Macroeconomic Resilience

The core insight  of the resilience-stability tradeoff is that stability leads to loss of resilience. Therefore stabilisation too leads to increased systemic fragility. But there is a lot more to it. In comparing economic crises to forest fires and river floods, I have highlighted the common patterns to the process of system fragilisation which eventually leaves the system “manager” in a situation where there are no good options left.

Drawing upon the work of Mancur Olson, I have explored how the buildup of special interests means that stability is self-reinforcing. Once rent-seeking has achieved sufficient scale, “distributional coalitions have the incentive and..the power to prevent changes that would deprive them of their enlarged share of the social output”. But what if we “solve” the Olsonian problem? Would that mitigate the problem of increased stabilisation and fragility? In this post, I will argue that the cycle of fragility and collapse has much deeper roots than any particular form of democracy.

In this analysis, I am going to move away from ecological analogies and instead turn to an example from modern medicine. In particular, I am going to compare the experience and history of psychiatric medication in the second half of the twentieth century to some of the issues we have already looked at in macroeconomic and ecological stabilisation. I hope to convince you that the uncanny similarities in the patterns observed in stabilised systems across such diverse domains are not a coincidence. In fact, the human body provides us with a much closer parallel to economic systems than even ecological systems with respect to the final stages of stabilisation. Most ecological systems collapse sooner simply because the limits to which resources will be spent in an escalating fashion to preserve stability are much smaller. For example, there are limits to the resources that will be deployed to prevent a forest fire, no matter how catastrophic. On the other hand, the resources that will be deployed to prevent collapse of any system that is integral to human beings are much larger.

Even by the standards of this blog, this will be a controversial article. In my discussion of psychiatric medicine I am relying primarily on Robert Whitaker’s excellent but controversial and much-disputed book ‘Anatomy of an Epidemic’. Nevertheless, I want to emphasise that my ultimate conclusions are much less incendiary than those of Whitaker. In the same way that I want to move beyond an explanation of the economic crisis that relies on evil bankers, crony capitalists and self-interested technocrats, I am trying to move beyond an explanation that blames evil pharma and misguided doctors for the crisis in mental health. I am not trying to imply that fraud and rent-seeking does not have a role to play. I am arguing that even if we eliminate them, the aim of a resilient economic and social system would not be realised.

THE PUZZLE

The puzzle of the history of macroeconomic stabilisation post-WW2 can be summarised as follows. Clearly every separate event of macroeconomic stabilisation works. Most monetary and fiscal interventions result in a rise in the financial markets, NGDP expectations and economic performance in the short run. Yet,

• we are in the middle of a ‘great stagnation’ and have been for a few decades.
• the frequency of crises seems to have risen dramatically in the last fifty years culminating in the environment since 2008 which is best described as a perpetual crisis.
• each recovery seems to be weaker than the previous one and requires an increased injection of stimulus to achieve results that were easily achieved by a simple rate cut not that long ago.

Similarly, the history of mental health post-WW2 too has been a puzzle and is summarised by Whitaker as follows:

The puzzle can now be precisely summed up. On the one hand, we know that many people are helped by psychiatric medications. We know that many people stabilize well on them and will personally attest to how the drugs have helped them lead normal lives. Furthermore, as Satcher noted in his 1999 report, the scientific literature does document that psychiatric medications, at least over the short term, are “effective.” Psychiatrists and other physicians who prescribe the drugs will attest to that fact, and many parents of children taking psychiatric drugs will swear by the drugs as well. All of that makes for a powerful consensus: Psychiatric drugs work and help people lead relatively normal lives. And yet, at the same time, we are stuck with these disturbing facts: The number of disabled mentally ill has risen dramatically since 1955, and during the past two decades, a period when the prescribing of psychiatric medications has exploded, the number of adults and children disabled by mental illness has risen at a mind-boggling rate.

Whitaker then asks the obvious but heretical question – “Could our drug-based paradigm of care, in some unforeseen way, be fueling this modern-day plague?” and answers the question in the affirmative. But what are the precise mechanisms and patterns that underlie this deterioration?

Adaptive Response to Intervention and Drug Dependence

The fundamental reason why interventions fail in complex adaptive systems is the adaptive response triggered by the intervention that subverts the aim of the intervention. Moreover once the system is artificially stabilised and system agents have adapted to this new stability, the system cannot cope with any abrupt withdrawal of the stabilising force. For example, Whitaker notes that

Neuroleptics put a brake on dopamine transmission, and in response the brain puts down the dopamine accelerator (the extra D2 receptors). f the drug is abruptly withdrawn, the brake on dopamine is suddenly released while the accelerator is still pressed to the floor. The system is now wildly out of balance, and just as a car might careen out of control, so too the dopaminergic pathways in the brain……In short, initial exposure to neuroleptics put patients onto a path where they would likely need the drugs for life.

Whitaker makes the same observation for benzodiazepines and antidepressants:

benzodiazepines….work by perturbing a neurotransmitter system, and in response, the brain undergoes compensatory adaptations, and as a result of this change, the person becomes vulnerable to relapse upon drug withdrawal. That difficulty in turn may lead some to take the drugs indefinitely.

(antidepressants) perturb neurotransmitter systems in the brain. This leads to compensatory processes that oppose the initial acute effects of a drug…. When drug treatment ends, these processes may operate unopposed, resulting in appearance of withdrawal symptoms and increased vulnerability to relapse.

Similarly, when a central bank protects incumbent banks against liquidity risk, the banks choose to hold progressively more illiquid portfolios. When central banks provide incumbent banks with cheap funding in times of crisis to prevent failure and creditor losses, the banks choose to take on more leverage. This is similar to what John Adams has termed the ‘risk thermostat’ – the system readjusts to get back to its preferred risk profile. The protection once provided is almost impossible to withdraw without causing systemic havoc as agents adapt to the new stabilised reality and lose the ability to survive in an unstabilised environment.

Of course, in economic systems when agents actively intend to arbitrage such commitments by central banks, it is simply a form of moral hazard. But such an adaptation can easily occur via the natural selective forces at work in an economy – those who fail to take advantage of the Greenspan/Bernanke put simply go bust or get fired. In our brain the adaptation simply reflects homeostatic mechanisms selected for by the process of evolution.

Transformation into a Pathological State, Loss of Core Functionality and Deterioration of the Baseline State

I have argued in many posts that the successive cycles of Minskyian stabilisation have a role to play in the deterioration in the structural performance of the real economy which has manifested itself as ‘The Great Stagnation’. The same conclusion holds for many other complex adaptive systems and our brain is no different. Stabilisation kills much of what makes human beings creative. Innovation and creativity are fundamentally disequilibrium processes so it is no surprise that an environment of stability does not foster them. Whitaker interviews a patient on antidepressants who said: “I didn’t have mood swings after that, but instead of having a baseline of functioning normally, I was depressed. I was in a state of depression the entire time I was on the medication.”

He also notes disturbing research on the damage done to children who were treated for ADHD with Ritalin:

when researchers looked at whether Ritalin at least helped hyperactive children fare well academically, to get good grades and thus succeed as students, they found that it wasn’t so. Being able to focus intently on a math test, it turned out, didn’t translate into long-term academic achievement. This drug, Sroufe explained in 1973, enhances performance on “repetitive, routinized tasks that require sustained attention,” but “reasoning, problem solving and learning do not seem to be [positively] affected.”……Carol Whalen, a psychologist from the University of California at Irvine, noted in 1997 that “especially worrisome has been the suggestion that the unsalutary effects [of Ritalin] occur in the realm of complex, high-order cognitive functions such as flexible problem-solving or divergent thinking.”

Progressive Increase in Required Dosage

In economic systems, this steady structural deterioration means that increasing amounts of stimulus need to be applied in successive cycles of stabilisation to achieve the same levels of growth. Whitaker too identifies a similar tendency:

Over time, Chouinard and Jones noted, the dopaminergic pathways tended to become permanently dysfunctional. They became irreversibly stuck in a hyperactive state, and soon the patient’s tongue was slipping rhythmically in and out of his mouth (tardive dyskinesia) and psychotic symptoms were worsening (tardive psychosis). Doctors would then need to prescribe higher doses of antipsychotics to tamp down those tardive symptoms.

At this point, some of you may raise the following objection: so what if the new state is pathological? Maybe capitalism with its inherent instability is itself pathological. And once the safety nets of the Greenspan/Bernanke put, lender-of-last-resort programs and too-big-to-fail bailouts are put in place why would we need or want to remove them? If we simply medicate the economy ad infinitum, can we not avoid collapse ad infinitum?

This argument however is flawed.

• The ability of economic players to reorganise to maximise the rents extracted from central banking and state commitments far exceeds the the resources available to the state and the central bank. The key reason for this is the purely financial nature of this commitment. For example, if the state decided to print money and support the price of corn at twice its natural market price, then it could conceivably do so forever. Sooner or later, rent extractors will run up against natural resource limits – for example,limits on arable land. But when the state commits to support a credit money dominant financial system and asset prices then the economic system can and will generate financial “assets” without limit to take advantage of this commitment. The only defense that the CB and the state possess is regulations aimed at maintaining financial markets in an incomplete, underdeveloped state where economic agents do not possess the tools to game the system. Unfortunately as Minsky and many others have documented, the pace of financial innovation over the last half-century has meant that banks and financialised corporates have all the tools they need to circumvent regulations and maximise rent extraction.
• Even in a modern state that can print its own fiat currency, the ability to maintain financial commitments is subordinate to the need to control inflation. But doesn’t the complete absence of inflationary pressures in the current environment prove that we are nowhere close to any such limits? Not quite – As I have argued before, the current macroeconomic policy is defined by an abandonment of the full employment target in order to mitigate any risk of inflation whatsoever. The inflationary risk caused by rent extraction from the stabilisation commitment is being counterbalanced by a “reserve army of labour”. The reason for giving up the full employment is simple – As Minsky identified, once the economy has gone through successive cycles of stabilisation, it is prone to ‘rapid cycling’.

Rapid Cycling and Transformation of an Episodic Illness into a Chronic Illness

Minsky noted that

A high-investment, high-profit strategy for full employment – even with the underpinning of an active fiscal policy and an aware Federal Reserve system – leads to an increasingly unstable financial system, and an increasingly unstable economic performance. Within a short span of time, the policy problem cycles among preventing a deep depression, getting a stagnant economy moving again, reining in an inflation, and offsetting a credit squeeze or crunch.

In other words, an economy that attempts to achieve full employment will yo-yo uncontrollably between a state of debt-deflation and high, variable inflation – somewhat similar to a broken shower that only runs either too hot or too cold. The abandonment of the full employment target enables the system to postpone this point of rapid cycling.

The structural malformation of the economic system due to the application of increasing levels of stimulus to the task of stabilisation means that the economy has lost the ability to generate the endogenous growth and innovation that it could before it was so actively stabilised. The system has now been homogenised and is entirely dependent upon constant stimulus. The phenomenon of ‘rapid cycling’ explains a phenomenon I noted in an earlier post which is the apparently schizophrenic nature of the markets, turning from risk-on to risk-off at the drop of a hat. It is the lack of diversity that causes this as the vast majority of agents change their behaviour based on absence or presence of stabilising interventions.

Whitaker again notes the connection between medication and rapid cycling in many instances:

As early as 1965, before lithium had made its triumphant entry into American psychiatry, German psychiatrists were puzzling over the change they were seeing in their manic-depressive patients. Patients treated with antidepressants were relapsing frequently, the drugs “transforming the illness from an episodic course with free intervals to a chronic course with continuous illness,” they wrote. The German physicians also noted that in some patients, “the drugs produced a destabilization in which, for the first time, hypomania was followed by continual cycling between hypomania and depression.””

(stimulants) cause children to cycle through arousal and dysphoric states on a daily basis. When a child takes the drug, dopamine levels in the synapse increase, and this produces an aroused state. The child may show increased energy, an intensified focus, and hyperalertness. The child may become anxious, irritable, aggressive, hostile, and unable to sleep. More extreme arousal symptoms include obsessive-compulsive and hypomanic behaviors. But when the drug exits the brain, dopamine levels in the synapse sharply drop, and this may lead to such dysphoric symptoms as fatigue, lethargy, apathy, social withdrawal, and depression. Parents regularly talk of this daily “crash.”

THE PATIENT WANTS STABILITY TOO

At this point, I seem to be arguing that stabilisation is all just a con-game designed to enrich evil bankers, evil pharma etc. But such an explanation underestimates just how deep-seated the temptation and need to stabilise really is. The most critical component that it misses out on is the fact that the “patient” in complex adaptive systems is as eager to choose stability over resilience as the doctor is.

The Short-Term vs The Long-Term

As Daniel Carlat notes, the reality is that on the whole, psychiatric drugs “work” at least in the short term. Similarly, each individual act of macroeconomic stabilisation such as a lender-of-last-resort intervention, quantitative easing or a rate cut clearly has a positive impact on the short-term performance of both asset markets and the economy.

Whitaker too acknowledges this:

Those are the dueling visions of the psychopharmacology era. If you think of the drugs as “anti-disease” agents and focus on short-term outcomes, the young lady springs into sight. If you think of the drugs as “chemical imbalancers” and focus on long-term outcomes, the old hag appears. You can see either image, depending on where you direct your gaze.

The critical point here is that just like in forest fires and macroeconomies, the initial attempts to stabilise can be achieved easily and with very little medication. The results may seem even miraculous. But this initial period does not last. From one of many cases Whitaker quotes:

at first, “it was like a miracle,” she says. Andrew’s fears abated, he learned to tie his shoes, and his teachers praised his improved behavior. But after a few months, the drug no longer seemed to work so well, and whenever its effects wore off, there would be this “rebound effect.” Andrew would “behave like a wild man, out of control.” A doctor increased his dosage, only then it seemed that Andrew was like a “zombie,” his sense of humor reemerging only when the drug’s effects wore off. Next, Andrew needed to take clonidine in order to fall asleep at night. The drug treatment didn’t really seem to be helping, and so Ritalin gave way to other stimulants, including Adderall, Concerta, and dextroamphetamine. “It was always more drugs,” his mother says.

Medication Seen as Revealing Structural Flaws

One would think that the functional and structural deterioration that follows constant medication would cause both the patient and the doctor to reconsider the benefits of stabilisation. But this deterioration too can be interpreted in many different ways. Whitaker gives an example where the stabilised state is seen to be beneficial by revealing hitherto undiagnosed structural problems:

in 1982, Michael Strober and Gabrielle Carlson at the UCLA Neuropsychiatric Institute put a new twist into the juvenile bipolar story. Twelve of the sixty adolescents they had treated with antidepressants had turned “bipolar” over the course of three years, which—one might think—suggested that the drugs had caused the mania. Instead, Strober and Carlson reasoned that their study had shown that antidepressants could be used as a diagnostic tool. It wasn’t that antidepressants were causing some children to go manic, but rather the drugs were unmasking bipolar illness, as only children with the disease would suffer this reaction to an anti-depressant. “Our data imply that biologic differences between latent depressive subtypes are already present and detectable during the period of early adolescence, and that pharmacologic challenge can serve as one reliable aid in delimiting specific affective syndromes in juveniles,” they said.

Drug Withdrawal as Proof That It Works

The symptoms of drug withdrawal can also be interpreted to mean that the drug was necessary and that the patient is fundamentally ill. The reduction in withdrawal symptoms when the patient goes back on provides further “proof” that the drug works. Withdrawal symptoms can also be interpreted as proof that the patient needs to be treated for a longer period. Again, quoting from Whitaker:

Chouinard and Jones’s work also revealed that both psychiatrists and their patients would regularly suffer from a clinical delusion: They would see the return of psychotic symptoms upon drug withdrawal as proof that the antipsychotic was necessary and that it “worked.” The relapsed patient would then go back on the drug and often the psychosis would abate, which would be further proof that it worked. Both doctor and patient would experience this to be “true,” and yet, in fact, the reason that the psychosis abated with the return of the drug was that the brake on dopamine transmission was being reapplied, which countered the stuck dopamine accelerator. As Chouinard and Jones explained: “The need for continued neuroleptic treatment may itself be drug-induced.”

while they acknowledged that some alprazolam patients fared poorly when the drug was withdrawn, they reasoned that it had been used for too short a period and the withdrawal done too abruptly. “We recommend that patients with panic disorder be treated for a longer period, at least six months,” they said.

Similarly, macroeconomic crises can and frequently are interpreted as a need for better and more stabilisation. The initial positive impact of each intervention and the negative impact of reducing stimulus only reinforces this belief.

SCIENCE AND STABILISATION

A typical complaint against Whitaker’s argument is that his thesis is unproven. I would argue that within the confines of conventional “scientific” data analysis, his thesis and others directly opposed to it are essentially unprovable. To take an example from economics, is the current rush towards “safe” assets a sign that we need to produce more “safe” assets? Or is it a sign that our fragile economic system is addicted to the need for an ever-increasing supply of “safe” assets and what we need is a world in which no assets are safe and all market participants are fully aware of this fact?

In complex adaptive systems it can also be argued that the modern scientific method that relies on empirical testing of theoretical hypotheses against the data is itself fundamentally biased towards stabilisation and against resilience. The same story that I trace out below for the history of mental health can be traced out for economics and many other fields.

Desire to Become a ‘Real’ Science

Whitaker traces out how the theory attributing mental disorders to chemical imbalances was embraced as it enabled psychiatrists to become “real” doctors and captures the mood of the profession in the 80s:

Since the days of Sigmund Freud the practice of psychiatry has been more art than science. Surrounded by an aura of witchcraft, proceeding on impression and hunch, often ineffective, it was the bumbling and sometimes humorous stepchild of modern science. But for a decade and more, research psychiatrists have been working quietly in laboratories, dissecting the brains of mice and men and teasing out the chemical formulas that unlock the secrets of the mind. Now, in the 1980s, their work is paying off. They are rapidly identifying the interlocking molecules that produce human thought and emotion…. As a result, psychiatry today stands on the threshold of becoming an exact science, as precise and quantifiable as molecular genetics.

Search for the Magic Bullet despite Complexity of Problem

In the language of medicine, a ‘magic bullet’ is a drug that counters the root cause of the disease without adversely affecting any other part of the patient. The chemical-imbalance theory took a ‘magic bullet’ approach which reduced the complexity of our mental system to “a simple disease mechanism, one easy to grasp. In depression, the problem was that the serotonergic neurons released too little serotonin into the synaptic gap, and thus the serotonergic pathways in the brain were “underactive”. Antidepressants brought serotonin levels in the synaptic gap up to normal, and that allowed these pathways to transmit messages at a proper pace.”

Search for Scientific Method and Objective Criteria

Whitaker traces out the push towards making psychiatry an objective science with a defined method and its implications:

Congress had created the NIMH with the thought that it would transform psychiatry into a more modern, scientific discipline…..Psychiatrists and nurses would use “rating scales” to measure numerically the characteristic symptoms of the disease that was to be studied. Did a drug for schizophrenia reduce the patient’s “anxiety”? His or her “grandiosity”? “Hostility”? “Suspiciousness”? “Unusual thought content”? “Uncooperativeness”? The severity of all of those symptoms would be measured on a numerical scale and a total “symptom” score tabulated, and a drug would be deemed effective if it reduced the total score significantly more than a placebo did within a six-week period. At least in theory, psychiatry now had a way to conduct trials of psychiatric drugs that would produce an “objective” result. Yet the adoption of this assessment put psychiatry on a very particular path: The field would now see short-term reduction of symptoms as evidence of a drug’s efficacy. Much as a physician in internal medicine would prescribe an antibiotic for a bacterial infection, a psychiatrist would prescribe a pill that knocked down a “target symptom” of a “discrete disease.” The six-week “clinical trial” would prove that this was the right thing to do. However, this tool wouldn’t provide any insight into how patients were faring over the long term.

It cannot be emphasised enough that even increasing the period of the scientific trial is not enough to give us definitive answers. The argument that structural flaws are being uncovered or that withdrawal proves that the drug works cannot be definitively refuted. Moreover, at every point of time after medication is started, the short-term impact of staying on or increasing the level of medication is better than the alternative of going off the medication. The deeper issue here is also that in such a system, statistical analysis that tries to determine the efficacy of the intervention cannot deal with the fact that the nature of the intervention itself is to shift the distribution of outcomes into the tail and continue to do so as long as the level of medication keeps increasing.

The Control Agenda and High Modernism

The desire for stability and the control agenda is not simply a consequence of the growth of Olsonian special interests in the economy. The title of this post is inspired by Holling and Meffe’s classic paper on this topic in ecology. Their paper highlights that stabilisation is embedded within the command-and-control approach which itself is inherent to the high modernist way that James Scott has criticised.

Holling and Meffe also recognise that it is a simplistic application of “scientific” methods that underpins this command-and-control philosophy:

much of present ecological theory uses the equilibrium definition of resilience, even though that definition reinforces the pathology of equilibrium-centered command and control. That is because much of that theory draws predominantly from traditions of deductive mathematical theory (Pimm 1984) in which simplified, untouched ecological systems are imagined, or from traditions of engineering in which the motive is to design systems with a single operating objective (Waide & Webster 1976; De Angelis et. al. 1980; O’Neill et al. 1986), or from small-scale quadrant experiments in nature (Tilman & Downing 1994) in which long-term, large-scale successional or episodic transformations are not of concern. That makes the mathematics more tractable, it accommodates the engineer’s goal to develop optimal designs, and it provides the ecologist with a rationale for utilizing manageable, small sized, and short-term experiments, all reasonable goals. But these traditional concepts and techniques make the world appear more simple, tractable, and manageable than it really is. They carry an implicit assumption that there is global stability – that there is only one equilibrium steady-state, or, if other operating states exist, they should be avoided with safeguards and regulatory controls. They transfer the command-and-control myopia of exploitive development to similarly myopic demands for environmental regulations and prohibitions.

Those who emphasize ecosystem resilience, on the other hand, come from traditions of applied mathematics and applied resource ecology at the scale of ecosystems, such as the dynamics and management of freshwater systems (Fiering 1982) forests (Clark et al. 19759, fisheries (Walters 1986) semiarid grasslands (Walker et al. 1969), and interacting populations in nature (Dublin et al. 1990; Sinclair et al. 1990). Because these studies are rooted in inductive rather than deductive theory formation and in experience with the effects of large-scale management disturbances, the reality of flips from one stable state to another cannot be avoided (Helling 1986).

My aim in this last section is not to argue against the scientific method but simply to state that we have adopted too narrow a definition of what constitutes a scientific endeavour. Even this is not a coincidence. High modernism has its roots firmly planted in Enlightenment rationality and philosophical viewpoints that lie at the core of our idea of progress. In many uncertain domains, genuine progress and stabilisation that leads to fragility cannot be distinguished from each other. These are topics that I hope to explore in future posts.

In an earlier post, I compared Minsky’s Financial Instability Hypothesis with Buzz Holling’s work on ecological resilience and briefly touched upon the consequences of wildfire suppression as an example of the resilience-stability tradeoff. This post expands upon the lessons we can learn from the history of fire suppression and its impact on the forest ecosystem in the United States and draws some parallels between the theory and history of forest fire management and macroeconomic management.

Origins of Stabilisation as the Primary Policy Objective and Initial Ease of Implementation

The impetus for both fire suppression and macroeconomic stabilisation came from a crisis. In economics, this crisis was the Great Depression which highlighted the need for stabilising fiscal and monetary policy during a crisis. Out of all the initiatives, the most crucial from a systems viewpoint was the expansion of lender-of-last-resort operations and bank bailouts which tried to eliminate all disturbances at their source. In Minsky’s words: “The need for lender-of-Iast-resort operations will often occur before income falls steeply and before the well nigh automatic income and financial stabilizing effects of Big Government come into play.” (Stabilizing an Unstable Economy pg 46)

SImilarly, the battle for complete fire suppression was won after the Great Idaho Fires of 1910. “The Great Idaho Fires of August 1910 were a defining event for fire policy and management, indeed for the policy and management of all natural resources in the United States. Often called the Big Blowup, the complex of fires consumed 3 million acres of valuable timber in northern Idaho and western Montana…..The battle cry of foresters and philosophers that year was simple and compelling: fires are evil, and they must be banished from the earth. The federal Weeks Act, which had been stalled in Congress for years, passed in February 1911. This law drastically expanded the Forest Service and established cooperative federal-state programs in fire control. It marked the beginning of federal fire-suppression efforts and effectively brought an end to light burning practices across most of the country. The prompt suppression of wildland fires by government agencies became a national paradigm and a national policy” (Sara Jensen and Guy McPherson). In 1935, the Forest Service implemented the ‘10 AM policy’, a goal to extinguish every new fire by 10 AM the day after it was reported.

In both cases, the trauma of a catastrophic disaster triggered a new policy that would try to stamp out all disturbances at the source, no matter how small. This policy also had the benefit of initially being easy to implement and cheap. In the case of wildfires, “the 10 am policy, which guided Forest Service wildfire suppression until the mid 1970s, made sense in the short term, as wildfires are much easier and cheaper to suppress when they are small. Consider that, on average, 98.9% of wildfires on public land in the US are suppressed before they exceed 120 ha, but fires larger than that account for 97.5% of all suppression costs” (Donovan and Brown). As Minsky notes, macroeconomic stability was helped significantly by the deleveraged nature of the American economy from the end of WW2 till the 1960s. Even in interventions by the Federal Reserve in the late 60s and 70s, the amount of resources needed to shore up the system was limited.

Consequences of Stabilisation

Wildfire suppression in forests that are otherwise adapted to regular, low-intensity fires (e.g. understory fire regimes) causes the forest to become more fragile and susceptible to a catastrophic fire. As Holling and Meffe note, “fire suppression in systems that would frequently experience low-intensity fires results in the systems becoming severely affected by the huge fires that finally erupt; that is, the systems are not resilient to the major fires that occur with large fuel loads and may fundamentally change state after the fire”. This increased fragility arises from a few distinct patterns and mechanisms:

Increased Fuel Load: Just like channelisation of a river results in increased silt load within the river banks, the absence of fires leads to a fuel buildup thus making the eventual fire that much more severe. In Minskyian terms, this is analogous to the buildup of leverage and ‘Ponzi finance’ within the economic system.

Change in Species Composition: Species compositions inevitably shift towards less fire resistant trees when fires are suppressed (Allen et al 2002). In an economic system, it is not simply that ‘Ponzi finance’ players thrive but that more prudently financed actors get outcompeted in the cycle. This has critical implications for the ability of the system to recover after the fire. This is an important problem in the financial sector where as Richard Fisher observed, “more prudent and better-managed banks have been denied the market share that would have been theirs if mismanaged big banks had been allowed to go out of business”.

Reduction in Diversity: As I mentioned here, “In an environment free of disturbances, diversity of competing strategies must reduce dramatically as the optimal strategy will outcompete all others. In fact, disturbances are a key reason why competitive exclusion is rarely observed in ecosystems”. Contrary to popular opinion, the post-disturbance environment is incredibly productive and diverse. Even after a fire as severe as the Yellowstone fires of 1988, the regeneration of the system was swift and effective as the ecosystem was historically adapted to such severe fires.

Increased Connectivity: This is the least appreciated impact of eliminating all disturbances in a complex adaptive system. Disturbances perform a critical role by breaking connections within a network. Frequent forest fires result in a “patchy” modularised forest where no one fire can cause catastrophic damage. As Thomas Bonnicksen notes: “Fire seldom spread over vast areas in historic forests because meadows, and patches of young trees and open patches of old trees were difficult to burn and forced fires to drop to the ground…..Unlike the popular idealized image of historic forests, which depicts old trees spread like a blanket over the landscape, a real historic forest was patchy. It looked more like a quilt than a blanket. It was a mosaic of patches. Each patch consisted of a group of trees of about the same age, some young patches, some old patches, or meadows depending on how many years passed since fire created a new opening where they could grow. The variety of patches in historic forests helped to contain hot fires. Most patches of young trees, and old trees with little underneath did not burn well and served as firebreaks. Still, chance led to fires skipping some patches. So, fuel built up and the next fire burned a few of them while doing little harm to the rest of the forest”. Suppressing forest fires converts the forest into one connected whole, at risk of complete destruction from the eventual fire that cannot be suppressed.

In the absence of disturbances, connectivity builds up within the network, both within and between scales. Increased within-scale connectivity increases the severity but between-scale connectivity increases the probability of a disturbance at a lower level propagating up to higher levels and causing systemic collapse. Fire suppression in forests adapted to frequent undergrowth fires can cause an accumulation of ladder fuels which connect the undergrowth to the crown of the forest. The eventual undergrowth ignition then risks a crown fire by a process known as “torching”. Unlike understory fires, crown fires can spread across firebreaks such as rivers by a process known as “spotting” where the wind carries burning embers through the air – the fire can spread in this manner even without direct connectivity. Such fires can easily cause systemic collapse and a state from which natural forces cannot regenerate the forest. In this manner, stabilisation can cause changes which cause a fundamental change in the nature of the system rather than simply an increased severity of disturbances. For example, “extensive stand-replacing fires are in many cases resulting in “type conversions” from ponderosa pine forest to other physiognomic types (for example, grassland or shrubland) that may be persistent for centuries or perhaps even millennia” (Allen 2007).

Long-Run Increase in Cost of Stabilisation and Area Burned: The initial low cost of suppression is short-lived and the cumulative effect of the fragilisation of the system has led to rapidly increasing costs of wildfire suppression and levels of area burned in the last three decades (Donovan and Brown 2007).

Dilemmas in the Management of a Stabilised System

In my post on river flood management, I claimed that managing a stabilised and fragile system is “akin to choosing between the frying pan and the fire”. This has been the case in many forests around the United States for the last few decades and is the condition into which the economies of the developed world are heading into. Once the forest ecosystem has become fragile, the resultant large fire exacerbates the problem thus triggering a vicious cycle. As Thomas Bonnicksen observed, “monster fires create even bigger monsters. Huge blocks of seedlings that grow on burned areas become older and thicker at the same time. When it burns again, fire spreads farther and creates an even bigger block of fuel for the next fire. This cycle of monster fires has begun”. The system enters an “unending cycle of monster fires and blackened landscapes”.

Minsky of course understood this end-state very well: “The success of a high-private-investment strategy depends upon the continued growth of relative needs to validate private investment. It also requires that policy be directed to maintain and increase the quasi-rents earned by capital – i.e.,rentier and entrepreneurial income. But such high and increasing quasi-rents are particularly conducive to speculation, especially as these profits are presumably guaranteed by policy. The result is experimentation with liability structures that not only hypothecate increasing proportions of cash receipts but that also depend upon continuous refinancing of asset positions. A high-investment, high-profit strategy for full employment – even with the underpinning of an active fiscal policy and an aware Federal Reserve system – leads to an increasingly unstable financial system, and an increasingly unstable economic performance. Within a short span of time, the policy problem cycles among preventing a deep depression, getting a stagnant economy moving again, reining in an inflation, and offsetting a credit squeeze or crunch….As high investment and high profits depend upon and induce speculation with respect to liability structures, the expansions become increasingly difficult to control; the choice seems to become whether to accomodate to an increasing inflation or to induce a debt-deflation process that can lead to a serious depression”. (John Maynard Keynes pg163–164)

The evolution of the system means that turning back the clock to a previous era of stability is not an option. As Minsky observed in the context of our financial system, “the apparent stability and robustness of the financial system of the 1950s and early 1960s can now be viewed as an accident of history, which was due to the financial residue of World War 2 following fast upon a great depression”. Re-regulation is not enough because it cannot undo the damage done by decades of financial “innovation” in a manner that does not risk systemic collapse.

At the same time, simply allowing an excessively stabilised system to burn itself out is a recipe for disaster. For example, on the role that controlled burns could play in restoring America’s forests to a resilient state, Thomas Bonnicksen observed: “Prescribed fire would come closer than any tool toward mimicking the effects of the historic Indian and lightning fires that shaped most of America’s native forests. However, there are good reasons why it is declining in use rather than expanding. Most importantly, the fuel problem is so severe that we can no longer depend on prescribed fire to repair the damage caused by over a century of fire exclusion. Prescribed fire is ineffective and unsafe in such forests. It is ineffective because any fire that is hot enough to kill trees over three inches in diameter, which is too small to eliminate most fire hazards, has a high probability of becoming uncontrollable”. The same logic applies to a fragile economic system.

In future posts, I will examine potential policy options that can restore system resilience as well as expanding on implications of the above for macro-prudential regulation of the financial sector. I will also examine some simple network models to examine the problem in a more formal manner.

Update: corrected date of Idaho fires from 2010 to 1910 in para 3 thanks to Dean.

In this post, I apply the framework outlined previously to some empirical patterns in the financial markets and the broader economy. The objective is not to posit crony capitalism as the sole explanation of the below patterns, but merely to argue that the below patterns are consistent with an increasingly crony capitalist economy.

The Paradox of Low Volatility and High Correlation

As many commentators have pointed out [1,2,3], the spike in volatility experienced during the depths of the financial crisis has largely reversed itself but correlation within equities and between various risky asset classes has kept on moving higher. The combination of high volatility and high correlation is associated with the process of collapse and typical of the Minsky moment when the system undergoes a rapid delevering. However the combination of high correlation and low volatility post the Minsky moment is unusual. In the absence of bailouts or protectionism, the economy should undergo a process of creative destruction and intense exploratory activity which by its diffuse nature results in low correlation. The combination of high correlation and low volatility instead signifies stasis and the absence of sufficient exploration in the economy, alongwith the presence of significant slack at firm level (micro-resilience).

As I mentioned in a previous post, financing constraints faced by small businesses hinder new firm entry across industries. Expanding lending to new firms is an act of exploration and incumbent banks are almost certainly content with exploiting their known and low-risk sources of income instead.

The Paradox of High Corporate Profitability, Rising Productivity and High Unemployment and The Paradox of High Cash Balances and High Debt Issuance

Although corporate profitability is not at an all-time high, it has recovered at an unusually rapid pace compared to the nonexistent recovery in employment and wages. The recovery in corporate profits has been driven by a rise in worker productivity and increased efficiency but the lag between an output recovery and an employment recovery seems to have increased dramatically. So far, this increased profitability has led not to increased business investment but to increased cash holdings by corporates. Big corporates with easy access to debt markets have even chosen to tap the debt markets simply for the purpose of increasing cash holdings.

Again, incumbent corporates are eager to squeeze efficiencies out of their current operations including downsizing the labour force but instead of channeling the savings from this increased efficiency into exploratory investment, they choose to increase holdings of liquid assets. In an environment where incumbents are under limited threat of being superceded by exploratory new entrants, holding cash is an extremely effective way to retain optionality (a strategy that is much less effective if the pace of exploratory innovation is high as an extended period of standing on the sidelines of exploratory activity can degrade the ability of the incumbent to rejoin the fray). Old jobs are being destroyed by the optimising activities of incumbents but the exploration required to create new jobs does not take place.

This discussion of profitability and unemployment echoes many of the common concerns of the far left. This is not a coincidence – one of the most damaging effects of Olsonian cronyism is its malformation of the economy from a positive-sum game into an increasingly zero-sum game. The dynamics of a predominantly crony capitalist economy are closer to a Marxian class struggle than they are to a competitive free-market economy. However, where I differ significantly from the left is in the proposed cure for the disease. For example, incumbent investment can be triggered by an increase in leverage by another sector – given the indebted state of the consumer, the government is the most likely candidate. But such a policy does nothing to tackle the reduced evolvability of the economy or the dominance of the incumbent special interest groups. Moreover, increased taxation and transfers of wealth to other organised groups such as labour only aggravate the ossification of the economic system into an increasingly zero-sum game. A sustainable solution must restore the positive-sum dynamics that are the essence of Schumpeterian capitalism. Such a solution involves reducing the power of the incumbent corporates and transferring wealth from incumbent corporates towards households not by taxation or protectionism but by restoring the invisible foot of new firm entry.

STABILITY AS THE PRIMARY CAUSE OF CRONY CAPITALISM

The core insight of the Minsky-Holling resilience framework is that stability and stabilisation breed fragility and loss of system resilience . TBTF protection and the moral hazard problem is best seen as a subset of the broader policy of stabilisation, of which policies such as the Greenspan Put are much more pervasive and dangerous.

By itself, stabilisation is not sufficient to cause cronyism and rent seeking. Once a system has undergone a period of stabilisation, the system manager is always tempted to prolong the stabilisation for fear of the short-term disruption or even collapse. However, not all crisis-mitigation strategies involve bailouts and transfers of wealth to the incumbent corporates. As Mancur Olson pointed out, society can confine its “distributional transfers to poor and unfortunate individuals” rather than bailing out incumbent firms and still hope to achieve the same results.

To fully explain the rise of crony capitalism, we need to combine the Minsky-Holling framework with Mancur Olson’s insight that extended periods of stability trigger a progressive increase in the power of special interests and rent-seeking activity. Olson also noted the self-preserving nature of this phenomenon.  Once rent-seeking has achieved sufficient scale, “distributional coalitions have the incentive and..the power to prevent changes that would deprive them of their enlarged share of the social output”.

SYSTEMIC IMPACT OF CRONY CAPITALISM

Crony capitalism results in a homogenous, tightly coupled and fragile macroeconomy. The key question is: Via which channels does this systemic malformation occur? As I have touched upon in some earlier posts [1,2], the systemic implications of crony capitalism arise from its negative impact on new firm entry. In the context of the exploration vs exploitation framework, absence of new firm entry tilts the system towards over-exploitation¹ .

Exploration vs Exploitation: The Importance of New Firm Entry in Sustaining Exploration

In a seminal article, James March distinguished between “the exploration of new possibilities and the exploitation of old certainties. Exploration includes things captured by terms such as search, variation, risk taking, experimentation, play, flexibility, discovery, innovation. Exploitation includes such things as refinement, choice, production, efficiency, selection, implementation, execution.” True innovation is an act of exploration under conditions of irreducible uncertainty whereas exploitation is an act of optimisation under a known distribution.

The assertion that dominant incumbent firms find it hard to sustain exploratory innovation is not a controversial one. I do not intend to reiterate the popular arguments in the management literature, many of which I explored in a previous post. Moreover, the argument presented here is more subtle: I do not claim that incumbents cannot explore effectively but simply that they can explore effectively only when pushed to do so by a constant stream of new entrants. This is of course the “invisible foot” argument of Joseph Berliner and Burton Klein for which the exploration-exploitation framework provides an intuitive and rigorous rationale.

Let us assume a scenario where the entry of new firms has slowed to a trickle, the sector is dominated by a few dominant incumbents and the S-curve of growth is about to enter its maturity/decline phase. To trigger off a new S-curve of growth, the incumbents need to explore. However, almost by definition, the odds that any given act of exploration will be successful is small. Moreover, the positive payoff from any exploratory search almost certainly lies far in the future. For an improbable shot at moving from a position of comfort to one of dominance in the distant future, an incumbent firm needs to divert resources from optimising and efficiency-increasing initiatives that will deliver predictable profits in the near future. Of course if a significant proportion of its competitors adopt an exploratory strategy, even an incumbent firm will be forced to follow suit for fear of loss of market share. But this critical mass of exploratory incumbents never comes about. In essence, the state where almost all incumbents are content to focus their energies on exploitation is a Nash equilibrium.

On the other hand, the incentives of any new entrant are almost entirely skewed in favour of exploratory strategies. Even an improbable shot at glory is enough to outweigh the minor consequences of failure² . It cannot be emphasised enough that this argument does not depend upon the irrationality of the entrant. The same incremental payoff that represents a minor improvement for the incumbent is a life-changing event for the entrepreneur. When there exists a critical mass of exploratory new entrants, the dominant incumbents are compelled to follow suit and the Nash equilibrium of the industry shifts towards the appropriate mix of exploitation and exploration.

The Crony Capitalist Boom-Bust Cycle: A Tradeoff between System Resilience and Full Employment

Due to insufficient exploratory innovation, a crony capitalist economy is not diverse enough. But this does not imply that the system is fragile either at firm/micro level or at the level of the macroeconomy. In the absence of any risk of being displaced by new entrants, incumbent firms can simply maintain significant financial slack³. If incumbents do maintain significant financial slack, sustainable full employment is impossible almost by definition.  However, full employment can be achieved temporarily in two ways: Either incumbent corporates can gradually give up their financial slack and lever up as the period of stability extends as Minsky’s Financial Instability Hypothesis (FIH) would predict, or the household or government sector can lever up to compensate for the slack held by the corporate sector.

Most developed economies went down the route of increased household and corporate leverage with the process aided and abetted by monetary and regulatory policy. But it is instructive that developing economies such as India faced exactly the same problem in their “crony socialist” days. In keeping with its ideological leanings pre-1990, India tackled the unemployment problem via increased government spending. Whatever the chosen solution, full employment is unsustainable in the long run unless the core problem of cronyism is tackled. The current over-leveraged state of the consumer in the developed world can be papered over by increased government spending but in the face of increased cronyism, it only kicks the can further down the road. Restoring corporate animal spirits depends upon corporate slack being utilised in exploratory investment, which as discussed above is inconsistent with a cronyist economy.

Micro-Fragility as the Key to a Resilient Macroeconomy and Sustainable Full Employment

At the appropriate mix of exploration and exploitation, individual incumbent and new entrant firms are both incredibly vulnerable. Most exploratory investments are destined to fail as are most firms, sooner or later. Yet due to the diversity of firm-level strategies, the macroeconomy of vulnerable firms is incredibly resilient. At the same time, the transfer of wealth from incumbent corporates to the household sector via reduced corporate slack and increased investment means that sustainable full employment can be achieved without undue leverage. The only question is whether we can break out of the Olsonian special interest trap without having to suffer a systemic collapse in the process.

1. It cannot be emphasized enough that absence of new firm entry is simply the channel through which crony capitalism malforms the macroeconomy. Therefore, attempts to artificially boost new firm entry are likely to fail unless they tackle the ultimate cause of the problem which is stabilisation [↩]
2. It is critical that the personal consequences of firm failure are minor for the entrepreneur – this is not the case for cultural and legal reasons in many countries around the world but is largely still true in the United States. [↩]
3. It could be argued that incumbents could follow this strategy even when new entrants threaten them. This strategy however has its limits – an extended period of standing on the sidelines of exploratory activity can degrade the ability of the incumbent to rejoin the fray. As Brian Loasby remarked : “For many years, Arnold Weinberg chose to build up GEC’s reserves against an uncertain technological future in the form of cash rather than by investing in the creation of technological capabilities of unknown value. This policy, one might suggest, appears much more attractive in a financial environment where technology can often be bought by buying companies than in one where the market for corporate control is more tightly constrained; but it must be remembered that some, perhaps substantial, technological capability is likely to be needed in order to judge what companies are worth acquiring, and to make effective use of the acquisitions. As so often, substitutes are also in part complements.” [↩]

In an earlier post, I drew an analogy between Minsky’s Financial Instability Hypothesis (FIH) and the ecologist Buzz Holling’s work on the resilience-stability tradeoff in ecosystems. Extended periods of stability reduce system resilience in complex adaptive systems such as ecologies and economies. By extension, policies that focus on stabilisation cause a loss of system resilience. Holling and Meffe called this the Pathology of Natural Resource Management which they described 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.” This pathology is as relevant to macroeconomic systems as it is to ecosystems and I briefly drew an analogy between forest fire management and economic management in the earlier post. In this post, I analyse the dilemmas faced in river flood management and their relevance to macroeconomic management.

A Case Study of River Flood Management: River Kosi

The Kosi is one of the most flood-prone rivers in India. The brunt of its fury is borne by the northern Indian state of Bihar and the Kosi is aptly also known as the “Sorrow of Bihar”. Like many other flood-prone rivers, the root cause lies in the extraordinary amount of silt that the Kosi carries from the Himalayas to the plains of Bihar. The silt deposition raises the river bed and gravity causes the river to seek out a new course – in this manner, it has been estimated that the river Kosi may have moved westwards by an incredible 210 km in the last 250 years. During the 1950s, in an effort to provide “permanent salvation from floods” the Indian government embarked on a program of building embankments on the river to curb the periodic shifting of the Kosi’s course – the embankments were aimed at converting the unpredictable behaviour of the river into something more predictable and by extension, more manageable. It was assumed that the people of Bihar would benefit from a stabilised and predictable river.

Unfortunately, the reality of the flood management program on the river Kosi has turned out to be anything but beneficial. The culmination of the failure of the program was the 2008 Bihar flood which was one of the most disastrous floods in the history of the state. So what went wrong? Was this just a result of an extraordinary natural event? Most certainly not – As Dinesh Mishra notes, in 2008 the Kosi carried only  1/7th of the capacity of the embankments and at various points of time since the 50s, the river had carried far greater quantities of water without causing anywhere near the damage it caused in 2008. This was a disaster caused by the loss of system resilience, highlighted by the inability of the system to “withstand even modest adverse shocks” after prolonged periods of stability.

So what caused this loss of system resilience? As Dinesh Mishra explains: “By building embankments on either side of a river and trying to confine it to its channel, its heavy silt and sand load is made to settle within the embanked area itself, raising the river bed and the flood water level. The embankments too are therefore raised progressively until a limit is reached when it is no longer possible to do so. The population of the surrounding areas is then at the mercy of an unstable river with a dangerous flood water level , which could any day flow over or make a disastrous breach.” As expected, the eventual breach was catastrophic – the course of the Kosi moved more than 120 kilometres eastwards in a matter of weeks. In the absence of the embankments, such a dramatic shift would have taken decades. With the passage of time, a progressively greater degree of resources were required to maintain system stability and the eventual failure was a catastrophic one rather than a moderate one.

As the above analysis highlights, the stabilisation did not merely substitute a series of regular moderately damaging outcomes for an occasional catastrophic outcome (although this alone would be a cause for concern if a catastrophic outcome was capable of triggering systemic collapse). In fact, the stabilisation transformed the system into a state where eventually even minor and frequently observed disturbances would trigger a catastrophic outcome. As Jon Stewart put it, even “regular storms” would topple a fragile boat. When faced with the possibility of a catastrophic outcome, the managing agency has two choices, neither of which are attractive.

Either it can continue to stabilise the system using ever-increasing resources in an effort to avoid the catastrophic outcome. But this option must only be followed if the managing agency has infinite resources or if there is some absolute limit to this vicious cycle of cost escalation that is within the resource capabilities of the agency. Or it can allow the catastrophic outcome to occur in an effort to restore the system to its unstabilised state. But this option risks systemic collapse – it is not just the unprecedented nature of the outcome that we have to fear from, but the very fact that the adaptive agents of the complex system may have lost the ability to deal with even the occasional moderate failures that the unstabilised system would throw up. In other words, once the system has lost resilience, managing it is akin to choosing between the frying pan and the fire.

For example, in the pre-embankment era when the Kosi was allowed to meander and change course in a natural manner, the villagers on its banks had a deep understanding of the river’s patterns and its vagaries. The floods sustained the fertility of the soil and ensured that groundwater resources were plentiful. This is not to deny that the Kosi caused damage but because the people had adapted to its regular flooding patterns, systemic damage only occured during the proverbial 100-year flood. This highlights an important lesson in complex adaptive systems: The impact of disturbances cannot be analysed in isolation to the adaptive capacities of the agents in the system. If disturbances are regular and predictable, agents will likely be adapted to them and conversely, prolonged periods of stability will render agents vulnerable to even the smallest disturbance.

The problems of managing floods on the river Kosi are not unique – many rivers around the world pose similar challenges. For example, the Yellow River, aptly named the “Sorrow of China” and the Mississippi river basin, the story of which was captured so well by John McPhee. So is there any way to avoid this evolutionary arms race against nature? Are we to conclude that the only sustainable strategy is to avoid any intervention in the complex adaptive system? Not necessarily - interventions on the system must avoid tampering with the fundamental patterns and evolutionary dynamics of the system. Indeed the best example of river management that works with the natural flow of the river rather than against it is the Dutch government’s aptly named “Room for the River” project in the Rhine river valley. Instead of building higher dikes, the Dutch have chosen to build lower dikes that allow the Rhine to flood over a larger area thus easing the pressure on the dike system as a whole. This program has been adopted despite the fact that many farmers need to be relocated out of the newly expanded flood zones of the river.

Macroeconomic Parallels

Axel Leijonhufvud’s “Corridor Hypothesis” postulates that a macroeconomy will adapt well to small shocks but “outside of a certain zone or “corridor” around its long-run growth path, it will only very sluggishly react to sufficiently large, infrequent shocks.” The adaptive nature of the macroeconomy implies that stability and by extension stabilisation reduces the width of the corridor to the point where even a small shock is enough to push the system outside the corridor. Just as embankments induced fragility in the river Kosi, bailouts and other economic transfers to specific firms and industries induce fragility into the macroeconomic system. Economic policy must allow the “river” of the macroeconomy to flow in a natural manner and restrict its interventions to insuring individual economic agents against the occasional severe flood.

This sentiment was also expressed by that great evolutionary macroeconomist of our time, Mancur Olson. In his final work “Power and Prosperity”, Olson notes: “subsidizing industries, firms and localities that lose money…at the expense of those that make money…is typically disastrous for the efficiency and dynamism of the economy, in a way that transfers unnecessarily to poor individuals…A society that does not shift resources from the losing activities to those that generate a social surplus is irrational, since it is throwing away useful resources in a way that ruins economic performance without the least assurance that it is helping individuals with low incomes. A rational and humane society, then, will confine its distributional transfers to poor and unfortunate individuals.” Olson understood the damage inflicted by rent-seeking not only from a systemic perspective but from a perspective of social justice. The logical consequence of micro-stabilisation is a crony capitalist economy - rents invariably flow to the strong and the result is a sluggish and an inegalitarian economic system, not unlike many developing economies. Contrary to popular opinion, it is not limiting handouts to the poor that defines a free and dynamic economy but limiting rents that flow to the privileged.

On the Damage Done by the Greenspan Put Variant of Monetary Policy

Clearly, some fiscal policies aimed at firm and industry stabilisation harm the economic system. But what about monetary policy? Isn’t monetary policy close-to-neutral and therefore exempt from the above criticism? On the contrary – the Greenspan Put variant of monetary policy damages macroeconomic resilience as well as being inegalitarian and unjust. Monetary policy during the Greenspan-Bernanke era has focused on stabilising incumbent banks and helping them shore up their capital in response to every economic shock, as well as a focus on asset prices as a transmission channel of monetary policy i.e. the Greenspan Put. Unlike a river system where the buildup of silt is a clear indicator of growing fragility, there are no clear signs of loss of system resilience in a macroeconomy. However, we can infer loss of macroeconomic resilience from the ever-increasing resources that are required to maintain system stability. Just as the embankments of the Kosi were raised higher and higher to combat even a minor flood, the resources needed to stabilise the financial system have grown over the last 25 years. In the early 90s, bank capital could be rebuilt by a few years of low rates but now we need a panoply of “liquidity” facilities, near-zero rates and quantitative easing aimed at compressing the entire yield curve to achieve the same result.

As I mentioned earlier, such a stabilisation policy may be credible if there is a limit to the costs of stabilisation. For example, the rents that can be extracted by any small, isolated sector of the economy are limited. Unfortunately, and this is a point that cannot be emphasised enough, there is no limit to the rents that can be extracted by the financial sector. Every commitment by the Central Bank to insure the financial sector against bad outcomes will be arbitraged for all its worth until the cost of maintaining the commitment becomes so prohibitive that it is no longer tenable. Of course, as long as the stabilising policy is in operation it appears to be a “free lunch” – the costs of programs such as the TARP appear to be limited and well worth their macroeconomic benefits just like flood protection appears to be a successful choice in the long period of calm before the eventual disaster. The loss of resilience and rent extraction is exacerbated as other financial market players are encouraged to mimic banks and take on similarly negatively skewed bets such as investing the proceeds from securities lending in “safe” assets.

In my last post, I noted the connection between inequality and rents emanating from the moral hazard subsidy but the larger culprit is the toxic combination of Greenspan Put monetary policy and a dynamically uncompetitive cronyist financial sector. Even if the sector were more competitive it is inevitable that monetary policy focused on shoring up asset prices will benefit the primary asset-holders in the economy, which in itself is a regressive transfer of wealth to the rich. The idea that supporting asset prices is the best way to support the wider economy is not far away from the notion of trickle-down economics (or as Will Rogers put it: “money was all appropriated for the top in hopes that it would trickle down to the needy.”).

Finally, although it goes without saying that even a fiat currency-issuing central bank does not have infinite resources, the move over the last century from a gold standard to a fiat money regime does have some important implications for system resilience. In evolving from a decentralised gold standard monetary system to a fiat-currency issuing central bank regime, the flexibility and resources at the monetary authority’s disposal have increased significantly. In the hands of a responsible central bank the ability to issue a fiat currency is beneficial, but in an excessively stabilised economy, it allows the process of stabilisation to be maintained for far longer than it would otherwise be. And just like in the case of the river Kosi, the longer the period of the stabilisation the more catastrophic are the results of the inevitable normal disturbance.

There are two schools of thought on the primary cause of our current unemployment problem: Some claim that the unemployment is cyclical (low aggregate demand) whereas others think it’s structural (mismatch in the labour market). The “Structuralists” point to the apparent shift in the Beveridge curve and the increased demand in healthcare and technology whereas the “Cyclicalists” point to the fall in employment across all other sectors. So who’s right? In my opinion, neither explanation is entirely satisfactory. This post is an expansion of some thoughts I touched upon in my last post that describe the “persistent unemployment” problem as a logical consequence of a dynamically uncompetitive “Post Minsky Moment” economy.

Narayana Kocherlakota explains the mismatch thesis as follows: “Firms have jobs, but can’t find appropriate workers. The workers want to work, but can’t find appropriate jobs. There are many possible sources of mismatch—geography, skills, demography—and they are probably all at work….the Fed does not have a means to transform construction workers into manufacturing workers.” Undoubtedly this argument has some merit – the real question is how much of our current unemployment can be attributed to the mismatch problem? Kocherlakota draws on work done by Robert Shimer and extrapolates from the Beveridge curve relationship since 2000 to arrive at a implied unemployment rate of 6.3% if mismatch were not a bigger problem and the Beveridge curve relationship had not broken down. Jan Hatzius of Goldman Sachs on the other hand attributes as little as 0.75% of the current unemployment problem to structural reasons. Murat Tasci and Dave Lindner however conclude that the recent behaviour of the Beveridge curve is not anomalous when viewed in the context of previous post-war recessions. Shimer himself was wary of extrapolating too much from the limited data set from 2000 (see pg 12-13 here)  This would imply that Kocherlakota’s estimate is an overestimate even if Jan Hatzius’ may be an underestimate.

Incorporating Uncertainty into the Mismatch Argument

It is likely therefore that there is a significant pool of unemployment that cannot be justified by the simple mismatch argument. But this does not mean that the “recalculation” thesis is not valid. The simple mismatch argument ignores the uncertainty involved in the “Post-Minsky Moment economy” – it assumes that firms have known jobs that remain unfilled whereas in reality, firms need to engage in a process of exploration that will determine the nature of jobs consistent with the new economic reality before they search for suitable workers. The problem we face right now is of firms unwilling to take on the risk inherent in such an exploration. The central message in my previous posts on evolvability and organisational rigidity is that this process of exploration is dependent upon the maintenance of a dynamically competitive economy rather than a statically competitive economy. Continuous entry of new firms is of critical importance in maintaining a dynamically competitive economy that retains the ability to evolve and reconfigure itself when faced with a dramatic change in circumstances.

The “Post Minsky Moment” Economy

In Minsky’s Financial Instability Hypothesis, the long period of stability before the crash creates a homogeneous and fragile ecosystem – the fragility arises due to the fragility of the individual firms as well the absence of diversity. Post the inevitable crash, the system inevitably regains some of its robustness via the slack built up by the incumbent firms, usually in the form of financial liquidity. However, so long as this slack at firm level is maintained, the macro-system cannot possibly revert to a state where it attains conventional welfare optima such as full employment. The conventional Keynesian solution suggests that the state pick up the slack in economic activity whereas some assume that sooner or later, market forces will reorganise to utilise this firm-level slack. This post is an attempt to partially refute both explanations – As Burton Klein often noted, there is no hidden hand that can miraculously restore the “animal spirits” of an economy or an industry once it has lost its evolvability. Similarly, Keynesian policies that shore up the position of the incumbent firms can cause fatal damage to the evolvability of the macro-economy.

Corporate Profits and Unemployment

This thesis does not imply that incumbent firms leave money on the table. In fact, incumbents typically redouble their efforts at static optimisation – hence the rise in corporate profits. Some may argue that this rise in profitability is illusory and represents capital consumption i.e. short-term gain at the expense of long-term loss of competence and capabilities at firm level. But in the absence of new firm entry, it is unlikely that there is even a long-term threat to incumbents’ survival i.e. firms are making a calculated bet that loss of evolvability represents a minor risk. It is only the invisible foot of the threat of new firms that prevents incumbents from going down this route.

Small Business Financing Constraints as a Driver of Unemployment

The role of new firms in generating employment is well-established and my argument implies that incumbent firms will effectively contribute to solving the unemployment problem only when prodded to do so by the hidden foot of new firm entry. The credit conditions faced by small businesses remain extremely tight despite funding costs for big incumbent firms having eased considerably since the peak of the crisis. Of course this may be due to insufficient investment opportunities – some of which may be due to dominant large incumbents in specific sectors. But a more plausible explanation lies in the unevolvable and incumbent-dominated state of our banking sector. Expanding lending to new firms is an act of exploration and incumbent banks are almost certainly content with exploiting their known and low-risk sources of income instead. One of Burton Klein’s key insights was how only a few key dynamically uncompetitive sectors can act as a deadweight drag on the entire economy and banking certainly fits the bill.

Amongst economic commentators, Raghuram Rajan has stood out recently for his consistent calls to raise interest rates from “ultra-low to the merely low”. Predictably, this suggestion has been met with outright condemnation by many economists, both of Keynesian and monetarist persuasion. Rajan’s case against ultra-low rates utilises many arguments but this post will focus on just one of these arguments that is straight out of the “resilience” playbook. In 2008, Raghu Rajan and Doug Diamond co-authored a paper, the conclusion of which Rajan summarises in his FT article: “the pattern of Fed policy over time builds expectations. The market now thinks that whenever the financial sector’s actions result in unemployment, the Fed will respond with ultra-low rates and easy liquidity. So even as the Fed has maintained credibility as an inflation fighter, it has lost credibility in fighting financial adventurism. This cannot augur well for the future.”

Much like he accused the Austrians, Paul Krugman accuses Rajan of being a “liquidationist”. This is not a coincidence – Rajan and Diamond’s thesis is quite explicit about its connections to Austrian Business Cycle Theory: “a central bank that promises to cut interest rates conditional on stress, or that is biased towards low interest rates favouring entrepreneurs, will induce banks to promise higher payouts or take more illiquid projects. This in turn can make the illiquidity crisis more severe and require a greater degree of intervention, a view reminiscent of the Austrian theory of cycles.” But as the summary hints, Rajan and Diamond’s thesis is fundamentally different from ABCT. The conventional Austrian story identifies excessive credit inflation and interest rates below the “natural” rate of interest as the driver of the boom/bust cycle but Rajan and Diamond’s thesis identifies the anticipation by economic agents of low rates and “liquidity” facilities every time there is an economic downturn as the driver of systemic fragility. The adaptation of banks and other market players to this regime makes the eventual bust all the more likely. As Rajan and Diamond note: “If the authorities are expected to reduce interest rates when liquidity is at a premium, banks will take on more short-term leverage or illiquid loans, thus bringing about the very states where intervention is needed.”

Rajan and Diamond’s thesis is limited to the impact of such policies on banks but as I noted in a previous post, market players also adapt to this implicit commitment from the central bank to follow easy money policies at the first hint of economic trouble. This thesis is essentially a story of the Greenspan-Bernanke era and the damage that the Greenspan Put has caused. It also explains the dramatically diminishing returns inherent in the Greenspan Put strategy as the stabilising policies of the central bank become entrenched in the expectations of market players and crucially banks – in each subsequent cycle, the central bank has to do more and more (lower rates, larger liquidity facilities) to achieve less and less.

This post is the first in a series that takes an ecological and dynamic approach to analysing market/macroeconomic regimes and transitions between these regimes.

Normal, Pre-Crisis and Crisis Regimes

In a post on market crises, Rick Bookstaber identified three regimes that any model of the market must represent (normal, pre-crisis and crisis) and analysed the statistical properties (volatility,correlation etc) of each of these regimes. The framework below however characterises each regime by the varying combinations of positive and negative feedback processes and the variations and regime shifts are determined by the adaptive and evolutionary processes operating within the system.

1. Normal regimes are resilient regimes. They are characterised by a balanced and diverse mix of positive and negative feedback processes. For every momentum trader who bets on the continuation of a trend, there is a contrarian who bets the other way.

2. Pre-crisis regimes are characterised by an increasing dominance of positive feedback processes. An unusually high degree of stability or a persistent trend progressively weeds out negative feedback processes from the system thus leaving it vulnerable to collapse even as a result of disturbances that it could easily absorb in its previously resilient normal state. Such regimes can arise from bubbles but this is not necessary. Pre-crisis only implies that a regime change into the crisis regime is increasingly likely – in ecological terms, the pre-crisis regime is fragile and has suffered a significant loss of resilience.

3. Crisis regimes are essentially transitional  - the disturbance has occurred and the positive feedback processes that dominated the previous regime have now reversed direction. However, the final destination of this transition is uncertain – if the system is left alone, it will undergo a discontinuous transition to a normal regime. However, if sufficient external stabilisation pressures are exerted upon the system, it may revert to the pre-crisis regime or even stay in the crisis regime for a longer period. It’s worth noting that I define a normal regime only by its resilience and not by its desirability – even a state of civilizational collapse can be incredibly resilient.

“Critical Transitions” from the Pre-Crisis to the Crisis Regime

In fragile systems even a minor disturbance can trigger a discontinuous move to an alternative regime – Marten Scheffer refers to such moves as “critical transitions”. Figures a,b,c and d below represent a continuum of ways in which the system can react to changing external conditions (ref Scheffer et al) . Although I will frequently refer to “equilibria” and “states” in the discussion below, these are better described as “attractors” and “regimes” given the dynamic nature of the system – the static terminology is merely a simplification.

In Figure a, the system state reacts smoothly to perturbations – for example, a large external change will trigger a large move in the state of the system. The dotted arrows denote the direction in which the system moves when it is not on the curve i.e. in equilibrium.  Any move away from equilibrium triggers forces that bring it back to the curve. In Figure b, the transition is non-linear and a small perturbation can trigger a regime shift – however a reversal of conditions of an equally small magnitude can reverse the regime shift. Clearly, such a system does not satisfactorily explain our current economic predicament where monetary and fiscal intervention far in excess of the initial sub-prime shock have failed to bring the system back to its previous state.

Figure c however may be a more accurate description of the current state of the economy and the market – for a certain range of conditions, there exist two alternative stable states separated by an unstable equilibrium (marked by the dotted line). As the dotted arrows indicate, movement away from the unstable equilibrium can carry the system to either of the two alternative stable states. Figure d illustrates how a small perturbation past the point F2 triggers a “catastrophic” transition from the upper branch to the lower branch – moreover, unless conditions are reversed all the way back to the point F1, the system will not revert back to the upper branch stable state. The system therefore exhibits “hysteresis” – i.e. the path matters. The forward and backward switches occur at different points F2 and F1 respectively, which implies that reversing such transitions is not easy. A comprehensive discussion of the conditions that will determine the extent of hysteresis is beyond the scope of this post – however it is worth mentioning that cognitive and organisational rigidity in the absence of sufficient diversity is a sufficient condition for hysteresis in the macro-system.

Before I apply the above framework to some events in the market, it is worth clarifying how the states in Figure d correspond to those chosen by Rick Bookstaber. The “normal” regime refers to the parts of the upper and lower branch stable states that are far from the points F1 and F2 i.e. the system is resilient to a change in external conditions. As I mentioned earlier, normal does not equate to desirable – the lower branch could be a state of collapse. If we designate the upper branch as a desirable normal state and the lower branch as an undesirable one, then the zone close to point F2 on the upper branch is the pre-crisis regime. The crisis regime is the short catastrophic transition from F2 to the lower branch if the system is left alone. If forces external to the system are applied to prevent a transition to the lower branch, then the system could either revert back to the upper branch or even stay in the crisis regime on the dotted line unstable equilibrium for a longer period.

The Magnetar Trade revisited

In an earlier post, I analysed how the infamous Magnetar Trade could be explained with a framework that incorporates catastrophic transitions between alternative stable states. As I noted: “The Magnetar trade would pay off in two scenarios – if there were no defaults in any of their CDOs, or if there were so many defaults that the tranches that they were short also defaulted alongwith the equity tranche. The trade would likely lose money if there were limited defaults in all the CDOs and the senior tranches did not default. Essentially, the trade was attractive if one believed that this intermediate scenario was improbable…Intermediate scenarios are unlikely when the system is characterised by multiple stable states and catastrophic transitions between these states. In adaptive systems such as ecosystems or macroeconomies, such transitions are most likely when the system is fragile and in a state of low resilience. The system tends to be dominated by positive feedback processes that amplify the impact of small perturbations, with no negative feedback processes present that can arrest this snowballing effect.”

In the language of critical transitions, Magnetar calculated that the real estate and MBS markets were in a fragile pre-crisis state and no intervention would prevent the rapid critical transition from F2 to the lower branch.

“Schizophrenic” Markets and the Long Crisis

Recently, many commentators have noted the apparently schizophrenic nature of the markets, turning from risk-on to risk-off at the drop of a hat. For example, John Kemp argues that the markets are “trapped between euphoria and despair” and notes the U-shaped distribution of Bank of England’s inflation forecasts (table 5.13). Although at first glance this sort of behaviour seems irrational, it may not be – As PIMCO’s Richard Clarida notes: “we are in a world in which average outcomes – for growth, inflation, corporate and sovereign defaults, and the investment returns driven by these outcomes – will matter less and less for investors and policymakers. This is because we are in a New Normal world in which the distribution of outcomes is flatter and the tails are fatter. As such, the mean of the distribution becomes an observation that is very rarely realized”

Richard Clarida’s New Normal is analogous to the crisis regime (the dotted line unstable equilibrium in Figures c and d). Any movement in either direction is self-fulfilling and leads to either a much stronger economy or a much weaker economy. So why is the current crisis regime such a long one? As I mentioned earlier, external stabilisation (in this case monetary and fiscal policy) can keep the system from collapsing down to the lower branch normal regime – the “schizophrenia” only indicates that the market may make a decisive break to a stable state sooner rather than later.

In a recent post, Rajiv Sethi questions the tendency to find behavioural explanations for financial crises and argues for an ecological approach instead – a sentiment that I agree with and have touched upon in previous posts on this blog. This post expands upon some of these themes.

A More Realistic View of Rationality and Human Cognition, Not Irrationality

Much of the debate on rationality in economics focuses on whether we as human beings are rational in the “homo economicus” sense. The “heuristics and biases” program pioneered by Daniel Kahneman and Amos Tversky argues that we are not “rational” – however, it does not question whether the definition of rationality implicit in “rational choice theory” is valid or not. Many researchers in the neural and cognitive sciences now believe that the conventional definition of rationality needs to be radically overhauled.

Most heuristics/biases are not a sign of irrationality but an entirely rational form of decision-making when faced with uncertainty. In an earlier post, I explained how Ronald Heiner’s framework can explain our neglect of tail events as a logical response to an uncertain environment, but the best exposition of this viewpoint can be seen in Gerd Gigerenzer’s work which itself is inspired by Herbert Simon’s ideas on “bounded rationality”. In his aptly named book “Rationality for Mortals: How People Cope with Uncertainty”, Gigerenzer explains the two key building blocks of “the science of heuristics”:

• The Adaptive Toolbox: “the building blocks for fast and frugal heuristics that work in real-world environments of natural complexity, where an optimal strategy is often unknown or computationally intractable”
• Ecological Rationality: “the environmental structures in which a given heuristic is successful” and the “coevolution between heuristics and environments”

The irony of course is that many classical economists had a more accurate definition of rationality than the one implicit in “rational choice theory” (See Brian Loasby’s book which I discussed here). Much of the work done in the neural sciences confirms the more nuanced view of human cognition espoused in Hayek’s “The Sensory Order” or Ken Boulding’s “The Image” (See Joaquin Fuster on Hayek or the similarities between Ken Boulding’s views and V.S. Ramachandran’s work discussed here).

Macro-Rationality is consistent with Micro-Irrationality

Even a more realistic definition of rationality doesn’t preclude individual irrationality. However, as Michael Mauboussin pointed out: “markets can still be rational when investors are individually irrational. Sufficient investor diversity is the essential feature in efficient price formation. Provided the decision rules of investors are diverse—even if they are suboptimal—errors tend to cancel out and markets arrive at appropriate prices. Similarly, if these decision rules lose diversity, markets become fragile and susceptible to inefficiency. So the issue is not whether individuals are irrational (they are) but whether they are irrational in the same way at the same time. So while understanding individual behavioral pitfalls may improve your own decision making, appreciation of the dynamics of the collective is key to outperforming the market.”

Economies as Complex Adaptive Systems: Behavioural Heterogeneity, Selection Pressures and Emphasis on System Dynamics

In my view, the ecological approach to macroeconomics is essentially a systems approach with the emphasis on the “adaptive” nature of the system i.e. incentives matter and the actors in a system tend to find ways to work around imposed rules that try to fight the impact of misaligned incentives. David Merkel explained it well when he noted: “People hate having their freedom restrained, and so when arbitrary rules are imposed, even smart rules, they look for means of escape.” And many of the posts on this blog have focused on how rules can be subverted even when economic agents don’t actively intend to do so.

The ecological approach emphasises the diversity of behavioural preferences and the role of incentives/institutions/rules in “selecting” from this pool of possible agent behaviours or causing agent behaviour to adapt in reaction to these incentives. When a behaviourally homogeneous pool of agents is observed, the ecological approach focuses on the selection pressures and incentives that could have caused this loss of diversity rather than attempting to lay the blame on some immutable behavioural trait. Again, as Rajiv Sethi puts it here: “human behavior differs substantially across career paths because of selection both into and within occupations….[Regularities] identified in controlled laboratory experiments with standard subject pools have limited application to environments in which the distribution of behavioral propensities is both endogenous and psychologically rare. This is the case in financial markets, which are subject to selection at a number of levels. Those who enter the profession are unlikely to be psychologically typical, and market conditions determine which behavioral propensities survive and thrive at any point in historical time.”