Doctoral Dissertations

Date of Award

6-1985

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Agricultural Economics

Major Professor

J. R. Brooker

Committee Members

David B. Eastwood, Dan L. McLemore, Luther H. Keller, David L. Kaserman

Abstract

The objectives of this study were: (1) to develop a theoret-ical and econometric model to estimate sets of household implicit price coefficients for nutritional attributes associated with foods consumed by households, (2) to estimate household demand functions for various dietary components of food, where the quantity of each nutritional attribute demanded by households was hypothesized to be related to the implicit prices of all nutritional attributes as well as geographic, demographic, and socioeconomic variables, and (3) to examine implications of the findings from objective one and two relative to current and future production, marketing, and consumption of foods. Household utility was assumed to be a function of total quan-tities consumed of m product characteristics, as determined by n physical quantities of goods consumed. The resulting hedonic price model stated that the price paid for each food product consumed was related to the quantities of attributes possessed by that product. By this price decomposition equation, each product price was expressed as a function of attribute prices. Allowing for prefer-ence structures to vary among households, demand for attributes would be affected by the prices of product attributes, income, and household characteristics. Data from approximately 2,200 households located in the con-tiguous states of the United States were utilized to specify household nutrient demand relationships. These data were separated by geographic location of the household to facilitate the estimation of nutrient demand relationships for households in the South, North east, North Central, and West regions of the United States. United States and regional household demand relationships were estimated for protein, fat, carbohydrates, calcium, iron, magnesium, phosphorus, vitamin A, thiamin, riboflavin, niacin, vitamin B6, vitamin B12 and vitamin C using multiple regression analysis. These nutrient demand relationships estimated the impact of implicit prices, income, and selected socioeconomic factors on household demand for the respective food nutrients.

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