IDEAS home Printed from
   My bibliography  Save this article

Cycles in Politics: Wavelet Analysis of Political Time Series


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


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

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. 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.
    2. Boying Li & Chun-Ping Chang & Yin Chu & Bo Sui, 2020. "Oil prices and geopolitical risks: What implications are offered via multi-domain investigations?," Energy & Environment, , vol. 31(3), pages 492-516, May.
    3. Maitra, Debasish & Dash, Saumya Ranjan, 2017. "Sentiment and stock market volatility revisited: A time–frequency domain approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 15(C), pages 74-91.
    4. 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.
    5. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2020. "Okun’s Law across time and frequencies," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    6. Antony, Jürgen & Klarl, Torben, 2020. "Estimating the income inequality-health relationship for the United States between 1941 and 2015: Will the relevant frequencies please stand up?," The Journal of the Economics of Ageing, Elsevier, vol. 17(C).
    7. 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.
    8. Swamy, Vighneswara, 2020. "Macroeconomic transmission of Eurozone shocks to India—A mean-adjusted Bayesian VAR approach," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 126-150.
    9. 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.
    10. 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.
    11. 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.
    12. Dash, Saumya Ranjan & Maitra, Debasish, 2018. "Does Shariah index hedge against sentiment risk? Evidence from Indian stock market using time–frequency domain approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 19(C), pages 20-35.
    13. 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.
    14. Torun, Erdost & Chang, Tzu-Pu & Chou, Ray Y., 2020. "Causal relationship between spot and futures prices with multiple time horizons: A nonparametric wavelet Granger causality test," Research in International Business and Finance, Elsevier, vol. 52(C).
    15. 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.

    More about this item


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:amposc:v:56:y:2012:i:2:p:500-518. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley Content Delivery). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.