Balancing blockchain and FDI: Implications for financial development derived from machine-learning analysis
1 Department of Economics and Banking, International Islamic University Chittagong, Bangladesh
2 Business School, Zhengzhou University, China.
3 School of Business, China West Normal University, Sichuan, China
* Author to whom correspondence should be addressed.
Received: 11 Oct 2025 / Accepted: 5 Apr 2026 / Published: 6 Apr 2026
Abstract
This study empirically investigates the relationship between blockchain technology and Foreign Direct Investment (FDI) and their combined impact on financial development in 27 OECD countries from 2010 to 2022. Employing 2-step system GMM to control for endogeneity, unobserved heterogeneity, and machine learning techniques, we analyze their effects on overall Financial Development (FD), Financial Institutions Depth (FID), and Financial Markets Depth (FMD). Our findings reveal that blockchain adoption significantly enhances all three dimensions of the financial system by fostering efficiency, transparency, and security. Conversely, while FDI independently contributes to the depth of financial institutions and markets, its interaction with blockchain exhibits a significant negative moderating effect. This suggests a "crowding-out" phenomenon, where high levels of FDI may dampen the positive contributions of domestic blockchain innovation. These results underscore the necessity for nuanced policymaking that strategically promotes blockchain integration while managing the composition and impact of FDI inflows to optimize financial system development in advanced economies.
Keywords: Blockchain, FDI, Financial development, financial depth, and OECD
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This is an open access article distributed under the Creative Commons Attribution
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CITE
Nipu, M.A.; Nejhom, A.S.; Nazim, M. Balancing blockchain and FDI: Implications for financial development derived from machine-learning analysis. JHSN 2026, 1, 6.
Nipu MA, Nejhom AS, Nazim M. Balancing blockchain and FDI: Implications for financial development derived from machine-learning analysis. JHSN. 2026; 1(1):6.
Nipu, Mymuna Akter; Nejhom, Alifa Shaira; Nazim, Md. 2026. "Balancing blockchain and FDI: Implications for financial development derived from machine-learning analysis." JHSN 1, no. 1: 6.
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