Abstract: The paper examines the properties of standard data transformations--such as growth rates and moving averages--used by applied economists. Because many resources are devoted to understanding the economic significance of incoming data by government and financial-market economists, for example, this paper considers data filters that do not drop recent observations, in contrast to the approximately "ideal" measures recently developed in the literature. Using frequency-domain techniques, it is established that moving averages of multi-period growth rates can attenuate the bias and phase shifts introduced by common data filters.

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