JOURNAL ARTICLE

Institutional Quality and Trade Competitiveness in ASEAN Region: Implication for Inclusive and Sustainable Development.

  • Published In: Journal of Asian & African Studies (Sage Publications, Ltd.), 2026, v. 61, n. 2. P. 965 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Omeje, Ambrose Nnaemeka 3 of 3

Abstract

This article investigates the impact of institutional quality on trade competitiveness within the Association of Southeast Asian Nations (ASEAN) using panel data from 2005 to 2020 and a fixed effect econometric model grounded in the revealed symmetric comparative advantage (RSCA) theory. The study finds that improvements in control of corruption, government effectiveness, and political stability significantly enhance trade competitiveness by approximately 33.1%, 92.0%, and 55.0%, respectively, while weak regulatory quality, partial rule of law, and low voice and accountability significantly reduce trade competitiveness by about 25.3%, 95.6%, and 7.6%, respectively. The analysis reveals a one-way causal relationship from institutional quality to trade competitiveness, with no feedback effect observed. Based on these findings, the study recommends that ASEAN governments and citizens strengthen democratic governance, regulatory frameworks, rule of law, and political stability to foster inclusive and sustainable economic growth through enhanced trade competitiveness.

Additional Information

  • Source:Journal of Asian & African Studies (Sage Publications, Ltd.). 2026/03, Vol. 61, Issue 2, p965
  • Document Type:Article
  • Subject Area:Economics
  • Publication Date:2026
  • ISSN:0021-9096
  • DOI:10.1177/00219096241303938
  • Accession Number:192177489
  • Copyright Statement:Copyright of Journal of Asian & African Studies (Sage Publications, Ltd.) is the property of Sage Publications Inc. 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.)

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