Economic and financial development as determinants of crypto adoption

This research investigates the macroeconomic determinants of crypto adoption, illuminating the potentials of cryptocurrencies to accelerate financial inclusion. By exploiting an extensive dataset from 165 countries between 2019 and 2021, this study employs various econometric methodologies, including Panel Feasible Generalized Least Squares (PFGLS), Robust Least Squares (RLS), and Quantile Regressions (QR). These classic econometric techniques are complemented by several machine learning techniques such as Bagging, Boosting, and Support Vector Machine (SVM) regressions, as well as Artificial Neural Networks (ANNs) and Naïve Bayes (NB) classification algorithms. The results show an interesting trend: cryptocurrency adoption is more prevalent in countries with robust financial markets and higher education levels. This suggests that crypto adoption is primarily a byproduct of sophisticated financial environments and an educated population, rather than a direct facilitator of financial inclusion. • We investigate macroeconomic factors' impact on crypto adoption in 165 countries from 2019–2021. • We employ a set of robust regression and machine learning methods to uncover nonlinear relationships. • GDP, financial market development, education and electricity prices are major drivers for crypto adoption. • Crypto adoption is more prevalent in countries with robust financial markets and higher education levels. • Findings suggest crypto adoption stems from strong financial markets and high education, not from financial inclusion.