JOURNAL ARTICLE
Reserving the right to say no? Equilibria around hard trade‐sustainability commitments in power‐asymmetric contexts.
Published In: Global Policy, 2024, v. 15, n. 2. P. 329 1 of 3
Database: Political Science Complete 2 of 3
Authored By: Cezar, Rodrigo Fagundes; Montagner, Oto Murer Küll 3 of 3
Abstract
When will stringent sustainability commitments (not) be a stumbling block in the negotiation of trade agreements? Although the existing literature has explored the determinants of the design of sustainability provisions in trade agreements, few works have explored when countries will accept/reject those provisions once their content cannot be changed. Based on insights from game theory, we flesh out the conditions under which there will be an equilibrium in favor of hard sustainability provisions in trade deals. We then present empirical illustrations related to Mexico's participation in the United States–Mexico–Canada Agreement (USMCA) and Brazil's participation in the EU‐Mercosur trade negotiations. Our model shows that (1) fears of partner opportunism, (2) the costs of nonparticipation in trade deals, and (3) costs of adjustments to hard trade‐sustainability commitments are key to understanding whether a compromise can arise on trade and strong sustainability commitments. The model highlights what sorts of concessions ought to be made for negotiations to prosper. The findings point to how the changing structure of trade governance may affect the decision‐making process of Global South countries. The paper concludes with recommendations and avenues for further research. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Global Policy. 2024/05, Vol. 15, Issue 2, p329
- Document Type:Article
- Subject Area:Law
- Publication Date:2024
- ISSN:1758-5880
- DOI:10.1111/1758-5899.13349
- Accession Number:177819247
- Copyright Statement:Copyright of Global Policy is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.