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Taking uncertainty seriously: simplicity versus complexity in financial regulation

Presented by: 
S Kapadia Bank of England
Date: 
Wednesday 17th December 2014 - 14:00 to 14:45
Venue: 
INI Seminar Room 1
Abstract: 
Co-authors: David Aikman (Bank of England), Mirta Galesic (Max Planck Institute for Human Development, Berlin), Gerd Gigerenzer (Max Planck Institute for Human Development, Berlin), Konstantinos Katsikopoulos (Max Planck Institute for Human Development, Berlin), Amit Kothiyal (Max Planck Institute for Human Development, Berlin), Emma Murphy (Bank of England), Tobias Neumann (Bank of England)

Distinguishing between risk and uncertainty, this paper draws on the psychological literature on heuristics to consider whether and when simpler approaches may outperform more complex methods for modelling and regulating the financial system. We find that: (i) simple methods can sometimes dominate more complex modelling approaches for calculating banks’ capital requirements, especially if limited data are available for estimating models or the underlying risks are characterised by fat-tailed distributions; (ii) simple indicators often outperformed more complex metrics in predicting individual bank failure during the global financial crisis; and (iii) when combining information from different indicators to predict bank failure, ‘fast-and-frugal’ decision trees can perform comparably to standard, but more information-intensive, regression techniques, while being simpler and easier to communicate.
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons