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Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors

  • Oliver Linton

    ()

  • Mototsugu Shintani

A positive Lyapunov exponent is one pratical definition of chaos. We develop a formal test for chaos in a noisy system based on the sign of the Lyapunov exponent. The test utilizes nonparametric regression techniques including local quadratic regression and neural networks. When our procedures are applied to international real output series, the Lyapunov exponent estimates are negative and the positivity hypothesis of the expononent is significantly rejected in many cases. One possible interpretation of this result is that the traditional exogenous models are better able to explain business cycle fluctuations than is the chaotic endogenous approach. However, our results are subject to a number of caveats, in particular our results could have been influenced by small sample bias, high noise level, incorrect filtering, and long memory of the data.

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File URL: http://www.lse.ac.uk/fmg/workingPapers/discussionPapers/fmg_pdfs/dp383.pdf
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Paper provided by Financial Markets Group in its series FMG Discussion Papers with number dp383.

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Date of creation: Jun 2001
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Handle: RePEc:fmg:fmgdps:dp383
Contact details of provider: Web page: http://www.lse.ac.uk/fmg/

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  1. Durlauf, Steven N, 1993. "Nonergodic Economic Growth," Review of Economic Studies, Wiley Blackwell, vol. 60(2), pages 349-66, April.
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  3. Mototsugu Shintani & Oliver Linton, 2003. "Nonparametric Neural Network Estimation of Lyapunov Exponents and a Direct Test for Chaos," Vanderbilt University Department of Economics Working Papers 0309, Vanderbilt University Department of Economics.
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