PTA 设计的决定因素:机器学习的启示

Stepan Gordeev , Sandro Steinbach
{"title":"PTA 设计的决定因素:机器学习的启示","authors":"Stepan Gordeev ,&nbsp;Sandro Steinbach","doi":"10.1016/j.inteco.2024.100504","DOIUrl":null,"url":null,"abstract":"<div><p>Preferential trade agreements (PTAs) have emerged as the dominant form of international trade governance. Provisions included in PTAs are increasingly numerous, broad in their purview, deep in their scope, and varied between agreements. We study the economic, political, and geographic determinants of PTA design differences. For each of the hundreds of classified PTA provisions, we consider 287 country-pair characteristics as potential determinants, covering many individual mechanisms the literature has studied. We employ random forests, a supervised machine learning technique, to handle this high dimensionality and complexity. We use a robust variable importance measure to identify the most critical determinants of the inclusion of each PTA provision. Contagion due to competition for export markets, geographic proximity, and governance quality emerge as essential determinants of PTA design. These results motivate future exploration of individual mechanisms our exercise points to.</p></div>","PeriodicalId":13794,"journal":{"name":"International Economics","volume":"178 ","pages":"Article 100504"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Determinants of PTA design: Insights from machine learning\",\"authors\":\"Stepan Gordeev ,&nbsp;Sandro Steinbach\",\"doi\":\"10.1016/j.inteco.2024.100504\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Preferential trade agreements (PTAs) have emerged as the dominant form of international trade governance. Provisions included in PTAs are increasingly numerous, broad in their purview, deep in their scope, and varied between agreements. We study the economic, political, and geographic determinants of PTA design differences. For each of the hundreds of classified PTA provisions, we consider 287 country-pair characteristics as potential determinants, covering many individual mechanisms the literature has studied. We employ random forests, a supervised machine learning technique, to handle this high dimensionality and complexity. We use a robust variable importance measure to identify the most critical determinants of the inclusion of each PTA provision. Contagion due to competition for export markets, geographic proximity, and governance quality emerge as essential determinants of PTA design. These results motivate future exploration of individual mechanisms our exercise points to.</p></div>\",\"PeriodicalId\":13794,\"journal\":{\"name\":\"International Economics\",\"volume\":\"178 \",\"pages\":\"Article 100504\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2110701724000271\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Economics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2110701724000271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

优惠贸易协定(PTAs)已成为国际贸易治理的主要形式。优惠贸易协定中包含的条款越来越多,范围越来越广,程度越来越深,而且各协定之间的差异也越来越大。我们研究了 PTA 设计差异的经济、政治和地理决定因素。对于数百项分类的 PTA 条款中的每一项,我们都考虑了 287 个国家对的特征作为潜在的决定因素,涵盖了文献中研究过的许多个别机制。我们采用随机森林(一种有监督的机器学习技术)来处理这种高维度和复杂性。我们使用稳健的变量重要性度量来确定纳入每项 PTA 条款的最关键决定因素。出口市场竞争、地理邻近性和治理质量导致的传染成为 PTA 设计的重要决定因素。这些结果促使我们在未来探索我们的工作所指向的个别机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Determinants of PTA design: Insights from machine learning

Preferential trade agreements (PTAs) have emerged as the dominant form of international trade governance. Provisions included in PTAs are increasingly numerous, broad in their purview, deep in their scope, and varied between agreements. We study the economic, political, and geographic determinants of PTA design differences. For each of the hundreds of classified PTA provisions, we consider 287 country-pair characteristics as potential determinants, covering many individual mechanisms the literature has studied. We employ random forests, a supervised machine learning technique, to handle this high dimensionality and complexity. We use a robust variable importance measure to identify the most critical determinants of the inclusion of each PTA provision. Contagion due to competition for export markets, geographic proximity, and governance quality emerge as essential determinants of PTA design. These results motivate future exploration of individual mechanisms our exercise points to.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
International Economics
International Economics Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
6.30
自引率
0.00%
发文量
74
审稿时长
71 days
期刊最新文献
Gauging the level of dynamic between climate policy and foreign aid in Vietnam Editorial Board The impact of the U.S. Covid-19 response on remittance flows to emerging markets and developing economies An investigation of monetary autonomy under corner solution and middle ground: A panel data analysis Measuring the contemporal and lead connectedness level between investor sentiment and exchange rate dynamics in Vietnam: Novel findings from TVP-VAR-SV technique
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1