In March 2020, due to the situation caused by the coronavirus pandemic (COVID-19) in Poland, almost half of the Polish consumers fear food price increases. Only 12 percent of respondents were not afraid of food shortage at all.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

A collection of over 75 charts and maps presenting key statistics on the farm sector, food spending and prices, food security, rural communities, the interaction of agriculture and natural resources, and more.

How much do you know about food and agriculture? What about rural America or conservation? ERS has assembled more than 75 charts and maps covering key information about the farm and food sectors, including agricultural markets and trade, farm income, food prices and consumption, food security, rural economies, and the interaction of agriculture and natural resources.

How much, for example, do agriculture and related industries contribute to U.S. gross domestic product? Which commodities are the leading agricultural exports? How much of the food dollar goes to farmers? How do job earnings in rural areas compare with metro areas? How much of the Nation’s water is used by agriculture? These are among the statistics covered in this collection of charts and maps—with accompanying text—divided into the nine section titles.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Ag and Food Sectors and the Economy Land and Natural Resources Farming and Farm Income Rural Economy Agricultural Production and Prices Agricultural Trade Food Availability and Consumption Food Prices and Spending Food Security and Nutrition Assistance For complete information, please visit https://data.gov.

Open Prices

  What is Open Prices?

Open Prices is a project to collect and share prices of products around the world. It's a publicly available dataset that can be used for research, analysis, and more. Open Prices is developed and maintained by Open Food Facts. There are currently few companies that own large databases of product prices at the barcode level. These prices are not freely available, but sold at a high price to private actors, researchers and other… See the full description on the dataset page: https://huggingface.co/datasets/openfoodfacts/open-prices.

Series Name: Consumer Food Price IndexSeries Code: AG_FPA_CFPIRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 2.c.1: Indicator of food price anomaliesTarget 2.c: Adopt measures to ensure the proper functioning of food commodity markets and their derivatives and facilitate timely access to market information, including on food reserves, in order to help limit extreme food price volatilityGoal 2: End hunger, achieve food security and improved nutrition and promote sustainable agricultureFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

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Agricultural commodity prices are an indicator of changes in supply and demand, and as such, can detect abnormal conditions that need to be brought to attention. Price monitoring supports well-functioning international and national markets through the provision of timely and transparent market information, and constitutes a basis for evidence-based decision making and food security strategies. Past price volatility events have put in evidence the value of timely market information and analysis in order to mitigate the negative effects on low-income groups of population whose expenditure on food represents a large proportion of their total expenses. FAO plays a key role in monitoring, analysing and disseminating food price data along the food supply chain, from producer to consumer through both domestic as well as international markets.

Series Name: Proportion of countries recording abnormally high or moderately high food prices according to the Indicator of Food Price Anomalies (percent)Series Code: AG_FPA_HMFPRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 2.c.1: Indicator of food price anomaliesTarget 2.c: Adopt measures to ensure the proper functioning of food commodity markets and their derivatives and facilitate timely access to market information, including on food reserves, in order to help limit extreme food price volatilityGoal 2: End hunger, achieve food security and improved nutrition and promote sustainable agricultureFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

April saw a large jump in consumer prices for food at home products in the United States in 2021. As a result of the coronavirus outbreak, food prices rose by 2.6 percent in April compared to March. From August 2020 to April 2021, the growth food prices has remained steadily between 0 and 0.4.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

This table contains data on the average cost of a market basket of nutritious food items relative to income for female-headed households with children, for California, its regions, counties, and cities/towns. The ratio uses data from the U.S. Department of Agriculture and the U.S. Census Bureau. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. An adequate, nutritious diet is a necessity at all stages of life. Inadequate diets can impair intellectual performance and have been linked to more frequent school absence and poorer educational achievement in children. Nutrition also plays a significant role in causing or preventing a number of illnesses, such as cardiovascular disease, some cancers, obesity, type 2 diabetes, and anemia. At least two factors influence the affordability of food and the dietary choices of families – the cost of food and family income. The inability to afford food is a major factor in food insecurity, which has a spectrum of effects including anxiety over food sufficiency or food shortages; reduced quality or desirability of diet; and disrupted eating patterns and reduced food intake. More information about the data table and a data dictionary can be found in the Attachments.

In January 2025, the 12-month inflation rate for food items in the United States was at 2.5 percent. That month, egg prices increased by over 50 percent compared to January 2024. Inflation for sugar and sweets saw an increase at 4.3 percent.

“Food Price Crowdsourcing Africa” (FPCA) is a research project led by the European Commission - Directorate Joint Research Centre (JRC), and implemented in collaboration with the International Institute of Tropical Agriculture (IITA), Nigeria and Wageningen University and Research (WUR), The Netherlands, to understand food price changes along the food chain while strengthening agricultural & market information systems through mobile phone technology and citizens' participation. This project is a component of a broader initiative themed "Support to the AgRi-Economic analysis & modelling of agriculture & development policies impact for Africa (AREA)", which is led and funded by the JRC and implemented in collaboration with WUR.

As society and economy rapidly transforms by the expansion of digital technologies, new data sources represent a unique opportunity to produce new and complementary statistics within collective collaborative frameworks. The goal of this project (~10 months) was to explore the potentiality of a “spontaneous crowdsourcing” (i.e. “Citizen Science”) approach by leveraging citizen involvement, smart phone technology and an adequate quality framework to produce reliable food price data with very high spatial details and temporal frequency, with the purpose to provide to consumers and farmers accurate and timely information on agricultural commodity markets, allowing them to make informed decisions about consumption and production and leading to a more efficient function of markets. Agricultural markets transparency is particularly relevant in many African countries where agriculture is still the main source of income for a big share of population as well as expenditure on food represents an important share of the total household income. At the same time market transparency can help to understand market dynamics and so to shape national and regional decisions and policies regarding food security and markets.

The dataset is continuously updated for the whole the duration of the project. The dataset is accompanied by an interactive dashboard updated twice a day that allows users to perform a wide exploration of the data. A set of graphs and charts are displayed according to states and regions, weeks, and products selected by the user.

This is considered a beta version: user feedback is welcome to further improve the dashboard.

The twenty-year average growth rate for eggs is 3.1 percent. From April 2020 to April 2021, the year-over-year price for eggs declined by -8.9 percent. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

This report contains key data regarding the cost of FNS' food assistance programs. The report summarizes data submitted by various reporting agencies for the United States during fiscal year 2013 and fiscal year 2014.

This Australian and New Zealand food category cost dataset was created to inform diet and economic modelling for low and medium socioeconomic households in Australia and New Zealand. The dataset was created according to the INFORMAS protocol, which details the methods to systematically and consistently collect and analyse information on the price of foods, meals and affordability of diets in different countries globally. Food categories were informed by the Food Standards Australian New Zealand (FSANZ) AUSNUT (AUStralian Food and NUTrient Database) 2011-13 database, with additional food categories created to account for frequently consumed and culturally important foods.

Methods The dataset was created according to the INFORMAS protocol [1], which detailed the methods to collect and analyse information systematically and consistently on the price of foods, meals, and affordability of diets in different countries globally.

Cost data were collected from four supermarkets in each country: Australia and New Zealand. In Australia, two (Coles Merrylands and Woolworths Auburn) were located in a low and two (Coles Zetland and Woolworths Burwood) were located in a medium metropolitan socioeconomic area in New South Wales from 7-11th December 2020. In New Zealand, two (Countdown Hamilton Central and Pak ‘n Save Hamilton Lake) were located in a low and two (Countdown Rototuna North and Pak ‘n Save Rosa Birch Park) in a medium socioeconomic area in the North Island, from 16-18th December 2020.

Locations in Australia were selected based on the Australian Bureau of Statistics Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD) [2]. The index ranks areas from most disadvantaged to most advantaged using a scale of 1 to 10. IRSAD quintile 1 was chosen to represent low socio-economic status and quintile 3 for medium SES socio-economic status. Locations in New Zealand were chosen using the 2018 NZ Index of Deprivation and statistical area 2 boundaries [3]. Low socio-economic areas were defined by deciles 8-10 and medium socio-economic areas by deciles 4-6. The supermarket locations were chosen according to accessibility to researchers. Data were collected by five trained researchers with qualifications in nutrition and dietetics and/or nutrition science.

All foods were aggregated into a reduced number of food categories informed by the Food Standards Australian New Zealand (FSANZ) AUSNUT (AUStralian Food and NUTrient Database) 2011-13 database, with additional food categories created to account for frequently consumed and culturally important foods. Nutrient data for each food category can therefore be linked to the Australian Food and Nutrient (AUSNUT) 2011-13 database [4] and NZ Food Composition Database (NZFCDB) [5] using the 8-digit codes provided for Australia and New Zealand, respectively.

Data were collected for three representative foods within each food category, based on criteria used in the INFORMAS protocol: (i) the lowest non-discounted price was chosen from the most commonly available product size, (ii) the produce was available nationally, (iii) fresh produce of poor quality was omitted. One sample was collected per representative food product per store, leading to a total of 12 food price samples for each food category. The exception was for the ‘breakfast cereal, unfortified, sugars ≤15g/100g’ food category in the NZ dataset, which included only four food price samples because only one representative product per supermarket was identified.

Variables in this dataset include: (i) food category and description, (ii) brand and name of representative food, (iii) product size, (iv) cost per product, and (v) 8-digit code to link product to nutrient composition data (AUSNUT and NZFCDB).

References

Vandevijvere, S.; Mackay, S.; Waterlander, W. INFORMAS Protocol: Food Prices Module [Internet]. Available online: https://auckland.figshare.com/articles/journal_contribution/INFORMAS_Protocol_Food_Prices_Module/5627440/1 (accessed on 25 October).
2071.0 - Census of Population and Housing: Reflecting Australia - Stories from the Census, 2016 Available online: https://www.abs.gov.au/ausstats/abs@.nsf/Lookup/by Subject/2071.0~2016~Main Features~Socio-Economic Advantage and Disadvantage~123 (accessed on 10 December).
Socioeconomic Deprivation Indexes: NZDep and NZiDep, Department of Public Health. Available online: https://www.otago.ac.nz/wellington/departments/publichealth/research/hirp/otago020194.html#2018 (accessed on 10 December)
AUSNUT 2011-2013 food nutrient database. Available online: https://www.foodstandards.gov.au/science/monitoringnutrients/ausnut/ausnutdatafiles/Pages/foodnutrient.aspx (accessed on 15 November).
NZ Food Composition Data. Available online: https://www.foodcomposition.co.nz/ (accessed on 10 December)

Usage Notes The uploaded data includes an Excel spreadsheet where a separate worksheet is provided for the Australian food price database and New Zealand food price database, respectively. All cost data are presented to two decimal points, and the mean and standard deviation of each food category is presented. For some representative foods in NZ, the only NFCDB food code available was for a cooked product, whereas the product is purchased raw and cooked prior to eating, undergoing a change in weight between the raw and cooked versions. In these cases, a conversion factor was used to account for the weight difference between the raw and cooked versions, to ensure that nutrient information (on accessing from the NZFCDB) was accurate. This conversion factor was developed based on the weight differences between the cooked and raw versions, and checked for accuracy by comparing quantities of key nutrients in the cooked vs raw versions of the product.

Real Time Prices (RTP) is a live dataset compiled and updated weekly by the World Bank Development Economics Data Group (DECDG) using a combination of direct price measurement and Machine Learning estimation of missing price data. The historical and current estimates are based on price information gathered from the World Food Program (WFP), UN-Food and Agricultural Organization (FAO), select National Statistical Offices, and are continually updated and revised as more price information becomes available. Real-time exchange rate data used in this process are from official and public sources.

RTP includes three sub-series, Real Time Food Prices (RTFP) includes prices on a variety of food items that primarily include country-specific staple foods, Real Time Energy Prices (RTEP) includes fuel prices, and Real Time Exchange Rates (RTFX) and includes unofficial exchange rate estimates as well as possible other unofficial deflators.

This online supplement contains data files and computer code, enabling the public to reproduce the results of the analysis described in the report titled “Thrifty Food Plan Cost Estimates for Alaska and Hawaii” published by USDA FNS in July 2023. The report is available at: https://www.fns.usda.gov/cnpp/tfp-akhi. The online supplement contains a user guide, which describes the contents of the online supplement in detail, provides a data dictionary, and outlines the methodology used in the analysis; a data file in CSV format, which contains the most detailed information on food price differentials between the mainland U.S. and Alaska and Hawaii derived from Circana (formerly Information Resources Inc) retail scanner data as could be released without disclosing proprietary information; SAS and R code, which use the provided data file to reproduce the results of the report; and an excel spreadsheet containing the reproduced results from the SAS or R code. For technical inquiries, contact: FNS.FoodPlans@usda.gov. Resources in this dataset:

Resource title: Thrifty Food Plan Cost Estimates for Alaska and Hawaii Online Supplement User Guide File name: TFPCostEstimatesForAlaskaAndHawaii-UserGuide.pdf Resource description: The online supplement user guide describes the contents of the online supplement in detail, provides a data dictionary, and outlines the methodology used in the analysis.

Resource title: Thrifty Food Plan Cost Estimates for Alaska and Hawaii Online Supplement Data File File name: TFPCostEstimatesforAlaskaandHawaii-OnlineSupplementDataFile.csv Resource description: The online supplement data file contains food price differentials between the mainland United States and Anchorage and Honolulu derived from Circana (formerly Information Resources Inc) retail scanner data. The data was aggregated to prevent disclosing proprietary information.

Resource title: Thrifty Food Plan Cost Estimates for Alaska and Hawaii Online Supplement R Code File name: TFPCostEstimatesforAlaskaandHawaii-OnlineSupplementRCode.R Resource description: The online supplement R code enables users to read in the online supplement data file and reproduce the results of the analysis as described in the Thrifty Food Plan Cost Estimates for Alaska and Hawaii report using the R programming language.

Resource title: Thrifty Food Plan Cost Estimates for Alaska and Hawaii Online Supplement SAS Code (zipped) File name: TFPCostEstimatesforAlaskaandHawaii-OnlineSupplementSASCode.zip Resource description: The online supplement SAS code enables users to read in the online supplement data file and reproduce the results of the analysis as described in the Thrifty Food Plan Cost Estimates for Alaska and Hawaii report using the SAS programming language. This SAS file is provided in zip format for compatibility with Ag Data Commons; users will need to unzip the file prior to its use.

Resource title: Thrifty Food Plan Cost Estimates for Alaska and Hawaii Online Supplement Reproduced Results File name: TFPCostEstimatesforAlaskaandHawaii-ReproducedResults.xlsx Resource description: The online supplement reproduced results are output from either the online supplement R or SAS code and contain the results of the analysis described in the Thrifty Food Plan Cost Estimates for Alaska and Hawaii report.

Series Name: Indicator of Food Price Anomalies (IFPA) by type of productSeries Code: AG_FPA_COMMRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 2.c.1: Indicator of food price anomaliesTarget 2.c: Adopt measures to ensure the proper functioning of food commodity markets and their derivatives and facilitate timely access to market information, including on food reserves, in order to help limit extreme food price volatilityGoal 2: End hunger, achieve food security and improved nutrition and promote sustainable agricultureFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

We use a nationally representative sample of 900 individuals in the UK to study food inflation perception. We have two parts: a first part, where consumers have to indicate the inflation of 38 different food categories, plus 3 aggregate food categories (all food, all grocery, all food eaten out-of-home), which we match the real inflation in the same period requested to participants; and a second part, with an experimental task that asks consumers to indicate the perceived size of the annual price change of 18 products, having only information on price, or with information on price + absolute annual price change, or price + annual percentage change (as before, actual data is available, and is in the codes).