Determinants of cryptocurrency adoption in developing countries

Lok, Jun Guang (2025) Determinants of cryptocurrency adoption in developing countries. Final Year Project, UTAR.

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Abstract

This study investigates the determinants of cryptocurrency adoption in 40 developing countries from 2020 to 2023, focusing on the role of regulatory challenges, perceived risk, technological awareness and trust, financial literacy, population size, and median age. Grounded in the Technology Acceptance Model (TAM), Risk Perception Theory, Institutional Theory, Network Effects Theory and Demographic Transition Theory, the study employs a panel data approach using secondary data. The Global Crypto Adoption Index from Chainalysis (2020–2023) was normalized to construct the dependent variable. The random-effects model identifies three statistically significant determinants. Technological awareness and trust (proxied by mobile cellular subscriptions) and population size exhibit significant positive effects on adoption, while regulatory challenges (proxied by the inverse of Regulatory Quality) show a significant negative influence, indicating that weaker regulatory environments are associated with lower adoption levels. The remaining variables were not statistically significant. The robustness of the findings is further supported by applying logarithmic transformations to key variables, a standard remedy for skewed distributions and outliers. These results demonstrate that cryptocurrency adoption in developing countries is primarily driven by structural factors related to digital infrastructure, market scale, and institutional quality. Policy implications emphasize a combined focus on building digital infrastructure, fostering clear and effective regulatory frameworks, and leveraging network effects, rather than relying solely on macroeconomic interventions. Model selection was further supported using the Hausman specification test and the Breusch–Pagan Lagrange Multiplier test for random effects, which confirmed the appropriateness of the Random Effects estimation for this study

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