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An analysis of the indicator saturation estimator as a robust regression

Author

Listed:
  • Søren Johansen

    (Department of Economics, University of Copenhagen)

  • Bent Nielsen

    (Department of Economics, University of Oxford)

Abstract

An algorithm suggested by Hendry (1999) for estimation in a regression with more regressors than observations, is analyzed with the purpose of finding an estimator that is robust to outliers and structural breaks. This estimator is an example of a one-step M-estimator based on Huber's skip function. The asymptotic theory is derived in the situation where there are no outliers or structural breaks using empirical process techniques. Stationary processes, trend stationary autoregressions and unit root processes are considered. Classification JEL: C32

Suggested Citation

  • Søren Johansen & Bent Nielsen, 2008. "An analysis of the indicator saturation estimator as a robust regression," Discussion Papers 08-03, University of Copenhagen. Department of Economics.
    • Handle: RePEc:kud:kuiedp:0803
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    File URL: http://www.econ.ku.dk/english/research/publications/wp/2008/0803.pdf/
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    Citations

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    Cited by:

    1. Søren Johansen & Bent Nielsen, 2010. "Discussion of The Forward Search: Theory and Data Analysis by Anthony C. Atkinson, Marco Riani, and Andrea Ceroli," Economics Papers 2010-W02, Economics Group, Nuffield College, University of Oxford.
    2. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Ragnar Nymoen, 2014. "Misspecification Testing: Non-Invariance of Expectations Models of Inflation," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 553-574, August.
    3. David Hendry & Grayham E. Mizon, 2012. "Forecasting from Structural Econometric Models," Economics Series Working Papers 597, University of Oxford, Department of Economics.
    4. Søren Johansen & Bent Nielsen, 2011. "Asymptotic theory for iterated one-step Huber-skip estimators," Discussion Papers 11-29, University of Copenhagen. Department of Economics.
    5. Hendry, David F., 2011. "On adding over-identifying instrumental variables to simultaneous equations," Economics Letters, Elsevier, vol. 111(1), pages 68-70, April.
    6. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
    7. Andrew B. Martinez, 2011. "Comparing Government Forecasts of the United States’ Gross Federal Debt," Working Papers 2011-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    8. David F. Hendry & Felix Pretis, 2013. "Anthropogenic influences on atmospheric CO2," Chapters, in: Roger Fouquet (ed.), Handbook on Energy and Climate Change, chapter 12, pages 287-326, Edward Elgar Publishing.
    9. David Hendry & Carlos Santos, 2010. "An Automatic Test of Super Exogeneity," Economics Series Working Papers 476, University of Oxford, Department of Economics.
    10. White, Halbert & Pettenuzzo, Davide, 2014. "Granger causality, exogeneity, cointegration, and economic policy analysis," Journal of Econometrics, Elsevier, vol. 178(P2), pages 316-330.
    11. David F. Hendry & Søren Johansen, 2011. "The Properties of Model Selection when Retaining Theory Variables," Discussion Papers 11-25, University of Copenhagen. Department of Economics.
    12. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2013. "Model Selection in Equations with Many ‘Small’ Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 6-22, February.
    13. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.
    14. Hendry, David F. & Johansen, Søren, 2015. "Model Discovery And Trygve Haavelmo’S Legacy," Econometric Theory, Cambridge University Press, vol. 31(1), pages 93-114, February.
    15. Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.
    16. Neil R. Ericsson, 2008. "The Fragility of Sensitivity Analysis: An Encompassing Perspective," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 895-914, December.
    17. J. James Reade & Ulrich Volz, 2011. "From the General to the Specific," Discussion Papers 11-18, Department of Economics, University of Birmingham.
    18. Neil R. Ericsson & Steven B. Kamin, 2008. "Constructive data mining: modeling Argentine broad money demand," International Finance Discussion Papers 943, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    Keywords

    empirical processes; Huber's skip; indicator saturation; M-estimator; outlier robustness; vector autoregressive process;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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