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Regression Discontinuity Marginal Threshold Treatment Effects

  • Yingying Dong

    ()

    (Department of Economics, University of California-Irvine)

  • Arthur Lewbel

    ()

    (Department of Economics, Boston College)

In regression discontinuity models, where the probability of treatment jumps discretely when a running variable crosses a threshold, an average treatment effect can be nonparametrically identified. We show that the derivative of this treatment effect with respect to the threshold is also nonparametrically identified and easily estimated, in both sharp and fuzzy designs. This marginal threshold treatment effect (MTTE) may be used to estimate the impact on treatment effects of small changes in the threshold. We use it to show how raising the age of Medicare eligibility would change the probability of take up of various types of health insurance.

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File URL: http://www.economics.uci.edu/files/docs/workingpapers/2011-2012/dong-05.pdf
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Paper provided by University of California-Irvine, Department of Economics in its series Working Papers with number 111205.

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Length: 31 pages
Date of creation: Nov 2011
Date of revision:
Handle: RePEc:irv:wpaper:111205
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Web page: http://www.economics.uci.edu/

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  1. David Card & Carlos Dobkin & Nicole Maestas, 2008. "The Impact of Nearly Universal Insurance Coverage on Health Care Utilization: Evidence from Medicare," American Economic Review, American Economic Association, vol. 98(5), pages 2242-58, December.
  2. James Heckman & Sergio Urzua, 2010. "Comparing IV with structural models: what simple IV can and cannot identify," CeMMAP working papers CWP08/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  3. Erich Battistin & Agar Brugiavini & Enrico Rettore & Guglielmo Weber, 2009. "The Retirement Consumption Puzzle: Evidence from a Regression Discontinuity Approach," American Economic Review, American Economic Association, vol. 99(5), pages 2209-26, December.
  4. David S. Lee & Thomas Lemieux, 2009. "Regression Discontinuity Designs In Economics," Working Papers 1118, Princeton University, Department of Economics, Industrial Relations Section..
  5. Dong, Yingying, 2010. "Jumpy or Kinky? Regression Discontinuity without the Discontinuity," MPRA Paper 25461, University Library of Munich, Germany.
  6. Pedro Carneiro & James J. Heckman & Edward J. Vytlacil, 2009. "Evaluating Marginal Policy Changes and the Average Effect of Treatment for Individuals at the Margin," NBER Working Papers 15211, National Bureau of Economic Research, Inc.
  7. Guido Imbens & Thomas Lemieux, 2007. "Regression Discontinuity Designs: A Guide to Practice," NBER Working Papers 13039, National Bureau of Economic Research, Inc.
  8. Imbens, Guido W. & Wooldridge, Jeffrey M., 2008. "Recent Developments in the Econometrics of Program Evaluation," IZA Discussion Papers 3640, Institute for the Study of Labor (IZA).
  9. repec:oup:restud:v:79:y::i:3:p:933-959 is not listed on IDEAS
  10. Angus S. Deaton, 2009. "Instruments of development: Randomization in the tropics, and the search for the elusive keys to economic development," NBER Working Papers 14690, National Bureau of Economic Research, Inc.
  11. Guido Imbens & Karthik Kalyanaraman, 2009. "Optimal Bandwidth Choice for the Regression Discontinuity Estimator," NBER Working Papers 14726, National Bureau of Economic Research, Inc.
  12. Kenneth Y. Chay & Michael Greenstone, 2005. "Does Air Quality Matter? Evidence from the Housing Market," Journal of Political Economy, University of Chicago Press, vol. 113(2), pages 376-424, April.
  13. James J. Heckman, 2010. "Building Bridges Between Structural and Program Evaluation Approaches to Evaluating Policy," NBER Working Papers 16110, National Bureau of Economic Research, Inc.
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