Using Matching Estimators to Evaluate Alternative Youth Employment Programs: Evidence from France, 1986-1988
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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- 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.
- 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).
- 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.
- Liliane Bonnal & Denis Fougère & Anne Sérandon, 1997. "Evaluating the Impact of French Employment Policies on Individual Labour Market Histories," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 683-713.
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