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Wavelet Variance Analysis of Output in G-7 Countries

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Author Info

  • Gallegati Marco

    ()
    (Università Politecnica delle Marche)

  • Gallegati Mauro

    ()
    (Università politecnica delle Marche)

Abstract

The large decline in output volatility experienced by most industrialized countries in the last decades has been thoroughly analyzed using standard time and frequency domain methods. In this paper we investigate the issue of moderation of volatility in G-7 economies and its sources, applying a multi-scaling approach to the industrial production indices of G-7 countries between 1961:1-2006:10. Using the MODWT estimates of wavelet variance we provide a scale-based analysis of variance that allows us to characterize the decline in volatility and to detect the importance of the various explanations of the moderation. The main scale-by-scale results stemming from multi scale analysis of variance are: i) a reduction in volatility which, although displayed by all the G-7 countries, is not uniform across time scales (as the decline is larger at short-term scales than at business cycle scales for France and Italy, and quite uniform across scale for the UK and the US) nor countries (as the decline is significant for a subset of countries only, i.e. France, Italy, the UK and the US); and ii) the moderation has to be attributable to the decline in the variance of both common (in the 1970s) and country-specific (in the 1960s) exogenous disturbances hitting the economy.

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Bibliographic Info

Article provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 11 (2007)
Issue (Month): 3 (September)
Pages: 1-25

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Handle: RePEc:bpj:sndecm:v:11:y:2007:i:3:n:6

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Cited by:
  1. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
  2. Luís Francisco Aguiar & Yi Wen, 2011. "OPEC´s Oil Exporting Strategy and Macroeconomic (In)Stability," NIPE Working Papers 10/2011, NIPE - Universidade do Minho.
  3. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2010. "The yield curve and the macro-economy across time and frequencies," CEF.UP Working Papers 1004, Universidade do Porto, Faculdade de Economia do Porto.
  4. Caraiani, Petre, 2012. "Money and output: New evidence based on wavelet coherence," Economics Letters, Elsevier, vol. 116(3), pages 547-550.
  5. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
  6. Joanna Bruzda, 2011. "Business cycle synchronization according to wavelets – the case of Poland and the euro zone member countries," Bank i Kredyt, National Bank of Poland, Economic Institute, vol. 42(3), pages 5-32.
  7. Peter Martey Addo & Monica Billio & Dominique Guegan, 2012. "Alternative Methodology for Turning-Point Detection in Business Cycle : A Wavelet Approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00694420, HAL.
  8. Haven, Emmanuel & Liu, Xiaoquan & Shen, Liya, 2012. "De-noising option prices with the wavelet method," European Journal of Operational Research, Elsevier, vol. 222(1), pages 104-112.
  9. Fernández-Macho, Javier, 2012. "Wavelet multiple correlation and cross-correlation: A multiscale analysis of Eurozone stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1097-1104.
  10. Crowley, Patrick & Aaron, Schultz, 2010. "A New Approach to Analyzing Convergence and Synchronicity in Growth and Business Cycles: Cross Recurrence Plots and Quantification Analysis," MPRA Paper 23728, University Library of Munich, Germany.
  11. Krüger, Niclas, 2012. "Estimating traffic demand risk - a multiscale analysis," Working papers in Transport Economics 2012:14, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
  12. Krüger, Niclas, 2012. "Does infrastructure really cause growth?: the time scale dependent causality nexus between infrastructure investments and GDP," Working papers in Transport Economics 2012:15, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
  13. Caraiani, Petre, 2012. "Stylized facts of business cycles in a transition economy in time and frequency," Economic Modelling, Elsevier, vol. 29(6), pages 2163-2173.
  14. Mikael Svensson & Niclas Krüger, 2012. "Mortality and economic fluctuations," Journal of Population Economics, Springer, vol. 25(4), pages 1215-1235, October.
  15. Aguiar-Conraria, Luís & Azevedo, Nuno & Soares, Maria Joana, 2008. "Using wavelets to decompose the time–frequency effects of monetary policy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2863-2878.
  16. Luís Aguiar-Conraria & Maria Soares, 2011. "Oil and the macroeconomy: using wavelets to analyze old issues," Empirical Economics, Springer, vol. 40(3), pages 645-655, May.

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