In one of his many speeches, Alan Greenspan, former Chairman of the FRB, talked about “Monetary Policy under Uncertainty”. According to a rather mischievous article in the Post-Autistic Economics Review, he “expressed numerous ideas which could have come straight out of the mouth of a complexity economist.”
The relevant quotes from the speech are highlighted below.
First, on uncertainty and the limits of models:
Uncertainty is … the defining feature of [the monetary] landscape… As a consequence, the conduct of monetary policy … requires an understanding of the many sources of risk and uncertainty that policy makers face…a critical result [of the attempt to achieve this understanding] has been the identification of a relatively small set of key relationships that, taken together, provide a useful approximation of our economy’s dynamics … [However] our knowledge about many … important linkages is far from complete and in all likelihood will always remain so. Every model … is a vastly simplified representation of the world that we experience…
A well-known proposition is that, under a very restrictive set of assumptions, uncertainty has no bearing on the actions that policy makers might choose … These assumptions are never met in the real world.
On assumptions of linearity and predictability:
… a prominent shortcoming of our structural models is that … not only are economic responses presumed fixed through time, but they are generally assumed to be linear …
… only a limited number of risks can be quantified with any confidence. And even these risks are generally quantifiable only if we accept the assumption that the future will replicate the past …
And on assumptions of interconnectedness:
… also the relationships underlying the economy’s structure change over time in ways that are difficult to anticipate … what constitutes money has been obscured by the introduction of technologies that have facilitated the proliferation of financial products …
… Our problem is not the complexity of our models but the far greater complexity of a world economy whose underlying linkages appear to be in a constant state of flux.
A little digging around highlighted another Greenspan speech, given to a symposium of central bankers in 2005:
We all temper the outputs of our models and test their results against the ongoing evaluations of a whole array of observations that we do not capture in either the data input or the structure of our models. We are particularly sensitive to observations that appear inconsistent with the causal relationships of our formal models.
And then this in an interview with the Daily Show in 2007:
I was telling my colleagues the other day… I’d been dealing with these big mathematical models for forecasting the economy… I’ve been in the forecasting business for 50 years, and I’m no better than I ever was, and nobody else is either…
And finally, Greenspan’s prepared testimony to the Financial Crisis Inquiry Commission in 2010, which utilises emergence, non-linear change, resilience and the limits of prediction:
Bubble emergence is easy to identify in narrowing credit spreads. But the trigger point of crisis is not. A financial crisis is descriptively defined as an abrupt, discontinuous drop in asset prices. If the imbalances that precipitate a crisis are visible, they tend to be arbitraged away. For the crisis to occur, it must be unanticipated by almost all market participants and regulators. Over the years, I have encountered an extremely small number of analysts who are consistently accurate at discontinuous turning points. The vast majority of supposedly successful turning point forecasts are, in fact, mere happenstance.
In my view, the recent crisis reinforces some important messages about what supervision and examination can and cannot do. Regulators who are required to forecast have had a woeful record of chronic failure. History tells us they cannot identify the timing of a crisis, or anticipate exactly where it will be located or how large the losses and spillovers will be. Regulators cannot successfully use the bully pulpit to manage asset prices, and they cannot calibrate regulation and supervision in response to movements in asset prices. Nor can they fully eliminate the possibility of future crises.
What supervision and examination can do is promulgate rules that are preventative and that make the financial system more resilient in the face of inherently unforeseeable shocks. Such rules would kick in automatically, without relying on the ability of a fallible human regulator to predict a coming crisis.
Of particular interest is whether and how these ideas move beyond speeches and conferences to have an influence on policy and practice. A few senior bankers do seem to be coming out of the ‘complexity closet’, drawing on the ideas expressed by Greenspan over the years.
- Andrew Haldane, a director at the Bank of England, has given numerous speeches in which he talks about enhancing the robustness and resilience of the global financial network using the ideas of complexity science.
- Dr DeLisle Worrell, Governor of the Central Bank of Barbados, has spoken about the importance of complexity science for re-thinking fundamental economic theories.
- A conference on systemic risk organised by the Federal Reserve Bank of New York, which concluded that systemic risk in the financial system bears a strong resemblance to the dynamics of complex adaptive systems in the physical world and that complexity science can help further understanding of the inherent risk in economies and markets
This is an interesting trend, and well worth watching. Some of the implications for development economics were explored in a previous Aid on the Edge post.