JOURNAL ARTICLE
FDI and Income Inequality: Do Digital Service Trade Restrictions Matter?
Published In: Journal of International Commerce, Economics & Policy, 2025, v. 16, n. 3. P. 1 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Nguyen, Dinh Trung; Do, Minh Hue 3 of 3
Abstract
The rapid digitalization of global economies has transformed trade and investment flows, yet many countries continue to impose restrictive policies on digital service trade, raising important questions about their broader economic consequences. Using the newly developed Digital Trade Restrictiveness Index (DTRI), this study explores how these restrictions moderate the relationship between foreign direct investment (FDI) and income inequality. By using panel regression and predictive margins analyses on a sample of 68 countries, we find that stricter digital trade restrictions significantly diminish the inequality-reducing effects of FDI. Notably, this moderating effect varies across the five dimensions of digital trade restrictions. While stringent regulations on electronic transactions primarily weaken the beneficial impact of FDI on reducing inequality, more severe restrictions on infrastructure and connectivity not only impede but also exacerbate inequality. These findings highlight the critical need for balanced digital trade policies that enable inclusive growth by maximizing the equitable benefits of FDI while addressing legitimate regulatory concerns. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of International Commerce, Economics & Policy. 2025/10, Vol. 16, Issue 3, p1
- Document Type:Article
- Subject Area:Economics
- Publication Date:2025
- ISSN:1793-9933
- DOI:10.1142/S1793993325500140
- Accession Number:188764517
- Copyright Statement:Copyright of Journal of International Commerce, Economics & Policy is the property of World Scientific Publishing Company 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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