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A single-blind controlled competition among tests for nonlinearity and chaos

Author

Listed:
  • Barnett, William A.
  • Gallant, A. Ronald
  • Hinich, Melvin J.
  • Jungeilges, Jochen A.
  • Kaplan, Daniel T.
  • Jensen, Mark J.

Abstract

This is the FINAL draft of this paper reporting the results of a long ongoing competition. The paper now is forthcoming in the Journal of Econometrics. This final version replaces the earlier draft that was also in this archive. Interest has been growing in testing for nonlinearity or chaos in economic data, but much controversy has arisen about the available results. This paper explores the reasons for these empirical difficulties. We apply five highly regarded tests for nonlinearity or chaos to ten simulated data series. The data generating mechanisms include linear processes, chaotic recursions, and nonchaotic stochastic processes; and both large and small samples were included in the experiment. The data series were produced in a single blind manner by the competition manager and sent by e-mail, without identifying information, to the experiment participants. Each such participant is an acknowledged expert in one of the tests and has a possible vested interest in producing the best possible results with that one test. The results of this competition provide much surprising information about the power functions of some of the best regarded tests for nonlinearity or noisy chaos. The simulated data and the code for some of the tests entered into this competition also are online in this archive.
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Suggested Citation

  • Barnett, William A. & Gallant, A. Ronald & Hinich, Melvin J. & Jungeilges, Jochen A. & Kaplan, Daniel T. & Jensen, Mark J., 1997. "A single-blind controlled competition among tests for nonlinearity and chaos," Journal of Econometrics, Elsevier, vol. 82(1), pages 157-192.
    • Handle: RePEc:eee:econom:v:82:y:1997:i:1:p:157-192
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    1. William A. Barnett & A. Ronald Gallant & Melvin J. Hinich & Jochen A. Jungeilges & Daniel T. Kaplan, 2004. "Robustness of Nonlinearity and Chaos Tests to Measurement Error, Inference Method, and Sample Size," Contributions to Economic Analysis, in: Functional Structure and Approximation in Econometrics, pages 529-548, Emerald Group Publishing Limited.
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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates

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