Been working on this for a few months. The problem: African macro data is either paywalled (Bloomberg, Refinitiv) or significantly lagged (World Bank annual releases). There’s not much in between for developers and researchers who need current, attributed data at a reasonable price.<\/p>\n
What I built: a cross-signal economic stress monitor that pulls directly from central banks and national statistics offices across 11 African economies (Nigeria, Ghana, Kenya, South Africa, Zambia, Tanzania, Uganda, Morocco, C\u00f4te d’Ivoire, Ethiopia, Rwanda).<\/p>\n
Two analytical layers: – Acute stress: FX momentum, inflation, export-weighted commodity shock, real interest rate, reserve drawdown – Structural vulnerability: debt distress, fiscal position, banking stress, REER misalignment, political stability This week’s most interesting finding: Zambia has the lowest acute stress score in the dataset (copper boom, appreciating kwacha, low inflation) while simultaneously carrying one of the highest structural vulnerability scores (debt at 114% of GNI from its 2020 default). The commodity windfall is masking unrestructured debt.<\/p>\n
Available on Apify with full source attribution on every record: https:\/\/apify.com\/malmon\/african-economic-stress-monitor<\/a><\/p>\n Free monthly newsletter with the findings if you’d rather not run it yourself: https:\/\/malmonde.substack.com\/p\/african-macro-signal-june-2026<\/a><\/p>\n Happy to answer questions about methodology or coverage.<\/p>\n<\/div>\n submitted by \/u\/g_kalle <\/a>
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