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The Unscientific Incompleteness and Bias of Unidirectional Projections (= Regressions): A Questionnaire

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  • Cornelis A Los

Abstract

Why do statisticians (econometricians, economists, financial analysts, etc.) continue to incompletely identify the algebraic/geometric structure of the multi-variate data series they profess to analyze, and instead continue to publish the results of incomplete, prejudiced and biased unidirectional projections (= 'regressions') of such covariance structures? Such incomplete, prejudiced and biased representations cannot lead to scientific knowledge, as has been demonstrated already more than twenty years ago.

Suggested Citation

  • Cornelis A Los, 2004. "The Unscientific Incompleteness and Bias of Unidirectional Projections (= Regressions): A Questionnaire," Econometrics 0410011, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0410011
    Note: Type of Document - pdf; pages: 6. Please, respond to this questionnaire with polite and concise answers. Your contibution will be properly acknowledged.
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0410/0410011.pdf
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    References listed on IDEAS

    as
    1. Los, Cornelis A., 1999. "Galton's Error and the under-representation of systematic risk," Journal of Banking & Finance, Elsevier, vol. 23(12), pages 1793-1829, December.
    2. R. E. Kalman & Cornelis A. Los, 1987. "The prejudices of least squares, principal components and common factor schemes," Research Paper 8701, Federal Reserve Bank of New York.
    3. Cornelis A. Los, 1987. "Identification of a linear system from inexact data: a three variable example," Research Paper 8703, Federal Reserve Bank of New York.
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    Cited by:

    1. Cornelis Los, 2004. "Measuring the Degree of Efficiency of Financial Market," Finance 0411003, University Library of Munich, Germany.

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    More about this item

    Keywords

    system identification; noisy data; regression analysis; projection; incompleteness; prejudice; bias;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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