This course teaches the application of digital techniques for solving models in economics based using numerical software, primarily Python. The course has the dual aim of teaching how to use digital tools for solving economic models and to apply these techniques to microeconomic models that are relevant for optimal decision making in firms.
We start the course with a recap of Python and how we can use Python to solve problems in mathematics as well to produce graphs.
We then go through different topics in Business Economics. For each topic, we go briefly through the economic content of the topics with an emphasis of the explicit models used. We then proceed to implement some of these models numerically and to analyse the models using numerical techniques.
The main substantive topics covered are:
In the final part of the course, students form groups and perform in-depth analyses of economic / business problems using the techniques taught in the course. Some emphasis is put on presenting analyses in an accessible way.
This is an excerpt from the complete course description for the course. If you are an active student at BI, you can find the complete course descriptions with information on eg. learning goals, learning process, curriculum and exam at portal.bi.no. We reserve the right to make changes to this description.