IDEAS home Printed from https://ideas.repec.org/p/ags/uersmp/404289.html

Long-Term Growth in U.S. Cheese Consumption May Slow

Author

Listed:
  • Davis, Christopher G.
  • Blayney, Don P.
  • Dong, Diansheng
  • Stefanova, Stela
  • Johnson, Ashley

Abstract

Cheese production and markets have emerged as important elements of the dairy industry over the past three decades. Three approaches were taken to assess factors affecting U.S. cheese consumption. The first showed the upward trend in total cheese consumption over time in a supply-and-use framework. The second approach examined consumption using selected demographic and economic factors and Nielsen 2005 Homescan data. Income, age, racial/ethnic factors, location, and gender influence cheese consumption in different, but significant, ways. Lastly, an analysis of Nielsen 2005 retail Homescan survey data was used to estimate cheese demand and expenditure elasticities. Own-price elasticities for all cheese products were statistically significant and elastic. Expenditure elasticities for all cheese products were also statistically significant, but only expenditures for American, cottage, and other cheeses were found to be elastic. The current White majority (the major consumers of cheese) of the population is expected to shrink as other groups grow in size. So, while U.S. per capita cheese consumption has more than doubled since the mid-1970s, future growth may slow as the U.S. population changes.

Suggested Citation

  • Davis, Christopher G. & Blayney, Don P. & Dong, Diansheng & Stefanova, Stela & Johnson, Ashley, 2010. "Long-Term Growth in U.S. Cheese Consumption May Slow," Miscellaneous Publications 404289, United States Department of Agriculture, Economic Research Service.
  • Handle: RePEc:ags:uersmp:404289
    DOI: 10.22004/ag.econ.404289
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/404289/files/LDP-M-193-01.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.404289?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Diansheng Dong & Brian W. Gould & Harry M. Kaiser, 2004. "Food Demand in Mexico: An Application of the Amemiya-Tobin Approach to the Estimation of a Censored Food System," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1094-1107.
    2. Daniel J. Phaneuf & Catherine L. Kling & Joseph A. Herriges, 2000. "Estimation and Welfare Calculations in a Generalized Corner Solution Model with an Application to Recreation Demand," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 83-92, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Davis, Christopher G. & Dong, Diansheng & Blayney, Donald P. & Owens, Ashley, 2010. "An Analysis of U.S. Household Dairy Demand," Technical Bulletins 184308, United States Department of Agriculture, Economic Research Service.
    2. Davis, Christopher G. & Blayney, Donald & Dong, Diansheng & Yen, Steven T. & Johnson, Rachel J., 2011. "Will Changing Demographics Affect U.S. Cheese Demand?," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 43(2), pages 259-273, May.
    3. Davis, Christopher G. & Dong, Diansheng & Blayney, Donald P. & Yen, Steven T. & Stillman, Richard, . "U.S. Fluid Milk Demand: A Disaggregated Approach," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 15(01), pages 1-26.
    4. Kyunghoon Ban & Sergio H. Lence, 2025. "Estimating demand systems with corner solutions: the performance of Tobit-based approaches," Applied Economics, Taylor & Francis Journals, vol. 57(14), pages 1559-1578, March.
    5. Golan, Amos & LaFrance, Jeffrey T & Perloff, Jeffrey M. & Seabold, Skipper, 2017. "Estimating a Demand System with Choke Prices," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt4qt9q8vr, Department of Agricultural & Resource Economics, UC Berkeley.
    6. Pellegrini, Andrea & Rose, John Matthew, 2025. "On allowing endogenous minimum consumption bounds in the multiple discrete continuous choice model: An application to expenditure patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 193(C).
    7. Fadhuile, Adelaide & Lemarie, Stephane & Pirotte, Alain, "undated". "Pesticides Uses in Crop Production: What Can We Learn from French Farmers Practices?," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103654, Agricultural and Applied Economics Association.
    8. Herriges, Joseph A. & Kling, Catherine L. & Phaneuf, Daniel J., 2004. "What's the use? welfare estimates from revealed preference models when weak complementarity does not hold," Journal of Environmental Economics and Management, Elsevier, vol. 47(1), pages 55-70, January.
    9. Kumar Dey, Bibhas & Anowar, Sabreena & Eluru, Naveen, 2021. "A framework for estimating bikeshare origin destination flows using a multiple discrete continuous system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 119-133.
    10. Ancev, Tihomir & Stoecker, Arthur L. & Storm, Daniel E. & White, Michael J., 2006. "The Economics of Efficient Phosphorus Abatement in a Watershed," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 31(3), pages 1-20, December.
    11. Diansheng Dong & Yuqing Zheng & Hayden Stewart, 2020. "The effects of food sales taxes on household food spending: An application of a censored cluster model," Agricultural Economics, International Association of Agricultural Economists, vol. 51(5), pages 669-684, September.
    12. Thiene, Mara & Swait, Joffre & Scarpa, Riccardo, 2017. "Choice set formation for outdoor destinations: The role of motivations and preference discrimination in site selection for the management of public expenditures on protected areas," Journal of Environmental Economics and Management, Elsevier, vol. 81(C), pages 152-173.
    13. Jing Li & Edward C. Jaenicke & Tobenna D. Anekwe & Alessandro Bonanno, 2018. "Demand for ready‐to‐eat cereals with household‐level censored purchase data and nutrition label information: A distance metric approach," Agribusiness, John Wiley & Sons, Ltd., vol. 34(4), pages 687-713, October.
    14. Fenichel, Eli P. & Abbott, Joshua K., 2014. "Heterogeneity and the fragility of the first best: Putting the “micro” in bioeconomic models of recreational resources," Resource and Energy Economics, Elsevier, vol. 36(2), pages 351-369.
    15. repec:ags:aaea22:343575 is not listed on IDEAS
    16. Okuyama, Tadahiro, 2018. "Analysis of optimal timing of tourism demand recovery policies from natural disaster using the contingent behavior method," Tourism Management, Elsevier, vol. 64(C), pages 37-54.
    17. French, Ryan R., 2006. "An analysis of the Iowan angler's fishing license renewal decision," ISU General Staff Papers 200601010800001876, Iowa State University, Department of Economics.
    18. Bernard Fortin & Nadia Joubert & Guy Lacroix, 2002. "Fiscalité, effets de voisinage et offre de travail au noir," Post-Print halshs-00178184, HAL.
    19. repec:isu:genstf:2008010108000016750 is not listed on IDEAS
    20. Goodwin, Barry K. & Phaneuf, Daniel J., 2001. "Microeconometric Modeling Of Household Food Demand: The Case Of Transition Bulgaria," 2001 Annual meeting, August 5-8, Chicago, IL 20713, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    21. Sikder, Sujan & Pinjari, Abdul Rawoof, 2013. "The benefits of allowing heteroscedastic stochastic distributions in multiple discrete-continuous choice models," Journal of choice modelling, Elsevier, vol. 9(C), pages 39-56.
    22. Khan, Mubassira & Machemehl, Randy, 2017. "Commercial vehicles time of day choice behavior in urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 68-83.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:uersmp:404289. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/ersgvus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.