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Nonlinear Policy Rules and the Identification and Estimation of Causal Effects in a Generalized Regression Kink Design

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Author Info

  • Zhuan Pei

    ()
    (Economics Department, Brandeis University)

  • David Card

    (UC Berkeley)

  • David S. Lee

    (Princeton University)

  • Andrea Weber

    (University of Mannheim)

Abstract

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly unemployment benefits) is determined by an observed but potentially endogenous assignment variable (like previous earnings). We provide new results on identi?cation and estimation for these settings, and apply our results to obtain estimates of the elasticity of joblessness with respect to UI benefit rates. We characterize a broad class of models in which a “Regression Kink Design” (RKD, or RK Design) provides valid inferences for the treatment-on-the-treated parameter (Florens et al. (2008)) that would be identified in an ideal randomized experiment. We show that the smooth density condition that is sufficient for identification rules out extreme sorting around the kink, but is compatible with less severe forms of endogeneity. It also places testable restrictions on the distribution of predetermined covariates around the kink point. We introduce a generalization of the RKD – the “fuzzy regression kink design” – that allows for omitted variables in the assignment rule, as well as certain types of measurement errors in the observed values of the assignment variable and the policy variable. We also show how standard local polynomial regression techniques can be adapted to obtain nonparametric estimates for the sharp and fuzzy RKD. We then use a fuzzy RKD approach to study the effect of unemployment insurance benefits on the duration of joblessness in Austria, where the benefit schedule has kinks at the minimum and maximum benefit level. Our estimates suggest that the elasticity of joblessness with respect to the benefit rate is on the order of 1.5.

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File URL: http://www.brandeis.edu/departments/economics/RePEc/brd/doc/Brandeis_WP60.pdf
File Function: First version, 2012
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Bibliographic Info

Paper provided by Brandeis University, Department of Economics and International Businesss School in its series Working Papers with number 60.

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Length: 96 pages
Date of creation: Nov 2012
Date of revision:
Handle: RePEc:brd:wpaper:60

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Postal: MS032, P.O. Box 9110, Waltham, MA 02454-9110
Web page: http://www.brandeis.edu/departments/economics/
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Related research

Keywords: Regression Discountinuity Design; Regression Kink Design; Treatment Effects; Nonseparable Models; Nonparametric Estimation;

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References

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  1. J.P. Florensy & J. J. Heckmanz & C. Meghirx & E. Vytlacil, 2008. "Identification of Treatment Effects Using Control Functions in Models with Continuous, Endogenous Treatment and Heterogeneous Effects," Working Papers 200832, Geary Institute, University College Dublin.
  2. Del Bono, Emilia & Weber, Andrea, 2006. "Do Wages Compensate for Anticipated Working Time Restrictions? Evidence from Seasonal Employment in Austria," IZA Discussion Papers 2242, Institute for the Study of Labor (IZA).
  3. Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
  4. Kroft, Kory, 2008. "Takeup, social multipliers and optimal social insurance," Journal of Public Economics, Elsevier, vol. 92(3-4), pages 722-737, April.
  5. Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
  6. David Card & Raj Chetty & Andrea Weber, 2007. "Cash-On-Hand and Competing Models of Intertemporal Behavior: New Evidence from the Labor Market," The Quarterly Journal of Economics, MIT Press, vol. 122(4), pages 1511-1560, November.
  7. Guido Imbens & Karthik Kalyanaraman, 2009. "Optimal Bandwidth Choice for the Regression Discontinuity Estimator," NBER Working Papers 14726, National Bureau of Economic Research, Inc.
  8. Lawrence F. Katz & Bruce D. Meyer, 1988. "The Impact of the Potential Duration of Unemployment Benefits on the Duration of Unemployment," NBER Working Papers 2741, National Bureau of Economic Research, Inc.
  9. Josef Zweimüller & Rudolf Winter-Ebmer & Rafael Lalive & Andreas Kuhn & Jean-Philippe Wuellrich & Oliver Ruf & Simon Büchi, 2009. "Austrian social security database," IEW - Working Papers 410, Institute for Empirical Research in Economics - University of Zurich.
    • Josef Zweimüller & Rudolf Winter-Ebmer & Rafael Lalive & Andreas Kuhn & Jean-Philippe Wuellrich & Oliver Ruf & Simon Büchi, 2009. "Austrian Social Security Database," NRN working papers 2009-03, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
  10. Baily, Martin Neil, 1978. "Some aspects of optimal unemployment insurance," Journal of Public Economics, Elsevier, vol. 10(3), pages 379-402, December.
  11. Landais, Camille, 2013. "Assessing the Welfare Effects of Unemployment Benefits Using the Regression Kink Design," IZA Discussion Papers 7589, Institute for the Study of Labor (IZA).
  12. Arthur Lewbel, 1998. "Semiparametric Latent Variable Model Estimation with Endogenous or Mismeasured Regressors," Econometrica, Econometric Society, vol. 66(1), pages 105-122, January.
  13. Marianne Simonsen & Lars Skipper & Niels Skipper, 2010. "Price Sensitivity of Demand for Prescription Drugs: Exploiting a Regression Kink Design," Economics Working Papers 2010-03, School of Economics and Management, University of Aarhus.
  14. Moffitt, Robert, 1985. "Unemployment insurance and the distribution of unemployment spells," Journal of Econometrics, Elsevier, vol. 28(1), pages 85-101, April.
  15. Joseph G. Altonji & Rosa L. Matzkin, 2005. "Cross Section and Panel Data Estimators for Nonseparable Models with Endogenous Regressors," Econometrica, Econometric Society, vol. 73(4), pages 1053-1102, 07.
  16. Lee, David S., 2008. "Randomized experiments from non-random selection in U.S. House elections," Journal of Econometrics, Elsevier, vol. 142(2), pages 675-697, February.
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Citations

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Cited by:
  1. Ando, Michihito, 2013. "How Much Should We Trust Regression-Kink-Design Estimates?," Working Paper Series 2013:22, Uppsala University, Department of Economics.
  2. Landais, Camille, 2013. "Assessing the Welfare Effects of Unemployment Benefits Using the Regression Kink Design," IZA Discussion Papers 7589, Institute for the Study of Labor (IZA).
  3. Arash Nekoei & Andrea Weber, 2014. "Does Extending Unemployment Benefits Improve Job Quality?," NRN working papers 2014-04, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
  4. repec:ese:iserwp:2014-05 is not listed on IDEAS
  5. Fuhito Kojima & Parag Pathak & Alvin Roth, 2013. "Matching with Couples: Stability and Incentives in Large Markets," Discussion Papers 12-018, Stanford Institute for Economic Policy Research.
  6. Jason M. Lindo & Peter Siminski & Oleg Yerokhin, 2014. "Breaking the Link Between Legal Access to Alcohol and Motor Vehicle Accidents: Evidence from New South Wales," NBER Working Papers 19857, National Bureau of Economic Research, Inc.
  7. Ganong, Peter & Jäger, Simon, 2014. "A Permutation Test and Estimation Alternatives for the Regression Kink Design," IZA Discussion Papers 8282, Institute for the Study of Labor (IZA).
  8. Böckerman, Petri & Kanninen, Ohto & Suoniemi, Ilpo, 2014. "A Kink that Makes You Sick: The Incentive Effect of Sick Pay on Absence," IZA Discussion Papers 8205, Institute for the Study of Labor (IZA).
  9. Dayanand S. Manoli & Nicholas Turner, 2014. "Cash-on-Hand & College Enrollment: Evidence from Population Tax Data and Policy Nonlinearities," NBER Working Papers 19836, National Bureau of Economic Research, Inc.

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