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Cited by 409

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.

Uniform Pricing in U.S. Retail Chains*

DellaVigna, Stefano, Gentzkow, Matthew·2019·The Quarterly Journal of Economics

Abstract

We show that most U.S. food, drugstore, and mass-merchandise chains charge nearly uniform prices across stores, despite wide variation in consumer demographics and competition. Demand estimates reveal substantial within-chain variation in price elasticities and suggest that the median chain sacrifices ${\$}$16 million of annual profit relative to a benchmark of optimal prices. In contrast, differences in average prices between chains are broadly consistent with the optimal benchmark. We discuss a range of explanations for nearly uniform pricing, highlighting managerial inertia and brand image concerns as mechanisms frequently mentioned by industry participants. Relative to our optimal benchmark, uniform pricing may significantly increase the prices paid by poorer households relative to the rich, dampen the response of prices to local economic shocks, alter the analysis of mergers in antitrust, and shift the incidence of intranational trade costs.

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Crossref · 10.1093/qje/qjz019

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Metadata

Authors
DellaVigna, S., & Gentzkow, M.
Venue
The Quarterly Journal of Economics
Published
2019-06-25
Volume
134
Issue
4
Pages
2011-2084
ISSN
  • 0033-5533 (ISSN-L)
  • 1531-4650
OpenAlex
W2954972926
Cited by
409
References
55
FWCI
53.33
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Uniform Pricing in U.S. Retail Chains*. https://app.cochat.ai/papers/10.1093/qje/qjz019
The paper
DellaVigna, S., & Gentzkow, M. (2019). Uniform Pricing in U.S. Retail Chains*. The Quarterly Journal of Economics. https://doi.org/10.1093/qje/qjz019

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.