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On Waves in War and Elections Wavelet Analysis of Political Time-Series


  • Luís Francisco Aguiar

    () (Universidade do Minho - NIPE)

  • Pedro C. Magalhães

    () (University of Lisbon, Social Sciences Institute)

  • Maria Joana Soares

    () (Universidade do Minho)


Spectral analysis and ARMA models have been the most established weapons of choice for the detection of cycles in time series data. However, such techniques are only appropriate when periodic components are time invariant. This has led some scholars to disregard the possibility of irregular cycles. We aim to contribute to further reconsideration of the possibility of cycles in political phenomena by introducing wavelet analysis. Its main contribution comes from the ability to estimate the spectral characteristics of a time series as a function of time, thus revealing how its different periodic components change over time, while preserving rigorous standards of statistical inference. We demonstrate the usefulness of wavelet analysis with two applications. The first concerns the possibility of long-cycles in wars, one of the central puzzles in the international relations sub-field. The second concerns election returns in presidential and congressional elections in the United States, where the existence of cyclical patterns has been equally controversial. Contrary to the prevailing wisdom, wavelet analysis allows the detection of transient and coexisting cycles, shedding some light over phenomena that have remained unaddressed so far.

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  • Luís Francisco Aguiar & Pedro C. Magalhães & Maria Joana Soares, 2010. "On Waves in War and Elections Wavelet Analysis of Political Time-Series," NIPE Working Papers 1/2010, NIPE - Universidade do Minho.
  • Handle: RePEc:nip:nipewp:1/2010

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    References listed on IDEAS

    1. Beck, Paul Allen, 1979. "The Electoral Cycle and Patterns of American Politics," British Journal of Political Science, Cambridge University Press, vol. 9(02), pages 129-156, April.
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    3. Patrick M. Crowley & David G. Mayes, 2009. "How fused is the euro area core?: An evaluation of growth cycle co-movement and synchronization using wavelet analysis," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2008(1), pages 63-95.
    4. Gencay, Ramazan & Selcuk, Faruk & Whitcher, Brandon, 2005. "Multiscale systematic risk," Journal of International Money and Finance, Elsevier, vol. 24(1), pages 55-70, February.
    5. Daron Acemoglu & Simon Johnson & James Robinson, 2005. "The Rise of Europe: Atlantic Trade, Institutional Change, and Economic Growth," American Economic Review, American Economic Association, vol. 95(3), pages 546-579, June.
    6. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists ," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    7. Enders, Walter & Sandler, Todd, 2000. "Is Transnational Terrorism Becoming More Threatening? A Time-Series Investigation," Staff General Research Papers Archive 1823, Iowa State University, Department of Economics.
    8. Luís Francisco Aguiar-Conraria & Maria Joana Soares & Nuno Azevedo, 2007. "Using Wavelets to decompose time-frequency economic relations," NIPE Working Papers 17/2007, NIPE - Universidade do Minho.
    9. Rosecrance, Richard, 1987. "Long cycle theory and international relations," International Organization, Cambridge University Press, vol. 41(02), pages 283-301, March.
    10. Michael Gerace, 2002. "US Military Expenditures and Economic Growth: Some Evidence from Spectral Methods," Defence and Peace Economics, Taylor & Francis Journals, vol. 13(1), pages 1-11.
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    Cited by:

    1. Luís Francisco Aguiar & Pedro C. Magalhães & Maria Joana Soares, 2010. "Synchronism in Electoral Cycles: How United are the United States?," NIPE Working Papers 17/2010, NIPE - Universidade do Minho.

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