Applications of demand analysis for the dairy industry using household scanner data
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This study illustrates the use of ACNielsen Homescan Panel (HSD) in three separate demand analyses of dairy products: (1) the effect of using cross-sectional data in a New Empirical Industrial Organization (NEIO) study of ice cream firm mergers in San Antonio; (2) the estimation of hedonic price models for fluid milk by quart, halfgallon and gallon container sizes; (3) the estimation of a demand system including white milk, flavored milk, carbonated soft drinks, bottled water, and fruit juice by various container sizes. In the NEIO study a standard LA/AIDS demand system was used to estimate elasticities evaluating seven simulated mergers of ice cream manufactures in San Antonio in 1999. Unlike previously published NEIO work, it is the first to use crosssectional data to address the issue associated with inventory effects. Using the method developed by Capps, Church and Love, none of the simulated price effects associated with the mergers was statistically different from zero at the 5% confidence level. In 1995 Nerlove proposed a quantity-dependent hedonic model as a viable alternative to the conventional price-dependent hedonic model as a means to ascertain consumer willingness to pay for the characteristics of a given good. We revisited Nerloves work validating his model using transactional data indigenous to the HSD. Hedonic models, both price-dependent and quantity-dependent, were estimated for the characteristics of fat content, container type, and brand designation for the container sizes of gallon, half- gallon, and quart. A rigorous explanation of the interpretation between the estimates derived from the two hedonic models was discussed. Using the Almost Ideal Demand System (AIDS), a matrix of own-price, crossprice, and expenditure elasticities was estimated involving various container sizes of white milk, flavored milk, carbonated soft drinks, bottled water, and fruit juices, using a cross-section of the 1999 HSD. We described price imputations and the handling of censored observations to develop the respective elasticities. These elasticities provided information about intra-product relationships (same product but different sizes), intrasize relationships (different products same container size), and inter-product relationships (different products and different sizes). This container size issue is unique in the extant literature associated with non-alcoholic beverage industry.
Stockton, Matthew C. (2004). Applications of demand analysis for the dairy industry using household scanner data. Doctoral dissertation, Texas A&M University. Texas A&M University. Available electronically from