Learning outcomes

After completing the course, the student is expected to be able to independently apply basic statistical/econometric methods on real life data in order to properly examine economic questions.

Content

This course provides insights into the practical use of statistical methods on economic problems. The course will deal with cross-sectional, time-series as well as panel data (i.e., cross-sectional data observed over several time periods). The cross-sectional analysis will cover both continuous and discrete models. Among others, the time-series topics will be autoregression, nonstationarity and unit-root tests, and estimation of dynamic causal effects. Economic problems that will be discussed include:

1. Wage differences

2. Driving behaviour and traffic fatalities

3. Class size and test scores

4. Weather and price of crops

Instruction

The course consists of lectures and applied work in the computer lab.

Assessment

The course will be examined through independent analyses of a series of take-home assignments.

There will be three grades: pass with distinction (VG), pass (G) and fail (U).