Teaching

The following course content and learning objectives applied across the three academic years listed above. This applied econometrics tutorial course focused on regression analysis, model diagnostics, and the practical use of R for empirical work.

Course Content

• Introduction to regression analysis
• The classical linear regression model
• Residual analysis, diagnostics, and influence measures
• Generalized regression models, heteroskedasticity, and autocorrelation
• Selected issues in applied econometrics

Learning Objectives

• Produce and compare different estimators using a variety of datasets.
• Develop familiarity with the statistical software R.
• Apply core econometric methods to empirical data.
• Describe and critically discuss a scientific article or study based on basic econometric methods.
• Apply the theoretical concepts covered in class to practical cases.