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The local quadratic trend model

  • Andrew Harvey

    (Faculty of Economics and Politics, University of Cambridge, UK)

The local quadratic trend model provides a flexible response to underlying movements in a macroeconomic time series in its estimates of level and change. If the underlying movements are thought of as a trend plus cycle, an estimate of the cycle may be obtained from the quadratic term. Estimating the cycle in this way may offer a useful alternative to other model-based methods of signal extraction, particularly when the series is short. The properties of the filter used to extract the cycle are analysed in the frequency domain and the technique is illustrated with macroeconomic time series from several countries. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1144
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 29 (2010)
Issue (Month): 1-2 ()
Pages: 94-108

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Handle: RePEc:jof:jforec:v:29:y:2010:i:1-2:p:94-108
DOI: 10.1002/for.1144
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Marianne Baxter & Robert G. King, 1995. "Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series," NBER Working Papers 5022, National Bureau of Economic Research, Inc.
  2. A. C. Harvey & Siem Jan Koopman, 2000. "Computing Observation Weights for Signal Extraction and Filtering," Econometric Society World Congress 2000 Contributed Papers 0888, Econometric Society.
  3. Gomez, Victor, 2001. "The Use of Butterworth Filters for Trend and Cycle Estimation in Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 365-73, July.
  4. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
  5. Harvey, Andrew C. & Trimbur, Thomas M. & Van Dijk, Herman K., 2007. "Trends and cycles in economic time series: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 618-649, October.
  6. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543, December.
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