USDA contracts with WRMA to compile food price data

Summary

USDA relies on accurate food price data to develop and inform federal nutrition and agricultural policies. USDA’s Food and Nutrition Service (FNS) currently uses commercially available food prices to set maximum Supplemental Nutrition Assistance Program (SNAP) benefit allotments in the U.S. states and territories. However, limited data exist on food prices in Alaska, Hawaii, and the U.S. territories, where food prices are significantly higher than in the U.S. mainland. There are no sources of food price data in the U.S. territories, and data in Hawaii and Alaska only represent the most urban areas: Honolulu and Anchorage.

Through this study, WRMA will support FNS by collecting food price data to accurately estimate the prices of foods and beverages in the Thrifty Food Plan market basket, used to set SNAP allotments, in each of the non-contiguous states and U.S. territories. By selecting a representative sample of stores, implementing a rigorous retailer recruitment strategy, and focusing our data collection efforts on scanner data acquisition, we will also help FNS better serve individuals and families by:

1. Supporting the exploration and development of SNAP cost adjustments that more accurately reflect food prices in the non-contiguous states and U.S. territories.
2. Informing development of a data infrastructure that supports FNS’ re-evaluation of the TFP every five years, as required in the 2018 Farm Bill.
3. Providing a foundation to tailor future research, policy, and consumer education efforts to meet local needs and advance nutrition security.

Details

The WRMA team is working with FNS to devise a rigorous sampling, recruitment, and data collection strategy to collect food and beverage price data from a representative sample of retailers in Alaska, American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, Hawaii, Puerto Rico, and the U.S. Virgin Islands. Our sampling and recruitment strategies, combined with a multi-mode data collection approach, increase the likelihood of retailer participation and ensure food prices are inclusive of all store types across urban, suburban, and rural areas.

We are working with retailers to extract scanner data from electronic point-of-sale systems or their websites, as available. To accommodate smaller retailers, we are developing tools for retailer self-reporting and in-person shelf price data collection. In implementing a multi-mode approach, we can design and test a variety of data collection methods to assess the feasibility, including cost and data quality, of incorporating different methods into future FNS data collection activities.

We are conducting proof-of-concept testing for all recruitment and data collection strategies and will modify our approach based on lessons learned. Over a two-year data collection period, we are recruiting a representative sample of retailers in each state and territory, then working with individual retailers to determine the best data collection approach for each store and collect food prices. After completing data collection, we are harmonizing data collected from disparate sources to produce a single analytic dataset, estimate average food prices in the study locations, and summarizing the findings of the study in a report for the USDA at the end of the five-year project.