Complexity theory is needed for better understanding and management of financial-economic crises, according to an interdisciplinary group of scientists from ecology, epidemiology, physics, computer science, sociology, economics and banking in Science. Applications of complex networks, agent-based models and laboratory experiments offer great potential to better grasp complex financial economic systems.
The authors include Professor Doyne Farmer, Co-Director of the Complexity Economics programme at the Institute for New Economic Thinking at the Oxford Martin School.
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Traditional economic theory could not explain, much less predict, the near collapse of the financial system and its long-lasting effects on the global economy. Since the 2008 crisis, there has been increasing interest in using ideas from complexity theory to make sense of economic and financial markets. Concepts such as tipping points, networks, contagion, feedback, and resilience have entered the financial and regulatory lexicon. Recent insights and techniques offer potential for better monitoring and management of highly interconnected economic and financial systems, and thus may help anticipate and manage future crises.
Complex network models may provide early warning signals for upcoming crises, as shown by Diego Garlaschelli, a physicist leading an interdisciplinary group at Leiden University: "A recent study of the Dutch interbank network showed that a heterogeneous network model could identify an early warning signal three years prior to the financial-economic crisis of 2008."
Agent-based models (ABMs) are computer models in which behavior of agents and their interactions are explicitly represented as decision rules mapping agents’ observations onto actions. "Though ABMs are less well established in analyzing financial-economic systems than in, e.g., traffic control, epidemiology, or battlefield conflict analysis, they have produced promising results’’, says Professor Farmer. "ABMs have been used to test systemic risk implications of reforms developed by the Basel Committee on Banking Supervision, showing how dynamically changing risk limits can lead to booms and busts in prices.’’
"It is an opportune time for academic economists, complexity scientists, social scientists, ecologists, epidemiologists, and researchers at financial institutions to join forces and develop tools from complexity theory, as a complement to existing economic modeling approaches," says Andy Haldane, Chief Economist of the Bank of England. "One ambitious option would be an online, financial-economic dashboard that integrates data, methods, and indicators. This might monitor and stress-test the global socio-economic and financial system in something close to real time, in a similar way as is done with other complex systems such as weather systems or social networks."