Do self-organization and relational embeddedness influence free trade agreements network formation? Evidence from an exponential random graph model

Gang Wu, Lianyue Feng, Mihaela Peres and Jiali Dan

The Journal of International Trade & Economic Development, 2020, vol. 29, issue 8, 995-1017

Abstract: The rapid development of free trade agreements (FTAs) has made FTA networks an important aspect of the global economic ecosystem and governance system. This study analyzes the network properties and its evolutionary process using data for 193 economies from 1965 to 2018 and applies the Exponential Random Graph Model (ERGM) and temporal Exponential Random Graph Model (TERGM) to made empirical tests. The work aims to clarify the effect of self-organization and relational embeddedness on FTA network formation and evolution. Our findings several conclusions: (I) The FTA networks tend to cluster with a growing density by self-organization – a FTA’s partners are more likely to be partners. (II) The formation and evolution of the FTA networks exhibits degree centrality and population Matthew effect. Economies with more FTA partners or population are more likely to sign FTAs with others. (III) Economies show obvious economic homogeneity and population heterogeneity in choosing FTA partners. (IV) The formation and evolution of FTA networks is significantly embedded in the international trade network, historical colonial network, and geographic contiguity network.

Date: 2020
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DOI: 10.1080/09638199.2020.1784254

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