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Consecuencias de la modelizacion ARIMA para la extraccion de senales en coyuntura


  • Ernest Pons Fanals
  • Jordi Surinach Caralt

    (Universitat de Barcelona)


In short-term evolution analysis, the economic time series are contamined by different types of noises which need to be erased in order to extract a trend signal. In the last years there has been increasingly developed some methods to estimate unobserved components based on the assumption that the economic series and their components follow ARIMA models. Nevertheless few atention has been focused to the practical consequences that arise from this assumption. In this paper, we discuss about some consequences from the ARIMA model based estimation of trend signal on economic time series, and relate that with its memory characteristics. Finally some of this problems are illustrated with the Spanish Industrial Production Index.

Suggested Citation

  • Ernest Pons Fanals & Jordi Surinach Caralt, 1999. "Consecuencias de la modelizacion ARIMA para la extraccion de senales en coyuntura," Working Papers in Economics 52, Universitat de Barcelona. Espai de Recerca en Economia.
  • Handle: RePEc:bar:bedcje:199952

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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles


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