Do deep regional trade agreements strengthen anti‐corruption? A social network analysis

Author:

Zhang Xingyuan12,Goel Rajeev K.345ORCID,Jiang Jiaming1ORCID,Capasso Salvatore567

Affiliation:

1. Okayama University Okayama Japan

2. Kobe University Kobe Japan

3. Illinois State University Normal Illinois USA

4. Kiel Institute for the World Economy Kiel Germany

5. Institute for Mediterranean Studies – ISMed Napoli Italy

6. University of Napoli Parthenope Napoli Italy

7. Center for Economics and Finance Napoli Italy

Abstract

AbstractThis paper adds to research on the international drivers of corruption and anti‐corruption by focusing on the influence of regional trade agreements (RTAs). Using cross‐national data and employing a social network analysis, we provide descriptions of the evolution of deep integration of RTAs' network in anti‐corruption and transparency with a comprehensive view in which we utilise the network's Closeness, Harmonic, Betweenness, Eigenvector, and PageRank centralities to demonstrate the positions of member countries. We examine the relations of the positions of member countries in the deep RTAs' network and the performance of those countries in fighting corruption. Our empirical results suggest that the countries which hold dominant positions in the deep RTAs' network may be associated with better performance in fighting corruption. At the same time, countries which may have traditionally lagged in the enforcement of anti‐bribery and corruption laws will benefit through the transfer of best practices and technical expertise in rulemaking and enforcement by using their positions in the deep RTAs' network. Furthermore, our results indicate that the provisions related to anti‐corruption or transparency in RTAs will play more important roles in fighting public sector corruption for member countries. The findings are robust to alternate corruption and governance measures.

Publisher

Wiley

Subject

Political Science and International Relations,Economics and Econometrics,Finance,Accounting

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