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Varying Biases in the Matching Estimates: Evidence from Two Randomized Job Search Training Experiments

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  • Kari Hämäläinen
  • Roope Uusitalo
  • Jukka Vuori

Abstract

We compare various matching estimators to the results of two randomized field experiments that evaluate employment effects of job search training programs. We find that commonly used non-experimental matching estimators tend to over-estimate the program effects and that the bias differs between programs owing to different procedures used in selecting the program participants. The bias is larger when participation is voluntary than when caseworkers assign the applicants to training. JEL codes: C93

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Bibliographic Info

Paper provided by Government Institute for Economic Research Finland (VATT) in its series Discussion Papers with number 438.

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Date of creation: 07 Feb 2008
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Handle: RePEc:fer:dpaper:438

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Keywords: Job search training; field experiments; matching; unemployment;

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  1. Charles Michalopoulos & Howard S. Bloom & Carolyn J. Hill, 2004. "Can Propensity-Score Methods Match the Findings from a Random Assignment Evaluation of Mandatory Welfare-to-Work Programs?," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 156-179, February.
  2. Gerard van den Berg & Bas van der Klaauw, 2000. "Counseling and Monitoring of Unemployed Workers: Theory and Evidence from a Social Experiment," Econometric Society World Congress 2000 Contributed Papers 0972, Econometric Society.
  3. Richard Blundell & Monica Costa Dias & Costas Meghir & John Van Reenen, 2004. "Evaluating the Employment Impact of a Mandatory Job Search Program," Journal of the European Economic Association, MIT Press, vol. 2(4), pages 569-606, 06.
  4. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-20, September.
  5. Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LP, vol. 4(3), pages 290-311, September.
  6. 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.
  7. V. Joseph Hotz & Guido W. Imbens & Jacob A. Klerman, 2006. "Evaluating the Differential Effects of Alternative Welfare-to-Work Training Components: A Re-Analysis of the California GAIN Program," NBER Working Papers 11939, National Bureau of Economic Research, Inc.
  8. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, 01.
  9. Peter Dolton & Donal O'Neill, 2002. "The Long-Run Effects of Unemployment Monitoring and Work-Search Programs: Experimental Evidence from the United Kingdom," Journal of Labor Economics, University of Chicago Press, vol. 20(2), pages 381-403, Part.
  10. Roberto Agodini & Mark Dynarski, 2004. "Are Experiments the Only Option? A Look at Dropout Prevention Programs," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 180-194, February.
  11. Edwin Leuven & Barbara Sianesi, 2003. "PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing," Statistical Software Components S432001, Boston College Department of Economics, revised 12 Feb 2014.
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