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Robust Estimation of Heckman Model

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Robustness in Econometrics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 692))

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Abstract

We first review the basic ideas of robust statistics and define the main tools used to formalize the problem and to construct new robust statistical procedures. In particular we focus on the influence function, the Gâteaux derivative of a functional in direction of a point mass, which can be used both to study the local stability properties of a statistical procedure and to construct new robust procedures. In the second part we show how these principles can be used to carry out a robustness analysis in [13] model and how to construct robust versions of Heckman’s two-stage estimator. These are central tools for the statistical analysis of data based on non-random samples from a population.

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Author information

Authors and Affiliations

  1. Research Center for Statistics and Geneva School of Economics and Management, University of Geneva, Geneva, Switzerland

    Elvezio Ronchetti

Authors
  1. Elvezio Ronchetti
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Correspondence to Elvezio Ronchetti .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso Department of Computer Science, El Paso, TX, USA

    Vladik Kreinovich

  2. Faculty of Economics, Chiang Mai University Faculty of Economics, Chiang Mai, Thailand

    Songsak Sriboonchitta

  3. Japan Adv. Inst. of Sci. & Tech. (JAIST) , Ishikawa, Japan

    Van-Nam Huynh

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Ronchetti, E. (2017). Robust Estimation of Heckman Model. In: Kreinovich, V., Sriboonchitta, S., Huynh, VN. (eds) Robustness in Econometrics. Studies in Computational Intelligence, vol 692. Springer, Cham. https://doi.org/10.1007/978-3-319-50742-2_1

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  • DOI: https://doi.org/10.1007/978-3-319-50742-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50741-5

  • Online ISBN: 978-3-319-50742-2

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