Estimating the Market Demand for Value-Added Beef: Testing for BSE Announcement
Effects Using a Nested PIGLOG Model Approach
Prepared for the 2006 American Agricultural Economics Association Annual Meeting
Steven S. Vickner1, DeeVon Bailey2 and Al Dustin3
1 Corresponding Author:
Associate Professor, Department of Economics, Utah State University,
Room 612, Eccles Business Building, 3530 Old Main Hill, Logan, UT, 84322-3530,
Phone: 435-797-2963, Fax: 435-797-2701, Email: svickner@econ.usu.edu
2 Professor, Department of Economics, Utah State University,
Room 606, Eccles Business Building, 3530 Old Main Hill, Logan, UT, 84322-3530,
Phone: 435-797-2316, Fax: 435-797-2701, Email: dbailey@econ.usu.edu
3 Head, Department of Farm & Ranch Management, Bridgerland Applied Technology
College, 1301 North 600 West, Logan, UT, 84321,
Phone: 435-753-6780, Fax: 435-752-2016, Email: adustin@bridgerlandatc.org
This project was funded in part by the USDA Rural Business Service Value-Added Producer
Grant program and the Utah Agricultural Experiment Station.
1
Literature Review
To analyze the market demand for fresh retail meats in the grocery store distribution channel, we
build upon a well-developed microeconomic model of consumer choice that incorporates the role
information plays in individual decision-making (Swartz and Strand; Smith, van Ravenswaay
and Thompson; Brown and Schrader; Wessells, Miller and Brooks; Piggott; Piggott and Marsh;
Kalaitzandonakes, Marks and Vickner; Marks, Kalaitzandonakes and Vickner). Mathios (2000)
in particular investigated the impact of labels on a processed food market using a random utility
model. Teisl, Bockstael and Levy (2001) used the Foster and Just (1989) framework in
conjunction with an Almost Ideal Demand System (Deaton and Muelbauer) to investigate the
impact of labeling in a small sample of stores in New England. Both the Mathios and Teisl et al.
studies were limited in terms of data quality; lack