Regression analysis is the primary procedure commonly used by researchers and managers whether their employments are within the goods or the resources market and/or within the agriculture, the manufacturing, the services, or the information sectors of an economy. Completion of this course in econometrics will help you progress from a student of economics to a practitioner of economics. By completing this course, you will gain an overview of econometrics, develop your ability to think like an economist, hone your skills building and testing models of consumer and producer behavior, and synthesize the results you find through analyses of data pertaining to market-based economic systems. In essence, professional economists conduct studies that combine and project their expertise both in statistical procedures and analysis and in economic concepts and relationships. There are two major benefits to a study of econometrics: one is that it facilitates communication between econometricians and users of their work; the other is that it helps individuals to develop perspectives on econometric work and to make a critical evaluation of the work. Experience with econometrics and knowledge of the potential problems are essential for developing judgments about a study. For example, you could find yourself assessing studies that conclude the price of a gallon of gasoline has little influence on how much of it a driver purchases and findings that affirm the cost of producing a gallon of gasoline has little bearing on the current price of a gallon of gasoline you are pumping into your vehicle.
Upon successful completion of this course, the student will be able to:
- Construct, test, and analyze econometric models, using variables and relationships commonly found in studies of economic theory.
- Collect, organize, and analyze economic data, and interpret results from statistical analyses.
- Identify the desirable properties of estimators.
- Identify key classical assumptions in the field of econometrics, explain their significance, and describe the effects that violations of the classical assumptions can have.
- Use the least squares method in evaluating the relationship of one explanatory variable to the dependent variable and the relationships of multiple explanatory variables to the dependent variable.
- Interpret key statistics and diagnostics typically generated by software.
Course Requirements:
Have completed the following courses from the “Core Program” of the Economics discipline: Single-Variable Calculus I, Introduction to Statistics, and Principles of Microeconomics or Principles of Macroeconomics.