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Revisiting Aggregate U.S. Meat Demand with a Bayesian Averaging of Classical Estimates Approach: Do We Need a More General Theory?

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  • Henry L. Bryant
  • George C. Davis

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. Copyright 2008, Oxford University Press.

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  • Henry L. Bryant & George C. Davis, 2008. "Revisiting Aggregate U.S. Meat Demand with a Bayesian Averaging of Classical Estimates Approach: Do We Need a More General Theory?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(1), pages 103-116.
    • Handle: RePEc:oup:ajagec:v:90:y:2008:i:1:p:103-116
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    File URL: http://hdl.handle.net/10.1111/j.1467-8276.2007.01054.x
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    Cited by:

    1. Harri, Ardian & Brorsen, B. Wade & Muhammad, Andrew & Anderson, John D., 2010. "Estimating a Demand System with Seasonally Differenced Data," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 42(2), May.
    2. McKendree, Melissa G.S. & Tonsor, Glynn T. & Schroder, Ted C. & Hendricks, Nathan P., 2017. "Changing Impacts of Beef Demand on Cattle Producers," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252730, Southern Agricultural Economics Association.
    3. Dharmasena, Senarath & Davis, George & Capps, Oral, Jr., 2014. "Partial versus General Equilibrium Calorie and Revenue Effects Associated with a Sugar-Sweetened Beverage Tax," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(2), pages 1-17.
    4. Matthew T. Holt & Joseph V. Balagtas, 2009. "Estimating Structural Change with Smooth Transition Regressions: An Application to Meat Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1424-1431.
    5. Kim, GwanSeon & Zheng, Yuqing, 2017. "U.S. Non-alcoholic Beverage Demand: Evidence from AIDS Model with Dynamic Effect," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 35(1), April.
    6. Mabiso, Athur & Weatherspoon, Dave D., 2008. "Fuel and Food Tradeoffs: A Preliminary Analysis of South African Food Consumption Patterns," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6126, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Claudia Schmidt & Steven C. Deller & Stephan J. Goetz, 2024. "Women farmers and community well‐being under modeling uncertainty," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 46(1), pages 275-299, March.
    8. Andreas Sachs, 2012. "What really drives unemployment? A bayesian approach to determine the impact of institutions on the unemployment rate," Economics Bulletin, AccessEcon, vol. 32(1), pages 1008-1019.
    9. Peyton Ferrier & Chen Zhen, 2014. "The producer welfare effects of trade liberalization when goods are perishable and habit-forming: the case of asparagus," Agricultural Economics, International Association of Agricultural Economists, vol. 45(2), pages 129-141, March.
    10. Rodriguez, Nestor & Eales, James S., 2015. "Structural Change via Threshold Effects: Estimating U.S. Meat Demand Using Smooth Transition Functions and the Effects of More Women in the Labor Force," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 206522, Agricultural and Applied Economics Association.

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