Hostname: page-component-848d4c4894-tn8tq Total loading time: 0 Render date: 2024-07-07T13:46:18.808Z Has data issue: false hasContentIssue false

Demographic Versus Media Advertising Effects on Milk Demand: The Case of the New York City Market

Published online by Cambridge University Press:  10 May 2017

Henry Kinnucan*
Affiliation:
Department of Agricultural Economics and Rural Sociology, Auburn University, Auburn, Alabama
Get access

Abstract

An advertising-sales response model is extended to include the effects of demographic factors (age and race) as additional determinants of milk demand. Previous research indicates that the age structure of a population and its racial composition are primary factors influencing fluid milk sales. Failure to incorporate these factors in the milk demand model results in a 30 percent downward biased estimate of the advertising effect. Consequently, the economic effectiveness of milk advertising is understated when the effects of demographic variables are ignored. Changes in demographic factors (growing nonwhite population and shrinking teenage market) appear to explain the relatively flat trend in per capita milk sales in the New York City market over the period 1971–80—a period in which dairy producers spent $12 million on generic advertising of milk. Net returns to Federal Order 2 dairy farmers from generic advertising of fluid milk is estimated to average $6.07 per media dollar invested over the 1972–79 period.

Type
Research Article
Copyright
Copyright © 1986 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.)

Footnotes

This research was completed while the author was a Research Associate in the Department of Agricultural Economics at Cornell University. Funds supporting this research were provided in part by the New York State Dairy Promotion Order. The author wishes to acknowledge the helpful suggestions and criticisms of Olan D. Forker, William G. Tomek, William H. Lesser, Gregory M. Sullivan, Lowell E. Wilson and two anonymous reviewers. AAES Journal No. 1-83540.

References

Almon, Shirley. “The Distributed Lag Between Capital Appropriations and Expenditures,Econometrica 33 (1965):178196.Google Scholar
Bandler, David K. Food Science Department, Cornell University, personal correspondence.Google Scholar
Boehm, W. T.The Household Demand for Fluid Milk in the United States with Regional Consumption Projections Through 1990.” Virginia Polytechnic Institute and State University, Research Div. Bull. 124, December, 1976.Google Scholar
Boehm, William T. and Babb, Emerson M. Household Consumption of Beverage Milk Products, Agr. Exper. Sta. Bull. No. 75, Purdue University, March, 1975.Google Scholar
Brewster, Letitia and Jacobson, Michael F. The Changing American Diet. Washington, D.C.: Center for Science in the Public Interests, 1978.Google Scholar
Hadar, Josef. Mathematical Theory of Economic Behavior. Massachusetts: Addison-Wesley Publishing Co., Inc., 1971.Google Scholar
Kinnucan, Henry W.Evaluating Farm Commodity Promotional Programs.” Symposium paper, American Agricultural Economics Association annual meetings, Cornell University, 1984.Google Scholar
Kinnucan, Henry W.Media Advertising Effects on Milk Demand: The Case of the Buffalo, New York Market With an Empirical Comparison of Alternative Functional Forms of the Sales Response Function.” Cornell University Agr. Econ. Research Paper No. 83-13, 1983.Google Scholar
Kinnucan, Henry W.Performance of Shiller Lag Estimates: Some Additional Evidence,” Cornell University Agr. Econ. Research Paper No. 81-8, 1981a.Google Scholar
Kinnucan, Henry W.Seasonality in Long-Run Advertising Elasticities for Fluid Milk: An Application of Smoothness Priors,” Cornell University Agr. Econ. Res. Paper No. 81-9, 1981b.Google Scholar
Massachusetts Institute of Technology. TROLL: The State of the Art in Econometric and Statistical Modeling. Center for Computational Research in Economics and Management Science. March 1983.Google Scholar
Nerlove, Marc and Waugh, F. V.Advertising Without Supply Control: Some Implications of a Study of the Advertising of Oranges,J. Farm Economics 43 (1961):813–37.Google Scholar
Novakovic, Andrew M.A Detailed Summary of the Dairy Production Stabilization Act of 1983.” Cornell University Agr. Econ. Staff Paper No. 83-26, 1983.Google Scholar
Rao, P. and Miller, R. L. Applied Econometrics. California: Wadsworth Publishing Co., Inc., 1971.Google Scholar
Salathe, Larry. “The Effects of Changes in Population Characteristics on U.S. Consumption of Selected Foods,Amer. J. Agr. Economics 61 (1979):1036–45.Google Scholar
Schenkler, Anna and Christ, Paul. Adjusting In-Area Fluid Milk Sales Data for Calendar Composition, USDA Agr. Marketing Service, Fed. Milk Order Marketing Station, FMOS-158, Apr. 1973.Google Scholar
Shiller, Robert J.A Distributed Lag Estimator Derived from Smoothness Priors,” Econometrica 41 (July 1973):775–88.Google Scholar
Thompson, S. R., and Eiler, D. A.Producer Returns from Increased Milk Advertising,Amer. J. Agr. Economics 57 (1975):505–08.Google Scholar
Thompson, S. R. and Eiler, D. A.Determinants of Milk Advertising Effectiveness,Amer. J. Agr. Economics 59 (1977):330–35.Google Scholar
Thompson, S. R.An Analysis of the Effectiveness of Generic Fluid Milk Advertising in New York State.” Cornell University Agr. Econ. Res. Paper No. 78-17, 1978.Google Scholar
USDA. SEA. “Nutrient Levels in Food Used by Households in the United States, Spring 1977,” Prelim. Report No. 3, January 1981.Google Scholar
U.S. Department of Agriculture. Economic Research Service. Dairy Outlook and Situation. December, 1984.Google Scholar