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Quantile treatment effects in the regression discontinuity design

  • Frandsen, Brigham R.
  • Frölich, Markus
  • Melly, Blaise

We introduce a nonparametric estimator for local quantile treatment effects in the regression discontinuity (RD) design. The procedure uses local distribution regression to estimate the marginal distributions of the potential outcomes. We illustrate the procedure through Monte Carlo simulations and an application on the distributional effects of a universal pre-K program in Oklahoma. We find that participation in a pre-K program significantly raises the lower end and the middle of the distribution of test scores.

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 168 (2012)
Issue (Month): 2 ()
Pages: 382-395

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Handle: RePEc:eee:econom:v:168:y:2012:i:2:p:382-395
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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  1. Victor Chernozhukov & Iv·n Fern·ndez-Val & Alfred Galichon, 2010. "Quantile and Probability Curves Without Crossing," Econometrica, Econometric Society, vol. 78(3), pages 1093-1125, 05.
  2. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March.
  3. 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.
  4. Lalive, Rafael, 2008. "How do extended benefits affect unemployment duration A regression discontinuity approach," Journal of Econometrics, Elsevier, vol. 142(2), pages 785-806, February.
  5. Brügger, Beatrix & Lalive, Rafael & Zweimüller, Josef, 2009. "Does Culture Affect Unemployment? Evidence from the Röstigraben," IZA Discussion Papers 4283, Institute for the Study of Labor (IZA).
  6. Kenneth Y. Chay & Patrick J. McEwan & Miguel Urquiola, 2005. "The Central Role of Noise in Evaluating Interventions That Use Test Scores to Rank Schools," American Economic Review, American Economic Association, vol. 95(4), pages 1237-1258, September.
  7. repec:adr:anecst:y:2008:i:91-92:p:07 is not listed on IDEAS
  8. Yu, Keming & Jones, M. C., 1997. "A comparison of local constant and local linear regression quantile estimators," Computational Statistics & Data Analysis, Elsevier, vol. 25(2), pages 159-166, July.
  9. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2012. "Inference on counterfactual distributions," CeMMAP working papers CWP05/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  10. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521608275, june. pag.
  11. David S. Lee & Thomas Lemieux, 2009. "Regression Discontinuity Designs in Economics," NBER Working Papers 14723, National Bureau of Economic Research, Inc.
  12. Jinyong Hahn & Petra Todd & Wilbert Van der Klaauw, 1999. "Evaluating the Effect of an Antidiscrimination Law Using a Regression-Discontinuity Design," NBER Working Papers 7131, National Bureau of Economic Research, Inc.
  13. John DiNardo & David S. Lee, 2004. "Economic Impacts of Unionization on Private Sector Employers: 1984-2001," NBER Working Papers 10598, National Bureau of Economic Research, Inc.
  14. Guido Imbens & Karthik Kalyanaraman, 2010. "Optimal bandwidth choice for the regression discontinuity estimator," CeMMAP working papers CWP05/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  15. Fredriksson, Peter & Öckert, Björn, 2005. "Is Early Learning Really More Productive? The Effect of School Starting Age on School and Labor Market Performance," IZA Discussion Papers 1659, Institute for the Study of Labor (IZA).
  16. Wilbert van der Klaauw, 2002. "Estimating the Effect of Financial Aid Offers on College Enrollment: A Regression-Discontinuity Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(4), pages 1249-1287, November.
  17. Guido Imbens & Thomas Lemieux, 2007. "Regression Discontinuity Designs: A Guide to Practice," NBER Technical Working Papers 0337, National Bureau of Economic Research, Inc.
  18. Markus Frölich, 2007. "Regression discontinuity design with covariates," University of St. Gallen Department of Economics working paper series 2007 2007-32, Department of Economics, University of St. Gallen.
  19. Lalive, Rafael & Wuellrich, Jean-Philippe & Zweimüller, Josef, 2009. "Do Financial Incentives for Firms Promote Employment of Disabled Workers? A Regression Discontinuity Approach," CEPR Discussion Papers 7373, C.E.P.R. Discussion Papers.
  20. Alberto Abadie & Joshua Angrist & Guido Imbens, 2002. "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings," Econometrica, Econometric Society, vol. 70(1), pages 91-117, January.
  21. Cook, Thomas D., 2008. ""Waiting for Life to Arrive": A history of the regression-discontinuity design in Psychology, Statistics and Economics," Journal of Econometrics, Elsevier, vol. 142(2), pages 636-654, February.
  22. Brian A. Jacob & Lars Lefgren, 2004. "The Impact of Teacher Training on Student Achievement: Quasi-Experimental Evidence from School Reform Efforts in Chicago," Journal of Human Resources, University of Wisconsin Press, vol. 39(1).
  23. Jonathan Guryan, 2001. "Does Money Matter? Regression-Discontinuity Estimates from Education Finance Reform in Massachusetts," NBER Working Papers 8269, National Bureau of Economic Research, Inc.
  24. Matsudaira, Jordan D., 2008. "Mandatory summer school and student achievement," Journal of Econometrics, Elsevier, vol. 142(2), pages 829-850, February.
  25. Patrick Puhani & Andrea Weber, 2007. "Does the early bird catch the worm?," Empirical Economics, Springer, vol. 32(2), pages 359-386, May.
  26. Wilbert van der Klaauw, 2008. "Regression-Discontinuity Analysis: A Survey of Recent Developments in Economics," LABOUR, CEIS, vol. 22(2), pages 219-245, 06.
  27. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-09, January.
  28. Edwin Leuven & Mikael Lindahl & Hessel Oosterbeek & Dinand Webbink, 2007. "The Effect of Extra Funding for Disadvantaged Pupils on Achievement," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 721-736, November.
  29. Buddelmeyer, Hielke & Skoufias, Emmanuel, 2004. "An evaluation of the performance of regression discontinuity design on PROGRESA," Policy Research Working Paper Series 3386, The World Bank.
  30. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
  31. Frölich, Markus & Melly, Blaise, 2010. "Quantile Treatment Effects in the Regression Discontinuity Design: Process Results and Gini Coefficient," IZA Discussion Papers 4993, Institute for the Study of Labor (IZA).
  32. Joshua D. Angrist & Victor Lavy, 1999. "Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 533-575.
  33. Guido W. Imbens & Donald B. Rubin, 1997. "Estimating Outcome Distributions for Compliers in Instrumental Variables Models," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 555-574.
  34. John DiNardo & David S. Lee, 2004. "Economic Impacts of New Unionization on Private Sector Employers: 1984–2001," The Quarterly Journal of Economics, Oxford University Press, vol. 119(4), pages 1383-1441.
  35. Anderson, Michael L., 2008. "Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1481-1495.
  36. van der Klaauw, Wilbert, 2008. "Breaking the link between poverty and low student achievement: An evaluation of Title I," Journal of Econometrics, Elsevier, vol. 142(2), pages 731-756, February.
  37. Bernard S. Black & Hasung Jang & Woochan Kim, 2006. "Does Corporate Governance Predict Firms' Market Values? Evidence from Korea," Journal of Law, Economics and Organization, Oxford University Press, vol. 22(2), pages 366-413, October.
  38. Arulampalam, W. & Robin A. Naylor & Jeremy P. Smith, 2002. "University of Warwick," Royal Economic Society Annual Conference 2002 9, Royal Economic Society.
  39. 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.
  40. Battistin, Erich & Rettore, Enrico, 2008. "Ineligibles and eligible non-participants as a double comparison group in regression-discontinuity designs," Journal of Econometrics, Elsevier, vol. 142(2), pages 715-730, February.
  41. Atkinson, Anthony B., 1970. "On the measurement of inequality," Journal of Economic Theory, Elsevier, vol. 2(3), pages 244-263, September.
  42. Dan A. Black & Jeffrey A. Smith & Mark C. Berger & Brett J. Noel, 2003. "Is the Threat of Reemployment Services More Effective Than the Services Themselves? Evidence from Random Assignment in the UI System," American Economic Review, American Economic Association, vol. 93(4), pages 1313-1327, September.
  43. Peter Hall & Rodney C. L. Wolff & Qiwei Yao, 1999. "Methods for estimating a conditional distribution function," LSE Research Online Documents on Economics 6631, London School of Economics and Political Science, LSE Library.
  44. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, 01.
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