Peer Effects and Peer Avoidance: Epidemic Diffusion in Coevolving Networks
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(3) EUROPEAN UNIVERSITY INSTITUTE. DEPARTMENT OF ECONOMICS. Peer Effects and Peer Avoidance: Epidemic Diffusion in Coevolving Networks CONSTANZA FOSCO, MATTEO MARSILI and FERNANDO VEGA-REDONDO. EUI Working Paper ECO 2008/19.
(4) This text may be downloaded for personal research purposes only. Any additional reproduction for other purposes, whether in hard copy or electronically, requires the consent of the author(s), editor(s). If cited or quoted, reference should be made to the full name of the author(s), editor(s), the title, the working paper or other series, the year, and the publisher. The author(s)/editor(s) should inform the Economics Department of the EUI if the paper is to be published elsewhere, and should also assume responsibility for any consequent obligation(s). ISSN 1725-6704. © 2008 Constanza Fosco, Matteo Marsili and Fernando Vega-Redondo Printed in Italy European University Institute Badia Fiesolana I – 50014 San Domenico di Fiesole (FI) Italy http://www.eui.eu/ http://cadmus.eui.eu/.
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(22) 1. 1. =1. prevalence. = 0.5. 0. 0 0. (a). c. 1. = 3.01. 0. 4. w. = 1.157. (b). c. = 40.1 40. 1. =2. (∞). = 10 (∞). 0. w. 0. = 8.23. ', <. 0. 25. (c). 8. ! !. &. !. /. #. #. #. #. 2-. 0,15. 0.03. = 1.2. =1. prevalence. -. 2 %5. /. 30. (d). social turnover. 0 0. (a). c. = 0.024. = 1.3. 0,25. 0.03. 0. c1. 0 = 0.495. c2. = 1.298 (b). 15. 1. (∞). = 2.5 (∞). 0 0 opt. ', <. 0. =0.7. 10. (c). 9. ! !. & /. (d). 0. social turnover. !. / %5. 2 #. #. # 7*. 10. # 2-.
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(25) considerations, this formulation might indeed be more appropriate. Finally, another interesting variation would be to have B and G behavior play a symmetric role in the model, with the switch in either direction being dependent on the behavior being displayed by neighbors. − − −−. References [1] Ball, F., D. Mollison and G. Scalia-Tomba (1997), “Epidemics in populations with two levels of mixing,” Annals Applied Probability 7, 46-89. [2] Bailey, N. T. J. (1975), The Mathematical Theory of Infectious Diseases and Its Applications, New York: Hafner Press. [3] ben-Avraham, D. and J. Köhler (1992), “Mean-field (n,m)-cluster approximation for lattice models,” Physical Review A 45, 8358-70. [4] Boots, M. and A. Sasaki (1999), “’Small Worlds’ and the evolution of virulence: infection occurs locally and at a distance,” Proceedings Biological Sciences 266 (1432), 1933-1938. [5] Borgers, T. and R. Sarin (1997), “Learning through reinforcement,” Journal of Economic Theory 77, 1-14. [6] Bush, R. and R. Mostellar (1955), Stochastic Models of Learning, New York: Wiley. [7] Camerer, C. and T.-H. Ho (1999): “Experience-weighted attraction learning in normal-form games,” Econometrica 67, 827-74. [8] Cross, J. (1983), A Theory of Adaptive Behavior, Cambridge: Cambridge University Press. [9] Ebel, H. and S. Bornholdt (2002), “Coevolutionary games on networks,” Physical Review E 66, 056118. [10] Fosco, C., M. Marsili, and F. Vega-Redondo (2007), “Avoiding bad company: the spread of misbehavior in complex networks,” working paper, Universidad de Alicante. [11] Eshel, I., L. Samuelson, and A. Shaked (1998), “Altruists, egoists, and hooligans in a local interaction model,” American Economic Review 88, 157-179. 21.
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