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Investigating Economic Trends And Cycles

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  • D.S.G. Pollock

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Abstract

Methods are described for extracting the trend from an economic data sequence and for isolating the cycles that surround it. The latter often consist of a business cycle of variable duration and a perennial seasonal cycle. There is no evident point in the frequency spectrum where the trend ends and the business cycle begins. Therefore, unless it can be represented by a simple analytic function, such as an exponential growth path, there is bound to be a degree of arbitrariness in the definition of the trend. The business cycle, however defined, is liable to have an upper limit to its frequency range that falls short of the Nyquist frequency, which is the maximum observable frequency in sampled data. This must be taken into account in fitting an ARMA model to the detrended data.

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File URL: http://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp07-17.pdf
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Bibliographic Info

Paper provided by Department of Economics, University of Leicester in its series Discussion Papers in Economics with number 07/17.

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Date of creation: Nov 2007
Date of revision: Apr 2008
Handle: RePEc:lec:leecon:07/17

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  1. D. S. G. Pollock, 2002. "A review of TSW: the Windows version of the TRAMO-SEATS program," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(3), pages 291-299.
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Cited by:
  1. Proietti, Tommaso, 2008. "Band spectral estimation for signal extraction," Economic Modelling, Elsevier, vol. 25(1), pages 54-69, January.
  2. Kitov, Ivan & Kitov, Oleg, 2012. "Real GDP per capita since 1870," MPRA Paper 39021, University Library of Munich, Germany.
  3. D.S.G. Pollock, 2008. "IDEOLOG: A Program for Filtering Econometric Data - A Synopsis of Alternative Methods," Discussion Papers in Economics 08/21, Department of Economics, University of Leicester.
  4. Willi Leibfritz & Gebhard Flaig, 2013. "Economic Growth in Africa: Comparing Recent Improvements with the "lost 1980s and early 1990s" and Estimating New Growth Trends," CESifo Working Paper Series 4215, CESifo Group Munich.
  5. Blöchl, Andreas, 2014. "Trend Estimation with Penalized Splines as Mixed Models for Series with Structural Breaks," Discussion Papers in Economics 18446, University of Munich, Department of Economics.

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