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General trimmed estimation: robust approach to nonlinear and limited dependent variable models

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Author Info
Cizek, P. (Tilburg University, Center for Economic Research)

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Abstract

High breakdown-point regression estimators protect against large errors and data contamination. Motivated by some { the least trimmed squares and maximum trimmed likelihood estimators { we propose a general trimmed estimator, which uni-es and extends many existing robust procedures. We derive here the consistency and rate of convergence of the proposed general trimmed estimator under mild --mixing conditions and demonstrate its applicability in nonlinear regression, time series, limited dependent variable models, and panel data.

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Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 130.

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Date of creation: 2004
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Handle: RePEc:dgr:kubcen:2004130

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models
C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Donald Andrews, 1993. "An introduction to econometric applications of empirical process theory for dependent random variables," Econometric Reviews, Taylor and Francis Journals, vol. 12(2), pages 183-216. [Downloadable!] (restricted)
  2. repec:cup:etheor:v:8:y:1992:i:2:p:241-57 is not listed on IDEAS
  3. Agullo, Jose, 2001. "New algorithms for computing the least trimmed squares regression estimator," Computational Statistics & Data Analysis, Elsevier, vol. 36(4), pages 425-439, June. [Downloadable!] (restricted)
  4. Andrews, Donald W. K., 1987. "Laws of Large Numbers for Dependent Non-Identically Distributed Random Variables," Working Papers 645, California Institute of Technology, Division of the Humanities and Social Sciences. [Downloadable!]
  5. Pavel Cizek, 2002. "Robust Estimation with Discrete Explanatory Variables," Econometrics 0203001, EconWPA. [Downloadable!]
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  6. Donald W.K. Andrews, 1990. "Generic Uniform Convergence," Cowles Foundation Discussion Papers 940, Cowles Foundation, Yale University. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Cizek, Pavel, 2006. "Efficient robust estimation of regression models," Discussion Paper 8, Tilburg University, Center for Economic Research.
  2. Pavel Cizek & Wolfgang Härdle, 2006. "Robust Econometrics," SFB 649 Discussion Papers SFB649DP2006-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  3. Cizek, Pavel, 2005. "Trimmed likelihood-based estimation in binary regression models," Discussion Paper 108, Tilburg University, Center for Economic Research. [Downloadable!]
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