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Correcting for Selective Compliance in a Re-Employment Bonus Experiment

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  • Govert Bijwaard
  • Geert Ridder

Abstract

We propose a two-stage instrumental variable estimator that is consistent if there is a selective compliance in the treatment group of a randomized experiment and the outcome variable is a censored duration The estimator assumes full compliance in the control group We use the estimator to reanalyze data from the Illinois re-employment bonus experiment

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Bibliographic Info

Paper provided by The Johns Hopkins University,Department of Economics in its series Economics Working Paper Archive with number 412.

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Date of creation: 18 Nov 1998
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Handle: RePEc:jhu:papers:412

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References

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  1. Bruce D. Meyer, 1988. "Implications of the Illinois Reemployment Bonus Experiments For Theories of Unemployment and Policy Design," NBER Working Papers 2783, National Bureau of Economic Research, Inc.
  2. Moffitt, Robert, 1983. "An Economic Model of Welfare Stigma," American Economic Review, American Economic Association, vol. 73(5), pages 1023-35, December.
  3. Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
  4. Horowitz, J. & Gorgens, T., 1995. "Semiparametric Estimation of a Censored Regression Model with an Unknown Transformation of the Dependent Variable," Working Papers 95-15, University of Iowa, Department of Economics.
  5. Stephen A. Woodbury & Robert G. Spiegelman, . "Bonuses to Workers and Employers to Reduce unemployment: Randomized Trials in Illinois," Upjohn Working Papers and Journal Articles sawrgs1987, W.E. Upjohn Institute for Employment Research.
  6. Meyer, Bruce D, 1996. "What Have We Learned from the Illinois Reemployment Bonus Experiment?," Journal of Labor Economics, University of Chicago Press, vol. 14(1), pages 26-51, January.
  7. Michael Baker & Angelo Melino, 1999. "Duration Dependence and Nonparametric Heterogeneity: A Monte Carlo Study," Working Papers melino-99-01, University of Toronto, Department of Economics.
  8. Ham, John C & LaLonde, Robert J, 1996. "The Effect of Sample Selection and Initial Conditions in Duration Models: Evidence from Experimental Data on Training," Econometrica, Econometric Society, vol. 64(1), pages 175-205, January.
  9. James Heckman, 1997. "Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 441-462.
  10. Horowitz, Joel & Manski, Charles, 1997. "Nonparametric Analysis of Randomized Experiments With Missing Covariate and Outcome Data," Working Papers 97-16, University of Iowa, Department of Economics.
  11. repec:fth:prinin:242 is not listed on IDEAS
  12. Lancaster, Tony, 1979. "Econometric Methods for the Duration of Unemployment," Econometrica, Econometric Society, vol. 47(4), pages 939-56, July.
  13. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  14. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097 Elsevier.
  15. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
  16. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
  17. Horowitz, Joel L, 1996. "Semiparametric Estimation of a Regression Model with an Unknown Transformation of the Dependent Variable," Econometrica, Econometric Society, vol. 64(1), pages 103-37, January.
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