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Assesing HP Filter Performance for Argentina and U.S. Macro Aggregates

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  • Hildegart Ahumada

    ()

  • María Lorena Garegnani

    (Universidad Nacional de La Plata)

Abstract

Hodrick-Prescott filter has been the favourite empirical technique among researchers studying "cycles". Software facilities and the optimality criterion, from which the filter can be derived, can explain its wide use. However, different shortcomings and drawbacks have been pointed out in the literature, as alteration of variability and persistence and detecting spurious cycles and correlations. This paper discusses these criticisms from an empirical point of view trying to clarify what the filter can and cannot do. In particular, a less mechanical use for descriptive analysis is proposed: testing how the estimated cyclical component behaves and using autocorrelation adjusted standard errors to evaluate cross correlations to differentiate the "genuine" from "spurious" case. Simulation results to test these bivariate correlations when there is a "genuine" relationship are presented. Some examples of descriptive analysis for macro aggregates (real activity, trade flows and money) of Argentina and USA are reported to show that not always the filter is appropriate. Simple tools are used to appreciate how the filtered series result and to evaluate cross correlations.

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Bibliographic Info

Article provided by Universidad del CEMA in its journal Journal of Applied Economics.

Volume (Year): III (2000)
Issue (Month): (November)
Pages: 257-284

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Handle: RePEc:cem:jaecon:v:3:y:2000:n:2:p:257-284

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Keywords: HP filter; cycles; spurious cycles; genuine cross correlation;

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References

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  1. Uhlig, H.F.H.V.S. & Ravn, M., 1997. "On Adjusting the H-P Filter for the Frequency of Observations," Discussion Paper, Tilburg University, Center for Economic Research 1997-50, Tilburg University, Center for Economic Research.
  2. Finn E. Kydland & Edward C. Prescott, 1990. "Business cycles: real facts and a monetary myth," Quarterly Review, Federal Reserve Bank of Minneapolis, Federal Reserve Bank of Minneapolis, issue Spr, pages 3-18.
  3. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780198283164, October.
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  6. Canova, Fabio, 1994. "Detrending and turning points," European Economic Review, Elsevier, Elsevier, vol. 38(3-4), pages 614-623, April.
  7. Bardsen, G. & Fisher, P.G. & Nymoen, R., 1994. "Business Cycles: Real Facts or Fallacies?," Papers, Norwegian School of Economics and Business Administration- 20-94, Norwegian School of Economics and Business Administration-.
  8. Edward C. Prescott, 1986. "Theory ahead of business cycle measurement," Staff Report, Federal Reserve Bank of Minneapolis 102, Federal Reserve Bank of Minneapolis.
  9. Hendry, David F & Mizon, Grayham E, 1978. "Serial Correlation as a Convenient Simplification, not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 88(351), pages 549-63, September.
  10. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 8(3), pages 231-47, July-Sept.
  11. Finn E. Kydland & Calos E.J.M.Zarazaga, 1997. "Is the business cycle of Argentina "different?"," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, Federal Reserve Bank of Dallas, issue Q IV, pages 21-36.
  12. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 17(1-2), pages 207-231.
  13. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 19(1-2), pages 253-278.
  14. Singleton, Kenneth J., 1988. "Econometric issues in the analysis of equilibrium business cycle models," Journal of Monetary Economics, Elsevier, Elsevier, vol. 21(2-3), pages 361-386.
  15. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, Econometric Society, vol. 50(6), pages 1345-70, November.
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Cited by:
  1. Ton Kwaak & Werner Liebregts, 2012. "Time series for main variables on the performance of Dutch SMEs," Scales Research Reports, EIM Business and Policy Research H201204, EIM Business and Policy Research.
  2. José Luis Arrufat & Alberto Martín Díaz Cafferata & José Antonio Viceconte, 2011. "Terms of trade cycles in extreme land abundant countries, 1870-2009. Spectral analysis," Working Papers, Instituto Universitario de Análisis Económico y Social 05/11, Instituto Universitario de Análisis Económico y Social.
  3. María Virginia Mattheus & Alberto Martín Díaz Cafferata, 2011. "Co-movements in terms of trade volatility in land-abundant countries," Working Papers, Instituto Universitario de Análisis Económico y Social 07/11, Instituto Universitario de Análisis Económico y Social.

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