guido Imbens

Abstract

It is common in regression discontinuity analysis to control for high order (third, fourth, or higher) polynomials of the forcing variable. We argue that estimators for causal effects based on such methods can be misleading, and we recommend researchers do not use them, and instead use estimators based on local linear or quadratic polynomials or other smooth functions.

Suggested Citation

  • Andrew Gelman & Guido Imbens, 2014. "Why High-order Polynomials Should not be Used in Regression Discontinuity Designs," NBER Working Papers 20405, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:20405
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    References listed on IDEAS

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    1. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    2. Brian A. Jacob & Lars Lefgren, 2004. "Remedial Education and Student Achievement: A Regression-Discontinuity Analysis," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 226-244, February.
    3. DiNardo, John & Lee, David S., 2011. "Program Evaluation and Research Designs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 5, pages 463-536, Elsevier.
    4. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    5. Guido Imbens & Karthik Kalyanaraman, 2012. "Optimal Bandwidth Choice for the Regression Discontinuity Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 933-959.
    6. John DiNardo & David S. Lee, 2010. "Program Evaluation and Research Designs," Working Papers 1228, Princeton University, Department of Economics, Industrial Relations Section..
    7. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    8. David S. Lee & Thomas Lemieux, 2010. "Regression Discontinuity Designs in Economics," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June.
    9. Wilbert Van Der Klaauw, 2008. "Regression–Discontinuity Analysis: A Survey of Recent Developments in Economics," LABOUR, CEIS, vol. 22(2), pages 219-245, June.
    10. Matsudaira, Jordan D., 2008. "Mandatory summer school and student achievement," Journal of Econometrics, Elsevier, vol. 142(2), pages 829-850, February.
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    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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