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Studying composite demand using scanner data: the case of ground beef in the US

Author

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  • Lee L. Schulz
  • Ted C. Schroeder
  • Tian Xia

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.
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Suggested Citation

  • Lee L. Schulz & Ted C. Schroeder & Tian Xia, 2012. "Studying composite demand using scanner data: the case of ground beef in the US," Agricultural Economics, International Association of Agricultural Economists, vol. 43, pages 49-57, November.
    • Handle: RePEc:bla:agecon:v:43:y:2012:i::p:49-57
    DOI: j.1574-0862.2012.00619.x
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    Cited by:

    1. Li, Wenying & Zhen, Chen, "undated". "A Reassessment of Product Aggregation Bias in Demand Analysis: An Application to the U.S. Meat Market," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258197, Agricultural and Applied Economics Association.
    2. Dong, Diansheng & Stewart, Hayden & Dong, Xiao & Hahn, William, . "Quantifying Consumer Welfare Impacts of Higher Meat Prices During the COVID-19 Pandemic," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, vol. 2022(Economic ).
    3. Sato, Hideyasu, 2021. "Generalized Axiom of Revealed Preference Tests for Foods and Drinks: The Case of Using POS Data in Japan," 2021 ASAE 10th International Conference (Virtual), January 11-13, Beijing, China 329424, Asian Society of Agricultural Economists (ASAE).
    4. Sato, Hideyasu & 佐藤, 秀保, 2020. "Do Large-scale Point-of-sale Data Satisfy the Generalized Axiom of Revealed Preference in Aggregation Using Representative Price Indexes?: A Case Involving Processed Food and Beverages," RCESR Discussion Paper Series DP19-2, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    5. Shang, Xia & Tonsor, Glynn T., 2017. "Food safety recall effects across meat products and regions," Food Policy, Elsevier, vol. 69(C), pages 145-153.
    6. Taylor, Mykel R. & Tonsor, Glynn T., 2013. "Revealed Demand for Country-of-Origin Labeling of Meat in the United States," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(2), pages 1-13, August.
    7. Heng, Yan & House, Lisa, 2016. "A Composite Demand Analysis for the Beverage Market," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235704, Agricultural and Applied Economics Association.
    8. Manami Ogura, 2024. "Testing the aggregation of goods and services without separability using panel data," Empirical Economics, Springer, vol. 67(4), pages 1581-1613, October.

    More about this item

    JEL classification:

    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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