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Pearson M-Estimators in Regression Analysis

Author

Listed:
  • Magdalinos, M.A.
  • Mitsopoulos, G.P.

Abstract

This paper derives and adaptive partial solution for the maximum likelihood normal equations of a regression, under the assumption that the errors belong to the Pearson family. This estimator can be "robustified" producing a M-estimator with satisfactory efficiency for a wider range of error distributions. Monte-Carlo evidence on the finite sample properties of the estimates is reported. The computational requirements are very modest: all the proposed improvements can be computed with the help of an auxilliary regression.

Suggested Citation

  • Magdalinos, M.A. & Mitsopoulos, G.P., 1995. "Pearson M-Estimators in Regression Analysis," Discussion Papers 9517, University of Exeter, Department of Economics.
    • Handle: RePEc:exe:wpaper:9517
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    Keywords

    ECONOMETRICS;

    JEL classification:

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

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