Date of Award

8-2012

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Applied Economics and Statistics

Committee Chair/Advisor

Carpio, Carlos E

Committee Member

Willis , David B

Committee Member

Bridges , William C

Abstract

This thesis consists of two essays focused on the estimation of food demand models from household-level data. The first essay examines the approach developed by Lewbel (1989) for the construction of household level commodity price indices (Stone-Lewbel prices) which can be used for the estimation of price effects in demand models. Stone-Lewbel prices are constructed using information on budget shares and Consumer Price Indices (CPIs) of the goods comprising the commodity groups. We consider three alternative CPIs for the construction of the Stone-Lewbel prices: monthly, quarterly and a constant (unity) price index (by a unity CPI we meant that all households face a unique same price). The unity CPI is used to simulate a scenario where no price index information is available. Data from the United States Consumer Expenditure Survey is used in the analyses. The EASI demand system is used as our parametric demand system. Two-stage estimate procedures are used to account for censoring in the data, and endogeneity of expenditures. Elasticities and marginal effect estimates from the demand models proved to be robust to the alternative CPIs considered in this study.
The second essay examines the demand for food commodities in Ecuador. We estimate three demand systems, one for the entire population, and one for urban and rural populations. The AIDS model is used as our parametric demand system. Specialized econometric procedures are used to account for censoring in the data, endogeneity of expenditures and the use of unit values as a proxy for prices. Estimated elasticities and marginal effects for the three systems are consistent with the theory. Substantial differences are observed between estimates for urban and rural populations.

Included in

Economics Commons

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