Real Time Prices (RTP) is a live dataset compiled and updated weekly by the World Bank. 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: food staples, fuel prices, and unofficial exchange rates.
Use Cases
- Modeling food price inflation based on staple food price data.
- Analyzing fuel price volatility based on Real Time Energy Prices (RTEP).
- Forecasting unofficial exchange rate movements based on Real Time Exchange Rates (RTFX).
- Assessing market conditions by integrating price data from multiple official and public sources.
Strengths
- Updated weekly, with a last update timestamp of 2026-03-15 18:11:04.590013.
- Compiled by the World Bank Development Economics Data Group (DECDG), an authoritative source.
- Uses Machine Learning to estimate missing price data, potentially improving coverage.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment for large-scale modeling.
- Data may reflect geographic bias inherent to the specific sources used for Guinea.
Provenance
- Source
- World Bank Group
- Collection Method
- Combination of direct price measurement and Machine Learning estimation, using data from WFP, FAO, and select National Statistical Offices.
- Time Range
- Historical and current estimates; dataset is live.
- Freshness
- Updated weekly.
- Geography
- Guinea