The Food-at-Home Monthly Area Prices (F-MAP) data product provides detailed food price data to support a broad range of food economics research, supplementing existing public food price data. The data product contains monthly mean unit values and 6 price index measures for 90 food-at-home categories across 10 major metropolitan areas and 4 census regions. This report introduces the USDA, Economic Research Service (ERS) Food Purchase Groups (EFPGs) food classification system and describes the methods used to construct the F-MAP data product using weighted retail scanner data from 2016 to 2018. The F-MAP data product is modeled after the Quarterly Food-at-Home Price Database (QFAHPD) previously published by USDA, ERS to report 1999–2010 food-at-home prices.
Details
Title
Development of the Food-at-Home Monthly Area Prices Data
Record Identifier
https://ageconsearch.umn.edu/record/342467
Language
English
Total Pages
64
Note
The report used proprietary Circana (formerly Information Resources, Inc. (IRI)) retail scanner data for 2016–18 to construct the F-MAP price measures. Circana retail scanner data is a commercial dataset that contains dollar sales (revenue) and quantities of food items sold at FAH retail establishments. The authors mapped food products in the data to the EFPGs, a system for classifying foods based on characteristics such as ingredients, nutritional content, and convenience level. The EFPGs are structured as a tiered hierarchy of products and include 90 detailed food categories that can be aggregated into summary categories. Researchers used the retail scanner data to calculate monthly weighted average unit values, price indexes, and total sales volumes for 90 EFPGs across 15 geographic areas of the United States for all months for the 2016–18 period.