Food Price Index Data
Retail food prices by product, store, and region -- CPI measures averages, but item-level price data reveals inflation hotspots and substitution patterns.
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Find Me This Data →Overview
What Is Food Price Index Data?
Food Price Index Data tracks the monthly change in retail and wholesale prices of food commodities across products, stores, and regions. Unlike broader Consumer Price Index (CPI) measures that report averages across fixed baskets, item-level food price data reveals granular inflation hotspots, regional variation, and consumer substitution patterns. This data captures real-time price movements for cereals, meat, dairy, vegetable oils, sugar, and other food groups, enabling analysts to identify where price pressures concentrate and how they propagate through supply chains and consumer behavior. The FAO Food Price Index (FFPI), the international standard, measures the average of five commodity group price indices weighted by average export shares. National food price indices—including retail CPI components and wholesale pricing indices—provide country-specific and regional perspectives. These datasets are essential for understanding food security, inflation dynamics, and the impact of climate, energy costs, and geopolitical events on food affordability.
Market Data
128.5 Index Points
FAO Food Price Index (March 2026)
Source: Food and Agriculture Organization of the United Nations
160.20 Index Points
Historical Peak (March 2022)
Source: Trading Economics / FAO
50.80 Index Points
All-Time Low (May 2002)
Source: Trading Economics / FAO
July 2010 – March 2025 (Monthly)
Data Coverage Period
Source: PubMed Central / World Bank
Who Uses This Data
What AI models do with it.do with it.
Policy & Government Analysis
Central banks and ministries of agriculture use food price indices to monitor inflation dynamics, assess food security risks, and design monetary and agricultural policy interventions. CPI changes are measured relative to a base year (value 100) to track year-over-year price movement.
Commodity Trading & Market Forecasting
Traders, brokers, and investment firms apply machine learning and time-series forecasting to wholesale price indices to predict commodity price trends, hedge positions, and identify trading opportunities across grain, oil, and protein markets.
Retail & Supply Chain Optimization
Supermarket chains and food distributors analyze regional and item-level price data to optimize inventory, pricing strategy, and substitution patterns. Data reveals where inflation hotspots emerge and enables dynamic pricing and procurement decisions.
Climate & Economic Risk Analysis
Researchers and risk analysts correlate food price indices with climate factors (temperature, precipitation), energy prices, and geopolitical events to understand systemic drivers of food inflation and forecast volatility.
What Can You Earn?
What it's worth.worth.
Research & Analysis Reports
€4,034–$4,490 USD
Market research publications covering food price index analysis and forecasts; pricing varies by scope and geography.
Item-Level Price Data (Granular)
Varies
Retail and wholesale price datasets by product, store, and region command premium rates; structure and frequency drive pricing.
Forecast & Modeling Services
Varies
Custom machine learning models for food price prediction; pricing depends on data scope, commodity groups, and forecast horizon.
What Buyers Expect
What makes it valuable.valuable.
Temporal Granularity
Monthly, weekly, or daily data frequency. Official FAO and national CPI releases follow monthly cycles; wholesale indices often provided weekly. Consistent release schedules and historical archives from defined base periods (e.g., June 1994) are expected.
Geographic & Item-Level Coverage
Data must be disaggregated by product group (cereals, meat, dairy, vegetable oils, sugar, etc.), region, and retail outlet type. National and subnational coverage, including rural and urban markets, increases utility for policy and supply chain analysis.
Metadata & Methodology Transparency
Clear documentation of base periods, weighting schemes (e.g., export share averages), sources (e.g., World Bank, FAO, national ministries), and adjustments for quality and substitution. Buyers verify data integrity and comparability over time.
Integration with Contextual Factors
Correlation with energy prices, climate variables (temperature anomalies, precipitation), and supply chain disruptions enhances analytical value. Machine learning applications require rich feature sets to model underlying drivers.
Companies Active Here
Who's buying.buying.
Maintains and publishes monthly Food Price Index data as a key component of economic monitoring and development analysis.
Produces the FAO Food Price Index (FFPI)—the international standard for tracking monthly changes in commodity prices across cereals, meat, dairy, oils, and sugar; releases monthly reports and the Food Price Monitoring and Analysis (FPMA) Tool.
Creates and maintains the national wholesale food price index using data from the national wholesale pricing information system for agricultural items; reflects grain market trends.
Aggregates and publishes historical food price index data, including real-time and forecasted values for global markets and individual countries.
FAQ
Common questions.questions.
How does Food Price Index Data differ from general CPI inflation data?
CPI measures average changes in a fixed basket of products over time with reference to a base year (value 100). Food Price Index Data goes deeper—it breaks down price changes by individual food commodities (cereals, meat, dairy, oils, sugar), geography, and retail outlet. This granularity reveals inflation hotspots and substitution patterns that aggregate CPI masks, making it essential for supply chain and policy analysis.
What drives food price volatility captured in these indices?
Food prices are influenced by climate factors (temperature anomalies, precipitation), energy costs (fuel, electricity, natural gas), geopolitical events, currency fluctuations, and supply chain disruptions. Research shows that weather patterns and energy price indices are strong predictive factors for food price movements, particularly for vegetables, oils, and sugar.
How frequently is Food Price Index Data updated, and from which sources?
Major sources release monthly: the FAO Food Price Index (FFPI) follows a published schedule (e.g., 9 January, 6 February, etc. in 2026), while national indices align with CPI release cycles. The World Bank maintains data from July 2010 onward; wholesale indices are sometimes updated weekly. Official sources include FAO, World Bank, national statistical agencies, and ministries of agriculture.
What are typical use cases for buyers of this data?
Central banks and governments use it for inflation monitoring and food security policy. Commodity traders apply machine learning forecasts to predict price trends and manage hedges. Retailers optimize pricing and inventory based on regional price hotspots. Researchers correlate price movements with climate and energy data to understand systemic risks. Risk analysts monitor geopolitical impacts on food costs.
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