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A New Hausmann Type Test to Detect the Presence of Influential Outliers

Author

Listed:
  • Catherine Dehon
  • Marjorie Gassner
  • Vincenzo Verardi

Abstract

In the presence of outliers in a dataset, a least squares estimation may not be the most adequate choice to get representative results. Indeed estimations could have been excessively infuenced even by a very limited number of atypical observations. In this article, we propose a new Hausman-type test to check for this. The test is based on the trade-off between robustness and effciency and allows to conclude if a least squares estimation is appropriate or if a robust method should be preferred. An economic example is provided to illustrate the usefulness of the test.

Suggested Citation

  • Catherine Dehon & Marjorie Gassner & Vincenzo Verardi, 2008. "A New Hausmann Type Test to Detect the Presence of Influential Outliers," Working Papers ECARES 2008_006, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:eca:wpaper:2008_006
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    Citations

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    Cited by:

    1. A. García-Pérez, 2014. "The p value line: a way to choose the tuning constant in tests based on the Huber $${\varvec{M}}$$ M -estimator," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 536-555, September.
    2. Quentin Max David, 2013. "Determinants of Research Production at Top Universities," Working Papers TIMES² 2014-007, ULB -- Universite Libre de Bruxelles.
    3. David Quentin, 2014. "Determinants of Research Production at Top US Universities," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 14(1), pages 81-109, January.
    4. Quentin David, 2009. "The Determinants of Research Production by U.S. Universities," DEM Discussion Paper Series 09-16, Department of Economics at the University of Luxembourg.
    5. Catherine Dehon & Marjorie Gassner & Vincenzo Verardi, 2011. "Extending the Hausman Test to Check for the presence of Outliers," Working Papers ECARES ECARES 2011-036, ULB -- Universite Libre de Bruxelles.

    More about this item

    Keywords

    Effciency; Hausman Test; Linear Regression; Outliers; Robustness; S-estimator;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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