Revisiting aggregate US meat demand with a Bayesian averaging of classical estimates approach: Do we need a more general theory? Academic Article

abstract

• Although meat demand is one of the most studied issues in agricultural economics, our understanding of this phenomenon has been hampered by valid concerns about model specification uncertainty. This article revisits the need for more general theories of aggregate U.S. meat demand. Using a Bayesian averaging of classical estimates approach, we draw comprehensive inferences over 1,048,576 demand systems. We find very little evidence supporting the need for more general theories that include demand determinants beyond prices and expenditures. We find strong evidence in support of symmetry and negativity, but strong evidence against homogeneity, which is consistent with other research. 2008 American Agricultural Economics Association.

authors

• Bryant, Henry

published proceedings

• AMERICAN JOURNAL OF AGRICULTURAL ECONOMICS

author list (cited authors)

• Bryant, H. L., & Davis, G. C.

citation count

• 9

complete list of authors

• Bryant, Henry L||Davis, George C

publication date

• February 2008

publisher

• Wiley  Publisher

published in

• American Journal of Agricultural Economics  Journal

keywords

• Demand Systems
• Meat Demand
• Model Averaging
• Model Uncertainty

Digital Object Identifier (DOI)

• 10.1111/j.1467-8276.2007.01054.x

start page

• 103

end page

• 116

volume

• 90

issue

• 1

URL

• http://dx.doi.org/10.1111/j.1467-8276.2007.01054.x