Social and Economic Networks: Theory, Modelling and Computations
This course is designed for the M.Sc. Programme in Mathematics. This course provides an overview of quantitative methods appropriate for the data analysis of social and economic networks. Many social and economic activities are embedded in networks because datasets with graph theoretic structure are increasingly available to practical users. Two of the main goals are to study
- how to describe, summarize and visually present network data together with computing software, e.g., MATLAB, Python and/or R and
- formal econometric models of network formation that admit heterogeneity, strategic behavior, and/or dynamics.
Theoretical/statistical/mathematical/computational models and their applications with respect to social and network data from development and labor economics are studied. Essential topics/case-studies are selected from, but not limited to, network formation, peer effects and the social multiplier, social capital and trust, information aggregation in networks, social learning, trading in networks, technology diffusion, job search, and other related topics.