Hostname: page-component-8448b6f56d-tj2md Total loading time: 0 Render date: 2024-04-19T18:49:30.367Z Has data issue: false hasContentIssue false

Unraveling Demand for Dairy-Alternative Beverages in the United States: The Case of Soymilk

Published online by Cambridge University Press:  15 September 2016

Senarath Dharmasena*
Affiliation:
Agribusiness, Food, and Consumer Economics Research Center in the Department of Agricultural Economics at Texas A&M University
Oral Capps Jr.
Affiliation:
Agribusiness, Food, and Consumer Economics Research Center in the Department of Agricultural Economics at Texas A&M University
*
Correspondence: Senarath DharmasenaAFCERCDepartment of Agricultural EconomicsTexas A&M University2124 TAMUCollege Station, TX 77843-2124Phone 979.862.2894 ▪ Email sdharmasena@tamu.edu.
Get access

Abstract

Soymilk is one of the fastest growing categories in the U.S dairy alternative functional beverage market. Using household-level purchase data from Nielsen's 2008 Homescan panel and the Tobit econometric procedure, we estimate conditional and unconditional own-price, cross-price, and income elasticities for soymilk, white milk, and flavored milk. Income, age, employment status, education level, race, ethnicity, region, and presence of children in a household are significant drivers of demand for soymilk. White milk and flavored milk are competitors for soymilk, and soymilk is a competitor for white milk. Strategies for pricing and targeted marketing of soymilk are also discussed.

Type
Selected Papers
Copyright
Copyright © 2014 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

Alviola, P.A., and Capps, O. Jr. 2010. “Household Demand Analysis of Organic and Conventional Fluid Milk in the United States Based on the 2004 Nielsen Homescan Panel.” Agribusiness 26(3): 369388.Google Scholar
Belsley, D.A., Kuh, E., and Welsch, R.E. 1980. Regression Diagnostics Identifying Influential Data and Sources of Collinearity. Hoboken, NJ: John Wiley & Sons.Google Scholar
Beverage Marketing Corporation. 2010a. Soy Beverages in the United States. New York, NY.Google Scholar
Beverage Marketing Corporation. 2010b. Beverage Marketing Corporation Multiple Beverage Marketplace Reports. New York, NY.Google Scholar
Beverage Marketing Corporation. 2011. Beverage Marketing Corporation Multiple Beverage Marketplace Reports. New York, NY.Google Scholar
Beverage Marketing Corporation. 2012. Beverage Marketing Corporation Multiple Beverage Marketplace Reports. New York, NY.Google Scholar
Capps, O. Jr., Tsai, R., Kirby, R., and Williams, G. 1994. “A Comparison of Demand for Meat Products in the Pacific Rim Region.” Journal of Agricultural and Applied Economics 19(1): 210224.Google Scholar
Dharmasena, S., and Capps, O. Jr. 2011. “Is Chocolate Milk the New-Age Energy/Sports Drink in the United States?Journal of Agricultural and Applied Economics 43(3): 461.Google Scholar
Dharmasena, S., and Capps, O. Jr. 2012. “Intended and Unintended Consequences of a Proposed National Tax on Sugar-Sweetened Beverages to Combat the U.S. Obesity Problem.” Health Economics 21(6): 669694 (DOI: 10.1002/hec.1738).Google Scholar
Dharmasena, S., Capps, O. Jr., and Clauson, A. 2009. “Nutritional Contributions of Nonalcoholic Beverages to the U.S. Diet: 1998–2003.“ Journal of Agricultural and Applied Economics 41(2): 546.Google Scholar
Food Business News. 2013. “More Ingredients Are Being Used for Dairy Alternatives.” January 7.Google Scholar
Gould, B.W. 1996. “Factors Affecting U.S. Demand for Reduced Fat Milk.” Journal of Agricultural and Resource Economics 21(1): 6881.Google Scholar
Heckman, J.J. 1979. “Sample Selection Bias as a Specification Error.” Econometrica 47(1): 153161.Google Scholar
Kennedy, P. 2003. Limited Dependent Variables. A Guide to Econometrics. Cambridge, MA: MIT Press.Google Scholar
Kinnucan, H.W., Miao, Y., Xiao, H., and Kaiser, H.M. 2001. “Effects of Adverting on U.S. Nonalcoholic Beverage Demand: Evidence from a Two-Stage Rotterdam Model.” In Baye, M.R. and Nelson, J.P., eds., Advertising and Differentiated Products (Advances in Applied Microeconomics, Vol. 10). Cambridge, MA: Emerald Group Publishing.CrossRefGoogle Scholar
Kyureghian, G., Capps, O. Jr., and Nayga, R. 2011. “A Missing Variable Imputation Methodology with an Empirical Application.” Advances in Econometrics 27A: 313337.Google Scholar
McDonald, J.F., and Moffitt, R.A. 1980. “The Uses of Tobit Analysis.” Review of Economics and Statistics 62(2): 318321.Google Scholar
Siega-Riz, A.M., Popkin, B.M., and Carson, T. 1998. “Trends in Breakfast Consumption for Children in the United States from 1965–1991.” American Journal of Clinical Nutrition 67(4): 74857565.CrossRefGoogle ScholarPubMed
Soyfoods Association of North America. 2013. “Soy Information: Sales and Trends.” Washington, DC. Available at www.soyfoods.org/soy-information/sales-and-trends (accessed February 12, 2013).Google Scholar
Storey, M.L., Forshee, R.A., and Anderson, P.A. 2006. “Beverage Consumption in the U.S. Population.” Journal of the American Dietetic Association 106(12): 19922000.Google Scholar
Tobin, J. 1958. “Estimation of Relationships for Limited Dependent Variables.” Econometrica 26(1): 2436.CrossRefGoogle Scholar
U.S. Department of Agriculture. 2011. “What Foods Are Included in the Dairy Group?” web page. Available at www.choosemyplate.gov/foodgroups/dairy.html (accessed September 9, 2011).Google Scholar
Yen, S.T., Lin, B-H., Smallwood, D.M., and Andrews, M. 2004. “Demand for Nonalcoholic Beverages: The Case of Low-Income Households.” Agribusiness 20(3): 309321.Google Scholar
Zheng, Y., and Kaiser, H.M. October 2008. “Advertising and U.S Nonalcoholic Beverage Demand.” Agricultural and Resource Economics Review 37(2): 147159.Google Scholar