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Advances in Neural Information Processing Systems
We examine the marriage of recent probabilistic generative models for social networks with classical frameworks from mathematical economics. We are particularly interested in how the statistical structure of such networks influences global economic quantities such as price variation. Our findings are a mixture of formal analysis, simulation, and experiments on an international trade data set from the United Nations.
Kakade, S., Kearns, M. J., Oritz, L. E., Pemantle, R., & Suri, S. (2004). Economic Properties of Social Networks. Advances in Neural Information Processing Systems, 17 Retrieved from https://repository.upenn.edu/statistics_papers/460
Date Posted: 27 November 2017