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Identification and estimation of causal effects of multiple treatments under the conditional independence assumption

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Econometric Evaluation of Labour Market Policies

Part of the book series: ZEW Economic Studies ((ZEW,volume 13))

Abstract

The assumption that the assignment to treatments is ignorable conditional on attributes plays an important role in the applied statistic and econometric evaluation literature. Another term for it is conditional independence assumption (CIA). This paper discusses identification using CIA when there are more than two types of mutually exclusive treatments. It turns out that low dimensional balancing scores, similar to the ones valid in the case of only two treatments, exist and can be used for identification of various causal effects. Therefore, a comparable reduction of the dimension of the estimation problem is achieved and the approach retains its basic simplicity. The paper also outlines a matching estimator potentially suitable in that framework.

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References

  • Angrist, J. D. (1998): Estimating Labor Market Impact of Voluntary Military Service Using Social Security Data. Econometrica 66, 249-288.

    Article  Google Scholar 

  • Brodaty, Th., Crepon, B., Fougere, D. (2000): Using Matching Estimators to Evaluate Alternative Youth Employment Programs: Evidence from France, 1986-1988, this volume.

    Google Scholar 

  • Dehejia, R., Wahba, S. (1998): Propensity Score Matching Methods for Nonexperimental Causal Studies. NBER working paper, 6829.

    Google Scholar 

  • Dawid, A. P. (1979): Conditional Independence in Statistical Theory. Journal of the Royal Statistical Society Series B 41, 1-31 (with discussion).

    Google Scholar 

  • Dehejia, R. H., Wahba, S. (1999): Causal Effects in Non-experimental Studies: Reevaluating the Evaluation of Training Programmes. Journal of the American Statistical Association 94, 1053-1062.

    Article  Google Scholar 

  • Frölich, M., Heshmati, A., Lechner, M. (2000): A Microeconometric Evaluation of Rehabilitation of Long-term Sickness in Sweden. Discussion paper, 200004, Department of Economics, University of St. Gallen.

    Google Scholar 

  • Gerfin, M., Lechner, M. (2000): Microeconometric Evaluation of the Active Labour Market Policy in Switzerland. Discussion paper, 200010, Department of Economics, University of St. Gallen.

    Google Scholar 

  • Hahn, J. (1998): On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects. Econometrica 66, 315-331.

    Article  Google Scholar 

  • Heckman, J. J. (2000): Causal Parameters and Policy Analysis in Economics: A Twentieth Century Retrospective. Quarterly Journal of Economics 115, 45-97.

    Article  Google Scholar 

  • Heckman, J. J., Ichimura, H., Todd, P. (1997): Matching as an Econometric Evaluation Estimator: Evidence from a Job Training Programme. Review of Economic Studies 64, 605-654.

    Article  Google Scholar 

  • Heckman, J. J., Ichimura, H., Todd, P. (1998): Matching as an Econometric Evaluation Estimator. Review of Economic Studies 65, 261-294.

    Article  Google Scholar 

  • Heckman, J. J., LaLonde, R.J., Smith, J.A. (1999): The Economics and Econometrics of Active Labor Market Programs. In: Ashenfelter, O., Card, D. (Eds.): Handbook of Labor Economics Vol. III 1865-2097.

    Chapter  Google Scholar 

  • Hirano, K., Imbens, G. W., Ridder, G. (2000): Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score. NBER Technical Working Papers 251.

    Google Scholar 

  • Holland, P. W. (1986): Statistics and Causal Inference. Journal of the American Statistical Association 81, 945-970, with discussion.

    Article  Google Scholar 

  • Imbens, G. (1999): The Role of the Propensity Score in Estimating Dose-Response Functions. NBER technical working paper 0237, Biometrica.

    Google Scholar 

  • Larsson, L. (2000): Evaluation of Swedish youth labour market programmes IFAU Discussion paper 2000:1.

    Google Scholar 

  • Lechner, M. (1999): Earnings and Employment Effects of Continuous Off-the-Job Training in East Germany After Unification. Journal of Business & Economic Statistics 17, 7490.

    Google Scholar 

  • Lechner, M. (2000a): Programme Heterogeneity and Propensity Score Matching: An Application to the Evaluation of Active Labour Market Policies. Discussion paper 200001, Department of Economics, University of St. Gallen.

    Google Scholar 

  • Lechner, M. (2000b): Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods. Discussion paper 20001X, Department of Economics, University of St. Gallen.

    Google Scholar 

  • Rosenbaum, P. R., Rubin, D. B. (1983): The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrica 70, 41-50.

    Article  Google Scholar 

  • Rosenbaum, P. R., Rubin, D. B. (1985): Constructing a Control Group Using Multivariate Matched Sampling Methods That Incorporate the Propensity Score. The American Statistician 39, 33-38.

    Google Scholar 

  • Roy, A. D. (1951): Some Thoughts on the Distribution of Earnings. Oxford Economic Papers 3, 135-146.

    Google Scholar 

  • Rubin, D. B. (1974): Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies. Journal of Educational Psychology 66, 688-701.

    Article  Google Scholar 

  • Rubin, D. B. (1977): Assignment to Treatment Group on the Basis of a Covariate. Journal of Educational Statistics 2, 1-26.

    Article  Google Scholar 

  • Rubin, D. B. (1991): Practical Implications of Modes of Statistical Inference for Causal Effects and the Critical Role of the Assignment Mechanism. Biometrics 47, 1213-1234.

    Article  Google Scholar 

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Lechner, M. (2001). Identification and estimation of causal effects of multiple treatments under the conditional independence assumption. In: Lechner, M., Pfeiffer, F. (eds) Econometric Evaluation of Labour Market Policies. ZEW Economic Studies, vol 13. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57615-7_3

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  • DOI: https://doi.org/10.1007/978-3-642-57615-7_3

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-1372-2

  • Online ISBN: 978-3-642-57615-7

  • eBook Packages: Springer Book Archive

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