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Convergencia y Estabilidad de los Tipos de Cambio Europeos: Una Aplicación de Exponentes de Lyapunov

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Author Info
Elena Olmedo
Ricardo Gimeno
Lorenzo Escot
Ruth Mateos

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Abstract

In this paper we applied the dynamic system theory to the measurement of the stability of the European process of convergence. In particular, Lyapunov’s exponents are used to verify the influence of political and economic decisions made during the creation of the European Union on the stability (or instability) of exchange rate fluctuation in different European countries. We find evidence of such relationship.

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Publisher Info
Article provided by Instituto de Economía. Pontificia Universidad Católica de Chile. in its journal Cuadernos de Economía.

Volume (Year): 44 (2007)
Issue (Month): 129 ()
Pages: 91-108
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Handle: RePEc:ioe:cuadec:v:44:y:2007:i:129:p:91-108

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Related research
Keywords: Estabilidad; Sistemas Dinámicos; Convergencia Europea; Euro; Exponente de Lyapunov; Redes Neuronales.;

Find related papers by JEL classification:
C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis
F02 - International Economics - - General - - - International Economic Order; Noneconomic International Organizations;; Economic Integration and Globalization: General

References listed on IDEAS
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  1. Bask, Mikael, 2000. "A Positive Lyapunov Exponent in Swedish Exchange Rates?," UmeÃ¥ Economic Studies 528, Umeå University, Department of Economics.
  2. Barnett, William A. & Ronald Gallant, A. & Hinich, Melvin J. & Jungeilges, Jochen A. & Kaplan, Daniel T. & Jensen, Mark J., 1995. "Robustness of nonlinearity and chaos tests to measurement error, inference method, and sample size," Journal of Economic Behavior & Organization, Elsevier, vol. 27(2), pages 301-320, July. [Downloadable!] (restricted)
  3. Mototsugu Shintani & Oliver Linton, 2003. "Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(1), pages 331-357, February. [Downloadable!] (restricted)
    Other versions:
  4. E.K. Berndt & B.H. Hall & R.E. Hall, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 103-116 National Bureau of Economic Research, Inc. [Downloadable!]
  5. Chung-Ming Kuan & Halbert White, 1994. "Artificial neural networks: an econometric perspective," Econometric Reviews, Taylor and Francis Journals, vol. 13(1), pages 1-91. [Downloadable!] (restricted)
    Other versions:
  6. Dechert, W D & Gencay, R, 1992. "Lyapunov Exponents as a Nonparametric Diagnostic for Stability Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S41-60, Suppl. De. [Downloadable!] (restricted)
  7. Abhyankar, A & Copeland, L S & Wong, W, 1997. "Uncovering Nonlinear Structure in Real-Time Stock-Market Indexes: The S&P 500, the DAX, the Nikkei 225, and the FTSE-100," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 1-14, January.
  8. 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. [Downloadable!] (restricted)
    Other versions:
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