政治相似性与全球核贸易网络的动力

IF 1.9 4区 经济学 Q2 ECONOMICS Computational Economics Pub Date : 2024-06-25 DOI:10.1007/s10614-024-10650-0
Yeongkyun Jang
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摘要

本研究使用 ERGM 和 TERGM 分析方法调查了 2006 至 2021 年各国核贸易的动态。研究结果揭示了三个重要结论。首先,随着各国在政治上越来越相似,它们参与核贸易的积极性也越来越高,这强调了政治相似性在促进核贸易关系中的重要性。其次,政治差异较大的国家往往会阻碍核贸易的形成,这凸显了政治差异是合作的潜在障碍。最后,研究发现,参与全球核贸易网络的国家保持着互惠关系,表明存在互利和相互依存关系。这些发现有助于理解影响核贸易的因素,并表明促进政治上相似的伙伴关系对于核工业成功合作的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Political Similarity and the Dynamics of the Global Nuclear Trade Network

This study investigates the dynamics of nuclear trade among countries from 2006 to 2021 using ERGM and TERGM analyses. The results reveal three key conclusions. First, as countries become more politically similar, their engagement in nuclear trade becomes more active, emphasizing the significance of political similarity in promoting nuclear trade relationships. Second, countries with greater political differences tend to impede the formation of nuclear trade, highlighting political disparities as a potential barrier to cooperation. Finally, the study finds that countries involved in the global nuclear trade network maintain reciprocal relationships, indicating the presence of mutual benefits and interdependence. These findings contribute to understanding the factors influencing nuclear trade and suggest the importance of fostering politically similar partnerships for successful collaboration in the nuclear industry.

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来源期刊
Computational Economics
Computational Economics MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.00
自引率
15.00%
发文量
119
审稿时长
12 months
期刊介绍: Computational Economics, the official journal of the Society for Computational Economics, presents new research in a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems from all branches in economics. The topics of Computational Economics include computational methods in econometrics like filtering, bayesian and non-parametric approaches, markov processes and monte carlo simulation; agent based methods, machine learning, evolutionary algorithms, (neural) network modeling; computational aspects of dynamic systems, optimization, optimal control, games, equilibrium modeling; hardware and software developments, modeling languages, interfaces, symbolic processing, distributed and parallel processing
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