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Treatment effect analysis of early reemployment bonus program: panel MLE and mode-based semiparametric estimator for interval truncation

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  • Hyun Kim
  • Yong-seong Kim
  • Myoung-jae Lee

    ()

Abstract

We use Korean data to find the effects of Early Reemployment Bonus (ERB) on unemployment duration; ERB is a bonus that the eligible unemployed receive if they find a job before their unemployment insurance benefit expires. A naive approach would be comparing the ERB receiving group with the non-receiving group, but the ERB receipt is partly determined by the unemployment duration itself (thus, an endogeneity problem). Interestingly, there were many individuals who did not receive the ERB despite being fully eligible, and this is attributed to being unaware of the ERB scheme. Taking this as a ‘pseudo randomization’, we construct treatment and control groups using only the eligible. Our data set is an unbalanced panel with the response variable interval-truncated due to eligibility requirement of the ERB. We propose a panel random-effect MLE and a semiparametric ‘mode-based’ estimator for the interval-truncated response. Our empirical finding is that the effect varies much, depending on individual characteristics. As for the mean effects, whereas the MLE indicates large duration-shortening effects, the semiparametric estimator shows much weaker and mostly insignificant effects. Copyright Springer-Verlag 2012

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Bibliographic Info

Article provided by Springer in its journal Portuguese Economic Journal.

Volume (Year): 11 (2012)
Issue (Month): 3 (December)
Pages: 189-209

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Handle: RePEc:spr:portec:v:11:y:2012:i:3:p:189-209

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Related research

Keywords: Treatment effect; Reemployment bonus; Unemployment duration; Program awareness; Interval truncation; Mode; C14; C21; C24; C41; J64;

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References

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  1. Lee, M.J., 1990. "Quadratic Mode Regression," Papers 9-90-10, Pennsylvania State - Department of Economics.
  2. 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.
  3. Gordon C.R. Kemp & J.M.C. Santos Silva, 2010. "Regression towards the mode," Economics Discussion Papers 686, University of Essex, Department of Economics.
  4. Yannis Bilias & Roger Koenker, 2001. "Quantile regression for duration data: A reappraisal of the Pennsylvania Reemployment Bonus Experiments," Empirical Economics, Springer, vol. 26(1), pages 199-220.
  5. 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).
  6. Markus Baldauf & J.M.C. Santos Silva, 2009. "On the use of robust regression in econometrics," Economics Discussion Papers 664, University of Essex, Department of Economics.
  7. Paul T. Decker & Christopher J. O'Leary, . "Evaluating Pooled Evidence from the Reemployment Bonus Experiments," Upjohn Working Papers and Journal Articles ptdcjo1995, W.E. Upjohn Institute for Employment Research.
  8. Lee, Myoung-jae, 2005. "Micro-Econometrics for Policy, Program and Treatment Effects," OUP Catalogue, Oxford University Press, number 9780199267699, September.
  9. Christopher J. O’Leary & Paul T. Decke & Stephen A. Wandner, 2005. "Cost-Effectiveness of Targeted Reemployment Bonuses," Journal of Human Resources, University of Wisconsin Press, vol. 40(1).
  10. Govert Bijwaard & Geert Ridder, 1998. "Correcting for Selective Compliance in a Re-employment Bonus Experiment," Tinbergen Institute Discussion Papers 98-096/4, Tinbergen Institute.
  11. Paul T. Decker, 1994. "The Impact of Reemployment Bonuses on Insured Unemployment in the New Jersey and Illinois Reemployment Bonus Experiments," Journal of Human Resources, University of Wisconsin Press, vol. 29(3), pages 718-741.
  12. Bruce D. Meyer, 1995. "Lessons from the U.S. Unemployment Insurance Experiments," Journal of Economic Literature, American Economic Association, vol. 33(1), pages 91-131, March.
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