Studying Composite Demand Using Scanner Data: The Case of Ground Beef in the US

Lee Schulz, Ted Schroeder and Tian Xia

Staff General Research Papers Archive from Iowa State University, Department of Economics

Abstract: This article reports tests of aggregation over elementary ground beef products and estimates composite demand elasticities. Results suggest that we obtain reliable information on consumers' actual ground beef purchases by grouping data according to either lean percentage or brand type. The results also suggest that we obtain reliable information by using the data to form a single ground beef composite. By testing for valid aggregates and providing estimates of composite demand elasticities the analysis provides economists and policymakers with information regarding the effects of food and agricultural policies on consumers and producers that buy and produce ground beef.

Keywords: agregation; beef demand; Generalized Composite Commodity Theorem; ground beef (search for similar items in EconPapers)
JEL-codes: Q13 Q18 R32 (search for similar items in EconPapers)
Date: 2012-07-31
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Published in Agricultural Economics, August 2012, vol. 43, pp. 1-9

Downloads: (external link)
http://www2.econ.iastate.edu/papers/p15441-2012-08-01.pdf (application/pdf)

Related works:
Journal Article: Studying composite demand using scanner data: the case of ground beef in the US (2012)
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:isu:genres:35441

Access Statistics for this paper

More papers in Staff General Research Papers Archive from Iowa State University, Department of Economics Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070. Contact information at EDIRC.
Bibliographic data for series maintained by Curtis Balmer ().