macroresilience

resilience, not stability

Knightian Uncertainty and the Resilience-Stability Trade-off

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This note examines the implications of adaptation by economic agents under Knightian uncertainty for the resilience of the macroeconomic system. It expands on themes I touched upon here and here. To summarise the key conclusions,

  • Under Knightian uncertainty, homo economicus is an irrelevant construct. The “optimal” course of action is one that restricts the choice of actions available and depends on a small set of simple rules and heuristics.
  • The choice of actions is restricted to those that are applicable in reasonably likely or recurrent situations. Actions applicable to rare situations are ignored. Therefore, it is entirely rational to take on severely negatively skewed bets.
  • By the same logic, economic agents find it harder to adapt to severe macroeconomic shocks as compared to mild shocks. This is the rationale for Axel Leijonhufvud’s “Corridor Hypothesis”.
  • Minsky’s Financial Instability Hypothesis states that prolonged periods of stability reduce the width of the “corridor” until the point where a macroeconomic crisis is inevitable.
  • The only assumptions needed to draw the above conclusions are the existence of uncertainty and sufficient adaptive/selective forces operating upon economic agents.
  • Minksy believed that this loss of resilience in the macroeconomic system is endogenous and inevitable. Although such a loss of resilience can arise endogenously, the evidence suggests that a significant proportion of the blame for the current crisis can be attributed to the stabilising policies favoured during the Great Moderation.
  • Buzz Holling’s work on ecosystem resilience has highlighted the peril of stabilising complex adaptive systems and how increased stability reduces system resilience.

Uncertainty and Negatively Skewed Payoffs

In a previous note, I explained how the existence of Knightian uncertainty leads to a perceived preference for severely negatively skewed payoffs. Ronald Heiner explains exactly how this occurs in his seminal paper on decision making under uncertainty.

Heiner argues that in the presence of uncertainty, the “optimal” course of action is one that restricts the choice of actions available and depends on a small set of simple rules and heuristics. In his words,

” 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. “

In Heiner’s framework, actions chosen must satisfy a “Reliability Condition” which he summarises as: ” do so if the actual reliability in selecting the action exceeds the minimum required reliability necessary to improve performance. ” This required reliability cannot be achieved in the tails of the distribution and economic agents therefore ignore actions that are appropriate only in such situations. This explains our reluctance to insure against rare disasters which Heiner notes:

” Rare events are precisely those which are remote to a person’s normal experience, so that uncertainty in detecting which rare disasters to insure against increases as p(probability of disaster) approaches zero. Such greater uncertainty will reduce the reliability of insurance decisions as disasters become increasingly remote to a person’s normal experience.”

” At some point as p approaches zero, the Reliability Condition will be violated. This implies people will switch from typically buying to typically ignoring insurance conditions, which is just the pattern documented in Kunreuther’s 1978 study.”

Note the similarity between Heiner’s analysis of tail risks under uncertainty and Kahneman and Tversky’s distinction between “possible” and “impossible” events. The reliability problem is also connected to the difficulty of ascertaining the properties of tail events through a statistical analysis of historical data.

In an uncertainty-driven framework, it may be more appropriate to refer to this pattern as a reluctance to insure against tail risks rather than a preference for “blowup risks”. This distinction is also relevant in the moral hazard debate where the actions are often characterised better as a neglect of insurance of tail risks than an explicit taking on of such risks.

Impossible Events and Axel Leijonhufvud’s “Corridor Hypothesis”

Heiner also extends this analysis of the reluctance to insure against “impossible” events to provide the rationale for Axel Leijonhufvud’s “Corridor Hypothesis” of macroeconomic shocks and recessions. In his words:

“Now suppose, analogous to the insurance case, that there are different types of shocks. some more severe than others; where larger shocks are possible but less and less likely to happen. In addition, the reliability of detecting when and how to prepare for large shocks decreases as their determinants and repercussions are more remote to agents’ normal experience.

In a similar manner to that discussed for the insurance case, we can derive that the economy’s structure will evolve so as to prepare for and react quickly to small shocks. However, outside of a certain zone or “corridor” around its long-run growth path, it will only very sluggishly react to sufficiently large, infrequent shocks.”

Minsky’s Financial Instability Hypothesis and Leijonhufvud’s Corridor

Minsky’s Financial Instability Hypothesis (FIH) asserts that stability breeds instability i.e. stability reduces the width of the corridor to the point where even a small shock is enough to push the system outside it. Leijonhufvud acknowledged Minsky’s insight that the width of the corridor was variable and depended upon the recency of past disturbances. In his own words: “Our theory implies a variable width of the corridor. Transactors who have once suffered through a displacement of unanticipated magnitude (on the order of the Great Depression, say) will be encouraged to maintain larger buffers thereafter-until the memory dims…”

The assertion that stability breeds instability is well established in ecology, especially in Buzz Holling’s work as I discussed here. Heiner’s framework explains Minsky’s assertion as the logical consequence of agent adaptation under uncertainty. But the same can also be explained via “natural selection”-like mechanisms as well. The most relevant is the principal-agent relationship. Principals that “select” agents under asymmetric information can effectively mimic the effect of natural selection in ecosystems.

Minsky also argues that sooner or later, a capitalist economy will move outside this corridor due to entirely endogenous reasons. This is a more controversial assertion and can only be evaluated through a careful analysis of the empirical evidence. The assertion that an economy can move outside the corridor due to endogenous factors is difficult to reject. All it takes is a chance prolonged period of stability. However, this does not imply that the economy must move outside the corridor, which requires us to prove that prolonged periods of stability are the norm rather than the exception in a capitalist economy.

Minsky’s Financial Instability Hypothesis and C.S. Holling’s conception of Resilience and Stability

Minsky’s idea that stability breeds instability is an important theme in the field of ecology. Buzz Holling however defined the problem as loss of resilience rather than instability. Resilience and stability are dramatically different concepts and Holling explained the difference in his seminal paper on the topic as follows:

“Resilience determines the persistence of relationships within a system and is a measure of the ability of these systems to absorb changes of state variables, driving variables, and parameters, and still persist. In this definition resilience is the property of the system and persistence or probability of extinction is the result. Stability, on the other hand, is the ability of a system to return to an equilibrium state after a temporary disturbance. The more rapidly it returns, and with the least fluctuation, the more stable it is. In this definition stability is the property of the system and the degree of fluctuation around specific states the result.”

The relevant insight in Holling’s work is that resilience and stability as goals for an ecosystem are frequently at odds with each other. In many ecosystems, “the very fact of low stability seems to produce high resilience“. Conversely, “the goal of producing a maximum sustained yield may result in a more stable system of reduced resilience”. Minsky’s hypothesis is thus better described as “stability breeds loss of resilience”, not “stability breeds instability”.

The Pathology of Macroeconomic Stabilisation

The “Pathology of Natural Resource Management” is described by Holling and Meffe as follows:

“when the range of natural variation in a system is reduced, the system loses resilience.That is, a system in which natural levels of variation have been reduced through command-and-control activities will be less resilient than an unaltered system when subsequently faced with external perturbations.”

Similarly, the dominant macroeconomic policy paradigm explicitly aims to stabilise the macroeconomy. In particular, monetary policy during the Great Moderation was used as a blunt instrument to put out all but the most minor macroeconomic fire. Stabilising policies of this nature can and do cause the same kind of loss of resilience that Minsky describes. Indeed, as I mentioned in my previous note, agent adaptation to stabilising monetary and fiscal policies can be viewed as a more profound kind of moral hazard. Economic agents may take on severely negatively skewed bets not even as an adaptation to uncertainty but merely as a rational response to stabilising macroeconomic policies.

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Written by Ashwin Parameswaran

January 30th, 2010 at 2:08 pm

11 Responses to 'Knightian Uncertainty and the Resilience-Stability Trade-off'

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  1. Do you see any link from Knightian uncertainty towards an account of the Equity Premium Puzzle? That is, agents might have risk aversions in the reasonable range but still require extra incentive to make investments in the presence of substantial/irreducible uncertainty.

    Also, any thoughts on the use of subjective expected utility in macro and finance? SEU seems to collapse uncertainty into risk, but Savage was wary of doing this in settings where it is impossible always to “look before you leap”.

    Iohannes

    30 Jan 10 at 5:44 pm

  2. Nice post. Keep up the good work. No doubt there are a lot of people buying bank debt and other instruments based on the no lehmans polcies. The biggest surprise of the next year could be the a run on a major bank and the inability of the government to save the institutions. I see a very complancent attitude that the government can indeed prevent all tail events, but reality is the damn they are trying to plug is getting absolutely massive with few policy tricks left.

    How dumb was the interest rate cut in january 2008 because of SocGen?
    There are no bullets left.

    shrek

    30 Jan 10 at 6:46 pm

  3. Another good post. I have a few sayings:

    A healthy market ecology has multiple strategies that are working in separate areas at the same time.

    The more entities manage for total return, the more unstable the financial system becomes.

    Stability only comes to markets in a self-reinforcing mode, from buy and hold (and sell and sit on cash) investors who act at the turning points.

    Markets are more akin to ecologies than physics experiments. When the ecology is diverse, but with variability, it is most robust.

    David Merkel

    30 Jan 10 at 11:53 pm

  4. Iohannes – Yes, I think many people have used “Ambiguity Aversion” as an explanation to the equity premium puzzle. Having said that, I tend to believe that equity risk premium is time-varying and frequently approaches zero. But that’s another post entirely!

    And yes, in my view the main problem with SEU and modern finance/macro is not that it ignores irrationality/”animal spirits”, but that it ignores uncertainty and more specifically evolution/adaptation under uncertainty.

    admin

    31 Jan 10 at 5:00 am

  5. Shrek – Thank you! All we’re doing is substituting many low intensity crises with an eventual high-intensity crisis. The best and most relevant example in ecology is the history of forest fire suppression in the United States which has prevented frequent low-intensity fires at the expense of eventual high-intensity fires that cause systemic collapse.

    And the SocGen episode was an example of the tendency we’ve seen from the Fed all through the last two decades, to use monetary policy as a blunt instrument to put every fire, no matter how minor.

    admin

    31 Jan 10 at 5:09 am

  6. David – you make some great points. Diversity is one of the most important determinants of resilience in a complex adaptive system.

    One of the key concepts in the stability-resilience tradeoff is that stability reduces system resilience by reducing diversity in the system. Essentially,adaptation or natural selection in a constant environment will reduce diversity as only one strategy will “win”. As a result, the very existence of variability in the environment increases diversity and promotes robustness.

    I’ll explore these themes in more detail in a later post.

    admin

    31 Jan 10 at 5:45 am

  7. Great thoughts. Thanks much!

    Iohannes

    1 Feb 10 at 12:49 am

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  9. [...] Jeffrey Friedman’s analysis of how Cioffi and Tannin clung to their beliefs in the face of mounting evidence to the contrary until the “threshold” was cleared and they finally threw in the towel is a perfect example of this phenomenon. In Ramachandran’s words, “At any given moment in our 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.” However, once a threshold is passed, the brain finds a way to revise the model completely. Ramachandran’s analysis also provides a neurological explanation for Thomas Kuhn’s phases of science where the “normal” period is overturned once anomalies accumulate beyond a threshold. It also provides further backing for the thesis that we follow simple rules and heuristics in the face of significant uncertainty which I discussed here. [...]

  10. [...] it neglects the principal’s option to walk away. A much better explanation that I mentioned here and here is the role of extended periods of stability in creating “moral hazard-like” [...]

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