Search arXivSearch

arXiv · 2512.02564

Retail Price Ripples

Abstract

Much like small ripples in a stream, which get lost in the larger waves, small changes in retail prices often fly under the radar of public perceptions, while large price changes appear as marketing moves associated with demand and competition. Unnoticed, these could increase consumers out of pocket expenses. Indeed, retailers could boost their profits by making numerous small price increases or by obfuscating large price increases with numerous small price decreases, thereby bypassing the consumers full attention and consideration, and triggering consumer fairness concerns. Yet only a handful of papers study small price changes. Extant results are often based on a single retailer, limited products, short time span, and legacy datasets dating back to the 1980s and 1990s, leaving their current practical relevance questionable. Researchers have also questioned whether the reported observations of small price changes are artifacts of measurement errors driven by data aggregation. In a series of analyses of a large dataset containing almost 79 billion weekly price observations from 2006 to 2015, covering 527 products, and about 35,000 stores across 161 retailers, we find robust evidence of asymmetric pricing in the small, where small price increases outnumber small price decreases, but no such asymmetry is present in the large. We also document the reverse phenomenon, where small price decreases outnumber small price increases. Our results are robust to several possible measurement issues. Importantly, our findings indicate a greater current relevance and generalizability of such asymmetric pricing practices than the existing literature recognizes.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Xiao Ling, Sourav Ray, Daniel Levy. 2025-12-02. Retail Price Ripples. https://doi.org/10.13140/rg.2.2.24328.07686

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Access to Live AI Advice and Behavior Under Risk: An Incentivized Experiment

Generative AI has become an everyday advisor, and the systems people consult are live and interactive, not pre-scripted. We ask whether access to such a system changes behavior under risk. In an incentivized experiment (N = 158), participants made lottery choices with an optional decision aid presented as a conventional pre-written tool, a live one-shot AI, or a live interactive AI they could query, with information format held equivalent across conditions. Risk preferences are elicited via DOSE. We find no evidence that access to a live AI advisor changes risk aversion.

econ.GN

Bricks or Cash? Externalities of Housing Upgrading in High-density Cities

We estimate housing externalities in a high-density city, exploiting the staggered rollout of Singapore's nationwide Main Upgrading Programme for public housing. Controlling for nonrandom neighborhood exposure, we find that upgrading raises treated buildings' prices by 11.5% upon completion and neighboring buildings' resale prices by about 2% within 500 meters, decaying to zero beyond. A model with distance-decaying externalities shows that in dense settings spillovers justify the distortions of in-kind provision; this advantage diminishes and reverses at lower densities. Administrative data on over 2 million residents show that upgrading disproportionately retains older incumbents, suggesting age-specific amenities as an underexplored externality channel.

econ.GN

The Joneses Visit an Economics Lab

Existing literature offers persuasive evidence that individuals care about how their consumption compares to that of peers, and proposes a large variety of explanatory models. The present paper proposes a common framework for many of those models, and compares their ability to predict behavior in a laboratory experiment. We find evidence of Keeping up with the Joneses motivations but also find that conspicuous consumption is enhanced by Veblen motivations arising from peers' ability to observe one's own choice. Among the seven quasi-linear preference models we compare, our data are best explained by a model that contrasts envy and pride (upward vs downward comparisons) using a value function borrowed from Prospect Theory.

econ.GN