Economic interdependencies have become increasingly present in globalized production, financial and trade systems. While establishing interdependencies among economic agents is crucial for the production of complex products, they may also increase systemic risk due to failure propagation. It is crucial to identify how network connectivity impacts both the emergent production and risk of collapse of economic systems. In this paper we propose a model to study the effects of network structure on the behavior of economic systems by varying the density and centralization of connections among agents. The complexity of production increases with connectivity given the combinatorial explosion of parts and products. Emergent systemic risks arise when interconnections increase vulnerabilities. Our results suggest a universal description of economic collapse given in the emergence of tipping points and phase transitions in the relationship between network structure and risk of individual failure. This relationship seems to follow a sigmoidal form in the case of increasingly denser or centralized networks. The model sheds new light on the relevance of policies for the growth of economic complexity, and highlights the trade-off between increasing the potential production of the system and its robustness to collapse. We discuss the policy implications of intervening in the organization of interconnections and system features, and stress how different network structures and node characteristics suggest different directions in order to promote complex and robust economic systems.
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Acemoglu, D., & Azar, P. D. (2017). Endogenous production networks. Tech. rep., National Bureau of Economic Research.
Acemoglu, D., Carvalho, V. M., Ozdaglar, A., & Tahbaz-Salehi, A. (2012). The network origins of aggregate fluctuations. Econometrica, 80, 1977–2016.
Albert, R., Jeong, H., & Barabási, A. L. (2000). Error and attack tolerance of complex networks. Nature, 406(6794), 378.
Allen, F., & Gale, D. (2000). Financial contagion. Journal of Political Economy, 108(1), 1–33.
Baqaee, D. R. (2018). Cascading failures in production networks. Econometrica, 86, 1819–1838.
Bar-Yam, Y. (1997). Dynamics of complex systems (Vol. 213). Reading, MA: Addison-Wesley.
Barabási, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.
Barabási, A. L., & Bonabeau, E. (2003). Scale-free networks. Scientific American, 288(5), 60–69.
Barrat, A., Barthelemy, M., & Vespignani, A. (2008). Dynamical processes on complex networks. Cambridge: Cambridge University Press.
Battiston, S., Gatti, D. D., Gallegati, M., Greenwald, B., & Stiglitz, J. E. (2007). Credit chains and bankruptcy propagation in production networks. Journal of Economic Dynamics and Control, 31(6), 2061–2084.
Battiston, S., Gatti, D. D., Gallegati, M., Greenwald, B., & Stiglitz, J. E. (2012a). Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk. Journal of Economic Dynamics and Control, 36(8), 1121–1141.
Battiston, S., Puliga, M., Kaushik, R., Tasca, P., & Caldarelli, G. (2012b). Debtrank: Too central to fail? Financial networks, the fed and systemic risk. Scientific Reports, 2, 541.
Battiston, S., Gatti, D. D., Gallegati, M., Greenwald, B., & Stiglitz, J. E. (2012c). Default cascades: When does risk diversification increase stability? Journal of Financial Stability, 8(3), 138–149.
Billio, M., Getmansky, M., Lo, A. W., & Pelizzon, L. (2012). Econometric measures of connectedness and systemic risk in the finance and insurance sectors. Journal of Financial Economics, 104(3), 535–559.
Bimpikis, K., Candogan, O., & Ehsan, S. (2019). Supply disruptions and optimal network structures. Management Science, 65(12), 5504–5517. https://doi.org/10.1287/mnsc.2018.3217.
Blume, L., Easley, D., Kleinberg, J., Kleinberg, R., & Tardos, E. (2011). Network formation in the presence of contagious risk. In Proceedings of the 12th ACM conference on electronic commerce (pp. 1–10). ACM.
Braha, D., & Bar-Yam, Y. (2006). From centrality to temporary fame: Dynamic centrality in complex networks. Complexity, 12(2), 59–63.
Brummitt, C. D., Huremovic, K., Pin, P., Bonds, M. H., & Vega-Redondo, F. (2017). Contagious disruptions and complexity traps in economic development. Nature Human Behaviour, 1, 665.
Buldyrev, S. V., Parshani, R., Paul, G., Stanley, H. E., & Havlin, S. (2010). Catastrophic cascade of failures in interdependent networks. Nature, 464(7291), 1025.
Cabrales, A., Gottardi, P., & Vega-Redondo, F. (2017). Risk sharing and contagion in networks. The Review of Financial Studies, 30, 3086–3127.
Caccioli, F., Barucca, P., & Kobayashi, T. (2018). Network models of financial systemic risk: A review. Journal of Computational Social Science, 1(1), 81–114.
Callaway, D. S., Newman, M. E., Strogatz, S. H., & Watts, D. J. (2000). Network robustness and fragility: Percolation on random graphs. Physical Review Letters, 85(25), 5468.
Carvalho, V. M. (2014). From micro to macro via production networks. Journal of Economic Perspectives, 28, 23–48.
Chérel, G., Cottineau, C., & Reuillon, R. (2015). Beyond corroboration: Strengthening model validation by looking for unexpected patterns. PLOS ONE, 10(9), e0138212. https://doi.org/10.1371/journal.pone.0138212.
Ciccone, A. (2002). Input chains and industrialization. The Review of Economic Studies, 69, 565–587.
Cifuentes, R., Ferrucci, G., & Shin, H. S. (2005). Liquidity risk and contagion. Journal of the European Economic Association, 3(2–3), 556–566.
Crucitti, P., Latora, V., Marchiori, M., & Rapisarda, A. (2003). Efficiency of scale-free networks: Error and attack tolerance. Physica A: Statistical Mechanics and its Applications, 320, 622–642.
Elliott, M., Golub, B., & Jackson, M. O. (2014). Financial networks and contagion. American Economic Review, 104(10), 3115–53.
Elliott, M., Golub, B., & Leduc, M. V. (2020). Supply network formation and fragility. arXiv preprint arXiv:2001.03853.
Elliott, M., Hazell, J., & Georg, C.-P. (2018). Systemic risk-shifting in financial networks, available at SSRN 2658249.
Erdos, P., & Rényi, A. (1960). On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci, 5(1), 17–60.
Erol, S. (2018). Network hazard and bailouts, available at SSRN 3034406.
Erol, S., & Vohra, R. (2018). Network formation and systemic risk, available at SSRN 2546310.
Fang, H., Jiang, D., Yang, T., Fang, L., Yang, J., Li, W., et al. (2018). Network evolution model for supply chain with manufactures as the core. PloS ONE, 13(1), e0191180. https://doi.org/10.1371/journal.pone.0191180
Gale, D., & Kariv, S. (2009). Trading in networks: A normal form game experiment. Americal Economic Journal: Microeconomics, 1, 114–132.
Harmon, D., Stacey, B., Bar-Yam, Y., & Bar-Yam, Y. (2010). Networks of economic market interdependence and systemic risk. arXiv preprint arXiv:1011.3707.
Harmon, D., de Aguiar, MAM., Chinellato, DD., Braha, D., Epstein, IR., Bar-Yam, Y. (2011). Predicting economic market crises using measures of collective panic. arXiv preprint arXiv:1102.2620.
Hidalgo, C. A., Klinger, B., Barabási, A. L., & Hausmann, R. (2007). The product space conditions the development of nations. Science, 317(5837), 482–487.
Iyer, S., Killingback, T., Sundaram, B., & Wang, Z. (2013). Attack robustness and centrality of complex networks. PLoS ONE, 8(4), e59613.
Jackson, M. O., Rogers, B. W., & Zenou, Y. (2017). The economic consequences of social-network structure. Journal of Economic Literature, 55(1), 49–95.
Jones, C. I. (2011). Intermediate goods and weak links in the theory of economic development. American Economic Journal: Macroeconomics, 3, 1–28.
Jorion, P., & Zhang, G. (2009). Credit contagion from counterparty risk. The Journal of Finance, 64(5), 2053–2087.
Jovanovic, B. (1987). Micro shocks and aggregate risk. The Quarterly Journal of Economics, 102, 395–409.
Kiyotaki, N., & Moore, J. (1997). Credit cycles. Journal of Political Economy, 105, 211–248.
Kremer, M. (1993). The O-ring theory of economic development. The Quarterly Journal of Economics, 108, 551–575.
Leduc, M., Poledna, S., & Thurner, S. (2017a). Systemic risk management in financial networks with credit default swaps.
Leduc, M. V., & Thurner, S. (2017b). Incentivizing resilience in financial networks. Journal of Economic Dynamics and Control, 82, 44–66.
Levchenko, A. A. (2007). Institutional quality and international trade. The Review of Economic Studies, 74, 791–819.
Levine, D. (2012). Production chains. Review of Economic Dynamics, 15, 271–282.
Lorenz, J., Battiston, S., & Schweitzer, F. (2009). Systemic risk in a unifying framework for cascading processes on networks. The European Physical Journal B, 71(4), 441.
Marsiglio, S., Bucci, A., La Torre, D., & Liuzzi, L. (2019). Financial contagion and Economic Development: An Epidemiological Approach. Journal of Economic Behavior and Organization.
Pichler, A., Poledna, S., & Thurner, S. (2018). Systemic-risk-efficient asset allocation: Minimization of systemic risk as a network optimization problem. arXiv preprint arXiv:1801.10515.
Reuillon, R., Chuffart, F., Leclaire, M., Faure, T., Dumoulin, N., & Hill, D. R. C. (2010). Declarative task delegation in OpenMOLE. In Proceedings of high performance computing and simulation (HPCS) international conference.
Reuillon, R., Leclaire, M., & Rey-Coyrehourcq, M. (2013). OpenMOLE, a workflow engine specifically tailored for the distributed exploration of simulation models. Future Generation Computer Systems.
Rostek, M., & Weretka, M. (2015). Dynamic thin markets. The Review of Financial Studies, 28, 2946–2992.
Roukny, T., Battiston, S., & Stiglitz, J. E. (2018). Interconnectedness as a source of uncertainty in systemic risk. Journal of Financial Stability, 35, 93–106.
Scheinkman, J. A., & Woodford, M. (1994). Self-organized criticality and economic fluctuations. The American Economic Review Paper and Proceedings, 84, 417–421.
Schweitzer, F., Fagiolo, G., Sornette, D., Vega-Redondo, F., Vespignani, A., & White, D. R. (2009). Economic networks: The new challenges. Science, 325(5939), 422–425.
Stiglitz, J., & Greenwald, B. (2003). Towards a new paradigm in monetary economics. Cambridge: Cambridge University Press.
Stiglitz, J. E. (2010). Risk and global economic architecture: Why full financial integration may be undesirable. American Economic Review, 100(2), 388–92.
Tang, L., Jing, K., He, J., & Stanley, H. E. (2016). Complex interdependent supply chain networks: Cascading failure and robustness. Physica A: Statistical Mechanics and its Applications, 443, 58–69.
Thurner, S., & Poledna, S. (2013). DebtRank-transparency: Controlling systemic risk in financial networks. Scientific Reports, 3, 1888.
Wilensky, U. (1999). NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. http://ccl.northwestern.edu/netlogo/.
Willems, S. P. (2008). Real-world multiechelon supply chains used for inventory optimization. Manufacturing & Service Operations Management, 10(1), 19–23.
Yang, Q., Scoglio, C., & Gruenbacher, D. (2019). Discovery of a phase transition behavior for supply chains against disruptive events, arXiv preprint arXiv:1908.02616.
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Vié, A., Morales, A.J. How Connected is Too Connected? Impact of Network Topology on Systemic Risk and Collapse of Complex Economic Systems. Comput Econ 57, 1327–1351 (2021). https://doi.org/10.1007/s10614-020-10021-5
- Network topology
- Systemic risk
- Economic complexity