Build a forecasting system that tracks Ethiopia's digital financial transformation using time series methods
# Forecasting Financial Inclusion in Ethiopia
Build a forecasting system that tracks Ethiopia's digital financial transformation using time series methods
Data Source: ethiopia_fi_unified_data
docs.google.com
Supporting files:
reference_codes -
docs.google.com — Valid values for all categorical fields
README.md -
drive.google.com — Schema documentation
Additional Data Points Guide -
docs.google.com
This spreadsheet contains four sheets to help you identify useful data for your forecasting model:
Sheet
Description
A. Alternative Baselines
Additional data sources (IMF FAS, G20 indicators, GSMA, ITU, NBE, financial institution reports)
B. Direct Correlation
Indicators directly tied to inclusion: active accounts, agent density, POS terminals, QR merchants, transaction volumes, ATM density, bank branches
C. Indirect Correlation
Enabler/proxy variables: smartphone penetration, data affordability, gender gap, agent networks, urbanization, mobile internet, 4G coverage, literacy, electricity access, digital ID
D. Market Nuances
Ethiopia-specific context you should understand: P2P dominance (used for commerce, not just transfers), mobile money-only users are rare (~0.5%), bank accounts are easily accessible, very low credit penetration