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Cycles in Politics: Wavelet Analysis of Political Time Series

Author

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  • Luís Aguiar‐Conraria
  • Pedro C. Magalhães
  • Maria Joana Soares

Abstract

Spectral analysis and ARMA models have been the most common weapons of choice for the detection of cycles in political time series. Controversies about cycles, however, tend to revolve around an issue that both techniques are badly equipped to address: the possibility of irregular cycles without fixed periodicity throughout the entire time series. This has led to two main consequences. On the one hand, proponents of cyclical theories have often dismissed established statistical techniques. On the other hand, proponents of established techniques have dismissed the possibility of cycles without fixed periodicity. Wavelets allow the detection of transient and coexisting cycles and structural breaks in periodicity. In this article, we present the tools of wavelet analysis and apply them to the study of two lingering puzzles in the political science literature: the existence of cycles in election returns in the United States and in the severity of major power wars.

Suggested Citation

  • Luís Aguiar‐Conraria & Pedro C. Magalhães & Maria Joana Soares, 2012. "Cycles in Politics: Wavelet Analysis of Political Time Series," American Journal of Political Science, John Wiley & Sons, vol. 56(2), pages 500-518, April.
  • Handle: RePEc:wly:amposc:v:56:y:2012:i:2:p:500-518
    DOI: 10.1111/j.1540-5907.2011.00566.x
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    Cited by:

    1. Aguiar-Conraria, Luis & Martins, Manuel M.F. & Soares, Maria Joana, 2018. "Estimating the Taylor rule in the time-frequency domain," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 122-137.
    2. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2019. "The Phillips Curve at 60: time for time and frequency," NIPE Working Papers 04/2019, NIPE - Universidade do Minho.
    3. Luís Francisco Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2014. "Analyzing the Taylor Rule with Wavelet Lenses," NIPE Working Papers 18/2014, NIPE - Universidade do Minho.
    4. Dong, Minyi & Chang, Chun-Ping & Gong, Qiang & Chu, Yin, 2019. "Revisiting global economic activity and crude oil prices: A wavelet analysis," Economic Modelling, Elsevier, vol. 78(C), pages 134-149.
    5. Chun-Ping Chang & Chien-Chiang Lee & GenFu Feng & Shao-Lin Ning, 2016. "Does higher government debt link to higher social expenditure? New method, new evidence," Applied Economics, Taylor & Francis Journals, vol. 48(16), pages 1429-1451, April.
    6. Georgios Magkonis & Karen Jackson, 2019. "Identifying Networks in Social Media: The case of #Grexit," Networks and Spatial Economics, Springer, vol. 19(1), pages 319-330, March.
    7. 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.
    8. Mustapha Olalekan Ojo & Luís Aguiar-Conraria & Maria Joana Soares, 2019. "A Time-Frequency Analysis of Sovereign Debt Contagion in Europe," NIPE Working Papers 11/2019, NIPE - Universidade do Minho.

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