Household‐Level Food Price Inflation Heterogeneity: Evidence and Insights From the U.S. Consumer Panel Data (2013–2023)
Prayash Pathak Chalise
What the paper says
ABSTRACT This paper investigates heterogeneity in household‐level food price inflation in the United States from 2013 to 2023 using scanner data from the NielsenIQ Consumer Panel. By combining prices paid and quantities purchased, we compute household‐specific inflation rates and document substantial variation in inflation experiences across U.S. households—variation that widened sharply during the post‐pandemic inflation surge. Inflation inequality is especially pronounced among low‐income, older, single‐person, Asian, Black, and SNAP‐eligible households, who faced higher food inflation than other demographic groups. We further analyze the behavioral mechanisms households use to mitigate inflation exposure, showing that strategies such as increasing shopping frequency, visiting multiple retailers, and purchasing products on sale are associated with lower inflation exposure. However, the strength of these strategies declined during the recent high‐inflation period. We also find strong evidence of substitution toward lower‐priced products as households adjust to rising prices. Finally, we discuss the managerial implications of these findings for food retailers and agribusiness firms, highlighting how pricing, promotions, and product assortment strategies can be tailored to support consumers facing disproportionate inflation burdens. In general, our results highlight the role of household‐level heterogeneity in understanding the unequal burden of inflation and its managerial implications for agribusiness retailers.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.