An introduction to regression analysis and its application to economic and business research. Topics include using secondary data sources, simple and multiple regression, forecasting, time series analysis, and interpretation and communication of results. The course develops various empirical techniques and culminates with a final research report.
- Construct, estimate, and interpret regression models to identify relationships between explanatory and outcome variables.
- Construct, estimate, and interpret various functional forms for regression models, including the use of binary variables, log and quadratic functions, and interaction effects.
- Identify assumptions and possible shortcomings to estimated regression models.
- Identify patterns and relationships among macroeconomic and financial variables by estimating and interpreting elementary time series regression models.
- Apply econometric models to data using the statistical package R.
- Apply econometric models to economic data as part of a significant research project culminating in a formal paper and presentation.