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Linear data transformations used in economics

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  • Darrel Cohen

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.

Suggested Citation

  • Darrel Cohen, 2001. "Linear data transformations used in economics," Finance and Economics Discussion Series 2001-59, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:2001-59
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    References listed on IDEAS

    as
    1. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    2. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
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    Cited by:

    1. Ard den Reijer, 2006. "The Dutch business cycle: which indicators should we monitor?," DNB Working Papers 100, Netherlands Central Bank, Research Department.
    2. André Nunes Maranhão & Nicole Rennó Castro, 2023. "Dissecting Brazilian agriculture business cycles in high-dimensional and time-irregular span contexts," Empirical Economics, Springer, vol. 65(4), pages 1543-1578, October.
    3. William Miles, 2015. "Regional House Price Segmentation and Convergence in the US: A New Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 50(1), pages 113-128, January.

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    Filters (Mathematics);

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