A New Hausmann Type Test to Detect the Presence of Influential Outliers
AbstractIn 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.
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Bibliographic InfoPaper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers ECARES with number 2008_006.
Length: 26 p.
Date of creation: 2008
Date of revision:
Publication status: Published by:
Effciency; Hausman Test; Linear Regression; Outliers; Robustness; S-estimator;
Find related papers by 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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- 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.
- Quentin David, 2009. "The Determinants of Research Production by U.S. Universities," CREA Discussion Paper Series 09-16, Center for Research in Economic Analysis, University of Luxembourg.
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