Monthly average retail prices for food, household supplies, personal care items, cigarettes and gasoline. Prices are presented for the current month and previous four months. Prices are in Canadian current dollars.

The Consumer Price Index (CPI) for food is a component of the all-items CPI. The CPI measures the average change over time in the prices paid by urban consumers for a representative market basket of consumer goods and services. While the all-items CPI measures the price changes for all consumer goods and services, including food, the CPI for food measures the changes in the retail prices of food items only.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: Web page with links to Excel files For complete information, please visit https://data.gov.

According to a survey conducted in March 2024, 45 percent of U.S. Generation Z consumers were purchasing meat/poultry/fish less often due to rising prices and/or supply shortages. Another 44 percent were purchasing snacks/desserts less often for the same reason.

The USA: Food price index, world average = 100: The latest value from 2021 is 117.52 index points, a decline from 123.827 index points in 2017. In comparison, the world average is 105.854 index points, based on data from 165 countries. Historically, the average for the USA from 2017 to 2021 is 120.674 index points. The minimum value, 117.52 index points, was reached in 2021 while the maximum of 123.827 index points was recorded in 2017.

Cost of food in the United States increased 2.90 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: North, South, Artibonite, Centre, South-East, Grande'Anse, North-East, West, North-West, Market Average

According to a survey carried out between October and November 2024, consumers in ******* were the most likely to be expecting food prices to increase. Some ** percent of South African survey respondents stated they expected the cost of their food shopping to increase in the coming six months. In comparison, **************** respondents said the same.

India: Food price index, world average = 100: The latest value from 2021 is 58.17 index points, a decline from 58.758 index points in 2017. In comparison, the world average is 105.854 index points, based on data from 165 countries. Historically, the average for India from 2017 to 2021 is 58.464 index points. The minimum value, 58.17 index points, was reached in 2021 while the maximum of 58.758 index points was recorded in 2017.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Food in U.S. City Average (CPIUFDNS) from Jan 1913 to May 2025 about urban, food, consumer, CPI, inflation, price index, indexes, price, and USA.

Food Price Index in World increased to 128 Index Points in June from 127.30 Index Points in May of 2025. This dataset includes a chart with historical data for World Food Price Index.

Guyana: Food price index, world average = 100: The latest value from 2021 is 127.45 index points, an increase from 111.953 index points in 2017. In comparison, the world average is 105.854 index points, based on data from 165 countries. Historically, the average for Guyana from 2017 to 2021 is 119.702 index points. The minimum value, 111.953 index points, was reached in 2017 while the maximum of 127.45 index points was recorded in 2021.

Survey results of grocery items conducted periodically islandwide by the Consumer Affairs Commission survey officers.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Other Food Away from Home in U.S. City Average (CUSR0000SEFV05) from Jan 1998 to May 2025 about urban, food, consumer, CPI, housing, inflation, price index, indexes, price, and USA.

Graph and download economic data for Global price of Food index (PFOODINDEXA) from 1992 to 2024 about World, food, indexes, and price.

This dataset contains Food Prices data for Benin, sourced from the World Food Programme Price Database. The World Food Programme Price Database covers foods such as maize, rice, beans, fish, and sugar for 98 countries and some 3000 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.

In May 2025, prices for food and non-alcoholic beverages were around 3.3 percent higher than in the same month last year. Compared to previous months earlier in the timeline, prices increased less.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: Anbar, Babil, Baghdad, Basrah, Diyala, Dahuk, Erbil, Ninewa, Kerbala, Kirkuk, Missan, Muthanna, Najaf, Qadissiya, Salah al-Din, Sulaymaniyah, Thi-Qar, Wassit, Market Average

This table contains 289 series, with data for years 1956 - 1997 (not all combinations necessarily have data for all years), and was last released on 2000-02-18. This table contains data described by the following dimensions (Not all combinations are available): Geography (6 items: Canada; Ontario; Atlantic Region; Quebec ...), Commodities (279 items: Meat; fish and dairy products; Meat products; Beef; veal; mutton and pork; fresh or frozen; Primary meat products ...).

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: North Darfur, Blue Nile, Northern, Nile, Eastern Darfur, West Kordofan, Gedaref, West Darfur, North Kordofan, South Kordofan, Kassala, Khartoum, White Nile, South Darfur, Red Sea, Sennar, Al Gezira, Central Darfur, Market Average