The average for 2021 based on 165 countries was 105.854 index points. The highest value was in South Korea: 208.84 index points and the lowest value was in India: 58.17 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

Since 2019, food prices have increased every year. In 2022 and 2023, prices went up drastically in many countries. In 2023, in the European Union, inflation reached almost 12.6 percent compared to the previous year. This figure decreased to 2.3 percent in 2024.

This statistic shows food prices in France, Germany and Ireland compared to the United Kingdom (UK) in 2016, by food and beverage type. Almost all food prices in each of the three European countries were comparatively higher than in the UK. Germany had the biggest difference with the price of alcoholic beverages costing 56.6 percent less on 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.

This dataset provides values for FOOD INFLATION reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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.

Geographic coverage notes

The data cover the following areas: Afghanistan, Armenia, Bangladesh, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Congo, Dem. Rep., Congo, Rep., Gambia, The, Guinea, Guinea-Bissau, Haiti, Indonesia, Iraq, Kenya, Lao PDR, Lebanon, Liberia, Libya, Malawi, Mali, Mauritania, Mozambique, Myanmar, Niger, Nigeria, Philippines, Senegal, Somalia, South Sudan, Sri Lanka, Sudan, Syrian Arab Republic, Yemen, Rep.

The FAO Food Price Index (FFPI) averaged 128.8 points in September 2025. This represents an increase of 3.4 percent compared to the same month of the previous year. Food prices worldwide Some food commodities have been hit harder than others in the past years. Global dairy, meat, and vegetable oil prices were on an upward trajectory in the first half of 2025. Regionally, the European Union (EU) and the UK have experienced a particularly high increase in the annual consumer prices for food and non-alcoholic beverages, as compared to other selected countries worldwide. Inflation in Europe The inflation rate for food in the EU grew from 0.2 percent in May 2021 to 19.2 percent in March 2023, as compared to the same month in the previous year. In the following months, the food inflation started decreasing again, yet has picked up again in 2025 in line with the global trend. The overall inflation rate in the Euro area reached its peak in December 2022 at 9.2 percent. The rate has since fallen to 2.4 percent in December 2024. As measured by the Harmonized Index of Consumer Prices (HICP), inflation rates in Europe were highest in Turkey, Romania, and Estonia as of April 2025.

This dataset provides an analysis of average monthly prices for four essential food items, namely Eggs, Milk, Bread, and Potatoes, in five different countries: Australia, Japan, Canada, South Africa, and Sweden. The dataset spans a five-year period, from 2018 to 2022, offering a comprehensive overview of how food prices have evolved over time in these nations.

The dataset includes information on the average monthly prices of each food item in the respective countries. This information can be valuable for studying and comparing the cost of living, assessing economic trends, and understanding variations in food price dynamics across different regions.

Use Cases:

Comparative Analysis: Researchers and analysts can compare food prices across the five countries over the five-year period to identify patterns, trends, and variations. This analysis can help understand differences in purchasing power and economic factors impacting food costs.

Cost of Living Studies: The dataset can be used to examine the cost of living in different countries, specifically focusing on the expenses related to basic food items. This information can be beneficial for individuals considering relocation or policymakers aiming to evaluate living standards.

Economic Studies: Economists and policymakers can utilize this dataset to analyze the impact of economic factors, such as inflation or currency fluctuations, on food prices in different countries. It can provide insights into the stability and volatility of food markets in each region.

Forecasting and Planning: Businesses in the food industry can leverage the dataset to forecast future food price trends and plan their operations accordingly. The historical data can serve as a foundation for predictive models and assist in optimizing pricing strategies and supply chain management.

Note: The dataset is based on average monthly prices and does not capture individual variations or specific regions within each country. Further analysis and interpretation should consider additional factors like seasonal influences, local market dynamics, and consumer preferences.

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.

Average food price inflation was highest in ********** countries in 2023 when compared to the rest of the world. When compared to the previous year, food prices were almost ** percent higher in September and October of 2023 in low-income countries. This figure stood at *** percent for high income countries.

Domestic Food Prices After COVID-19

Analyzing Impact on Developing Countries' Food Security

By [source]

About this dataset

This dataset looks at the effect of the COVID-19 pandemic on food prices in both domestic and international markets, particularly in developing countries. It contains data on monthly changes in food prices, categorised by country, market, price type (domestic or international) and commodities. In particular, this dataset provides insight into how the pandemic has impacted food security for those living in poorer countries where price increases may be more acutely felt. This dataset gives us a greater understanding of these changing dynamics of global food systems to enable more efficient interventions and support for those who are most vulnerable

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How to use the dataset

This dataset is an excellent resource for anyone looking to analyze the impact of COVID-19 on domestic food prices in developing countries. With this dataset, you can get an up-to-date overview of changes in the costs of various commodities in a given market and by a given price type. Additionally, you can filter data by commodity, country and price type.

In order to use this dataset effectively, here are some steps: - Identify your research question(s) - Filter the dataset by selecting specific columns that best answer your research question (ex: month, country, commodity) - Analyze the data accordingly (for example: Sorting the results then calculating averages). - Interpret results into actionable insights or visualizations

Research Ideas

• Analyzing trends in the cost of food items across different countries to understand regional disparities in food insecurity.
• Comparing pre- and post-COVID international food prices to study how nations altered their trade policies in response to the pandemic, indicating a shift towards or away from trading with other nations for food procurement.
• Using sentiment analysis to study consumer sentiment towards purchasing certain items based on their market prices, allowing businesses and governments alike to better target interventions aimed at improving access and availability of food supplies

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: dom_clean_data.csv | Column name | Description | |:---------------|:---------------------------------------------------------------------------| | month | The month in which the data was collected. (Date) | | country | The country in which the data was collected. (String) | | price_type | The type of price (domestic or international) that was collected. (String) | | market | The market in which the data was collected. (String) | | commodity | The type of commodity that was collected. (String) |

File: int_clean_data.csv | Column name | Description | |:---------------|:---------------------------------------------------------------------------| | country | The country in which the data was collected. (String) | | commodity | The type of commodity that was collected. (String) | | price_type | The type of price (domestic or international) that was collected. (String) | | time | The month in which the data was collected. (String) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Graph and download economic data for Consumer Price Index for All Urban Consumers: Food at Home in U.S. City Average (CUSR0000SAF11) from Jan 1952 to Sep 2025 about urban, food, consumer, CPI, housing, inflation, price index, indexes, price, and USA.

Food purchases differ substantially across countries. We use detailed household level data from the US, France and the UK to (i) document these differences; (ii) estimate a demand system for food and nutrients, and (iii) simulate counterfactual choices if households faced prices and nutritional characteristics from other countries. We find that differences in prices and characteristics are important and can explain some difference (e.g., US-France difference in caloric intake), but generally cannot explain many of the compositional patterns by themselves. Instead, it seems an interaction between the economic environment and differences in preferences is needed to explain cross country differences.

The annual FAO Food Price Index* (FFPI) averaged 127.8 points in 2025. This represents an increase of 4.7 percent compared to the previous year. That year, the highest price index was registered in the vegetable oils category, at 160.1 points.

Context:

Welcome to the "Milk, Cheese, and Eggs Prices Dataset" on Kaggle! This dataset provides comprehensive information about the prices of milk, cheese, and eggs across various countries in the year 2017. Understanding the pricing trends of these essential food items is crucial for economists, policymakers, and consumers alike, as they form the foundation of many diets worldwide. This dataset is a valuable resource for researchers, analysts, and anyone interested in studying global food pricing dynamics.

Content:

The dataset consists of the following columns:

1.**Countries**: This column represents the names of different countries included in the dataset. It is a categorical variable.

2.**Milk, Cheese, and Eggs Prices, 2017**: This column contains the average prices of milk, cheese, and eggs in each respective country for the year 2017. These prices are provided as numerical values, typically in the local currency per unit (e.g., per liter, per kilogram, etc.). This column is a numerical variable.

3.**Global Rank**: This column indicates the global ranking of each country based on the average prices of milk, cheese, and eggs in 2017. A lower rank suggests lower prices, while a higher rank indicates higher prices. This column is a numerical variable.

4.**Available Data**: This column informs users about the availability of data for each country. It can have binary values (e.g., "Yes" or "No"), indicating whether complete data is available for that specific country. This column is a categorical variable.

Column Features: 1.**Countries**: Categorical - Description: The names of countries included in the dataset. - Example: "United States," "France," "India."

2.**Milk, Cheese, and Eggs Prices, 2017**: Numerical - Description: The average prices of milk, cheese, and eggs in each respective country for the year 2017. - Example: 2.50 (indicating the average price in the local currency per unit).

3.**Global Rank**: Numerical - Description: The global ranking of each country based on the average prices of milk, cheese, and eggs in 2017. - Example: 5 (indicating the country's rank).

4.**Available Data**: Categorical - Description: Indicates whether complete data is available for a specific country or not. - Example: "Yes" or "No."

This dataset allows you to explore and analyze the pricing disparities of milk, cheese, and eggs across different countries, identify trends, and gain insights into the global food market. Researchers can use it for comparative studies, and policymakers can use it to inform decisions related to food affordability and accessibility.

Feel free to perform your analyses, build predictive models, or generate visualizations to extract meaningful insights from this dataset. We encourage you to share your findings with the Kaggle community and contribute to a better understanding of global food pricing dynamics.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Food in U.S. City Average (CPIUFDSL) from Jan 1947 to Sep 2025 about urban, food, consumer, CPI, inflation, price index, indexes, price, and USA.

Pakistan Food Prices: Compared to Last 6 Mos: Positive data was reported at 0.840 % in Nov 2018. This records a decrease from the previous number of 2.440 % for Sep 2018. Pakistan Food Prices: Compared to Last 6 Mos: Positive data is updated monthly, averaging 1.665 % from Jan 2012 (Median) to Nov 2018, with 42 observations. The data reached an all-time high of 9.580 % in Mar 2015 and a record low of 0.390 % in Nov 2013. Pakistan Food Prices: Compared to Last 6 Mos: Positive data remains active status in CEIC and is reported by State Bank of Pakistan. The data is categorized under Global Database’s Pakistan – Table PK.H003: Consumer Confidence Survey.

This dataset provides values for FOOD INFLATION reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

A table comparing the cost of living in various European Union countries, including expenses for rent, utilities, food, and transportation in major cities

European Prepared Pet Food Labour Cost Per Employee FTE by Country, 2023 Discover more data with ReportLinker!