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Robust Estimation with Discrete Explanatory Variables

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  • Pavel Cizek

Abstract

The least squares estimator is probably the most frequently used estimation method in regression analysis. Unfortunately, it is also quite sensitive to data contamination and model misspecification. Although there are several robust estimators designed for parametric regression models that can be used in place of least squares, these robust estimators cannot be easily applied to models containing binary and categorical explanatory variables. Therefore, I design a robust estimator that can be used for any linear regression model no matter what kind of explanatory variables the model contains. Additionally, I propose an adaptive procedure that maximizes the efficiency of the proposed estimator for a given data set while preserving its robustness.

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Bibliographic Info

Paper provided by The Center for Economic Research and Graduate Education - Economic Institute, Prague in its series CERGE-EI Working Papers with number wp183.

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Date of creation: Nov 2001
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Handle: RePEc:cer:papers:wp183

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Keywords: discrete explanatory variables; linear regression; robust statistics; least trimmed squares;

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References

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  1. Zaman, Asad & Rousseeuw, Peter J. & Orhan, Mehmet, 2001. "Econometric applications of high-breakdown robust regression techniques," Economics Letters, Elsevier, vol. 71(1), pages 1-8, April.
  2. repec:wop:humbsf:2001-25 is not listed on IDEAS
  3. Franco Peracchi, 1988. "Robust M-Estimators," UCLA Economics Working Papers 477, UCLA Department of Economics.
  4. White, Halbert, 1980. "Nonlinear Regression on Cross-Section Data," Econometrica, Econometric Society, vol. 48(3), pages 721-46, April.
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Cited by:
  1. Cizek, P., 2007. "General Trimmed Estimation: Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaces DP 2007-1)," Discussion Paper 2007-65, Tilburg University, Center for Economic Research.
  2. Cizek, P., 2006. "Efficient Robust Estimation of Regression Models (Replaced by DP 2007-87)," Discussion Paper 2006-8, Tilburg University, Center for Economic Research.
  3. Cizek, P., 2007. "General Trimmed Estimation: Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaced by DP 2007-65)," Discussion Paper 2007-1, Tilburg University, Center for Economic Research.
  4. Čížek, Pavel, 2008. "General Trimmed Estimation: Robust Approach To Nonlinear And Limited Dependent Variable Models," Econometric Theory, Cambridge University Press, vol. 24(06), pages 1500-1529, December.

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