Econometrics (BSc)

I taught this second year BSc economics course in Tilburg from 2010-11 to 2016-2017. I taught a similar course at the University of Chicago in 2000-01 (Econ 210). It provides an introduction to econometric methods, with a strong emphasis on the application of these methods in applied economic research.

In the first half of the course, students first acquire a basic understanding of the nature of empirical research and the possibilities and limitations of econometric methods. Then, they study the basics of one of econometrics’ key tools, linear regression analysis of cross-sectional data. Along the way, students are introduced to the software package Stata and econometric methods are illustrated with empirical examples and empirical exercises.

In the second half of the course, more advanced topics, including regression analysis with heteroskedastic and autocorrelated data, causal inference, instrumental variables estimation, and simultaneous equations models are studied. In addition, students are guided in writing a small research paper in empirical economics.

Students who have successfully completed this course have a good grasp of basic techniques of empirical economics, including linear regression and instrumental variables estimation. They are able to apply these techniques using the software package Stata, in applied economic research leading to a term paper or a BSc thesis. They are well prepared to study more advanced topics in applied econometrics, such as the analysis of time series data and panel data and latent variable models.

The course uses

  • Jeffrey Wooldridge (2016), Introductory Econometrics. A Modern Approach, Sixth edition, Cengage Learning.


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