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On the Typical Spectral Shape of an Economic Variable

  • Daniel Levy

    (Bar-Ilan & Emory)

  • Hashem Dezhbakhsh

    (Emory)

In a classical article, Granger (1966) argued that the levels of most economic time series have spectra that exhibit a smooth declining shape with considerable power at very low frequencies. He termed it "the typical spectral shape of an economic variable." Granger's assertion has not been examined systematically with international data. We estimate output level spectra for 58 countries, divided into developed, high- income developing, and low-income developing groups. We find the shapes of the estimated spectra to be strikingly similar to Granger's typical shape, particularly for the developed countries.

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File URL: http://econwpa.repec.org/eps/mac/papers/0402/0402017.pdf
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Paper provided by EconWPA in its series Macroeconomics with number 0402017.

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Length: 17 pages
Date of creation: 07 Feb 2004
Date of revision:
Handle: RePEc:wpa:wuwpma:0402017
Note: Type of Document - pdf; prepared on Win 98; to print on Any printer; pages: 17; figures: Figures are included
Contact details of provider: Web page: http://econwpa.repec.org

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  1. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
  2. Daniel Levy & Haiwei Chen, 2005. "Estimates of the Aggregate Quarterly Capital Stock for the Post- War U.S. Economy," Others 0505008, EconWPA, revised 16 May 2005.
  3. John Y. Campbell & N. Gregory Mankiw, 1988. "International Evidence on the Persistence of Economic Fluctuations," NBER Working Papers 2498, National Bureau of Economic Research, Inc.
  4. Daniel Levy, 2005. "Investment-Saving Comovement and Capital Mobility: Evidence from Century Long U.S. Time Series," International Finance 0505006, EconWPA, revised 16 May 2005.
  5. 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.
  6. Daniel Levy & Hashem Dezhbakhsh, 2004. "International Evidence on Output Fluctuation and Shock Persistence," Macroeconomics 0402016, EconWPA.
  7. Prescott, Edward C., 1986. "Theory ahead of business-cycle measurement," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 25(1), pages 11-44, January.
  8. Granger, C.W.J. & Watson, Mark W., 1984. "Time series and spectral methods in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 17, pages 979-1022 Elsevier.
  9. King, Robert G & Watson, Mark W, 1996. "Money, Prices, Interest Rates and the Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 35-53, February.
  10. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-73, September.
  11. Lawrence H. Summers, 1982. "The Nonadjustment of Nominal Interest Rates: A Study of the Fisher Effect," NBER Working Papers 0836, National Bureau of Economic Research, Inc.
  12. Carpenter, Robert E & Levy, Daniel, 1998. "Seasonal Cycles, Business Cycles, and the Comovement of Inventory Investment and Output," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 30(3), pages 331-46, August.
  13. Daniel Levy, 2005. "Output, Capital, and Labor in the Short, and Long-Run," Development and Comp Systems 0505012, EconWPA.
  14. Zarnowitz, Victor, 1992. "Business Cycles," National Bureau of Economic Research Books, University of Chicago Press, number 9780226978901.
  15. Lucas, Robert E, Jr, 1980. "Two Illustrations of the Quantity Theory of Money," American Economic Review, American Economic Association, vol. 70(5), pages 1005-14, December.
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