- Instructor: Temie Alehegn
This course requires completion of Statistics for Agribusiness (Stat212) for ABVM students and Statistics for Economists (AgEc 232) for AgEc students, as part of their respective program requirements. However, all students must have a solid foundation in economic theory, statistical concepts, and mathematical economics to succeed in this course. Econometrics (AgEc 312), provides an introduction to the principles and applications of econometrics. This course builds upon foundational knowledge from previous semesters to equip students with the skills to quantitatively analyze economic data, test economic theories, and forecast future trends. Students will learn how to develop and estimate econometric models, interpret results, and use these models for prediction and forecasting. The course emphasizes the practical application of econometric techniques using statistical software packages like SPSS, STATA, and Excel. This hands-on approach, combined with the online delivery via Moodle, prepares students to effectively use econometrics in their research projects and future careers.
Course Objectives:
Upon successful completion of this course, students will be able to:
- Understand the core goals and purpose of econometrics.
- Develop and formulate appropriate regression models based on economic theory.
- Estimate regression models using real-world data and interpret the results.
- Utilize estimated equations for prediction and forecasting.
- Apply econometric methodologies to their research projects.
The course covers the following topics:
- Unit 1: Introduction to Econometrics: Definition, scope, goals, methodology, desirable properties of econometric models, and elements of econometrics.
- Unit 2: Correlation Theory: Basic concepts, coefficient of linear correlation, and types of correlation coefficients.
- Unit 3: Simple Linear Regression Models: Basic concepts and assumptions, least squares criteria, normal equations of OLS, coefficient of correlation and determination, and hypothesis testing.
- Unit 4: Multiple Regression Analysis: Models with two explanatory variables, notations and assumptions, estimation of partial regression coefficients, variance and standard errors of OLS estimators, hypothesis testing, and other functional forms.
- Unit 5: Econometric Problems: Non-normality, multicollinearity, heteroskedasticity, and autocorrelation.
- Unit 6: Non-linear Regression and Time Series Econometrics: Overview of non-linear regression models and an introduction to time series analysis.
- Instructor: Gedisha Katola
This course requires a basic knowledge of microeconomics and macroeconomics as a prerequisite. It is a one-semester course in international trade theory and policy emphasizing the agricultural sector. The course aims to explain patterns of world agricultural trade and ask if international trade is beneficial in the context of an agrarian economy. This will be done with the help of models from international trade theory that are toolkits of contemporary international trade analysis. The course will extensively explore trade protection mechanisms and different arguments in the field. The techniques include partial equilibrium analysis to demonstrate the welfare impacts and trade-off of trade policies, measures of price distortions, and competitiveness and limitations of such models. The issue of regional integration and its pros and cons will be covered, focusing mainly on the existing integrations in Africa. Finally, the course will hint at the contemporary trading systems and networks in the world and their implications for economic development.
- Instructor: Gedisha Katola