Econometric Methods 1

Students who are not enrolled in the research master Multidisciplinary Economics should contact the course coordinator for enrollment in this course.

This course is the first of two required courses on the main econometric techniques that are used in empirical research in economics. The first part of the course aims to provide a thorough knowledge of the linear regression model in terms of an application through cross-sectional, time-series and panel data. The estimators and testing procedures will be derived – included the statistical properties – for which the technique of linear algebra will be used. In addition, attention will be paid to the assumptions on which the statistical techniques are based. The econometric techniques will be illustrated by empirical examples of research by using the econometric software of Stata.

Part 1: OLS, exogeneity, consistency; 4.5 weeks in total. Part 2: Central Limit Theorem, GLS, time-series econometrics (non-stationarity, VAR, multivariate co-integration models) and panel data; 4 weeks in total.
 

Intended Learning Outcomes
The graduate:

• has broad knowledge of core and state-of-the-art theories and empirical methods in economics
• formulate a data management plan, and manage data sets, using statistical software
• can think in a logical way
• can apply acquired knowledge of theories and empirical methods within economics

The Real World Perspective
Although this is an advanced, theory-driven econometrics course, real-world relevance is incorporated through empirical illustrations in the tutorials. Students work with real datasets to demonstrate how theoretical econometric methods are applied in practice using statistical software. Examples typically include data from housing markets and individual-level datasets used to analyze labor market outcomes. These illustrations demonstrate how theoretical econometric assumptions and estimators operate when applied to real economic data used in empirical research.

Assessment method