EconPapers    
Economics at your fingertips  
 

A meta‐analysis of U.S. food demand elasticities to detect the impacts of scanner data

Younghyeon Jeon, Hoa Hoang, Wyatt Thompson and David Abler

Applied Economic Perspectives and Policy, 2024, vol. 46, issue 2, 760-780

Abstract: This paper investigates how scanner data affect demand elasticity estimates and develops methods for scientists to adapt estimated elasticities to analyses of specific policies. We conduct a meta‐analysis of U.S. demand elasticities and find evidence that scanner data generate statistically different elasticities, with more elastic demand than other data types. Own‐price elasticity estimates from household scanner quantity data appear to be more elastic than other quantity types. Household‐level estimates using retail scanner price data, as proxies for prices, tend to be more price‐elastic than other price types. These results suggest caution or adjustment when selecting elasticities for policy analysis.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/aepp.13414

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:apecpp:v:46:y:2024:i:2:p:760-780

Access Statistics for this article

More articles in Applied Economic Perspectives and Policy from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-20
Handle: RePEc:wly:apecpp:v:46:y:2024:i:2:p:760-780