Adv Tops In Aec:Advanced Ag Informatics
Advanced study in special topics in agricultural economics. May be repeated under a different subtitle to a maximum of fifteen credits. Lecture, one to three hours; laboratory, zero to six hours per week.
Advanced study in special topics in agricultural economics. May be repeated under a different subtitle to a maximum of fifteen credits. Lecture, one to three hours; laboratory, zero to six hours per week.
This course surveys a variety of current public policies that influence the agricultural and rural economies. Students are exposed to the conflicting views of those concerned with food and agricultural policy issues in an international economy. Economic principles are used to evaluate alternatives in terms of the general welfare of society.
Directed independent study of a selected problem that generally is sustained over an entire semester, requires data analysis, and results in a significant written product suitable for publication. May be repeated to a maximum of six credits.
Directed independent study of a selected problem that generally is sustained over an entire semester, requires data analysis, and results in a significant written product suitable for publication. May be repeated to a maximum of six credits.
Directed independent study of a selected problem that generally is sustained over an entire semester, requires data analysis, and results in a significant written product suitable for publication. May be repeated to a maximum of six credits.
Directed independent study of a selected problem that generally is sustained over an entire semester, requires data analysis, and results in a significant written product suitable for publication. May be repeated to a maximum of six credits.
A critical examination of objectives and results of various types of research in marketing organization, marketing functions, price analysis, markets over time, space and form, market information, commodity promotion programs, quality standards, and macroeconomic linkages to marketing.
This course uses statistical tools to model agricultural and economic systems. Subjects covered include: (1) the classical linear regression model, techniques for single and simultaneous equation models.
This course introduces students to the econometric models, estimation procedures, and model applications in the literature. The course includes an overview of different econometric models, model estimations using Stata and SAS, discussion of agricultural and applied economics papers applying these models, and writing mini projects and a term paper with econometric applications. Topics include discrete and limited dependent variable models, panel data models, time-series models, instrumental variables, survival analysis, spatial econometrics and other special topics.
Half-time to full-time work on thesis. May be repeated to a maximum of six semesters.