Segregation in networks |
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| Institution: | 1. Laboratory of Economics and Management, Sant’Anna School of Advanced Studies, Pisa, Italy;2. Department of Economics, University of L’Aquila, L’Aquila, Italy;3. Department of Economics, Queen Mary, University of London, Mile End Road, London E1 4NS, UK;1. Institute for Comprehensive Analysis of the Economy and Department of Economics, Johannes Kepler University Linz, Altenbergerstrasse 69, Linz, Austria;2. Department of Mathematics, Yale University, 10 Hillhouse Avenue, New Haven, CT 06511, United States;1. School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Iran;2. Department of Computer Engineering, Sharif University of Technology, and School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Iran;3. Department of Mathematical Sciences, Sharif University of Technology and School of Mathematics, Institute for Research in Fundamental Sciences (IPM), Iran |
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| Abstract: | Schelling Schelling, T., 1969. Models of segregation. American Economic Review 59, 488–493; Schelling, T., 1971a. Dynamic models of segregation. Journal of Mathematical Sociology 1, 143–186; Schelling, T., 1971b. On the ecology of micromotives. The Public Interest 25, 61–98; Schelling, T., 1978. Micromotives and Macrobehavior. W.W. Norton and Company, New York] considered a model with individual agents who only care about the types of people living in their own local neighborhood. The spatial structure was represented by a one- or two-dimensional lattice. Schelling showed that an integrated society will generally unravel into a rather segregated one even though no individual agent strictly prefers this. We generalize this spatial proximity model to a proximity model of segregation, examining models with individual agents who interact ‘locally’ in a range of more general social network structures. The levels of segregation attained are in line with those reached in the lattice-based spatial proximity model. |
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