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Filters for Short Nonstationary Sequences

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Author Info

  • Stephen Pollock

    (Queen Mary, University of London)

Abstract

This paper describes a methodology for implementing bidirectional frequency-selective filters in cases where the data sequence is short and nonstationary. A simple method is proposed for dealing with the start-up problem. The method has a firm theoretical basis and it is computationally efficient.

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File URL: http://www.econ.qmul.ac.uk/papers/doc/wp423.pdf
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Bibliographic Info

Paper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 423.

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Date of creation: Oct 2000
Date of revision:
Handle: RePEc:qmw:qmwecw:wp423

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Related research

Keywords: Signal extraction; Linear Filtering; Frequency-domain analysis; Trend estimation;

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Cited by:
  1. Pollock, D.S.G., 2006. "Econometric methods of signal extraction," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2268-2292, May.
  2. Iolanda Lo Cascio & Stephen Pollock, 2007. "Comparative Economic Cycles," Working Papers 599, Queen Mary, University of London, School of Economics and Finance.
  3. McElroy, Tucker & Sutcliffe, Andrew, 2006. "An iterated parametric approach to nonstationary signal extraction," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2206-2231, May.
  4. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
  5. Stephen Pollock, 2001. "Signal Extraction, Maximum Likelihood Estimation and the Start-up Problem," Working Papers 433, Queen Mary, University of London, School of Economics and Finance.

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