# Data-driven analysis of central bank digital currency (CBDC) projects drivers

arXiv: https://arxiv.org/abs/2102.11807 · HTML: https://mlsanity.com/paper/2102.11807/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 26 references that are in the map.
- First posted on arXiv 23 Feb 2021.

## Builds on (most cited first, 1 of 1)

- [Learning Internal Representations (COLT 1995)](https://mlsanity.com/paper/1911.05781/) (2019)

## Abstract (arXiv)

In this paper, we use a variety of machine learning methods to quantify the extent to which economic and technological factors are predictive of the progression of Central Bank Digital Currencies (CBDC) within a country, using as our measure of this progression the CBDC project index (CBDCPI). We find that a financial development index is the most important feature for our model, followed by the GDP per capita and an index of the voice and accountability of the country's population. Our results are consistent with previous qualitative research which finds that countries with a high degree of financial development or digital infrastructure have more developed CBDC projects. Further, we obtain robust results when predicting the CBDCPI at different points in time.