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Growth and volatility analysis using wavelets

Author

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  • Maslova, Inga
  • Onder, Harun
  • Sanghi, Apurva

Abstract

The magnitude and persistence of growth in gross domestic product are topics of intense scrutiny by economists. Although the existing techniques provide a range of tools to study the nature of growth and volatility time series, these usually come with shortcomings, including the need to arbitrarily define acceleration spells, and focus on a particular frequency at a time. This paper explores the application of"wavelet-based"techniques to study the time-varying nature of growth and volatility. These techniques lend themselves to a more robust analysis of short-term and long-term determinants of growth and volatility than the traditional decomposition techniques, as demonstrated on a small sample of countries. In addition to having desirable technical advantages, such as localization in time and frequency and the ability to work with non-stationary series, these techniques also make it possible to accurately decompose the association between growth trajectories of different countries over different time horizons. Such"co-movement"analysis can provide policy makers with important insights on regional integration, growth poles, and how short and long term developments in other countries affect their domestic economy.

Suggested Citation

  • Maslova, Inga & Onder, Harun & Sanghi, Apurva, 2013. "Growth and volatility analysis using wavelets," Policy Research Working Paper Series 6578, The World Bank.
  • Handle: RePEc:wbk:wbrwps:6578
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    References listed on IDEAS

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    1. Craig Burnside & Alexandra Tabova, 2009. "Risk, Volatility, and the Global Cross-Section of Growth Rates," NBER Working Papers 15225, National Bureau of Economic Research, Inc.
    2. Ramey, Garey & Ramey, Valerie A, 1995. "Cross-Country Evidence on the Link between Volatility and Growth," American Economic Review, American Economic Association, vol. 85(5), pages 1138-1151, December.
    3. Diego Comin & Mark Gertler, 2006. "Medium-Term Business Cycles," American Economic Review, American Economic Association, vol. 96(3), pages 523-551, June.
    4. Pritchett, Lant, 2000. "Understanding Patterns of Economic Growth: Searching for Hills among Plateaus, Mountains, and Plains," World Bank Economic Review, World Bank Group, vol. 14(2), pages 221-250, May.
    5. Ramsey, James B. & Lampart, Camille, 1998. "Decomposition Of Economic Relationships By Timescale Using Wavelets," Macroeconomic Dynamics, Cambridge University Press, vol. 2(01), pages 49-71, March.
    6. Gençay, Ramazan & Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon J., 2001. "An Introduction to Wavelets and Other Filtering Methods in Finance and Economics," Elsevier Monographs, Elsevier, edition 1, number 9780122796708.
    7. Corbae, Dean & Ouliaris, Sam & Phillips, Peter C B, 1994. "A Reexamination of the Consumption Function Using Frequency Domain Regressions," Empirical Economics, Springer, vol. 19(4), pages 595-609.
    8. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
    9. Corbae, Dean & Ouliaris, Sam & Phillips, Peter C B, 1994. "A Reexamination of the Consumption Function Using Frequency Domain Regressions," Empirical Economics, Springer, vol. 19(4), pages 595-609.
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    Cited by:

    1. Usman Khalid, 2016. "Catch-up in Institutional Quality: An Empirical Assessment," Discussion Papers 2016-04, University of Nottingham, CREDIT.

    More about this item

    Keywords

    Economic Conditions and Volatility; Achieving Shared Growth; Science Education; Scientific Research&Science Parks; Emerging Markets;

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