Empirical Economics (Economics)

Course goals

Learning objectives
At the end of the course the student is able to:

• Apply econometrics to analyze research questions using empirical data, and justify the chosen approach.
• Use basic statistics and mathematics to understand and derive the basic properties of several econometric models.
• Interpret and critically evaluate quantitative empirical studies to provide a policy recommendation.
• Understand various advanced approaches to statistical inference.
• Apply these and other methods in an Economics research project.

Content

This course aims to provide students with an understanding of basic econometric methods, and with knowledge on how to apply them. Students learn to understand the modern empirical economic literature and to independently analyze data to answer a research question. The course contains an introduction to statistical programming, followed by the linear regression model, and proceeds to focus on frequently-used techniques and settings in the empirical economics literature, such as panel data. The course focuses on the theory, but also on applying these methods using a statistical programming language, Python or R.
           
The second part of the course is uniquely for students in the Economics and Data Analysis and Economic Policy MSc programmes, and will focus on statistical inference, binary outcomes and an application of this and other techniques discussed in the course.

Format
Lectures: 1 lecture per week, 2 contact hours.
Tutorials: 1 tutorial per week, 2 contact hours.

Assessment method
Midterm exam (50%) and final exam (50%), conducted in-person on Remindo. The midterm exam will focus on the theory and the content in the first half of the course. Tentatively, the final exam will require you to use a statistical programming language to answer practical questions to demonstrate applied coding ability in an econometric context.

Intended Learning Outcomes

• Understand basic econometric theory.
• Understand linear and panel regression methods.
• Be able to implement basic econometric designs in a statistical programming language.
• Independently conduct an Economics research project.

In case online access is required for this course and you are not in the position to buy the access code, you are advised to contact the course coordinator for an alternative solution. Please note that access codes are not re-usable meaning that codes from second hand books do not work, as well as access codes from books with a different ISBN. Separate or spare codes are usually not available.