Students will have a good knowledge of econometric methods. They will have the skills to apply these methods to a set of economic data.

This course is part of the programme for second-year econometrics students. The challenge of econometrics is to answer the question, what everyday reality has to tell about economic theories. Here, everyday reality takes the form of numerical observations or 'data', while economic theories are translated into a formal statistical 'model' with corresponding hypotheses. In order to extract as much information as possible out of the former concerning the latter, an appeal is made to statistical induction. These are the 'econometric methods' that are the subject of this course. They comprise mainly the estimation of the model parameters, the testing of the model hypotheses, and making (conditional) predictions with the model. We will study the most frequently used statistical methods and techniques in the first place for the classical linear model, but finally also for equation systems representing an interdependent economic system and other frequently used econometric models. Econometrics students will work on a project. The objective of the project is to apply econometric methods to a problem studied in the parallel course "Financial Markets". The weekly assignments cover part of the work required for the project. Students who have chosen the course as an elective will have to hand in the assignments only. Econometrics students will continue to work on the project, which will lead to a second-year paper Econometrics.

Greene, W. (2012), Econometric Analysis, 7th ed., Pearson.

A first course in econometrics (see, e.g. Empirical Econometrics). Exchange students should have advanced knowledge of: 1) Mathematical statistics, 2) probability theory, 3) matrix algebra, 4) introduction to quantitative methods with an emphasis to the linear model
An advanced level of English.