macroresilience

resilience, not stability

Micro-Foundations of a Resilience Approach to Macro-Economic Analysis

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Before assessing whether a resilience approach is relevant to macro-economic analysis, we need to define resilience. Resilience is best defined as “the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks.”

The assertion that an ecosystem can lose resilience and become fragile is not controversial. To claim that the same can occur in social systems such as macro-economies is nowhere near as obvious, not least due to our ability to learn, forecast the future and adapt to changes in our environment. Any analysis of how social systems can lose resilience is open to the objection that loss of resilience implies systematic error on the part of economic actors in assessing the economic conditions accurately and an inability to adapt to the new reality. For example, one of the common objections to Minsky’s Financial Instability Hypothesis (FIH) is that it requires irrational behaviour on the part of economic actors. Rajiv Sethi’s post has a summary of this debate with a notable objection coming from Bernanke’s paper on the subject which insists thatHyman Minsky and Charles Kindleberger have in several places argued for the inherent instability of the financial system, but in doing so have had to depart from the assumption of rational behavior.”

One response to this objection is “So What?” and indeed the stability-resilience trade-off can be explained within the Kahneman-Tversky framework. Another response which I’ve invoked on this blog and Rajiv has also mentioned in a recent post focuses on the pervasive principal-agent relationship in the financial economy. However, I am going to focus on a third and a more broadly applicable rationale which utilises a “rationality” that incorporates Knightian uncertainty as the basis for the FIH. The existence of irreducible uncertainty is sufficient to justify an evolutionary approach for any social system, whether it be an organization or a macro-economy.

Cognitive Rigidity as a Rational Response to Uncertainty

Rajiv touches on the crux of the issue when he notes: “Selection of strategies necessarily implies selection of people, since individuals are not infinitely flexible with respect to the range of behavior that they can exhibit.” But is achieving infinite flexibility a worthwhile aim? The evidence suggests that it is not. In the face of true uncertainty, infinite flexibility is not only unrealistic due to finite cognitive resources but it is also counterproductive and may deliver results that are significantly inferior to a partially “rigid” framework. V.S. Ramachandran explains this brilliantly: “At any given moment in out waking lives, our brains are flooded with a bewildering variety of sensory inputs, all of which have to be incorporated into a coherent perspective based on what stored memories already tell us is true about ourselves and the world. In order to act, the brain must have some way of selecting from this superabundance of detail and ordering it into a consistent ‘belief system’, a story that makes sense of the available evidence. When something doesn’t quite fit the script, however, you very rarely tear up the entire story and start from scratch. What you do, instead, is to deny or confabulate in order to make the information fit the big picture. Far from being maladaptive, such everyday defense mechanisms keep the brain from being hounded into directionless indecision by the ‘combinational explosion’ of possible stories that might be written from the material available to the senses.”

This rigidity is far from being maladaptive and appears to be irrational only when measured against a utopian definition of rational choice. Behavioural Economics also frequently commits the same error – As Brian Loasby notes: “It is common to find apparently irrational behaviour attributed to ‘framing effects’, as if ‘framing’ were a remediable distortion. But any action must be taken within a framework.” This notion of true rationality being less than completely flexible is not a new one – Ramachandran’s work provides the neurological bases for the notion of ‘rigidity as a rational response to uncertainty’. I have already discussed Ronald Heiner’s framework in a previous post which bears a striking resemblance to Ramachandran’s thesis:

“Think of an omniscient agent with literally no uncertainty in identifying the most preferred action under any conceivable condition, regardless of the complexity of the environment which he encounters. Intuitively, such an agent would benefit from maximum flexibility to use all potential information or to adjust to all environmental conditions, no matter how rare or subtle those conditions might be. But what if there is uncertainty because agents are unable to decipher all of the complexity of the environment? Will allowing complete flexibility still benefit the agents?

I believe the general answer to this question is negative: that when genuine uncertainty exists, allowing greater flexibility to react to more information or administer a more complex repertoire of actions will not necessarily enhance an agent’s performance.”

Brian Loasby has an excellent account of ‘rationality under uncertainty’ and its evolutionary implications in this excellent book which traces hints of this idea running through the work of Adam Smith, Alfred Marshall, George Kelly’s ‘Personal Construct Theory’ and Hayek’s ‘Sensory Order’. But perhaps the clearest exposition of the idea was provided by Kenneth Boulding in his description of subjective human knowledge as an ‘Image’. Most external information either conforms so closely to the image that it is ignored or it adds to the image in a well-defined manner. But occasionally, we receive information that is at odds with our image. Boulding recognised that such change is usually abrupt and explained it in the following manner: “The sudden and dramatic nature of these reorganizations is perhaps a result of the fact that our image is in itself resistant to change. When it receives messages which conflict with it, its first impulse is to reject them as in some sense untrue….As we continue to receive messages which contradict our image, however, we begin to have doubts, and then one day we receive a message which overthrows our previous image and we revise it completely.” He also recognises that this resistance is not “irrational” but merely a logical response to uncertainty in an “imperfect” market. “The buyer or seller in an imperfect market drives on a mountain highway where he cannot see more than a few feet around each curve; he drives it, moreover, in a dense fog. There is little wonder, therefore, that he tends not to drive it at all but to stay where he is. The well-known stability or stickiness of prices in imperfect markets may have much more to do with the uncertain nature of the image involved than with any ideal of maximizing behavior.”

Loasby describes the key principles of this framework as follows: “The first principle is that all action is decided in the space of representations. These representations include, for example, neural networks formed in the brain by processes which are outside our conscious control…None are direct copies of reality; all truncate complexity and suppress uncertainty……The second principle of this inquiry is that viable processes must operate within viable boundaries; in human affairs these boundaries limit our attention and our procedures to what is manageable without, we hope, being disastrously misleading – though no guarantees are available……The third principle is that these frameworks are useless unless they persist, even when they do not fit very well. Hahn’s definition of equilibrium as a situation in which the messages received by agents do not cause them to change the theories that they hold or the policies that they pursue offers a useful framework for the analysis both of individual behaviour and of the co-ordination of economic activity across a variety of circumstances precisely because it is not to be expected that theories and policies will be readily changed just because some evidence does not appear readily compatible with them.” (For a more detailed account, read Chapter 3 ‘Cognition and Institutions’ of the aforementioned book or his papers here and here.)

The above principles are similar to Ronald Heiner’s assertion that actions chosen under true uncertainty must satisfy a ‘reliability condition’. It also accounts for the existence of the stability-resilience trade-off. In Loasby’s words: “If behaviour is a selected adaptation and not a specific application of a general logic of choice, then the introduction of substantial novelty – a change not of weather but of climate – is liable to be severely disruptive, as Schumpeter also insisted. In biological systems it can lead to the extinction of species, sometimes on a very large scale.” Extended periods of stability narrow the scope of events that fit the script and correspondingly broaden the scope of events that appear to be anomalous and novel. When the inevitable anomalous event comes along, we either adapt too slowly or in extreme cases, not at all.

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Written by Ashwin Parameswaran

April 11th, 2010 at 7:51 am

4 Responses to 'Micro-Foundations of a Resilience Approach to Macro-Economic Analysis'

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  1. […] can’t even remember what got me linked to Macroeconomic Resilience, but this post on the micro-economic foundations of the claim that a macro-economy can exhibit sudden fragility […]

  2. Thanks very much for sharing these thoughts. It’s troubled me that the standard representative agent models in macro have yet really to come to terms with Knightian uncertainty. This post helped a lot to untangle some thoughts that have occurred to me in at most only a vague, inarticulate form.

    Have you applied this analysis to theories about the ’87 crash? It seems a sudden jolt, whatever the origin, that somehow triggers radical updating of expectations could help account for the cascading plunge in markets.

    John

    16 Apr 10 at 11:24 pm

  3. John – Thanks. I’m afraid that I haven’t analysed the ’87 crash in this framework.

    admin

    19 Apr 10 at 3:43 pm

  4. […] a previous post, I asserted that “the existence of irreducible uncertainty is sufficient to justify an […]

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