Academic journal article Federal Reserve Bank of New York Economic Policy Review

Part 5: Concluding Observations

Academic journal article Federal Reserve Bank of New York Economic Policy Review

Part 5: Concluding Observations

Article excerpt

Complex systems abound, and many different disciplines are concerned with understanding catastrophic change in such systems. People who study atmospheric science are very interested in precipitous climate change, people in ecology look extensively at so-called regime shifts and precipitous ecological change, engineers design complex systems so as to lessen the risk of catastrophic failures. What opportunities exist to leverage this great interest from across many fields for the benefit of the central banks and financial authorities, the financial sector, and the nation's economy more generally? The conference explored this question by focusing on three principal issues associated with catastrophic events in complex systems: risk assessment, modeling and prediction, and mitigation.

Risk Assessment

The economists, central bankers, market practitioners, and scientists and engineers at the conference agreed in large part on key mechanisms that produce instability in large systems. Positive feedback--such as the portfolio insurance and collateral and margin calls that may have played a role in driving the stock market down so dramatically in October 1987--is one such mechanism. Another, synchrony, was mentioned by Simon Levin of Princeton University as possible in any complex adaptive system, sometimes with deleterious consequences, and several conference participants pointed to the increase in systemic vulnerability that can come about when behaviors of various actors become too similar. Charles Taylor of the Risk Management Association amplified this idea in describing how banks' decision making has changed: A number of years ago, while there was a high level of homogeneity in the mix of business taken on by banks, their quantitative methods were less precise and more ad hoc--with some variation in the speed of their responses to events. The result was that individual banks would differ in how they executed processes and how quickly they responded to changes in conditions. Thus, there would be heterogeneity of response to crisis. But now, as the banking system has become more integrated and the time lags have been driven out by efficiency measures, in Taylor's view the system may be evolving in a direction that makes it more fragile in some respects.

One area in which the approaches of financial economists and market practitioners differ from those of engineers such as Yacov Haimes of the University of Virginia and Massoud Amin of the University of Minnesota is in identifying extreme events. The conference background paper (1) and the keynote remarks of Governor Kohn discussed how potential extreme events are identified through stress testing. This procedure involves developing a model of an economic or market process, applying extreme values from the distribution of the drivers of the model, and examining the output. Those who commented on stress testing acknowledged that a limitation of this approach is its assumption that behavior in the model does not change dramatically under extreme conditions. This assumption conflicts with what market participants in part 1 of this volume vividly described as the feeling of regime shift during the events of 1997-98: the Asian currency crisis, the Russian default, and the Long-Term Capital Management collapse.

Part 3 of this volume explains the approaches followed by Haimes and Amin for identifying possible extreme events--for instance, a shutdown of the electric grid--and considering what set of circumstances could produce the failure. Haimes described a systematic process using small models and arranging factors in a hierarchy that probes what failures, mechanisms, and regime shifts in what combination might lead to catastrophic failure. This paradigm of identifying a range of possible bad outcomes (risks) and backtracking to estimate their probabilities and identify options for reducing their likelihood or lessening their impact is a common one in engineering. …

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