I am not sure the modelling methodology described in this article is quite as good as the title suggests…
“Chaos Researchers Can Now Predict Perilous Points of No Return”
… but it would be very interesting if it lives up to the claims made in the article. It is a quick read and the subject matter seems worth keeping an eye on.
Here are two short extracts to give you a flavour of the claims made
A custom-built machine learning algorithm can predict when a complex system is about to switch to a wildly different mode of behavior.
In a series of recent papers, researchers have shown that machine learning algorithms can predict tipping-point transitions in archetypal examples of such “nonstationary” systems, as well as features of their behavior after they’ve tipped. The surprisingly powerful new techniques could one day find applications in climate science, ecology, epidemiology and many other fields.
The whole series is highly recommended but I especially like this quote in which he attempts to sum up the series
“Life eventually humbles us all. What I love about experts, the best of them anyway, is that they get to their humility early, they have to, it’s part of who they are, it’s necessary for what they are doing. They set out to get to the bottom of something that has no bottom, and so they are reminded, constantly, of what they don’t know. They move through the world focussed not on what they know but on what they might find out.”
Shout out to Tim Harford for this introduction to the study of how, in his words, ignorance can be deliberately produced. The technical term “agnatology” is I suspect unlikely to catch on but the underlying message is one worth understanding. At a minimum it is a handy addition to your Scrabble dictionary.
The article was originally published in March 2017 but I only came across it recently via this podcast interview Harford did with Cardiff Garcia on “The New Bazaar”. The context in 2017 was the successful campaign for the US presidency that Donald Trump ran during 2016 with a bit of Brexit thrown in but this is a challenge that is not going away anytime soon.
Harford notes that it is tempting to think that the answer to the challenge posed by what has come to be known as a post truth society lies in a better process to establish the facts
The instinctive reaction from those of us who still care about the truth — journalists, academics and many ordinary citizens — has been to double down on the facts.
He affirms the need to have some agreement on how we distinguish facts from opinions and assertions but he cautions that this is unlikely to solve the problem. He cites the tobacco industry response to the early evidence that smoking causes cancer to illustrate why facts alone are not enough.
A good place to start is by delving into why facts alone are not enough – a few extracts from the article hopefully capture the main lessons
Doubt is usually not hard to produce, and facts alone aren’t enough to dispel it. We should have learnt this lesson already; now we’re going to have to learn it all over again…
Tempting as it is to fight lies with facts, there are three problems with that strategy…
The first is that a simple untruth can beat off a complicated set of facts simply by being easier to understand and remember. When doubt prevails, people will often end up believing whatever sticks in the mind…
There’s a second reason why facts don’t seem to have the traction that one might hope. Facts can be boring. The world is full of things to pay attention to, from reality TV to your argumentative children, from a friend’s Instagram to a tax bill. Why bother with anything so tedious as facts?…
In the war of ideas, boredom and distraction are powerful weapons. The endgame of these distractions is that matters of vital importance become too boring to bother reporting…
There’s a final problem with trying to persuade people by giving them facts: the truth can feel threatening, and threatening people tends to backfire. “People respond in the opposite direction,” says Jason Reifler, a political scientist at Exeter University. This “backfire effect” is now the focus of several researchers, including Reifler and his colleague Brendan Nyhan of Dartmouth…
The problem here is that while we like to think of ourselves as rational beings, our rationality didn’t just evolve to solve practical problems, such as building an elephant trap, but to navigate social situations. We need to keep others on our side. Practical reasoning is often less about figuring out what’s true, and more about staying in the right tribe…
We see what we want to see — and we reject the facts that threaten our sense of who we are…
When we reach the conclusion that we want to reach, we’re engaging in “motivated reasoning”…
Even in a debate polluted by motivated reasoning, one might expect that facts will help. Not necessarily: when we hear facts that challenge us, we selectively amplify what suits us, ignore what does not, and reinterpret whatever we can. More facts mean more grist to the motivated reasoning mill. The French dramatist Molière once wrote: “A learned fool is more foolish than an ignorant one.” Modern social science agrees…
When people are seeking the truth, facts help. But when people are selectively reasoning about their political identity, the facts can backfire.
So what are we to do?
Harford cites a study that explores the value of scientific curiosity
What Kahan and his colleagues found, to their surprise, was that while politically motivated reasoning trumps scientific knowledge, “politically motivated reasoning . . . appears to be negated by science curiosity”. Scientifically literate people, remember, were more likely to be polarised in their answers to politically charged scientific questions. But scientifically curious people were not. Curiosity brought people together in a way that mere facts did not. The researchers muse that curious people have an extra reason to seek out the facts: “To experience the pleasure of contemplating surprising insights into how the world works.”
It is of course entirely possible that Tim Harford’s assessment is just calling to my own bias. I will admit that one the things that I always looked for when hiring, or working, with people was curiosity. These people are surprisingly rare but (IMHO) worth their weight in gold. An intellectually curious mind makes up for a lot of other areas where the person might not be perfect in terms of skills or experience. The general point (I think) also ties to the often cited problem that people with lots of knowledge can sometimes be prone to not being so street smart. Nassim Taleb makes this argument in nearly everything he writes.
So Tim Harford might not be offering the entire answer but I think his article is worth reading on two counts
Firstly as a cautionary tale against expecting that all debates and disputes can be resolved by simply establishing the “facts”
Secondly as a reminder of the power of a curious mind and the value of the never-ending search for “what am I missing?”
A BIS paper titled “Green Swan 2 – Climate change and Covid-19: reflections on efficiency versus resilience” initially caught my attention because of the reference to the tension between efficiency versus resilience. This tension is, for me at least, one of the issues that has tended to be ignored in the pursuit of growth and optimised solutions. The papers mainly deal with the challenges that climate change creates for central banks but I think there are also some insights to be drawn on what it means for bank capital management.
A core argument in the paper is that challenges like climate change and pandemics ….
“… require us to rethink the trade-offs between efficiency and resilience of our socio-economic systems … one way to address this issue is to think about buffers or some necessary degree of redundancy for absorbing such large shocks. Countries build FX reserves, banks maintain capital buffers as required by regulators, and so on. Perhaps similar “buffers” could be used in other areas of our societies. For example, could it be time to reassess our production systems, which are meant to be lean and less costly for maximum efficiency?”
The paper draws on a (much longer and more technical) BIS research paper titled “The green swan: Central banking and financial stability in the age of climate change”. Both papers contain the usual caveat that the views expressed do not necessarily reflect those of their respective institutions. With that warning noted, this post draws on both papers to make some observations about what the papers say, and what this means for bank capital management.
There is a lot of content in the combined papers but the points that resonated the most with me were
Climate change shares some of the features of a Black Swan event but is better thought of a distinct type of risk which the authors label a “Green Swan”.
Green swan problems are created in part by choices we have made regarding the value of efficiency over resilience – part of the solution lies in rethinking these choices but this will not be easy.
Climate change is a “collective action” problem which cannot be addressed by individual actors (including banks) operating independently – market based solutions like a carbon price may also be insufficient to bring about a solution that does not involve an unacceptable level of financial disruption.
Scenario analysis (including stress testing) appears to be one of the better tools for dealing with climate change and similar types of risk – but it needs to be used differently (by both the supervised and the supervisors) from the way it is applied to conventional risks.
I am not an expert on climate change modelling, but Chapter 3 of the second paper also has what looks to be a useful overview of the models used to analyse climate change and how the outputs of these models are used to generate economic impacts.
Black, white and green swans
Climate change clearly operates in the domain of radical uncertainty. As such it shares some common elements with “black swan” events; in particular the fact that conventional risk models and analysis are not well suited to measuring and managing the potential adverse impacts. It is equally important however to understand the ways in which climate change differs from a classic black swan event. There is a longer list but the ones that I found most relevant were:
Predictability – Black Swans are, by definition, not predictable whereas the potential for adverse Climate Change outcomes is well understood even if not universally accepted. The point is that understanding the potential for adverse impact means we have a choice about what to do about it.
Impact – Black Swan events can have substantial impacts but the system can recover (e.g. the GFC has left a lasting impact but economic activity did recover once the losses were absorbed). The impacts of climate change, in contrast, may be irreversible and have the potential to result in people dying in large numbers.
Given the conceptual differences, the authors classify Climate Change as a distinct form which they label a “Green Swan”. To the best of my knowledge, this may be the first time the term has been used in this way. That said, the general point they are making seems to be quite similar to what other authors have labelled as “Grey Rhinos” or “Black Elephants” (the latter an obvious allusion to the “elephant in the room”, a large risk that is visible to everyone but no one wants to address).
A typology of swans
A typology of Swans: similarities and differences – BIS Green Swan 2 – Climate change and Covid-19: reflections on efficiency versus resilience
Categorising climate risk
The papers distinguish two main channels through which climate change can affect financial stability – physical risks and transition risks.
Physical risks are defined as
… “those risks that arise from the interaction of climate-related hazards […] with the vulnerability of exposure to human and natural systems” (Batten et al (2016)). They represent the economic costs and financial losses due to increasing frequency and severity of climate-related weather events (eg storms, floods or heat waves) and the effects of long-term changes in climate patterns (eg ocean acidification, rising sea levels or changes in precipitation). The losses incurred by firms across different financial portfolios (eg loans, equities, bonds) can make them more fragile.
Transition risks are defined as those
“… associated with the uncertain financial impacts that could result from a rapid low-carbon transition, including policy changes, reputational impacts, technological breakthroughs or limitations, and shifts in market preferences and social norms.
A rapid and ambitious transition to lower emissions, for example, would obviously be desirable from the perspective of addressing climate change but might also mean that a large fraction of proven reserves of fossil fuel cannot be extracted, becoming “stranded assets”. The write down of the value of these assets may have potentially systemic consequences for the financial system. This transition might occur in response to policy changes or by virtue of some technological breakthrough (e.g. problem of generating cheap energy by nuclear fusion is solved).
Efficiency versus resilience
I started this post with a quote from the first (shorter) paper regarding the way in which the Covid 19 had drawn attention to the extent to which the pursuit of efficiency had made our economies more fragile. The paper explores the ways in which the COVID 19 pandemic exhibits many of the same features that we see in the climate change problem and how the global response to the COVID 19 pandemic might offer some insights into how we should respond to climate change.
The paper is a useful reminder of the nature of the problem but I am less confident that it offers a solution that will work without some form of regulation or public sector investment in the desired level of redundancy. The paper cites bank capital buffers introduced post GFC as an example of what to do but this was a regulated outcome that would most likely not be acceptable for non-financial companies in countries that remain committed to free market ideology.
The Economist published an article on this question that offered numerous examples of similar problems that illustrate the propensity of “humanity, at least as represented by the world’s governments … to ignore them until forced to react” .
If recent weeks have shown us anything, it’s that the world is not just flat. It’s fragile.
And we’re the ones who made it that way with our own hands. Just look around. Over the past 20 years, we’ve been steadily removing man-made and natural buffers, redundancies, regulations and norms that provide resilience and protection when big systems — be they ecological, geopolitical or financial — get stressed. We’ve been recklessly removing these buffers out of an obsession with short-term efficiency and growth, or without thinking at all.
The New York Times, 30 May 2020
Managingcollective action problems
The second paper, in particular, argues that it is important to improve our understanding of the costs of climate change and to ensure that these costs are incorporated into the prices that drive the resources we allocate to dealing with the challenge (e.g. via a carbon price or tax). However one of its key conclusions is that relying on markets to solve the problem is unlikely to be sufficient even with the help of some form of carbon price that reflects a more complete account of the costs of our current carbon based economy.
In short, the development and improvement of forward-looking risk assessment and climate- related regulation will be essential, but they will not suffice to preserve financial stability in the age of climate change: the deep uncertainty involved and the need for structural transformation of the global socioeconomic system mean that no single model or scenario can provide sufficient information to private and public decision-makers. A corollary is that the integration of climate-related risks into prudential regulation and (to the extent possible) into monetary policy would not suffice to trigger a shift capable of hedging the whole system again against green swan events.
The green swan: Central banking and financial stability in the age of climate change; Chapter 5 (page 66)
Using scenario based methodologies to assess climate related risks
Both papers highlight the limitations of trying to measure and understand climate change using conventional probability based risk management tools. The one area they do see as worth pursuing is using scenario based approaches. This makes sense to me but it is also important to distinguish this kind of analysis from the standard stress testing used to help calibrate capital buffers.
The standard application of stress testing takes a severe but plausible macro economic scenario such as a severe recession and determines what are the likely impacts on capital adequacy ratios. This offers a disciplined way of deciding how much capital surplus is required to support the risk appetite choices a bank has made in pursuit of its business objectives.
A simplistic application of climate based stress testing scenarios might take the same approach; i.e. work out how much the scenario impacts the capital and ensure that the buffer is sufficient to absorb the impact. That I think is not the right conclusion and my read of the BIS papers is that they are not advocating that either. The value of the scenario based modelling is to first get a handle on the size of the problem and how exposed the bank is to it. A capital response may be required but the answer may also be to change the nature of your exposure to the risk. That may involve reduced risk limits but it may also involve active participation in collective action to address the underlying problem. A capital management response may be part of the solution but it is far from the first step.
Conclusion
I have only scratched the surface of this topic in this post but the two papers it references are worth reading if you are interested in the question of what climate change, and related Green Swan or Black Elephant problems, mean for the banking system and for central banking. There is a bit more technical detail in the appendix below but it is likely only of interest for people working at the sharp end of trying to measure and manage the problem.
I want to dig deeper into the question of how you use stress testing to assess climate change and related types of risk but that is a topic best left for another post.
Tony – From the outside
Appendix – Modelling the impacts of climate change
Section 3 of the longer paper (“Measuring climate-related risks with scenario-based approaches”) discusses the limitations of the models that are typically used to generate estimates of the ecological and financial impacts of climate change scenarios. There is plenty of material there for climate sceptics but it also assists true believers to understand the limits of what they can actually know and how coming to terms with the radical uncertainty of how climate change plays out shapes the nature of our response.
I have copied some extracts from the chapter below that will give you a flavour of what it has to say. It is pretty technical so be warned …
“… the standard approach to modelling financial risk consisting in extrapolating historical values (eg PD, market prices) is no longer valid in a world that is fundamentally reshaped by climate change (Weitzman (2011), Kunreuther et al (2013)). In other words, green swan events cannot be captured by traditional risk management.
The current situation can be characterised as an “epistemological obstacle” (Bachelard (1938)). The latter refers to how scientific methods and “intellectual habits that were useful and healthy” under certain circumstances, can progressively become problematic and hamper scientific research. Epistemological obstacles do not refer to the difficulty or complexity inherent to the object studied (eg measuring climate-related risks) but to the difficulty related to the need of redefining the problem”
Page 21
nothing less than an epistemological break (Bachelard, 1938) or a “paradigm shift” (Kuhn (1962)) is needed today to overcome this obstacle and more adequately approach climate-relate risks (Pereira da Silva (2019a)).
In fact, precisely an epistemological break may be taking place in the financial sector: recently emerged methodologies aim to assess climate-related risks while relying on the fundamental hypothesis that, given the lack of historical financial data related to climate change and the deep uncertainty involved, new approaches based on the analysis of prospective scenarios are needed. Unlike probabilistic approaches to financial risk management, they seek to set up plausible hypotheses for the future. This can help financial institutions integrate climate-related risks into their strategic and operational procedures (eg for the purpose of asset allocation, credit rating or insurance underwriting) and financial supervisors assess the vulnerability of specific institutions or the financial system as a whole
Climate-economic models and forward-looking risk analysis are important and can still be improved, but they will not suffice to provide all the information required to hedge against “green swan” events.
As a result of these limitations, two main avenues of action have been proposed. We argue that they should be pursued in parallel rather than in an exclusive manner. First, central banks and supervisors could explore different approaches that can better account for the uncertain and nonlinear features of climate-related risks. Three particular research avenues (see Box 5 below) consist in: (i) working with non- equilibrium models; (ii) conducting sensitivity analyses; and (iii) conducting case studies focusing on specific risks and/or transmission channels. Nevertheless, the descriptive and normative power of these alternative approaches remain limited by the sources of deep and radical uncertainty related to climate change discussed above. That is, the catalytic power of scenario-based analysis, even when grounded in approaches such as non-equilibrium models, will not be sufficient to guide decision-making towards a low-carbon transition.
As a result of this, the second avenue from the perspective of maintaining system stability consists in “going beyond models” and in developing more holistic approaches that can better embrace the deep or radical uncertainty of climate change as well as the need for system-wide action (Aglietta and Espagne (2016), Barmes (2019), Chenet et al (2019a), Ryan-Collins (2019), Svartzman et al (2019)).
Pages 42 – 43
Embracing deep or radical uncertainty therefore calls for a second “epistemological break” to shift from a management of risks approach to one that seeks to assure the resilience of complex adaptive systems in the face of such uncertainty (Fath et al (2015), Schoon and van der Leeuw (2015)).38 In this view, the current efforts aimed at measuring, managing and supervising climate-related risks will only make sense if they take place within a much broader evolution involving coordination with monetary and fiscal authorities, as well as broader societal changes such as a better integration of sustainability into financial and economic decision-making.
‘In this situation, what you started getting was probabilities that disguised uncertainty as opposed to actually providing you with more useful information.’
Barack Obama commenting on making the decision whether to attack a target which evidence suggested could be Osama Bin Laden
This quote is a drawn from an article that John Kay published on his website under the title “The point of probabilities”. The point he is making is
Similar to one touched on in a Bank Underground post that I discussed in a recent post on my blog.
Bank Underground is a blog for Bank of England staff to share views that challenge – or support – prevailing policy orthodoxies. The views expressed are those of the authors, and are not necessarily those of the Bank of England, or its policy committees. Posting on this blog, Adam Brinley Codd and Andrew Gimber argue that false confidence in people’s ability to calculate probabilities of rare events might end up worsening the crises regulators are trying to prevent.
The post concludes with their personal observations about how best to deal with this meta-uncertainty.
Policymakers couldavoid talking about probabilities altogether. Instead of a 1-in-X event, the Bank of England’s Annual Cyclical Scenario is described as a “coherent ‘tail risk’ scenario”.
Policymakers could avoid some of the cognitive biases that afflict people’s thinking about low-probability events, byrephrasing low-probability events in terms of less extreme numbers. A“100-year” floodhas a 1% chance of happening in any given year, but anyone who lives into their 70s is more likely than not to see one in their lifetime.
Policymakers could be vocal about the fact that there are worse outcomes beyond the 1-in-X point of the distribution.
I have been wanting to put something down on the question of Australian major bank ROE for a while. The issue generates a lot of heat but the public discussion I have observed has been truncated, in my opinion, by misconceptions.
I think we can agree that banks need to be profitable to be healthy and a healthy banking system underpins the health of the economy as a whole. Excessive profitability however is clearly bad for consumers, business and for the economy as a whole. The problem is determining what level of profitability is excessive. This post is unlikely to be the final word on this topic but hopefully it introduces a couple of considerations that seem to me to be largely missing from the public debate.
Most of what I read on this topic seems to treat the ROE of the Australian majors as self evidently excessive and focuses on what to do about it. Exhibit A is the reported ROE which in the 2019 half year updates varied from 10.05% to 14.10%. This is much less than it was but still substantially better than what is being achieved by most banks outside Australia and by the smaller local banks. Exhibit B is the fact that the Australian banking system is an oligopoly which almost by definition earn excess profits.
Reported ROE exceeds COE – case closed
Any discussion of ROE must be anchored by the estimated Cost of Equity (COE), the minimum return that investors require to hold equity risk. There are a variety of ways of calculating this but all of them generate a number that is much less than the ROE the majors currently earn. So case closed.
There is no question that the Australian majors cover their cost of equity, but it is less clear to me that the margin of excess profitability is as excessive as claimed.
Corporate finance 101 teaches us that we can derive a company’s cost of equity using the Capital Asset Pricing Model (CAPM) which holds that the required return is equal to the Risk Free Return plus the Equity Risk Premium (ERP) multiplied by the extent to which the return the individual stock is correlated with the market as a whole. The general idea of being paid a premium for taking on equity risk makes sense but there are a bunch of issues with the CAPM once you get into the detail. One of the more topical being what do you do when the risk free rate approaches zero.
I don’t want to get into the detail of those issues here but will assume for the purposes of this post that a rate of return in the order of 8-10% can be defended as a minimum acceptable return. I recognise that some of the more mechanical applications of the CAPM might generate a figure lower than this if they simply apply a fixed ERP to the current risk free rate.
Two reasons why a simple comparison of ROE and COE may be misleading
Banking is an inherently cyclical business and long term investors require a return that compensates them for accepting this volatility in returns.
Book value does not define market value
Banking is a highly cyclical business – who knew?
It is often asserted that banking is a low risk, “utility” style business and hence that shareholders should expect commensurately low returns. The commentators making these assertions tend to focus on the fact that the GFC demonstrated that it is difficult (arguably impossible) to allow large banks to fail without imposing significant collateral damage on the rest of the economy. Banks receive public sector support to varying degrees that reduces their risk of failure and hence the risk to shareholders. A variation of this argument is that higher bank capital requirements post the GFC have reduced the risk of investing in a bank by reducing the risk of insolvency.
There is no question that banks do occupy a privileged space in the economy due to the central bank liquidity support that is not available to other companies. This privilege (sometimes referred to as a “social licence”) is I think an argument for tempering the kinds of ROE targeted by the banks but it does not necessarily make them a true utility style investment whose earnings are largely unaffected by cyclical downturns.
The reality is that bank ROE will vary materially depending on the state of the credit cycle and this inherent cyclicality is probably accentuated by accounting for loan losses and prudential capital requirements. Loan losses for Australian banks are currently (October 2019) close to their cyclical low points and can be expected to increase markedly when the economy eventually moves into a downturn or outright recession. Exactly how much downside in ROE we can expect is open to debate but history suggests that loan losses could easily be 5 times higher than what we observe under normal economic conditions.
There is also the issue of how often this can be expected to happen. Again using history as a guide for the base rate, it seems that downturns might be expected every 7-10 years on average and long periods without a downturn seem to be associated with increased risk of more severe and prolonged periods of reduced economic activity.
What kind of risk premium does an investor require for this cyclicality? The question may be academic for shareholders who seek to trade in and out of bank stocks based on their view of the state of the cycle but I will assume that banks seek to cater to the concerns and interests of long term shareholders. The answer for these shareholders obviously depends on how frequent and how severe you expect the downturns to be, but back of the envelope calculations suggest to me that you would want ROE during the benign part of the credit cycle to be at least 200bp over the COE and maybe 300bp to compensate for the cyclical risk.
Good risk management capabilities can mitigate this inherent volatility but not eliminate it; banks are inherently cyclical investments on the front line of the business cycle. Conversely, poor risk management or an aggressive growth strategy can have a disproportionately negative impact. It follows that investors will be inclined to pay a premium to book value for banks they believe have good risk management credentials. I will explore this point further in the discussion of book value versus market value.
Book Value versus Market Value
Apart from the cyclical factors discussed above, the simple fact that ROE is higher than COE is frequently cited as “proof” that ROE is excessive. It is important however to examine the unstated assumption that the market value of a bank should be determined by the book value of its equity. To the best of my knowledge, there is no empirical or conceptual basis for this assumption. There are a number of reasons why a company’s share price might trade at a premium or a discount to its book value as prescribed by the relevant accounting standards.
The market may be ascribing value to assets that are not recognised by the accounting standards.The money spent on financial control and risk management, for example, is largely expensed and hence not reflected in the book value of equity. That value however becomes apparent when the bank is under stress. These “investments” cannot eliminate the inherent cyclicality discussed above but they do mitigate those risk.
A culture built on sound risk management and financial control capabilities is difficult to value and won’t be reflected in book value except to the extent it results in conservative valuation and provisioning outcomes. It is however worth something. Investors will pay a premium for the banks they believe have these intangible strengths while discounting or avoiding altogether the shares of banks they believe do not.
Summing up …
This post is in no way an exhaustive treatment of the topic. Its more modest objective was simply to offer a couple of issues to consider before jumping to the conclusion that the ROE earned by the large Australian banks is excessive based on simplistic comparisons of point in time ROE versus mechanical derivations of the theoretical COE.
As always, it is entirely possible that I am missing something – if so let me know what it is ….
We probably tend to take the monetary and financial system we have today for granted, somewhat like the air we breathe. I was also challenged during the week to describe a non-money future and my response was judged a failure to look outside the square. The best I could offer was to note that Star Trek imagines a society in which unlimited cheap energy coupled with replicators has made money redundant.
By chance, I came across a couple of articles in recent weeks that offer interesting perspectives on what money is and its role in the economy.
The Bretton Woods agreement of course is not the system we have today but Cowen makes the point that the system we operate under today would appear equally unlikely to previous generations:
“Currencies are fiat, the ties to gold are gone, and most exchange rates for the major currencies are freely floating, with periodic central bank intervention to manipulate exchange rates. For all the criticism it receives, this arrangement has also proved to be a viable global monetary order, and it has been accompanied by an excellent overall record for global growth.
Yet this fiat monetary order might also have seemed, to previous generations of economists, unlikely to succeed. Fiat currencies were associated with the assignat hyperinflations of the French Revolution, the floating exchange rates and competitive devaluations of the 1920s were not a success, and it was hardly obvious that most of the world’s major central banks would pursue inflation targets of below 2%. Until recent times, the record of floating fiat currencies was mostly disastrous”
Cowen’s main message is that the lesson of history suggests that it is brave to assume that the monetary and financial institution status quo will hold forever – so what comes next?
This brings us to Stefan Heidenreich.
“Stefan Heidenreich believes that some day, money will seem like an ancient religion. In his recent book Money: For a Non-money Economy, the German philosopher and media theorist speculates on how the money-based global economy could soon transition to an entirely different system based on the algorithmic matching of goods and services. Such a system could match people with what they need at a given moment without relying on the concept of a stable, universal price — and, just possibly, do away with the vast inequities caused by the market.
If you find the idea of an economy without money hard to imagine, you’re not alone. As the saying goes, it’s easier to imagine the end of the world than the end of capitalism. But that very difficulty proves Heidenreich’s main point: We have to imagine what may sound like wild possibilities now in order to steer the future before it’s upon us. Getting rid of money could lead to what he calls a “leftist utopia” of equal distribution — or it could enable mass surveillance and algorithmic control on a whole new scale. Faced with the second option, Heidenreich says, we have no choice but to try to envision the first.”
It is not obvious to me that Heidenreich’s “matching” proposal provides a workable alternative to what we have today but that is not the point. The bigger point raised by both Cowen and Heidenreich is that what we have today is unlikely to be the system that governs our economic interactions in 50 years time so what is the alternative?
This article in Bloomberg caught my attention. It is a background piece on a team known as the “Applied Critical Thinking” unit that has been operating inside the New York Federal Reserve since 2016.
The general idea of contrarian thinking and recognising the limitations of what is and is not knowable are not huge innovations in themselves. What was interesting for me is the extent to which this unit can be thought of as a way of building that thought process into the structure of organisations that might otherwise tend towards consensus and groupthink built on simple certainties.
I don’t have all the answers but this initiative by the NY Fed is I think worth watching. Something like this seem to me to have the potential to help address some of the culture problems that have undermined trust in large companies (it is not just the banks) and the financial system as a whole.
From the outside 