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Testing Models of Low-Frequency Variability

  • Ulrich Mueller
  • Mark W. Watson

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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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 12671.

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Date of creation: Nov 2006
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Publication status: published as Müller, Ulrich K. and Mark W. Watson. "Testing Models of Low-Frequency Variability." Econometrica 76, 5 (2008): 979-1016.
Handle: RePEc:nbr:nberwo:12671
Note: EFG ME
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