Advertisement

Spectral Analysis for Economic Time Series

  • Alessandra Iacobucci
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 551)

Summary

The last ten years have witnessed an increasing interest of the econometrics community in spectral theory. In fact, decomposing the series evolution in periodic contributions allows a more insightful view of its structure and of its cyclical behavior at different time scales. In this paper, the issues of cross-spectral analysis and filtering are concisely broached, dwelling in particular upon the windowed filter [15]. In order to show the usefulness of these tools, an application to real data — namely to US unemployment and inflation — is presented. By means of cross spectral analysis and filtering, a correlation can be found between these two quantities (i.e. the Phillips curve) in some specific frequency bands, even if it does not appear in raw data.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bartlett, M. S., An Introduction to Stochastic Processes with Special Reference to Methods and Applications, Cambridge University Press, Cambridge (1953).Google Scholar
  2. 2.
    Baxter, M. and R. G. King, “Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series”, The Review of Economics and Statistics vol. 8, no. 4 (November 1999), pp. 575–93.Google Scholar
  3. 3.
    Benati, L., “Band-Pass Filtering, Cointegration and Business Cycle Analysis”, Bank of England, working paper (2001).Google Scholar
  4. 4.
    Box, G. E. P., G. M. Jenkins and G. C. Reinsel, Time Series Analysis. Forecasting and Control, third edition, Prentice Hall, Upper Saddle River, New Jersey (1994).Google Scholar
  5. 5.
    Christiano, L. and T. J. Fitzgerald, “The Band-Pass Filter”, International Economic Review, vol. 44, no. 2, May 2003.Google Scholar
  6. 6.
    Hamilton, J. D., “Time Series Analysis”, Princeton University Press, Princeton, New Jersey (1994).Google Scholar
  7. 7.
    Hamming, R. W., Numerical Methods for Scientists and Engineers, second edition, Dover Publications, Inc., New York, 1973.Google Scholar
  8. 8.
    Hamming, R. W., Digital Filters, third edition, Dover Publications, Inc., New York, 1998.Google Scholar
  9. 9.
    Hodrick, R. J. and E. C. Prescott, “Postwar US Business Cycles: An Empirical Investigation”, Journal of Money, Credit, and Banking, vol. 29-1 (1997), pp. 1–16.Google Scholar
  10. 10.
    Gaffard, J. L. and A. Iacobucci, “The Phillips Curve: Old Theories and New Statistics”, mimeo.Google Scholar
  11. 11.
    Granger, C. W. J. and M. Hatanaka, Spectral Analysis of Economic Time Series, Princeton University Press, Princeton, New Jersey (1964).Google Scholar
  12. 12.
    Granger, C. W. J, “The Typical Spectral Shape of an Economic Variable”, Econometrica, vol. 34(1), (1966), pp. 150–161.Google Scholar
  13. 13.
    Granger, C. W. J, “Investigating Casual Relations by Econometric Models and Cross-Spectral Methods”, Econometrica, vol. 37(3), (1969), pp. 424–438.MathSciNetGoogle Scholar
  14. 14.
    Haldane, A. and D. Quah, “UK Phillips Curves and Monetary Policy”, Journal of Monetary Economics, Special Issue: The Return of the Phillips Curve, vol. 44, no. 2, (1999), pp. 259–278.Google Scholar
  15. 15.
    Iacobucci, A. and A. Noullez, “Frequency Filters for Short Length Time Series”, Working Paper IDEFI-IDEE 2002, n. 1.Google Scholar
  16. 16.
    Jenkins, G. M. and D. G. Watts, Spectral Analysis and Its Applications, Holden-Day, San Francisco, (1969).Google Scholar
  17. 17.
    Lee, J., “The Phillips Curve Behavior Over Different Horizons”, Journal of Economics and Finance, 19 (1995), pp. 51–69.CrossRefGoogle Scholar
  18. 18.
    Mitchell, J. and K. Mouratidis, ‘Is There a Common Euro-Zone Business Cycle?’, presented at the coloquium on Modern Tools for Business Cycles Analysis, EUROSTAT, Luxembourg, 28–29 November 2002.Google Scholar
  19. 19.
    Murray, C. J., “Cyclical Properties of Baxter-King Filtered Time Series”, The Review of Economics and Statistics, May 2003, 85(2): 472–476.Google Scholar
  20. 20.
    Nerlove, M., “Spectral Analysis of Seasonal Adjustment Procedures”, Econometrica, vol. 32(3), (1964), pp. 241–286.MATHGoogle Scholar
  21. 21.
    Oppenheim, A. V. and R. W. Schafer, Discrete-Time Signal Processing, second edition, Prentice-Hall, New Jersey, 1999.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Alessandra Iacobucci
    • 1
    • 2
  1. 1.OFCEParis Cedex 07France
  2. 2.CNRS - IDEFIValbonneFrance

Personalised recommendations