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Persistent Patterns of International Commerce

Author

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  • Michael D. Ward

    (Department of Political Science, University of Washington,mdw@u.washington.edu.)

  • Peter D. Hoff

    (Departments of Statistics and Biostatistics, University of Washington)

Abstract

The authors examine a standard gravity model of international commerce augmented to include political as well as institutional influences on bilateral trade. Using annual data from 1980-2001, they estimate regression coefficients and residual dependencies using a hierarchy of models in each year. Rather than gauge the generalizability of these patterns via traditional measures of statistical significance such as p-values, this article develops and employs a strategy to evaluate the out-of-sample predictive strength of various models. The analysis of recent international commerce shows that in addition to a typical gravity-model specification, political and institutional variables are important. The article also demonstrates that the often-reported link between international conflict and bilateral trade is elusive, and that inclusion of conflict in a trade model can sometimes lead to reduced out-of-sample predictive performance. Further, this article illustrates that there are substantial, persistent residual exporter- and importer-specific effects, and that ignoring such patterns in relational trade data results in an incomplete picture of international commerce, even in the context of a well-established framework such as the gravity model.

Suggested Citation

  • Michael D. Ward & Peter D. Hoff, 2007. "Persistent Patterns of International Commerce," Journal of Peace Research, Peace Research Institute Oslo, vol. 44(2), pages 157-175, March.
  • Handle: RePEc:sae:joupea:v:44:y:2007:i:2:p:157-175
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    Cited by:

    1. Lee, Kevin H. & Xue, Lingzhou & Hunter, David R., 2020. "Model-based clustering of time-evolving networks through temporal exponential-family random graph models," Journal of Multivariate Analysis, Elsevier, vol. 175(C).

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