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Determinants of price elasticities for private labels and national brands of cheese

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  • Min-Hsin Huang
  • Eugene Jones
  • David Hahn

Abstract

An Almost Ideal Demand System model is developed and used to estimate price elasticities for US cheese sold at retail. Growing consumption of cheese coupled with fierce competition between private labels and national brands serves as motivating factors for this study. Per capita consumption of cheese grew by 75% during 1980-2004 and private labels captured a rising share of this growth. Private labels today account for 35% of market share; national brands, for the remaining 65%. Kraft accounts for 45% of national brands, but price increases for Kraft brands led to a sizeable price gap between its brands and private labels. This gap helped to stimulate growth of private labels. Marketing managers seek to capitalize on both growing cheese sales and price gaps for brands. Relevant information for marketing managers is consumer sensitivity to price changes. This study uses 69 weeks of scanner data, with consumers segmented by income levels to derive price elasticities for both lower-and higher-income consumers. Results show lower-income consumers to be more price sensitive. If large price gaps are maintained, the results suggest continued growth of private labels. Yet, meta-analyses for this study suggest that Kraft could lower the price gap and regain market share.

Suggested Citation

  • Min-Hsin Huang & Eugene Jones & David Hahn, 2007. "Determinants of price elasticities for private labels and national brands of cheese," Applied Economics, Taylor & Francis Journals, vol. 39(5), pages 553-563.
  • Handle: RePEc:taf:applec:v:39:y:2007:i:5:p:553-563
    DOI: 10.1080/00036840500439069
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    1. Jasper M. Dalhuisen & Raymond J. G. M. Florax & JHenri L. F. de Groot & Peter Nijkamp, 2003. "Price and Income Elasticities of Residential Water Demand: A Meta-Analysis," Land Economics, University of Wisconsin Press, vol. 79(2), pages 292-308.
    2. Giancarlo Moschini, 1995. "Units of Measurement and the Stone Index in Demand System Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(1), pages 63-68.
    3. Folkes, Valerie S & Martin, Ingrid M & Gupta, Kamal, 1993. "When to Say When: Effects of Supply on Usage," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(3), pages 467-477, December.
    4. George Baltas, 2002. "An applied analysis of brand demand structure," Applied Economics, Taylor & Francis Journals, vol. 34(9), pages 1171-1175.
    5. Pollak, Robert A & Wales, Terence J, 1980. "Comparison of the Quadratic Expenditure System and Translog Demand Systems with Alternative Specifications of Demographic Effects," Econometrica, Econometric Society, vol. 48(3), pages 595-612, April.
    6. Brian Gould, 1997. "Consumer promotion and purchase timing: the case of cheese," Applied Economics, Taylor & Francis Journals, vol. 29(4), pages 445-457.
    7. Richard Green & Julian M. Alston, 1990. "Elasticities in AIDS Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(2), pages 442-445.
    8. T. D. Stanley, 2001. "Wheat from Chaff: Meta-analysis as Quantitative Literature Review," Journal of Economic Perspectives, American Economic Association, vol. 15(3), pages 131-150, Summer.
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    1. Davis, Christopher G. & Blayney, Donald P. & Dong, Diansheng & Yen, Steven T. & Johnson, Rachel J., 2011. "Will Changing Demographics Affect U.S. Cheese Demand?," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 43(2), pages 1-15, May.
    2. Bakhtavoryan, Rafael & Capps, Jr., Oral, . "A Demand Systems Analysis for Cheese Varieties Using a Balanced Panel of US-Designated Market Areas, 2018–2020," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 49(2).
    3. Luqman Olawale & Okewale Joel, 2017. "Factors Influencing Pricing Decision: Evidence from Non-Financial Firms in Nigeria," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 13(1), pages 157-172, February.
    4. Bouhlal, Yasser & Capps, Oral, Jr. & Ishdorj, Ariun, 2013. "Estimating the Censored Demand for U.S. Cheese Varieties Using Panel Data: Impact of Economic and Demographic Factors," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151298, Agricultural and Applied Economics Association.
    5. Rainer Olbrich & Michael Hundt & Hans Christian Jansen, 2016. "Proliferation of Private Labels in Food Retailing: A Literature Overview," International Journal of Marketing Studies, Canadian Center of Science and Education, vol. 8(6), pages 63-76, December.
    6. Timothy J. Richards, 2017. "Analysis of Umbrella Branding with Crowdsourced Data," Agribusiness, John Wiley & Sons, Ltd., vol. 33(2), pages 135-150, April.

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