This course is only available for students registered on the Banking & Finance Master programme.
The course introduces the student to the statistical and econometrical analysis of data. It combines a theoretical approach with empirical applications from Economics and Finance. During the course, the student also works on real data applications using statistical software. The first part of the course covers some basic elements of Probability Theory and Statistics which are the foundations of the subsequent parts of the course. The second part introduces the linear regression analysis, emphasizing the assumptions and statistical properties of the OLS model. This part also covers Hypothesis testing and post-estimation diagnosis is also covered in this part. The third part of the course focuses on the use of regression analysis for answering empirical questions. It addresses the endogeneity problems created by omitted variables, measurement error and reverse causation. Then, it introduces some basic tools for identification of causal effects including Randomized Control Trials, Instrumental Variables, Differences-in-Differences and Regression Discontinuity Designs. The last part of the course introduces time series analysis.
This is a 7.5 credit course.
Course material will be available through the learning platform Athena during the course.
Instruction is given in the form of lectures and computer exercises. The language of instruction is English.
The course is examined on the basis of a written examination. Students may be awarded examination creditsduring the course through voluntary partial examination.
ScheduleThe schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.
Course literatureNote that the course literature can be changed up to two months before the start of the course.
Angrist, J. D., and Pischke, J.-S., Mastering 'metrics: The path from cause to effect. Latest edition.
Stock J. and Watson M., Introduction to Econometrics. Addison Wesley Longman. Latest edition.
Additional references that can be consulted for some topics:
Cunningham, S., Causal Inference: The Mixtape. 2018. Free available at author’s website http://scunning.com/cunningham_mixtape.pdf
Brooks, C., Introductory Econometrics for Finance, (3rd edition). Cambridge University Press. 2014.
The course will also cover some articles from academic journals.