Gambia's Real Time Prices dataset is compiled and updated weekly by the World Bank Development Economics Data Group. It combines direct price measurement with machine learning estimation for missing data, using sources like the World Food Program and UN-FAO. The dataset includes three sub-series for food, energy, and exchange rates, with the last update recorded on 2026-03 15.
Use Cases
- Model weekly food price inflation based on staple food price data.
- Analyze fuel price volatility based on real-time energy price sub-series.
- Track unofficial exchange rate fluctuations based on the exchange rate sub-series.
- Assess food security risks based on the combination of price data and machine learning estimates.
Strengths
- Updated weekly, with the last update on 2026-03-15.
- Combines direct measurement with machine learning estimation for data completeness.
- Sourced from authoritative bodies like the World Bank, WFP, and FAO.
- Includes three distinct sub-series for food, energy, and exchange rates.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Data may reflect geographic and source bias inherent to the compilation methodology.
Provenance
- Source
- World Bank Development Economics Data Group (DECDG).
- Collection Method
- Combination of direct price measurement and machine learning estimation, using data from WFP, FAO, and National Statistical Offices.
- Time Range
- Historical and current estimates, updated weekly.
- Freshness
- Updated weekly.
- Geography
- Gambia.