January 15, 2020
Please note that, if you happen to find conflicting information between this page and Sisu page, consider the Sisu page the primary source of information.
Method of completion: contact teaching
- Can be found in the Moodle learning platform
- Log in with your Hanken username to be able to use all the features of the course workspace
- Access to many Moodle courses requires an enrollment key (course password), which you can get from the teacher of the course. The key is sent to you by email or it is posted as a message in Sisu couple of days before the course starts.
- In Hanken’s Sisu with your Hanken username
- To be able to register for the course in Sisu, please note that
- You must have a valid right to study at the course host university
- You have created your primary personal study plan (HOPS) based on your study right
- You have added the course for which you are registering to your HOPS
- More information can be found on the webpage How to enroll in the courses?
This course aims to provide students with a solid understanding of the modern empirical tools used in empirical industrial economics (EIE) to analyse consumer behaviour, (strategic) behavior of firms and market outcomes. EIE combines formal economic theory, knowledge of relevant institutions, micro-economic data, sophisticated econometric tools and computer programming to evaluate how markets function and how much market power firms have. The course covers estimation of static demand (incl. elementary discrete choice models), estimation of marginal costs and mark-ups of firms, evaluating the product choice of firms, as well as the basics of simulating data and counterfactual outcomes. By doing so the course helps the students to develop skills needed to conduct solid analysis in EIE.
The methods covered are also widely used in marketing, finance, health economics and international trade. Students learn to implement some of the estimation techniques covered in the course using econometric software Stata. The most motivated students are also encouraged to use R and Matlab.
Doctoral students can also take this course.