Quantitative Research Methods

The purpose of this course is to introduce modern econometric techniques and apply them to real world data sets. The material covered in this course includes an in-depth analysis of the linear regression model, least-squares estimation and statistical inference in this setting. Subsequently, nonlinear regression models are discussed and an introduction to panel data as well as stationary time series analysis is given. Empirical data sets are taken from finance and macroeconomics.

By the end of this course, students will have a sound understanding of fundamental
econometric techniques and will be able to apply them to real world data sets using
modern software.

The entire course relies on the following text. Stock, J. H. & M. W. Watson (2015). Introduction to Econometrics. 3rd updated ed. Boston: Pearson.ISBN: 9781292071312.URL: http://wps.pearsoned.co.uk/ema_ge_stock_ieupdate_3

The course takes the form of interactive lectures with exercises: on the one hand, theoretical material is presented and illustrated by means of empirical examples using the R statistical computing environment; on the other hand, participants are given exercises to practice the use of newly-learned concepts, both conceptually and on the computer.

written exam

Familiarity with the topics covered in Statistics I and II is assumed.

180 hrs