Estimating statistical regression models of economic relationships; treatment of special problems that may arise in analysis of economic data.
Upon completion of the course, the student should:
- understand the nature and scope of economics as a social science.
- use statistical analysis, including the classical regression model, to estimate relevant economic parameters, predict economic outcomes, and test economic hypotheses using quantitative data.
- understand the basic assumptions of the classical linear regression model, and identify and correct (if possible) any violations of these assumptions, such as autocorrelation and heteroscedasticity.
- develop and maintain a working knowledge of econometrics that will provide a basic foundation for future study in econometrics and statistical techniques.
This course will utilize Gretl, a free and user-friendly econometric software, for graphics, data management, basic statistics, and econometric estimation.
This course is approved for Validation by Education Experience (VEE) by the Society of Actuaries (SOA).
ECON 204 (Principles of Macroeconomics); MATH 141 (Calculus in Management Sciences) or MATH 155 (Calculus for Biological Sciences I) or MATH 160 (Calculus for Physical Sciences I); STAT 201 (General Statistics) or STAT 204 (Statistics for Business Students) or STAT 301 (Introduction to Statistical Methods) or Introduction to Biostatistics; Credit not allowed for both ECON 335 and AREC 335 (Introduction to Econometrics)
Prerequisites: Introductory microeconomics, introductory macroeconomics, introductory calculus, introductory statistics. Credit not allowed for both ECON 335 and AREC 335 (Introduction to Econometrics).