Applications of demand analysis for the dairy industry using household scanner data

by Stockton, Matthew C.

Abstract (Summary)
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

Nerlove?s 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.

Bibliographical Information:

Advisor:Capps, Oral, Jr.; Nixon, Clair; Davis, George; Siebert, John; Schwart, Robert

School:Texas A&M University

School Location:USA - Texas

Source Type:Master's Thesis

Keywords:consumer demand household scanner data systems


Date of Publication:12/01/2004

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