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Economic Evidence of Willingness to Pay for the National Animal Identification System in the US


  • Resende Filho, Moises de Andrade
  • Buhr, Brian L.


This article investigates the willingness to pay for the National Animal Identification System (NAIS) in the US. It is assumed that with the NAIS in place, consumers' risk perception about zoonosis, BSE or mad cow and residues in meat may be mitigated. Therefore, food safety indices for beef, pork and poultry summing the number of references to meat safety found in the top fifty English language news articles in circulation in the US have been constructed. These indices were incorporated in generalized almost ideal demand systems to estimate the effect of those food safety scares on the demand for meat in the US. It has been found that food safety impacts upon the final demand for meat in the US are small and do not show lagged effects. Using the preferred model, three scenarios have been constructed on the basis of hypothesized impacts of the NAIS on consumers' food safety concerns about meat. Finally, the differences in the predicted total revenue for beef, pork and poultry between scenarios are used as gross measures of the NAIS' economic value to the meat sector. The main conclusion is that if the defense of the NAIS is based on its effect on the demand side of the market for meats it is expected that the US Federal government will need to pay for a great part of the costs with the NAIS; otherwise the NAIS is likely to be economically unfeasible in the US.

Suggested Citation

  • Resende Filho, Moises de Andrade & Buhr, Brian L., 2006. "Economic Evidence of Willingness to Pay for the National Animal Identification System in the US," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25342, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae06:25342

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    References listed on IDEAS

    1. Dickinson, David L. & Bailey, DeeVon, 2002. "Meat Traceability: Are U.S. Consumers Willing To Pay For It?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(02), December.
    2. Douglas Fisher & Adrian R. Fleissig & Apostolos Serletis, 2006. "An Empirical Comparison of Flexible Demand System Functional Forms," World Scientific Book Chapters,in: Money And The Economy, chapter 13, pages 247-277 World Scientific Publishing Co. Pte. Ltd..
    3. Paul Cashin, 1991. "A Model Of The Disaggregated Demand For Meat In Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 35(3), pages 263-283, December.
    4. Nicholas E. Piggott & Thomas L. Marsh, 2004. "Does Food Safety Information Impact U.S. Meat Demand?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 154-174.
    5. Carter, Colin A. & Smith, Aaron D., 2004. "The Market Effect of a Food Scare: The Case of Genetically Modified StarLink Corn," Working Papers 11997, University of California, Davis, Department of Agricultural and Resource Economics.
    6. DeeVon Bailey & Jeremy Slade, 2004. "Factors Influencing Support for a National Animal Identification System for Cattle in the United States," Working Papers 2004-09, Utah State University, Department of Economics.
    7. Alston, Julian M. & Chalfant, James A. & Piggott, Nicholas E., 2001. "Incorporating demand shifters in the Almost Ideal demand system," Economics Letters, Elsevier, vol. 70(1), pages 73-78, January.
    8. Bailey, DeeVon & Slade, Jeremy, 2004. "Factors Influencing Support For A National Animal Identification System In The United States," 2004 Annual meeting, August 1-4, Denver, CO 20293, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Hobbs, Jill E., 2003. "Consumer Demand For Traceability," Working Papers 14614, International Agricultural Trade Research Consortium.
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    Cited by:

    1. Seyoum, Bruk Tefera & Adam, Brian D. & Ge, Candi, 2013. "The Value of Genetic Information in a Whole-Chain Traceability System for Beef," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150458, Agricultural and Applied Economics Association.
    2. Adam, Brian D. & Holcomb, Rodney & Buser, Michael & Mayfield, Blayne & Thomas, Johnson & O’Bryan, Corliss A. & Crandall, Philip & Knipe, Dar & Knipe, Richard & Ricke, Steven C., 2016. "Enhancing Food Safety, Product Quality, and Value-Added in Food Supply Chains Using Whole-Chain Traceability," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association (IFAMA), vol. 19(A).
    3. Larson, Ronald B. & Rana, Kulmani, 2011. "Consumer Support for Food Tracing with RFID Technology," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103672, Agricultural and Applied Economics Association.

    More about this item


    Animal Identification System; Food Safety; System of Demand Equations; Meat Industry; USA; Food Consumption/Nutrition/Food Safety; Livestock Production/Industries; C22; Q11; Q13; Q18;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • 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


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