Network Theory with Applications to Economics and Finance

Transcription

1 Network Theory with Applications to Economics and Finance Instructor: Michael D. König University of Zurich, Department of Economics, Schönberggasse 1, CH Zurich, michael.koenig@econ.uzh.ch. 1 Literature: Jackson, Matthew, Social and Economic Networks, Princeton University Press, Jackson, Matthew and Zenou, Yves, Games on Networks, Handbook of Game Theory, Vol. 4, Amsterdam: Elsevier, Newman, Mark, Networks: An Introduction, Oxford University Press, König, Michael D. and Battiston, Stefano, From Graph Theory to Models of Economic Networks. A Tutorial., in Networks, Topology and Dynamics, Theory and Applications to Economics and Social Systems, Springer, Additional Literature: Vega-Redondo, Fernando, Complex Social Networks, Cambridge University Press, Goyal, Sanjeev, Connections: an introduction to the economics of networks, Princeton University Press, Young, Peyton, Individual strategy and social structure: An evolutionary theory of institutions, Princeton University Press, Van der Hofstad, Remco, Random Graphs and Complex Networks, Vol. I+II, Durrett, Richard, Random Graph Dynamics, Cambridge University Press, Grimmett, Geoffrey, Probability on Graphs, Cambridge University Press, Mesbahi, Mehran and Egerstedt, Magnus, Graph theoretic methods in multiagent networks, Princeton University Press, Mitzenmacher, Michael, and Eli Upfal. Probability and computing: Randomized algorithms and probabilistic analysis, Cambridge University Press, West, Douglas, Introduction to graph theory., Vol. 2. Upper Saddle River: Prentice hall, Van Mieghem, Piet, Graph spectra for complex networks, Cambridge University Press,

2 Carrington, Peter, John Scott, and Stanley Wasserman, Models and methods in social network analysis, Vol. 28. Cambridge University Press, Stein, Clifford, T. Cormen, R. Rivest, and C. Leiserson. Introduction to algorithms, The MIT Press Brandes, Ulrik, and Thomas Erlebach, eds. Network analysis: methodological foundations. Vol Springer, Kolaczyk, Eric, Statistical Analysis of Network Data: Methods and Models, Springer, Kolaczyk, Eric and Csárdi, Gábor, Statistical Analysis of Network Data with R, Springer, Wainwright, Martin and Jordan, Michael, Graphical models, exponential families, and variational inference, Foundations and Trends in Machine Learning, Now Publishers Inc., Airoldi, E., Goldenberg, A., Zheng, A. and Fienberg, S., A Survey of Statistical Network Models, Machine Learning, Course Schedule: Monday 09:30-11:00 Lecture 1 11:00-11:30 Break 11:30-01:00 Lecture 2 01:00-02:30 Lunch break 02:30-04:30 Lecture 3 04:30-05:00 Break 05:00-06:00 Discussions Tuesday 09:30-11:00 Lecture 4 11:00-11:30 Break 11:30-01:00 Lecture 5 01:00-02:30 Lunch break 02:30-04:30 Lecture 6 and evaluation 04:30-05:00 Break 05:00-06:00 Discussions

3 Content: 1. Introduction Why Networks in Economics Examples of Social and Economic Networks 2. Characterization of Networks Elements of Graph Theory Graphs and Matrices Bipartite Graphs Irreducible and Primitive Graphs Graph Laplacian Network Measurements Average Path Length Clustering Assortativity and Nearest Neighbor Connectivity Centrality Degree Centrality Closeness Centrality Betweenness Centrality Eigenvector Centrality Katz-Bonacich Centrality Page Rank 3. Network Algorithms Shortest Paths Lecture 1 Lecture 2 4. Random Networks Poisson Random Graphs Generalized Random Graphs Random Graph Construction Neighborhood Size, Diameter, Phase Transition and Clustering Average Component Size Below the Phase Transition Inhomogeneous Random Graphs Small World Networks Network Construction Degree Distribution Mean-Field Solution for Average Path Length

4 Lecture 3 5. Growing Networks Uniform Attachment Preferential Attachment Entry and Exit Copying Models Growing Networks in Space 6. Stochastic Processes on Networks Random Walks on Networks Epidemic Models Susceptible Infected (SI) Epidemic Model Susceptible Infected Removed/Recovered (SIR) Epidemic Model Susceptible Infected Susceptible (SIS) Epidemic Model The Agreement Protocol Learning in Networks and the DeGroot Model Clearing Mechanisms and Systemic Risk 7. Strategic Network Formation Pairwise Stability and Pairwise Nash Stability One-sided and Two-sided Network Formation Noncooperative vs. Cooperative Network Formation Games Equilibrium Selection and Stochastic Stability Lecture 4 Lecture 5 8. Games on Networks Games with Strategic Substitutes Best-Shot Public Goods Games Public Goods with Continuous Actions Games with Strategic Complements Binary Games Coordination Games Stochastic Stability on Complete Graphs Stochastic Stability on Star Graphs Linear Quadratic Games The Baseline Model Ex Ante Heterogeneity Local Complements and Global Substitues Multiple Activities Welfare

5 Key Players Directed, Weighted Networks and Input-Output Economies Perfect Competition Monopolistic Competition 9. Coevolution of Networks and Behavior Coordination Games on Evolving Networks Network Formation with Local Complements and Global Substitutes Diffusion in Endogenous Networks Lecture Policy Implications R&D Networks: Theory, Empirics and Policy Implications Networks in Conflict: Theory and Evidence from the Great War of Africa