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Testing models of low-frequency variability

Author: Uli Mueller; Mark W Watson; National Bureau of Economic Research.
Publisher: Cambridge, Mass. : National Bureau of Economic Research, 2006.
Series: Working paper series (National Bureau of Economic Research), no. 12671.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
We develop a framework to assess how successfully standard times eries models explain low-frequency variability of a data series. The low-frequency information is extracted by computing a finite number of weighted averages of the original data, where the weights are low-frequency trigonometric series. The properties of these weighted averages are then compared to the asymptotic implications of a number of common  Read more...
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Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Uli Mueller; Mark W Watson; National Bureau of Economic Research.
OCLC Number: 75394912
Description: 1 online resource (1 volume).
Series Title: Working paper series (National Bureau of Economic Research), no. 12671.
Responsibility: Ulrich Mueller, Mark W. Watson.

Abstract:

We develop a framework to assess how successfully standard times eries models explain low-frequency variability of a data series. The low-frequency information is extracted by computing a finite number of weighted averages of the original data, where the weights are low-frequency trigonometric series. The properties of these weighted averages are then compared to the asymptotic implications of a number of common time series models. We apply the framework to twenty U.S. macroeconomic and financial time series using frequencies lower than the business cycle.

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