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Spectral based methods to identify common trends and common cycles

Author

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  • Camba-Méndez, Gonzalo
  • Kapetanios, George

Abstract

The rank of the spectral density matrix conveys relevant information in a variety of modelling scenarios. Phillips (1986) showed that a necessary condition for cointegration is that the spectral density matrix of the innovation sequence at frequency zero is of a reduced rank. In a recent paper Forni and Reichlin (1998) suggested the use of generalized dynamic factor model to explain the dynamics of a large set of macroeconomic series. Their method relied also on the computation of the rank of the spectral density matrix. This paper provides formal tests to estimate the rank of the spectral density matrix at any given frequency. The tests of rank at frequency zero are tests of the null of 'cointegration', complementary to those suggested by Phillips and Ouliaris (1988) which test the null of 'no cointegration'. JEL Classification: C12, C15, C32

Suggested Citation

  • Camba-Méndez, Gonzalo & Kapetanios, George, 2001. "Spectral based methods to identify common trends and common cycles," Working Paper Series 0062, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20010062
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    File URL: http://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp062.pdf
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    References listed on IDEAS

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    1. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
    2. Kohn, R, 1979. "Asymptotic Estimation and Hypothesis Testing Results for Vector Linear Time Series Models," Econometrica, Econometric Society, vol. 47(4), pages 1005-1030, July.
    3. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    4. Engle, Robert F. & Issler, Joao Victor, 1995. "Estimating common sectoral cycles," Journal of Monetary Economics, Elsevier, vol. 35(1), pages 83-113, February.
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    Cited by:

    1. 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.
    2. 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.
    3. Crowley, Patrick M., 2005. "An intuitive guide to wavelets for economists," Research Discussion Papers 1/2005, Bank of Finland.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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