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Consecuencias para la predicción de la existencia de caos utilizando modelos TAR

Listed author(s):
  • Lorenzo Escot Mangas

    (Departamento de Economía Aplicada III (Política Económica). Universidad Complutense de Madrid.)

  • Ricardo Gimeno Nogués

    (Facultad de Ciencias Económicas y Empresariales. Universidad Complutense de Madrid.)

  • Pilar Grau Carles

    (Facultad de Ciencias Económicas y Empresariales. Universidad Complutense de Madrid.)

  • Ruth Mateos de Cabo

    (Facultad de Ciencias Económicas y Empresariales. Universidad Complutense de Madrid.)

  • Elena Olmedo Fernández

    (Facultad de Ciencias Económicas y Empresariales. Universidad Complutense de Madrid.)

En el presente trabajo se analizan las consecuencias que tiene para la predicción de datos de coyuntura española, en concreto para las importaciones nominales de bienes intermedios, la detección de indicios de comportamiento caótico. Para esta detección se ha utilizado una estimación de un modelo tipo umbral autorregresivo (TAR) y se ha representado gráficamente su diagrama de bifurcación. En concreto, se analizan las diferencias cuando el modelo presenta dinámica caótica y cuando no las presenta tanto en la estimación de los parámetros como en los errores de predicción.

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Paper provided by Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales in its series Documentos de trabajo de la Facultad de Ciencias Económicas y Empresariales with number 03-10.

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Length: 35 pages
Date of creation: 2003
Handle: RePEc:ucm:doctra:03-10
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