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- W2890169934 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." @default.
- W2890169934 created "2018-09-27" @default.
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- W2890169934 date "2006-11-01" @default.
- W2890169934 modified "2023-09-27" @default.
- W2890169934 title "Testing Models of Low-Frequency Variability" @default.
- W2890169934 hasPublicationYear "2006" @default.
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