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Multicollinearity and maximum entropy leuven estimator

Author

Listed:
  • Sudhanshu Mishra

    (North-Eastern Hill University)

Abstract

Multicollinearity is a serious problem in applied regression analysis. Q. Paris (2001) introduced the MEL estimator to resolve the multicollinearity problem. This paper improves the MEL estimator to the Modular MEL (MMEL) estimator and shows by Monte Carlo experiments that MMEL estimator performs significantly better than OLS as well as MEL estimators.

Suggested Citation

  • Sudhanshu Mishra, 2004. "Multicollinearity and maximum entropy leuven estimator," Economics Bulletin, AccessEcon, vol. 3(25), pages 1-11.
    • Handle: RePEc:ebl:ecbull:eb-04c10016
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    File URL: http://www.accessecon.com/pubs/EB/2004/Volume3/EB-04C10016A.pdf
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    References listed on IDEAS

    as
    1. Quirino Paris, 2001. "Multicollinearity and maximum entropy estimators," Economics Bulletin, AccessEcon, vol. 3(11), pages 1-9.
    2. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Mishra, SK, 2012. "A comparative study of trends in globalization using different synthetic indicators," MPRA Paper 38028, University Library of Munich, Germany.
    2. Mishra, SK, 2004. "Estimation under Multicollinearity: Application of Restricted Liu and Maximum Entropy Estimators to the Portland Cement Dataset," MPRA Paper 1809, University Library of Munich, Germany.
    3. Sudhanshu K. MISHRA, 2016. "Shapley Value Regression and the Resolution of Multicollinearity," Journal of Economics Bibliography, KSP Journals, vol. 3(3), pages 498-515, September.

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    More about this item

    Keywords

    maximum entropy;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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