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Dyadic Analysis in International Relations: A Cautionary Tale

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  • Erikson, Robert S.
  • Pinto, Pablo M.
  • Rader, Kelly T.

Abstract

International relations scholars frequently rely on data sets with country pairs, or dyads, as the unit of analysis. Dyadic data, with its thousands and sometimes hundreds of thousands of observations, may seem ideal for hypothesis testing. However, dyadic observations are not independent events. Failure to account for this dependence in the data dramatically understates the size of standard errors and overstates the power of hypothesis tests. We illustrate this problem by analyzing a central proposition among IR scholars, the democratic trade hypothesis, which claims that democracies seek out other democracies as trading partners. We employ randomization tests to infer the correct p-values associated with the trade hypotheses. Our results show that typical statistical tests for significance are severely overconfident when applied to dyadic data.

Suggested Citation

  • Erikson, Robert S. & Pinto, Pablo M. & Rader, Kelly T., 2014. "Dyadic Analysis in International Relations: A Cautionary Tale," Political Analysis, Cambridge University Press, vol. 22(4), pages 457-463.
    • Handle: RePEc:cup:polals:v:22:y:2014:i:04:p:457-463_01
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    Cited by:

    1. Max Gallop, 2017. "More dangerous than dyads: how a third party enables rationalist explanations for war," Journal of Theoretical Politics, , vol. 29(3), pages 353-381, July.
    2. Kim Yeaji & Antenangeli Leonardo & Kirkland Justin, 2016. "Measurement Error and Attenuation Bias in Exponential Random Graph Models," Statistics, Politics and Policy, De Gruyter, vol. 7(1-2), pages 29-54, December.
    3. Bian, Bo & Meier, Jean-Marie & Xu, Ting, 2021. "Cross-Border Institutions and the Globalization of Innovation," LawFin Working Paper Series 23, Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin).
    4. Timm Betz & Amy Pond & Weiwen Yin, 2021. "Investment agreements and the fragmentation of firms across countries," The Review of International Organizations, Springer, vol. 16(4), pages 755-791, October.
    5. Bryan S. Graham, 2019. "Network Data," NBER Working Papers 26577, National Bureau of Economic Research, Inc.
    6. Jon Echevarria & Javier Gardeazabal, 2016. "Refugee gravitation," Public Choice, Springer, vol. 169(3), pages 269-292, December.
    7. Kobayashi, Yoshiharu & Howell, Christopher & Heinrich, Tobias & Motta, Matthew, 2022. "Investigating how historical legacies of militarized violence can motivate COVID-19 vaccine hesitancy: Evidence from global dyadic survey," Social Science & Medicine, Elsevier, vol. 311(C).
    8. Bryan S. Graham, 2019. "Network Data," CeMMAP working papers CWP71/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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