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Notes on Time Series Analysis, ARIMA Models and Signal Extraction

  • Regina Kaiser


    (Universidad Carlos III de Madrid)

  • Agustín Maravall


    (Banco de España)

Present practice in applied time series work, mostly at economic policy or data producing agencies, relies heavily on using moving average filters to estimate unobserved components in time series, such as the seasonally adjusted series, the trend, or the cycle. The purpose of the present paper is to provide an informal introduction to the time series analysis tools and concepts required by the user or analyst to understand the basic methodology behind the application of filters.

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Paper provided by Banco de Espa�a in its series Banco de Espa�a Working Papers with number 0012.

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Length: 73 pages
Date of creation: 2000
Date of revision:
Handle: RePEc:bde:wpaper:0012
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  1. Burridge, Peter & Wallis, Kenneth F, 1984. "Unobserved-Components Models for Seasonal Adjustment Filters," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 350-59, October.
  2. Agustín Maravall & Cristophe Planas, 1996. "Estimation Error and the Specification of Unobserved Component Models," Banco de Espa�a Working Papers 9608, Banco de Espa�a.
  3. Edward C. Prescott, 1986. "Theory ahead of business cycle measurement," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages 9-22.
  4. David A. Pierce, 1978. "Seasonal Adjustment When Both Deterministic and Stochastic Seasonality Are Present," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 242-280 National Bureau of Economic Research, Inc.
  5. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-52, April.
  6. David A. Pierce, 1978. "Seasonal adjustment when both deterministic and stochastic seasonality are present," Special Studies Papers 107, Board of Governors of the Federal Reserve System (U.S.).
  7. Gomez, Victor, 1999. "Three Equivalent Methods for Filtering Finite Nonstationary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 109-16, January.
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