M2 Ind Modélisation et Méthodes Math. en Economie et Finance - algorithmic models of socio-economic interactions
Topic outline
- General
General
- OUTLINE
OUTLINE
In strongly connected environments like financial networks, global supply chains or social networks, the diffusion and amplification of micro-level risks can lead to the emergence of macro-level events such as financial crisis or epidemic processes. The class will present mathematical models from complex systems theory, game theory and general equilibrium theory that can be used to capture these diffusion processes and their socio-economic consequences. We will focus on three main types of risk:
Epidemic risk
Climate-related risks
Financial risks.
- REFERENCES
REFERENCES
- Acemoglu, D., Carvalho, V. M., Ozdaglar, A., & Tahbaz-Salehi, A. (2012). The network origins of aggregate fluctuations. Econometrica, 80(5), 1977-2016.
- Barrot, J. N., & Sauvagnat, J. (2016). Input specificity and the propagation of idiosyncratic shocks in production networks. The Quarterly Journal of Economics, 131(3), 1543-1592.
- Battiston, S., Puliga, M., Kaushik, R., Tasca, P., & Caldarelli, G. (2012). Debtrank: Too central to fail? financial networks, the fed and systemic risk. Scientific reports, 2, 541.
- Battiston, S., Mandel, A., Monasterolo, I., Schütze, F., & Visentin, G. (2017). A climate stress-test of the financial system. Nature Climate Change, 7(4), 283-288.
- Eisenberg, L., & Noe, T. H. (2001). Systemic risk in financial systems. Management Science, 47(2), 236-249
- Hethcote, H. W. (1976) Qualitative analyses of communicable disease mod- els. Math. Biosci., 28:335–356, http://people.kzoo.edu/barth/math280/articles/communicable_disease.pdf
- Hethcote, H. W. (2000) The mathematics of infectious diseases. SIAM Rev., 42(4):599–653, https://www.maths.usyd.edu.au/u/marym/populations/hethcote.pdf
- Pastor-Satorras, R., Castellano, C., Van Mieghem, P., & Vespignani, A. (2015). Epidemic processes in complex networks. Reviews of modern physics, 87(3), 925.
- Van Mieghem, P., Omic, J., & Kooij, R. (2008). Virus spread in networks. IEEE/ACM Transactions On Networking, 17(1), 1-14.
- Avery, C., Bossert, W., Clark, A., Ellison, G., & Ellison, S. F. (2020). An Economist's Guide to Epidemiology Models of Infectious Disease. Journal of Economic Perspectives, 34(4), 79-104.
- Harko, T., Lobo, F. S., & Mak, M. K. (2014). Exact analytical solutions of the Susceptible-Infected-Recovered (SIR) epidemic model and of the SIR model with equal death and birth rates. Applied Mathematics and Computation, 236, 184-194.
- Ellison, G. (2020). Implications of heterogeneous SIR models for analyses of COVID-19 (No. w27373). National Bureau of Economic Research.
- Papers for oral presentation
Papers for oral presentation
- Salje, Henrik, et al. "Estimating the burden of SARS-CoV-2 in France." Science (2020), see https://science.sciencemag.org/content/369/6500/208 and https://science.sciencemag.org/content/suppl/2020/05/12/science.abc3517.DC1
- Chang S. et al. (2020) Mobility network models of COVID-19 explain inequities and inform reopening. Nature. 2020 Nov 10:1-6, see https://www.nature.com/articles/s41586-020-2923-3
- Van Mieghem, P., Omic, J., & Kooij, R. (2008). Virus spread in networks. IEEE/ACM Transactions On Networking, 17(1), 1-14, in particular proof of Theorem 5 and Lemma 6.
- Salje, Henrik, et al. "Estimating the burden of SARS-CoV-2 in France." Science (2020), see https://science.sciencemag.org/content/369/6500/208 and https://science.sciencemag.org/content/suppl/2020/05/12/science.abc3517.DC1