The econometrics program is offered in a cycle over 3 terms:  Econometrics I,   Econometrics II, and Applied Econometrics.

In Econometrics I, we will cover the foundations of econometrics: causality and correlation, the Ordinary Least Squares (OLS) method, OLS model assumptions and properties, functional forms, dummy variables, and heteroscedasticity. The course includes as well an introduction of a statistical software (R or Stata) in order to conduct empirical exercises.

This course provides an introduction to the analysis of economic data using econometric methods. After having taken the course, students should be able to understand empirical studies published in scientific journals and carry out econometric work by themselves.

Attendance is compulsory and up to two sessions are allowed to be missed without formal justification

Midterm exam (30 points), final exam (40 points), empirical exercises (30 points). At least 30 points together in the mid-term and final exam in order to pass the course.

Sound knowledge of statistics (distributions, moments, and properties) and mathematics  (optimization, derivatives, sum operators and matrix).

carolina.lennon@wu.ac.at

Software:

Carrying out empirical work is part of the content of the course. As standard software package we will use R, but, if you you prefer, you can use Stata instead.

Supplementary Literature:

Baltagi, B. (2008). Econometrics, New York: Springer.

Greene, W. (2003). Econometric analysis, 5. ed., U.S.River, N.J.: Prentice Hall.

Gujarati, D.N., Porter, D.C. (2009). Basic Econometrics, New York: McGraw Hill.

Hackl, P. (2005). Einführung in die Ökonometrie. München: Pearson Studium.