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Using Matching Estimators to Evaluate Alternative Youth Employment Programs : Evidence from France, 1986-1988

  • Thomas Brodaty

    (Crest)

  • Bruno Crépon

    (Crest)

  • Denis Fougère

    (Crest)

In this paper we apply the statistical framework recently proposed by Imbens (1999) and Lechner (1999) to identify the causal effects of multiple treatments under the conditional independence assumption. We show that under this assumption, matching with respect to the ratio of the scores allows to estimate nonparametrically the average conditional treatment effect for any pair of treatments. Consequently it is possible to estimate this effect by implementing nonparametric matching estimators, which were recently studied by Heckman, Ichimura, Smith and Todd (1998) and Heckman, Ichimura and Todd (1998). The application concerns the youth employment programs that were set up in France during the eighties to improve the labour market prospects of the most disadvantaged and unskilled young workers. The empirical analysis makes use of nonexperimental longitudinal micro data collected by INSEE (Institut National de la Statistique et des Etudes Economiques, Paris) from 1986 to 1988.

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Paper provided by Centre de Recherche en Economie et Statistique in its series Working Papers with number 2000-25.

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Date of creation: 2000
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Handle: RePEc:crs:wpaper:2000-25
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  1. Fougère & Kramarz & Thierry Magnac, 2000. "Youth employment policies in France," Working Papers 156232, Institut National de la Recherche Agronomique, France.
  2. Bonnal, Liliane & Fougere, Denis & Serandon, Anne, 1997. "Evaluating the Impact of French Employment Policies on Individual Labour Market Histories," Review of Economic Studies, Wiley Blackwell, vol. 64(4), pages 683-713, October.
  3. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
  4. Rajeev H. Dehejia & Sadek Wahba, 1998. "Causal Effects in Non-Experimental Studies: Re-Evaluating the Evaluation of Training Programs," NBER Working Papers 6586, National Bureau of Economic Research, Inc.
  5. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
  6. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," NBER Working Papers 6699, National Bureau of Economic Research, Inc.
  7. Guido W. Imbens, 1999. "The Role of the Propensity Score in Estimating Dose-Response Functions," NBER Technical Working Papers 0237, National Bureau of Economic Research, Inc.
  8. Heckman, J.J. & Hotz, V.J., 1988. "Choosing Among Alternative Nonexperimental Methods For Estimating The Impact Of Social Programs: The Case Of Manpower Training," University of Chicago - Economics Research Center 88-12, Chicago - Economics Research Center.
  9. James J. Heckman & Jeffrey A. Smith, 1999. "The Pre-Program Earnings Dip and the Determinants of Participation in a Social Program: Implications for Simple Program Evaluation Strategies," NBER Working Papers 6983, National Bureau of Economic Research, Inc.
  10. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Wiley Blackwell, vol. 65(2), pages 261-94, April.
  11. Lechner, Michael, 1999. "Identification and Estimation of Causal Effects of Multiple Treatments Under the Conditional Independence Assumption," IZA Discussion Papers 91, Institute for the Study of Labor (IZA).
  12. Heckman, James J & Smith, Jeffrey A, 1999. "The Pre-programme Earnings Dip and the Determinants of Participation in a Social Programme. Implications for Simple Programme Evaluation Strategies," Economic Journal, Royal Economic Society, vol. 109(457), pages 313-48, July.
  13. Thierry Magnac, 1997. "State Dependence and Heterogeity in youth Employment Histories," Working Papers 97-47, Centre de Recherche en Economie et Statistique.
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