Networks in Micro- and Macro-Economics

About

Networks play an increasingly dominant role in many social, business, and economic environments. Moreover, network data becomes increasingly important and available due to the rise of online digital data sources. This course offers a concise introduction into the most recent economic models and econometric methods developed for processing, visualizing and learning from network data. We provide a comprehensive approach for analyzing networks, both, from microeconomic as well as macroeconomic perspectives. This will provide course participants with a generic network analysis toolbox that can then be applied to particular environments and applications, depending on idiosyncratic needs and interests. To further aid the understanding of network concepts and methods the course will combine lectures with hands-on empirical and programming exercises.

Course leader

Andrei Levchenko is the John W. Sweetland Professor of International Economics at the University of Michigan and Michael D. König is associate professor at the Department of Spatial Economics at Vrije Universiteit Amsterdam.

Target group

Level
The Summer School welcomes master students, advanced bachelor, PhD students, post-docs as well as practitioners who are interested in learning the most recent economic models and econometric methods developed for processing, visualizing and learning from network data. We provide a comprehensive approach for analyzing networks, both, from microeconomic as well as macroeconomic perspectives. This will provide course participants with a generic network analysis toolbox that can then be applied to particular environments and applications, depending on idiosyncratic needs and interests.

Admission requirements
The course will be accessible to advanced undergraduate and graduate students as well as practitioners from related fields.

Course aim

Learning Objectives
Upon successful completion of the course, participants will:

become acquainted with different methodologies for analyzing 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 recognize, understand, and analyze societal and business problems in which networks are central.
learn how networks affect demand and supply in markets, how this leads to market failures, and how government policies can address these.

Fee info