Hostname: page-component-8448b6f56d-c4f8m Total loading time: 0 Render date: 2024-04-23T12:15:59.095Z Has data issue: false hasContentIssue false
  • English
  • Français

Dairy-borne Disease Outbreak and Milk Demand: A Study Using Outbreak Surveillance Data

Published online by Cambridge University Press:  15 September 2016

Yuqing Zheng  and
Harry M. Kaiser
Yuqing Zheng
Affiliation:
Department of Applied Economics and Management at Cornell University in Ithaca, New York
Harry M. Kaiser
Affiliation:
Department of Applied Economics and Management at Cornell University in Ithaca, New York
Get access

Abstract

We utilize the outbreak surveillance data from the Centers for Disease Control and Prevention (CDC) to examine whether consumer demand is impacted by the outbreak of food-borne disease. An additional person sickened due to the ingestion of tainted cheese products at home is found to decrease per capita milk demand in New York State by 0.13 percent (or 0.07 pound), while milk-and ice cream-borne disease outbreaks, occurring at home or in public places, are found to have no impact on fluid milk demand. Our results imply the existence of word-of-mouth effects, which cannot be tested by the popular information/media index approach used to measure food-borne disease outbreaks. We also find that a 7 percent increase in generic advertising expenditures or a 10 percent increase in expenditures on non-advertising marketing activities can offset the negative influence of one ill person in cheese-borne disease outbreaks at home, while holding other demand factors constant.

Keywords

Centers for Disease Control and Preventiondairy-borne disease outbreak (DBDO)fluid milk demandfood-borne disease outbreak (FBDO)outbreak surveillance data
Type
Contributed Papers
Information
Agricultural and Resource Economics Review , Volume 38 , Issue 3 , December 2009 , pp. 330 - 337
Copyright
Copyright © 2009 Northeastern Agricultural and Resource Economics Association 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Centers for Disease Control and Prevention. 2005. “Bacterial Foodborne and Diarrheal Disease National Case Surveillance.” Annual report, 2005. Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention.Google Scholar
Cox, T. 1992. “A Rotterdam Model Incorporating Advertising Effects: The Case of Canadian Fats and Oils.” In Kinnucan, H.W., Thompson, S.R., and Chang, , eds., Commodity Advertising and Promotion (pp. 139–164). Ames, IA: Iowa State Press.Google Scholar
Dong, D., Schmit, T.M., and Kaiser, H.M. 2007. “Optimal Media Allocation of Generic Fluid Milk Advertising Expenditures: The Case of New York State.” Agricultural and Resource Economics Review 36(2): 253–266.Google Scholar
Foster, W, and Just, R.E. 1989. “Measuring Welfare Effects of Product Contamination with Consumer Uncertainty.” Journal of Environmental Economics and Management 17(3): 266–283.Google Scholar
Greene, W.H. 1993. Econometric Analysis. Upper Saddle River, NJ: Prentice Hall, pp. 297–299.Google Scholar
Iraizoz, B., Bardaji, I., and Manuel, R. 2005. “The Spanish Beef Sector in the 1990s: Impact of the BSE Crisis on Efficiency and Profitability.” Applied Economics 37(4): 473–484.Google Scholar
Kinnucan, H.W., Miao, Y., Xiao, H., and Kaiser, H.M. 2001. “Effects of Advertising on U.S. Non-Alcoholic Beverage Demand: Evidence from A Two-Stage Rotterdam Model.” In Baye, M.R. and Nelson, J.P., eds., Advances in Applied Microeconomics. Elsevier Science, Amsterdam, pp. 1–30.Google Scholar
Larkin, C. 2009. “Tainted Peanut Butter May Have Killed 5, Sickened 453.” Bloomberg, January 16. Retrieved from http://www.bloomberg.com.Google Scholar
Lloyd, T, McCorriston, S., Morgan, C.W., and Rayner, A.J. 2001. “The Impact of Food Scares on Price Adjustment in the UK Beef Market.” Agricultural Economics 25(2-3): 347–357.Google Scholar
Lloyd, T., McCorriston, S., Morgan, C.W., and Rayner, A.J. 2006. “Food Scares, Market Power and Price Transmission: The UK BSE Crisis.” European Review of Agricultural Economics 33(2): 119–147.Google Scholar
Mazzocchi, M. 2006. “No News is Good News: Stochastic Parameters versus Media Coverage Indices in Demand Models after Food Scares.” American Journal of Agricultural Economics 88(3): 727–741.Google Scholar
Park, M., Jin, Y.H., and Bessler, D.A. 2008. “The Impacts of Animal Disease Crises on the Korean Meat Market.” Agricultural Economics 39(2): 183–195.Google Scholar
Pendell, D.L., Leatherman, J., Schroeder, T.C., and Alward, G.S. 2007. “The Economic Impacts of a Foot-and-Mouth Disease Outbreak: A Regional Analysis.” Journal of Agricultural and Applied Economics 39(special issue): 19–33.Google Scholar
Smith, M.E., van Ravenswaay, E.O., and Thompson, S.R. 1988. “Sales Loss Determination in Food Contamination Incidents: An Application to Milk Bans in Hawaii.” American Journal of Agricultural Economics 70(3): 513–520.Google Scholar
Vande Kamp, P.R., and Kaiser, H.M. 1999. “Irreversibility in Advertising-Demand Response Functions: An Application to Milk.” American Journal of Agricultural Economics 81(2): 385–396.Google Scholar
Verbeke, W., and Ward, R.W. 2001. “A Fresh Meat Almost Ideal Demand System Incorporating Negative TV Press and Advertising Impact.” Agricultural Economics 25(2-3): 359–374.Google Scholar
Zheng, Y., and Kaiser, H.M. 2009. “Evaluating the Effectiveness of Generic Advertising versus Non-advertising Marketing Activities on New York State Milk Markets.” Agribusiness: an International Journal 25(3): 351–368.Google Scholar