Type of Document Dissertation Author Sulgham, Anil Kumar Author's Email Address firstname.lastname@example.org URN etd-11152006-205531 Title Econometric Essays on Specification and Estimation of Demand Systems Degree Doctor of Philosophy (Ph.D.) Department Agricultural Economics & Agribusiness Advisory Committee
Advisor Name Title Hector O. Zapata Committee Chair Krishna K. Paudel Committee Member R. Wes Harrison Committee Member Roger A. Hinson Committee Member Sudipta Sarangi Committee Member Dick R. Parish Dean's Representative Keywords
- Dynamic Models
- Static Models
- AIDS Model
- Demand Systems
- U.S. Meats
Date of Defense 2006-10-25 Availability unrestricted AbstractThis dissertation focuses on two research themes related to econometric estimation of
linear almost ideal demand systems (LAIDS) for U.S. meats. The first theme addresses whether
nonstationarity (unit-roots and cointegration) contributes to a dynamic specification of LAIDS
models. The results of the effect of nonstationarity are reported in two case studies. The second theme explores the relationship between age and household size with budget shares to specify semiparametric LAIDS model. The results are reported in a third case study that compares parametric and semiparametric models estimates of price and expenditure elasticities.
The first case study conducts a comparative analysis of elasticity estimates from static
and dynamic LAIDS models. Historical meat consumption data (1975:1-2002:4) for beef, pork
and poultry products were used. Hylleberg et al. (1990) seasonal unit roots tests were conducted.
Unit roots and cointegration analysis lead to the specification of an ECM of the Engle-Granger
type for the LAIDS model. Marshallian and compensated elasticities were generated from the
static and dynamic LAIDS models. The study found some model differences in elasticity
estimates and rejected homogeneity in the dynamic model.
The second case study evaluates the forecasting performance of static and dynamic
LAIDS models. Forecast evaluation was based on mean square error (MSE) criteria and recently
developed MSE-tests. The study found ECM-LAIDS model performs uniformly better under all
forecasting horizons for the beef equation. However, in the case of the pork equation the static model performed better in one-step-ahead and two-step-ahead forecasting horizons while the
dynamic model was superior in the three-step-ahead and four-step-ahead forecasting horizons
using MSE comparisons. In testing, only the two-steps ahead was superior for pork.
The third case study specifies a semiparametric LAIDS model that maintains the linearity
assumption of prices and total expenditures and allows nonparametric effects of age and
household size. 2003 U.S. Consumer Expenditure Survey data for four meat products (beef,
pork, poultry and seafood) were used in the study. Model fit and elasticity estimates revealed negligible differences exist between parametric and semiparametric models.
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