Coalitions in international relations and coordination of agricultural trade policies

IF 4.4 2区 经济学 Q1 AGRICULTURAL ECONOMICS & POLICY
R. Mao
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引用次数: 1

Abstract

PurposeThe author attempts to examine the existence and pattern of coalitions in international relations across countries, and investigates whether international relations of coalition partners influence a country's enaction of agricultural non-tariff measures (NTMs).Design/methodology/approachThe author adopts a machine learning technique to identify international relation coalition partnerships and use network analysis to characterize the clustering pattern of coalitions with high-frequent records of global event data. The author then constructs a monthly dataset of agricultural NTMs against China and international relations with China of each importer and its coalition partners, and designs a panel structural vector autoregressive (PSVAR) model to estimate impulse response functions of agricultural NTMs with regard to international relation shocks.FindingsThe author finds countries to establish coalition partnerships. Two major clusters of coalitions are noted, with one composed of coalitions primarily among “North” countries and the other of coalitions among “South” countries. The United States is found to play a pivotal role by connecting the two clusters. The PSVAR estimation reveals reductions of NTMs against China following improved international relations with China of both the importer and its coalition partners. NTM responses are more substantial for measures that are trade restrictive. These results confirm that coalitions in international relations lead to coordination of agricultural NTMs.Originality/valueThe author provides international political insights into agricultural trade policymaking by showing interactions of NTM enaction across countries in the same coalition of international relations. These insights offer useful policy implications to predict and cope with hidden barriers to agricultural trade.
国际关系联盟和农业贸易政策协调
作者试图考察国际关系中联盟的存在和模式,并探讨联盟伙伴的国际关系是否会影响一个国家农业非关税措施(ntm)的制定。设计/方法/方法作者采用机器学习技术来识别国际关系联盟伙伴关系,并使用网络分析来表征具有全球事件数据高频记录的联盟的聚类模式。然后,作者构建了每个进口商及其联盟伙伴针对中国的农业ntm月度数据集以及与中国的国际关系,并设计了面板结构向量自回归(PSVAR)模型来估计农业ntm在国际关系冲击方面的脉冲响应函数。作者发现各国建立联盟伙伴关系。注意到两组主要的联盟,一组主要由“北方”国家之间的联盟组成,另一组由“南方”国家之间的联盟组成。通过连接这两个集群,美国发挥了关键作用。PSVAR估算显示,在进口商及其联盟伙伴改善与中国的国际关系后,针对中国的ntm减少了。NTM对贸易限制措施的回应更为实质性。这些结果证实,国际关系中的联盟导致农业ntm的协调。原创性/价值作者通过展示在同一国际关系联盟中各国NTM制定的相互作用,为农业贸易政策制定提供了国际政治见解。这些见解为预测和应对潜在的农业贸易壁垒提供了有益的政策启示。
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来源期刊
China Agricultural Economic Review
China Agricultural Economic Review AGRICULTURAL ECONOMICS & POLICY-
CiteScore
9.80
自引率
5.90%
发文量
41
审稿时长
>12 weeks
期刊介绍: Published in association with China Agricultural University and the Chinese Association for Agricultural Economics, China Agricultural Economic Review publishes academic writings by international scholars, and particularly encourages empirical work that can be replicated and extended by others; and research articles that employ econometric and statistical hypothesis testing, optimization and simulation models. The journal aims to publish research which can be applied to China’s agricultural and rural policy-making process, the development of the agricultural economics discipline and to developing countries hoping to learn from China’s agricultural and rural development.
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