26 July 2024
on course website
Statistical and Econometric Analysis of Network Data
Learn about recent econometric methods to analyse network data.
Networks play an increasingly dominant role in many social, business, and economic environments. Moreover, network data becomes increasingly relevant and available due to the rise of online social media and digitisation.
1. Examples of Networks and Data
2. Network Statistics, Visualization and Graphs
3. Econometrics of Interactions in Networks
4. Econometrics of Network Formation
5. Joint Estimation of Outcomes and Network Formation
6. Spatial Modeling Approach for Dynamic Network Formation and Interactions
7. Big Data Meets Networks
Michael D. König
The course is accessible to advanced undergraduate and graduate students as well as professionals from related fields.
If you have doubts about your eligibility for the course, please contact us: firstname.lastname@example.org.
Upon successful completion of the course, students will:
- Become acquainted with different statistical methodologies for analysing networks while learning how to see these different methodologies complementing each other.
- Learn to model network problem situations mathematically, and adapt the methods learned to new situations at hand.
- Be able to recognise, understand, and analyse societal and business problems in which networks are central.
- Learn how networks affect supply and demand in markets, how this leads to market failures, and how government policies can address these.
Contact hours: 20
EUR 995: Tuition fees one-week course
VU Students/PhD candidates and employees of VU Amsterdam* or an Aurora Network Partner €525
Students at Partner Universities of VU Amsterdam €680
Students and PhD candidates at non-partner universities of VU Amsterdam €785
Early Bird offer
Applications received before 15 March (14 March CET 23:59) receive €50 Early Bird discount!
VU Amsterdam Summer School offers two kinds of scholarships: the Equal Access Scholarship and the Photographer Scholarship. More information can be found on the VU Amsterdam Summer School website.Register for this course
on course website