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Testing Models of Low-Frequency Variability

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  • 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.

Suggested Citation

  • Ulrich Mueller & Mark W. Watson, 2006. "Testing Models of Low-Frequency Variability," NBER Working Papers 12671, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:12671
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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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