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Non-parametric adjustment for covariates when estimating a treatment effect

Author

Listed:
  • Cantoni, Eva

    (Department of of Econometrics, University of Geneva)

  • de Luna, Xavier

    (Department of Statistics, Umeå University)

Abstract

We consider a non-parametric model for estimating the effect of a binary treatment on an outcome variable while adjusting for an observed covariate. A naive procedure consists in performing two separate non-parametric regression of the response on the covariate: one with the treated individuals and the other with the untreated. The treatment effect is then obtained by taking the difference between the two fitted regression functions. This paper proposes a backfitting algorithm which uses all the data for the two above-mentioned non-parametric regression. We give theoretical results showing that the resulting estimator of the treatment effect can have lower finite sample variance. This improvement may be achieved at the cost of a larger bias. However, in a simulation study we observe that mean squared error is lowest for the proposed backfitting estimator. When more than one covariate is observed our backfitting estimator can still be applied by using the propensity score (probability of being treated for a given setup of the covariates). We illustrate the use of the backfitting estimator in a several covariate situation with data on a training program for individuals having faced social and economic problems.

Suggested Citation

  • Cantoni, Eva & de Luna, Xavier, 2004. "Non-parametric adjustment for covariates when estimating a treatment effect," Working Paper Series 2004:9, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    • Handle: RePEc:hhs:ifauwp:2004_009
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    References listed on IDEAS

    as
    1. Anders Forslund & Daniela Froberg & Linus Lindqvist, 2004. "The Swedish Activity Guarantee," OECD Social, Employment and Migration Working Papers 16, OECD Publishing.
    2. Schröder, Lena, 2004. "The role of youth programmes in the transition from school to work," Working Paper Series 2004:5, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    3. Nilsson, Anna, 2004. "Income inequality and crime: The case of Sweden," Working Paper Series 2004:6, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    4. Nilsson, Anna, 2004. "Income Inequality and Crime: The Case of Sweden," Research Papers in Economics 2004:3, Stockholm University, Department of Economics.
    5. Larsson, Laura, 2004. "Harmonizing unemployment and sickness insurance: Why (not)?," Working Paper Series 2004:8, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Analysis of covariance; backfitting algorithm; linear smoothers; propensity score;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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