A1367
Title: Quantile time dummy product model for estimating cheapflation
Authors: Federico Crescenzi - University of Tuscia (Italy) [presenting]
Abstract: A novel quantile time product dummy approach is introduced to measure cheapflation -- the disproportionate rise in the prices of cheaper products relative to more expensive ones -- using high-frequency web-scraped food price data from Italy between 2020 and 2024. Unlike existing studies that rely on fixed price categories or quality ladders, this method directly estimates price inflation for arbitrary quantiles of the price distribution without requiring prior classification. The results reveal substantial inflation gradients: lower-priced items experienced significantly faster price growth than higher-end counterparts. These findings align with recent evidence on level pass-through pricing, asymmetric markup adjustments, and demand shifts toward low-cost goods.
