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A Dynamic Factor Approach to Nonlinear Stability Analysis

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  • Mototsugu Shintani

Abstract

A method of principal components is employed to investigate nonlinear dynamic factor structure using a large panel data. The evidence suggests the possibility of nonlinearity in the U.S. while it excludes the class of nonlinearity that can generate endogenous fluctuation or chaos.
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Suggested Citation

  • Mototsugu Shintani, 2004. "A Dynamic Factor Approach to Nonlinear Stability Analysis," Levine's Bibliography 122247000000000621, UCLA Department of Economics.
    • Handle: RePEc:cla:levrem:122247000000000621
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    File URL: http://www.vanderbilt.edu/econ/wparchive/workpaper/vu04-w18.pdf
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    References listed on IDEAS

    as
    1. Shintani, Mototsugu & Linton, Oliver, 2004. "Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos," Journal of Econometrics, Elsevier, vol. 120(1), pages 1-33, May.
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    Cited by:

    1. Mototsugu Shintani & Zi-Yi Guo, 2018. "Improving the finite sample performance of autoregression estimators in dynamic factor models: A bootstrap approach," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 360-379, April.
    2. Shintani, Mototsugu & Guo, Zi-Yi, 2011. "Finite Sample Performance of Principal Components Estimators for Dynamic Factor Models: Asymptotic vs. Bootstrap Approximations," EconStor Preprints 167627, ZBW - Leibniz Information Centre for Economics.

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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