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Spectral Analysis as a Tool for Financial Policy: An Analysis of the Short-End of the British Term Structure


  • Andrew Hughes Hallett


  • Christian R. Richter



In this paper, we show how to derive the spectra and cross-spectra of economic time series from an underlying econometric or VAR model. This allows us to conduct a proper frequency analysis evaluation of economic and financial variables on a reduced sample of data, without it being ruled out by the large sample requirements of direct spectral estimation. We show, in particular, how this can be done for time-varying models and time-varying spectra. We use our techniques to show how the behaviour of British interest rates changed during and following the ERM crisis of 1992/3.

Suggested Citation

  • Andrew Hughes Hallett & Christian R. Richter, 2004. "Spectral Analysis as a Tool for Financial Policy: An Analysis of the Short-End of the British Term Structure," Computational Economics, Springer;Society for Computational Economics, vol. 23(3), pages 271-288, April.
  • Handle: RePEc:kap:compec:v:23:y:2004:i:3:p:271-288

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    References listed on IDEAS

    1. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
    2. Renate Meyer & David A. Fournier & Andreas Berg, 2003. "Stochastic volatility: Bayesian computation using automatic differentiation and the extended Kalman filter," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 408-420, December.
    3. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 361-393.
    4. repec:bla:restud:v:65:y:1998:i:3:p:361-93 is not listed on IDEAS
    5. A. W. Coats, 1996. "Introduction," History of Political Economy, Duke University Press, vol. 28(5), pages 3-11, Supplemen.
    6. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
    7. Sandmann, Gleb & Koopman, Siem Jan, 1998. "Estimation of stochastic volatility models via Monte Carlo maximum likelihood," Journal of Econometrics, Elsevier, vol. 87(2), pages 271-301, September.
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    Cited by:

    1. Essahbi Essaadi & Mohamed Boutahar, 2010. "A Measure of Variability in Comovement for Economic Variables: a Time-Varying Coherence Function Approach," Economics Bulletin, AccessEcon, vol. 30(2), pages 1054-1070.
    2. Crowley, Patrick M., 2010. "Long cycles in growth : explorations using new frequency domain techniques with US data," Research Discussion Papers 6/2010, Bank of Finland.
    3. Vrowley, Patrick M. & Maraun, Douglas & Mayes, David, 2006. "How hard is the euro area core? : an evaluation of growth cycles using wavelet analysis," Research Discussion Papers 18/2006, Bank of Finland.
    4. Mario Cunha & Christian Richter, 2010. "Modelling the Cyclical Behaviour of Wine Production in the Douro Region Using a Time-Varying Parameters Approach," Working Papers 2010.1, International Network for Economic Research - INFER.
    5. Christian Richter & Andrew Hughes Hallett, 2005. "A Time-Frequency Analysis of the Coherences of the US Business," Computing in Economics and Finance 2005 45, Society for Computational Economics.
    6. Crowley, Patrick M., 2005. "An intuitive guide to wavelets for economists," Research Discussion Papers 1/2005, Bank of Finland.
    7. Maria do Rosario CORREIA & Christian GOKUS & Andrew Hughes HALLETT & Christian R. RICHTER, 2016. "A Dynamic Analysis of the Determinants of the Greek Credit Default Swaps," Journal of Economics and Political Economy, KSP Journals, vol. 3(2), pages 350-376, June.
    8. Hallett, Andrew Hughes & Richter, Christian, 2011. "Trans-Pacific Economic Relations and US-China Business Cycles: Convergence within Asia versus US Economic Leadership," ADBI Working Papers 292, Asian Development Bank Institute.
    9. Bachar Fakhry & Christian Richter, 2015. "Is the sovereign debt market efficient? Evidence from the US and German sovereign debt markets," International Economics and Economic Policy, Springer, vol. 12(3), pages 339-357, September.
    10. Andrew Hallett & Christian Richter, 2006. "Measuring the Degree of Convergence among European Business Cycles," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 229-259, May.
    11. Renne, J-P., 2009. "Frequency-domain analysis of debt service in a macro-finance model for the euro area," Working papers 261, Banque de France.
    12. David Gray, 2014. "Central European foreign exchange markets: a cross-spectral analysis of the 2007 financial crisis," The European Journal of Finance, Taylor & Francis Journals, vol. 20(6), pages 550-567, June.
    13. repec:hal:journl:halshs-00333582 is not listed on IDEAS
    14. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2011. "Synchronization of Economic Sentiment Cycles in the Euro Area: a time-frequency analysis," CEF.UP Working Papers 1105, Universidade do Porto, Faculdade de Economia do Porto.
    15. Andrew Hughes Hallett & Christian Richter, 2006. "Is the convergence of business cycles a global or regional issue? The UK, US and Euroland," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(3), pages 177-194.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C29 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Other
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects


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