Complexity theory and financial regulation

By Stefano Battiston, J. D. Farmer, A. Flache, Diego Garlaschelli, Andrew G. Haldane, H. Heesterbeek, Cars H. Hommes, C. Jaeger, Robert M. May, Marten Scheffer. Science, 2016

474 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/97668cd871e3723962b5d9131b5e244dfe2fedd8

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Citations in the corpus

An agent-based stock-flow consistent model of the sustainable transition in the energy sector (2018, unknown): “The need of new approaches and tools based on complex system and network analysis has been advocated by (Battiston et al., 2016; Farmer et al., 2015; Rezai and Stagl, 2016).”
Toward understanding the impact of artificial intelligence on labor (2019, background): “…network science have already provided new insights into modeling (and minimizing) systemic risk (73) in global credit (74) and financial industries (75), forecasting the future exports of national economies (76 – 78), mapping worker flows between industries (79) and firms (80), and charting the…”
Climate Change and the Financial System (2020, background): “Monasterolo and Battiston (2016) assessed the exposure of the Caribbean Development Bank (CDB)’s top 100 projects (in capital value, with a 30-year maturity) in the Caribbean region, across all the areas of economic activities (e.g. agriculture, infrastructures, energy, manufacturing, etc.).”
Interconnectedness in the global financial market (2017, unknown): “Several studies exist that have mainly focused on dependencies and possible cascading effects in the financial sector, especially interbank markets (see Battiston et al., 2016; Summer, 2013; Gai et al., 2011; Levy-Carciente et al., 2015; Glasserman and Young, 2015).”
Modelling innovation and the macroeconomics of low-carbon transitions: theory, perspectives and practical use (2019, background): “…to representations of money and finance in models, particularly in the field of energy-economy modelling (Grubb et al., 1993; Grubb et al., 2002; Grubb et al., 2006), as computational experiments with finance have been made outside of the field (Battiston et al., 2016; Haldane & Turrell, 2018).”