• Demonstrate knowledge of concepts, models, methods and tools in econometrics, corresponding to the course syllabus
• Evaluate an empirical study which another has produced
• Implement a reasonably simple econometric analysis in practice

Do family owned businesses do better than other companies? Is it a problem that the risk of stocks – their betas – are often derived based on historical data? How can one determine a company's returns to scale? How does one estimate a price elasticity? Generally, how does one ‘confront’ a research hypothesis with data?

The main course objective is to provide students with the necessary tools to answer such questions by introducing a range of models and methods in econometrics. The course will focus more heavily on the applied aspects of econometrics, as opposed to the theoretical. The curriculum is designed to target students who intend to conduct an empirical analysis as part of their undergraduate/graduate study program.

The course will focus on the various applications of regression models. Two different types of data often encountered in economics and business will be considered along with the appropriate techniques for such data.  Throughout the course, emphasis will be placed on quantitative and qualitative understanding of the models employed. That is, how one can translate a qualitative research question to a quantitative model and of course the ability of students to interpret resulting output. A recurring theme in such an interpretation is the distinction between correlation and causation. Despite the intuitive simplicity of such a distinction, much of the difficulty of econometrics stems from the simple fact that we use observational data. For instance, can we determine whether equity markets affect the real economy, or is it the reverse?

Stock, J. H. and Watson, M., Introduction to Econometrics (Pearson Education, 2011).

 The textbook is supplemented with a few scientific articles that are relevant to some of the course examples.