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Consumer willingness-to-pay to reduce the probability of retail foodborne pathogen contamination

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  • Teisl, Mario F.
  • Roe, Brian E.

Abstract

The US Department of Agriculture applies a cost-of-illness approach to value reductions in morbidity, which may understate the projected benefits from proposed food-safety improvements by ignoring costs such as pain, suffering and worry. We use a national survey with a hypothetical food-choice experiment to estimate a more comprehensive measure of consumer willingness-to-pay for food-safety improvements. Our approach differs from previous evaluations of food-safety improvements because we: (1) provide the respondent with information about the promised change in the probability of pathogen contamination in retail food packages rather than changes in the probability of becoming ill, (2) elicit changes in respondents' subjective probability of becoming ill, and (3) elicit predicted changes in the quantity demanded for products that have enhanced food-safety properties. We estimate the consumer's choice between a safety-enhanced and an existing product, the change in subjective probability of contracting foodborne illness associated with the enhanced product and the change-in-demand for the enhanced product in a manner that recognizes the correlation among unobserved elements. The aggregated results suggest benefit estimates that are significantly larger than previous estimates for similar improvements.

Suggested Citation

  • Teisl, Mario F. & Roe, Brian E., 2010. "Consumer willingness-to-pay to reduce the probability of retail foodborne pathogen contamination," Food Policy, Elsevier, vol. 35(6), pages 521-530, December.
  • Handle: RePEc:eee:jfpoli:v:35:y:2010:i:6:p:521-530
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    References listed on IDEAS

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    Cited by:

    1. Marette, Stéphan & Roe, Brian E. & Teisl, Mario, 2012. "The welfare impact of food pathogen vaccines," Food Policy, Elsevier, vol. 37(1), pages 86-93.
    2. Alphonce, Roselyne & Alfnes, Frode & Sharma, Amit, 2014. "Consumer vs. citizen willingness to pay for restaurant food safety," Food Policy, Elsevier, vol. 49(P1), pages 160-166.
    3. Gao, Zhifeng & House, Lisa & Bi, Xiang, 2016. "Impact of satisficing behavior in online surveys on consumer preference and welfare estimates," Food Policy, Elsevier, vol. 64(C), pages 26-36.
    4. Linhai Wu & Xiaolin Liu & Dian Zhu & Hongsha Wang & Shuxian Wang & Lingling Xu, 2015. "Simulation of Market Demand for Traceable Pork with Different Levels of Safety Information: A Case Study in Chinese Consumers," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 63(4), pages 513-537, December.
    5. Kevin Boyle & Sapna Kaul & Ali Hashemi & Xiaoshu Li, 2015. "Applicability of benefit transfers for evaluation of homeland security counterterrorism measures," Chapters,in: Benefit–Cost Analyses for Security Policies, chapter 10, pages 225-253 Edward Elgar Publishing.
    6. Yang, Ruoye & Raper, Kellie Curry & Lusk, Jayson L., 2017. "The Impact of Hormone Use Perception on Consumer Meat Preference," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252772, Southern Agricultural Economics Association.
    7. Ochieng’, Brian J. & Hobbs, Jill E., 2016. "Incentives for cattle producers to adopt an E. Coli vaccine: An application of best–worst scaling," Food Policy, Elsevier, vol. 59(C), pages 78-87.
    8. Petrolia, Daniel R., 2016. "Risk preferences, risk perceptions, and risky food," Food Policy, Elsevier, vol. 64(C), pages 37-48.
    9. Lilavanichakul, Apichaya & Boecker, Andreas, 2013. "Consumer Acceptance of a New Traceability Technology: A Discrete Choice Application to Ontario Ginseng," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association (IFAMA), vol. 16(4).
    10. Watanabe Masahide & Kawata Yukichika, 2017. "What Extent of Welfare Loss is Caused by the Disparity between Perceived and Scientific Risks? A Case Study of Food Irradiation," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 17(1), pages 1-17, February.
    11. Daniel R. Petrolia & Joonghyun Hwang & Craig E. Landry & Keith H. Coble, 2015. "Wind Insurance and Mitigation in the Coastal Zone," Land Economics, University of Wisconsin Press, vol. 91(2), pages 272-295.
    12. Dan Rigby & Michael Burton & Jo Pluske, 2016. "Preference Stability and Choice Consistency in Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(2), pages 441-461, October.

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