Band Spectral Estimation for Signal Extraction

Tommaso Proietti

CEIS Research Paper from Tor Vergata University, CEIS

Abstract: The paper evaluates the potential of band spectral estimation for extracting signals in economic time series. Two situations are considered. The first deals with trend extraction when the original data have been permanently altered by routine operations, such as prefiltering, temporal aggregation and disaggregation, and seasonal adjustment, which modify the high frequencies properties of economic time series. The second is when the measurement model is only partially specified, in that it aims at fitting the series in a particular frequency range, e.g. at interpreting the long run behaviour. These issues are illustrated with reference to a simple structural model, namely the random walk plus noise model.

Keywords: Temporal Aggregation; Seasonal Adjustment; Trend Component; Frequency Domain. (search for similar items in EconPapers)
JEL-codes: C22 E3 (search for similar items in EconPapers)
Pages: 29
Date: 2007-05-21
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mac
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https://ceistorvergata.it/RePEc/rpaper/No-104.pdf (application/pdf)

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Journal Article: Band spectral estimation for signal extraction (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:rtv:ceisrp:104

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