Restructuring Basel’s capital buffers

Douglas Elliott at Oliver Wyman has written a short post which I think makes a useful contribution to the question of whether the capital buffers in the BCBS framework are serving their intended purpose.

The short version is that he argues the Countercyclical Capital Buffer (CCyB) has worked well while the Capital Conservation Buffer (CCB) has not. The solution he proposes is that the “the Basel Committee should seriously consider shrinking the CCB and transferring the difference into a target level of the CCyB in normal times”. Exactly how much is up for debate but he uses an example where the base rate for the CCyB is 1.0% and the CCB is reduced by the same amount to maintain the status quo.

The idea of having a non-zero CCyB as the default setting is not new. The Bank of England released a policy statement in April 2016 that had a non zero CCyB at its centre (I wrote about that approach in this post from April 2018). What distinguishes Elliott’s proposal is that he argues that the increased CCyB should be seeded by a transfer from the CCB. While I agree with many of his criticisms of the CCB (mostly that it is simply not usable in practice), my own view is that a sizeable CCB offers a margin of safety that offers a useful second line of defence against the risk that a bank breaches its minimum capital requirement. My perspective is heavily influenced by a concern that both bankers and supervisors are prone to underestimate the extent to which they face an uncertain world.

For anyone interested, this post sets out my views on how the cyclical capital buffer framework should be constructed and calibrated. This issue is especially relevant for Australian banks because APRA has an unresolved discussion paper which includes a proposal to increase the size of the capital buffers the Australian banks are expected to maintain. I covered that discussion paper here. A speech that APRA Chair Wayne Byres gave in May 2020 covering some of the things APRA had learned from dealing with the economic fallout of COVID-19 is also worth checking out (covered in this post).

Tony – From the Outside

What does the “economic perspective” add to an ICAAP?

… the question I reflected on as I read the ECB Report on Banks’ ICAAP Practices (August 2020).

That I should be asking the question is even more curious given the years I spent working with economic capital but there was something in the ECB position that I was not comfortable with. There is nothing particularly wrong in the ways that the ECB envisages that an economic perspective can add value to a bank’s ICAAP. The problem (for me), I came to realise, is more the lack of emphasis on recognising the fundamental limitations of economic models. In short, my concern is that the detailed focus on risk potentially comes at the expense of an equally useful consideration of the ways in which a bank is subject to radical uncertainty.

The rest of this post offers an overview of what the ECB survey observed and some thoughts on the value of explicitly incorporating radical uncertainty into an ICAAP.

The ECB report sample set

The ECB report, based on a survey of 37 significant institutions it supervises, assesses the extent to which these organisations were complying (as at April 2019) with ECB expectations for how the ICAAP should be constructed and executed. The selected sample focuses on the larger (and presumably more sophisticated) banks, including all global systematically important banks supervised by the ECB. I am straying outside my area of expertise (Australian bank capital management) in this post but there is always something to learn from considering another perspective.

The ECB assessment on ICAAP practices

The ECB notes that progress has been made in some areas of the ICAAP. In particular; all banks in the survey have risk identification processes in place, they produce summary documents (“Capital Adequacy Statements” in ECB parlance) that enable bank management (not just the technical specialists) to engage with and take responsibility for the capital strength of their bank and the sample banks do incorporate stress testing into their capital planning process.

The ECB believes however that there is still a lot of room for improvement. The general area of concern is that the banks it supervises are still not paying sufficient attention to the question of business continuity. The ECB cites three key areas as being particularly in need of improvement if the ICAAPs are to play their assigned role in effectively contributing to a bank’s continuity:

  1. Data quality
  2. The application of the “Economic Perspective” in the ICAAP
  3. Stress testing

The value of building the ICAAP on sound data and testing the outcomes of the process under a variety of severe stress scenarios is I think uncontentious.

The value the economic perspective contributes is less black and white. Like many thing in life, the challenge is to get the balance right. My perspective is that economic models are quite useful but they are far from a complete answer and dangerous when they create an illusion of knowledge, certainty and control.

The economic internal perspective

The ECB’s guide to the ICAAP defines the term “economic internal perspective” as follows:

“Under this perspective, the institution’s assessment is expected to cover the full universe of risks that may have a material impact on its capital position from an economic perspective. In order to capture the undisguised economic situation, this perspective is not based on accounting or regulatory provisions. Rather, it should take into account economic value considerations for all economically relevant aspects, including assets, liabilities and risks. …. The institution is expected to manage economic risks and assess them as part of its stress-testing framework and its monitoring and management of capital adequacy”

ECB Guide to the internal capital adequacy assessment process (ICAAP) – Principles, November 2018 (Paragraph 49 / pages 18-19)

So far so good – the key points seem (to me) to be quite fair as statements of principle.

The ECB sees value in looking beyond the accounting and regulatory measures that drive the reported capital ratios (the “normative perspective” in ECB terminology) and wants banks to consider “the full universe of risks that may have a material impact on its capital position”. The ECB Report also emphasises the importance of thinking about capital from a “business continuity” perspective and cites the “… unjustified inclusions of certain capital components (e.g. minority interests, Additional Tier 1 … or Tier 2 … instruments) … which can inflate the internal capital figures” as evidence of banks failing to meet this expectation. Again a fair point in my view.

These are all worthy objectives but I wonder

  • firstly about the capacity of economic capital models to reliably deliver the kinds of insights the ECB expects and
  • secondly whether there are more cost effective ways to achieve similar outcomes.

The value of a different perspective

As a statement of principle, the value of bringing a different perspective to bear clearly has value. The examples that the ECB cites for ways in which the economic perspective can inform and enhance the normative perspective are all perfectly valid and potentially useful. My concern is that the ECB seems to be pursuing an ideal state in which an ICAAP can, with sufficient commitment and resources, achieve a degree of knowledge that enables a bank to control its future.

Business continuity is ultimately founded on a recognition that there are limits to what we can know about the future and I side with the risk philosophy that no amount of analysis will fundamentally change this.

The ECB’s economic perspective does not neccesarily capture radical uncertainty

I have touched on the general topic of uncertainty and what it means for the ICAAP a couple of times in this blog. The ECB report mentions “uncertainty” twice; once in the context of assessing climate change risk

Given the uncertainty surrounding the timing of climate change and its negative consequences, as well as the potentially far-reaching impact in breadth and magnitude along several transmission channels via which climate-related risks may impact banks’ capital adequacy, it is rather concerning that almost one-third of the banks has not even considered these risks in their risk identification processes at all.

Page 39

… and then in the context of making allowances for data quality

However, … in an internal deep dive on risk quantification in 2019, half of the risk quantifications showed material deficiencies. This finding is exacerbated by the data quality issues generally observed and moreover by the fact that one-half of the banks does not systematically ensure that the uncertainty surrounding the accuracy of risk quantifications (model risk) is appropriately addressed by an increased level of conservatism. 

Page 54

This is not a question of whether we should expect that banks can demonstrate that they are thinking about climate change and making allowances for model risk along with a host of other plausible sources of adverse outcomes. It is a surprise that any relatively large and sophisticated banks might be found wanting in the ways in which these risks are being assessed and the ECB is right to call the out.

However, it is equally surprising (for me at least) that the ECB did not seem to see value in systematically exploring the extent to which the ICAAPs of the banks it supervises deal with the potential for radical uncertainty.

Business continuity is far more likely if banks can also demonstrate that they recognise the limits of what they can know about the future and actively plan to deal with being surprised by the unexpected. In short one of the key ICAAP practices I would be looking for is evidence that banks have explicitly made allowances for the potential for their capital plan to have to navigate and absorb “unknown unknowns”.

For what it is worth, my template for how a bank might make explicit allowances in the ICAAP for unknown unknowns is included in this post on the construction of calibration of cyclical capital buffers. My posts on the broader issue of risk versus uncertainty can be found on the following links:

Feel free to let me know what I am missing …

Tony – From the Outside

Constructive dissent

I am currently reading “Thinking in Bets” by Annie Duke. It is early days but I suspect that this is a book that has some useful things to say about creating the kinds of corporate culture that truely reflect the values espoused in corporate mission statements. It is a truth that actions speak louder than words and she cites a practice employed by the American Foreign Service Association which has not one but four awards for employees who have exhibited behaviours that demonstrate initiative, integrity, intellectual courage and constructive dissent.

The attached quote comes from the AFSA website setting out the criteria employed for these awards

Criteria for the Dissent Awards

The awards are for Foreign Service employees who have “exhibited extraordinary accomplishment involving initiative, integrity, intellectual courage and constructive dissent”. The awards publicly recognize individuals who have demonstrated the intellectual courage to challenge the system from within, to question the status quo and take a stand, no matter the sensitivity of the issue or the consequences of their actions. The issue does not have to be related to foreign policy. It can involve a management issue, consular policy, or, in the case of the recently established F. Allen “Tex” Harris Award, the willingness of a Foreign Service Specialist to take an unpopular stand, to go out on a limb, or to stick his/her neck out in a way that involves some risk

https://www.afsa.org/constructive-dissent-awards

Climate change – a central banking perspective

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

  1. 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”.
  2. 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.
  3. 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.
  4. 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:

  1. 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.
  2. 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
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” .

Thomas Friedman’s article (“How we broke the world”) is also worth reading on this question …

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
Managing collective 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.

Page 48

When safety proves dangerous …

… is the title of a post on the Farnham Street blog that provides a useful reminder of the problem of “risk compensation”; i.e. the way in which measures designed to make us safer can be a perverse prompt for us to take more risk because we feel safer. I want to explore how these ideas apply to bank capital requirements but will first outline the basic ideas covered by Farnham Street.

we all internally have a desired level of risk that varies depending on who we are and the context we are in. Our risk tolerance is like a thermostat—we take more risks if we feel too safe, and vice versa, in order to remain at our desired “temperature.” It all comes down to the costs and benefits we expect from taking on more or less risk.

The notion of risk homeostasis, although controversial, can help explain risk compensation.

The classic example is car safety measures such as improved tyres, ABS braking systems, seat belts and crumple zones designed to protect the driver and passengers. These have helped reduce car fatality rates for the people inside the car but not necessarily reduced accident rates given that drivers tend to drive faster and more aggressively because they can. Pedestrians are also at greater risk.

Farnham Street suggests the following lessons for dealing with the problem risk compensation:

  1. Safety measures are likely to be more effective is they are less visible
  2. Measures designed to promote prudent behaviour are likely to be more effective than measures which make risky behaviour safer
  3. Recognise that sometimes it is better to do nothing if the actions we take just leads to an offset in risk behaviour somewhere else
  4. If we do make changes then recognise that we may have to put in place other rules to ensure the offsetting risk compensating behaviour is controlled
  5. Finally (and a variation on #3), recognise that making people feel less safe can actually lead to safer behaviour.

If you are interested in this topic then I can also recommend Greg Ip’s book “Foolproof” which offers a good overview of the problem of risk compensation.

Applying these principles to bank capital requirements

The one area where I would take issue with the Farnham Street post is where it argues that bailouts and other protective mechanisms contributed to scale of the 2008 financial crisis because they led banks to take greater risks. There is no question that the scale of the crisis was amplified by the risks that banks took but it is less obvious to me that the bailouts created this problem.

The bailouts were a response to the problem that banks were too big to fail but I can’t see how they created this problem; especially given that the build up of risk preceded the bailouts. Bailouts were a response to the fact that the conventional bankruptcy and restructure process employed to deal with the failure of non-financial firms simply did not work for financial firms.

It is often asserted that bankers took risks because they expected that they would be bailed out; i.e/ that banks deliberately and consciously took risk on the basis that they would be bailed out. I can’t speak for banks as a whole but I have never witnessed that belief in the four decades that I worked in the Australian banking system. Never attribute to malice what can be equally explained by mistaken beliefs. I did see bankers placing excessive faith in the economic capital models that told them they could safely operate with reduced levels of capital. That illusion of knowledge and control is however a different problem altogether, largely to do with not properly understanding the distinction between risk and uncertainty (see here and here).

If I am right, that would suggest that making banks hold more capital might initially make them safer but might also lead to banks looking for ways to take more risk. This is a key reason why I think the answer to safer banks is not just making them hold higher and higher levels of common equity. More common equity is definitely a big part of the answer but one of the real innovations of Basel 3 was the development of new forms of loss absorbing capital that allow banks to be recapitalised by bail-in rather than bail-out.

If you want to go down the common equity is the only solution path then it will be important to ensure that Farnham Street Rule #4 above is respected; i.e. bank supervisors will need to ensure that banks do not simply end up taking risks in places that regulation or supervision does not cover. This is not a set and forget strategy based on the idea that increased “skin in the game” will automatically lead to better risk management.

Based on my experience, the risk of common equity ownership being diluted by the conversion of this “bail-in” capital is a far more effective constraint on risk taking than simply requiring banks to hold very large amounts of common equity. I think the Australian banking system has this balance about right. The Common Equity Tier 1 requirement is calibrated to a level intended to make banks “Unquestionably Strong”. Stress testing suggest that this level of capital is likely to be more than sufficient for well managed banks operating with sensible risk appetites but banks (the larger ones in particular) are also required to maintain a supplementary pool of capital that can be converted to common equity should it be required. The risk that this might be converted into a new pool of dilutive equity is a powerful incentive to not push the boundaries of risk appetite.

Tony – From the Outside

Navigating a radically uncertain world

The distinction between risk and uncertainty is a long running area of interest for me so I have enjoyed reading John Kay and Mervyn King’s book “Radical Uncertainty: Decision-Making for an Unknowable Future”. My initial post on the book offered an overview of the content and a subsequent post explored Kay and King’s analysis of why the world is prone to radical uncertainty.

This post looks at how Kay and King propose that we navigate a world that is prone to radical uncertainty. Kay and King start (Ch 8) with the question of what it means to make rational choices.

No surprises that the answer from their perspective is not the pursuit of maximum expected value based on a priori assumptions of what is rational in a world ruled by probability (“axiomatic reasoning”). They concede that there are some problems that can be solved this way. Games of chance where you get repeated opportunities to play the odds is one, but Kay and King are firmly in the camp that the real world is, for the most part, too complex and unknowable to rely on this approach for the big issues.

It is not just that these models do not offer any useful insight into these bigger world choices. They argue, convincingly I think, that these types of precise quantitative models can also tend to create an illusion of knowledge and control that can render the systems we are seeking to understand and manage even more fragile and more prone to uncertainty. An obvious example of this risk is the way in which the advanced measures of bank capital requirements introduced under Basel II tended to encourage banks to take (and bank supervisors to approve) more leverage.

Their argument broadly makes sense to me but there was nothing particularly new or noteworthy in this part of the book. It goes over familiar ground covered equally well by other writers – see for example these posts Epsilon Theory, Bank Underground, Paul Wilmott and David Orrell, Andrew Haldane which discuss contributions these authors have made to the debate.

However, there were two things I found especially interesting in their analysis.

  • One was the argument that the “biases” catalogued by behavioural finance were not necessarily irrational when applied to a radically uncertain world.
  • The other was the emphasis they place on the idea of employing abductive reasoning and reference narratives to help navigate this radically uncertain future.

Behavioural Finance

Kay and King argue that some of the behaviours that behavioural finance deems to be irrational or biased might be better interpreted as sensible rules of thumbs that people have developed to deal with an uncertain world. They are particularly critical of the way behavioural finance is used to justify “nudging” people to what behavioural finance deems to be rational.

Behavioural economics has contributed to our understanding of decision-making in business, finance and government by introducing observation of how people actually behave. But, like the proselytisers for the universal application of probabilistic reasoning, practitioners and admirers of behavioural economics have made claims far more extensive than could be justified by their findings…

…. a philosophy of nudging carries the risk that nudgers claim to know more about an uncertain world than they and their nudgees do or could know.

I struggled with this part of the book because I have generally found behavioural finance insights quite useful for understanding what is going on. The book reads at times like behavioural finance as a whole was a wrong turn but I think the quote above clarifies that they do see value in it provided the proponents don’t push the arguments too far. In particular they are arguing that rules of thumb that have been tested and developed over time deserve greater respect.

Abductive Reasoning and Reference Narratives

The part of Kay and King’s book I found most interesting was their argument that “abductive reasoning” and “reference narratives” are a useful way of mapping our understanding of what is going on and helping us make the right choices to navigate a world prone to enter the domain of radical uncertainty.

If we go back to first principles it could be argued that the test of rationality is that the decisions we make are based on reasonable beliefs about the world and internal consistency. The problem, Kay and King argue, is that this approach still does not address the fundamental question of whether we can ever really understand a radically uncertain world. The truely rational approach to decision making has to be resilient to the fact that our future is shaped by external events taking paths that we have no way of predicting.

The rational answer for Kay and King lies in an “abductive” approach to reasoning. I must confess that I had to look this up (and my spell checker still struggles with it) but it turns out that this is a style of reasoning that works with the available (not to mention often incomplete and ambiguous) information to form educated guesses that seek to explain what we are seeing.

Abduction is similar to induction in that it starts with observations. Where it differs is what the abductive process does with the evidence. Induction seeks to derive general or universal principles from the evidence. Abduction in contrast is context specific. It looks at the evidence and tries to fit “an explanation” of what is going on while being careful to avoid treating it as “the explanation” of what is going on.

Deductive, inductive and abductive reasoning each have a role to play in understanding the world, and as we move to larger worlds the role of the inductive and abductive increases relative to the deductive. And when events are essentially one-of-a-kind, which is often the case in the world of radical uncertainty, abductive reasoning is indispensable.

Reference Narratives

If I have understood their argument correctly, the explanations or hypotheses generated by this abductive style of reasoning are expressed in “reference narratives” which we use to explain to ourselves and others what we are observing. These high level reference narratives can then provide a basis for longer term planning and a framework for day-to-day choices.

Deductive, inductive and abductive reasoning each have a role to play in understanding the world, and as we move to larger worlds the role of the inductive and abductive increases relative to the deductive. And when events are essentially one-of-a-kind, which is often the case in the world of radical uncertainty, abductive reasoning is indispensable.

Kay and King acknowledge that this approach is far from foolproof and devote a considerable part of their book to what distinguishes good narratives from bad and how to avoid the narrative being corrupted by groupthink.

Good and Bad Reference Narratives

Kay and King argue that credibility is a core feature distinguishing good and bad narratives. A good narrative offers a coherent and internally consistent explanation but it also needs to avoid over-reach. A warning sign for a bad narrative is one that seeks to explain everything. This is especially important given that our species seems to be irresistibly drawn to grand narratives – the simpler the better.

Our need for narratives is so strong that many people experience a need for an overarching narrative–some unifying explanatory theme or group of related themes with very general applicability. These grand narratives may help them believe that complexity can be managed, that there exists some story which describes ‘the world as it really is’. Every new experience or piece of information can be interpreted in the light of that overarching narrative.

Kay and King use the fox and the hedgehog analogy to illustrate their arguement that we should always be sceptical of the capacity of any one narrative to explain everything,

…. The hedgehog knows one big thing, the fox many little things. The hedgehog subscribes to some overarching narrative; the fox is sceptical about the power of any overarching narrative. The hedgehog approaches most uncertainties with strong priors; the fox attempts to assemble evidence before forming a view of ‘what is going on here’.

Using Reference Narratives

Kay and King cite the use of scenario based planing as an example of using a reference narrative to explore exposure to radical uncertainty and build resilience but they caution against trying too hard to assign probabilities to scenarios. This I think is a point well made and something that I have covered in other posts (see here and here).

Scenarios are useful ways of beginning to come to terms with an uncertain future. But to ascribe a probability to any particular scenario is misconceived…..

Scenario planning is a way of ordering thoughts about the future, not of predicting it.

The purpose is … to provide a comprehensive framework for setting out the issues with which any business must deal: identifying markets, meeting competition, hiring people, premises and equipment. Even though the business plan is mostly numbers–many people will describe the spreadsheet as a model–it is best thought of as a narrative. The exercise of preparing the plan forces the author to translate a vision into words and numbers in order to tell a coherent and credible story.

Kay and King argue that reference narratives are a way of bringing structure and conviction to the judgment, instinct and emotion that people bring to making decisions about an uncertain future

We make decisions using judgement, instinct and emotions. And when we explain the decisions we have made, either to ourselves or to others, our explanation usually takes narrative form. As David Tuckett, a social scientist and psychoanalyst, has argued, decisions require us ‘to feel sufficiently convinced about the anticipated outcomes to act’. Narratives are the mechanism by which conviction is developed. Narratives underpin our sense of identity, and enable us to recreate decisions of the past and imagine decisions we will face in the future.

Given the importance they assign to narratives, Kay and King similarly emphasise the importance of having a good process for challenging the narrative and avoiding groupthink.

‘Gentlemen, I take it we are all in complete agreement on the decision here. Then, I propose we postpone further discussion of this matter until the next meeting to give ourselves time to develop disagreement, and perhaps gain some understanding of what the decision is all about.’

Alfred P. Sloan (Long time president chairman and CEO of General Motors Corporation) quoted in the introduction to Ch 16: Challenging Narratives

These extracts from their book nicely captures the essence of their argument

Knowledge does not advance through a mechanical process of revising the probabilities people attach to a known list of possible future outcomes as they watch for the twitches on the Bayesian dial. Instead, current conventional wisdom is embodied in a collective narrative which changes in response to debate and challenge. Mostly, the narrative changes incrementally, as the prevalent account of ‘what is going on here’ becomes more complete. Sometimes, the narrative changes discontinuously – the process of paradigm shift described by the American philosopher of science Thomas Kuhn.

the mark of the first-rate decision-maker confronted by radical uncertainty is to organise action around a reference narrative while still being open to both the possibility that this narrative is false and that alternative narratives might be relevant. This is a very different style of reasoning from Bayesian updating.

Kay and King argue that the aim in challenging the reference narrative is not simply to find the best possible explanation of what is going on. That in a sense is an almost impossible task given the premise that the world is inherently unpredictable. The objective is to find a narrative that seems to offer a useful guide to what is going on but not hold too tightly to it. The challenge process also tests the weaknesses of plans of action based on the reference narrative and, in doing so, progressively secures greater robustness and resilience.


The quote below repeats a point covered above but it does nicely capture their argument that the pursuit of quantitative precision can be a distraction from the broader objective of having a robust and resilient process. By all means be as rigorous and precise as possible but recognise the risk that the probabilities you assign to scenarios and “risks” may end up simply serving to disguise inherent uncertainties that cannot be managed by measurement.

The attempt to construct probabilities is a distraction from the more useful task of trying to produce a robust and resilient defence capability to deal with many contingencies, few of which can be described in any but the sketchiest of detail.

robustness and resilience, not the assignment of arbitrary probabilities to a more or less infinite list of possible contingencies, are the key characteristics of a considered military response to radical uncertainty. And we believe the same is true of strategy formulation in business and finance, for companies and households.

Summing Up

Overall a thought provoking book. I am not yet sure that I am ready to embrace all of their proposed solutions. In particular, I am not entirely comfortable with the criticisms they make of risk maps, bayesian decision models and behavioural finance. That said, I do think they are starting with the right questions and the reference narrative approach is something that I plan to explore in more depth.

I had not thought of it this way previously but the objective of being “Unquestionably Strong” that was recommended by the 2014 Australian Financial System Inquiry and subsequently fleshed out by APRA can be interpreted as an example of a reference narrative that has guided the capital management strategies of the Australian banks.

Tony – From The Outside

Why we fail to prepare for disasters

Tim Harford (The Undercover Economist) offers a short and readable account here of some of the reasons why, faced with clear risks, we still fail to act. We can see the problem, typically one of many, but don’t do enough to manage or mitigate the risk. New Orleans’ experiences with severe weather events features prominently as does (not surprisingly) COVID 19.

This, then, is why you and I did not see this coming: we couldn’t grasp the scale of the threat; we took complacent cues from each other, rather than digesting the logic of the reports from China and Italy; we retained a sunny optimism that no matter how bad things got, we personally would escape harm; we could not grasp what an exponentially growing epidemic really means; and our wishful thinking pushed us to look for reasons to ignore the danger.

Why we fail to prepare for disasters; Tim Harford (The Undercover Economist)

Another big part of the problem is that the cost of being fully prepared can be more than we are willing to pay. Especially when there is continuous pressure to find cost economies in the here and now

Serious scenarios are useful, but … no use if they are not taken seriously. That means spending money on research that may never pay off, or on emergency capacity that may never be used. It is not easy to justify such investments with the day-to-day logic of efficiency.

So the key points I took from his post:

  • Sometimes it can be something genuinely new and unexpected (i.e. Black Swan events) but risks we are well aware of can be equally damaging
  • Part of the problem is that we are social animals and take our cues from what the rest of the herd is doing (“normalcy bias” or “negative panic”)
  • Even where we understand the statistics and know that someone will be impacted, we tend to assume it will be someone else or someone else’s family (“optimism bias”)
  • We are especially bad at understanding risks that have an exponential driver (“exponential myopia”)
  • We are also quite good at finding reasons to justify ignoring risks we want to ignore or otherwise find inconvenient (“wishful thinking”)
  • Last, but far from least, efficiency is the enemy of resilience.

We need to remember that most of the factors listed above can also be useful in many other contexts (arguably most of the time). A tendency not to panic can be pretty useful and optimism has helped dreamers and ordinary people achieve many great things that have benefited the herd. Efficiency as a rule seems like a good thing to strive for.

Harford does not offer any easy answers but his post touches on issues that I have also been considering in Kay and King’s book titled “Radical Uncertainty: Decision-Making for an Unknowable Future”. I have done a couple of posts on that book already (here and here) and am working on a final one that focuses on Chapters 8-16 which set out their ideas for how we navigate a world prone to radical uncertainty.

Tony – From the Outside

The why of Radical Uncertainty

A recent post offered an overview of a book by John Kay and Mervyn King titled “Radical Uncertainty: Decision-Making for an Unknowable Future”. It is a rich topic and this post covers the underlying drivers that tend to result in radically uncertain outcomes.

Kay and King nominate “reflexivity” as a key driver of radical uncertainty

The sociologist Robert K. Merton identified reflexivity as a distinctive property of social systems–the system itself is influenced by our beliefs about it. The idea of reflexivity was developed by the Austrian émigré philosopher Karl Popper and became central to the thinking of Popper’s student, the highly successful hedge fund manager George Soros. And it would form part of the approach to macroeconomics of the Chicago economist Robert Lucas and his followers … although their perspective on the problem and its solution would be very different.

Reflexivity undermines stationarity. This was the essence of ‘Goodhart’s Law’–any business or government policy which assumed stationarity of social and economic relationships was likely to fail because its implementation would alter the behaviour of those affected and therefore destroy that stationarity.

Kay and King, Chapter 3: Radical Uncertainty is Everywhere”

Radical uncertainty also features in Richard Bookstaber’s book “The End of Theory: Financial Crises, the Failure of Economics, and the Sweep of Human Interaction”. Bookstaber identifies four broad phenomena he argues are endemic to financial crises

Emergent phenomena.
“When systemwide dynamics arise unexpectedly out of the activities of individuals in a way that is not simply an aggregation of that behavior, the result is known as emergence”.

Non-ergodicity.
“An ergodic process … is one that does not vary with time or experience.
Our world is not ergodic—yet economists treat it as though it is.”

Radical uncertainty.
“Emergent phenomena and non-ergodic processes combine to create outcomes that do not fit inside defined probability distributions.”

Computational irreducibility.
“There is no formula that allows us to fast-forward to find out what the result will be. The world cannot be solved; it has to be lived.

Bookstaber, Chapter 2: Being Human

If you want to delve into the detail of why the world can be radically uncertain then Bookstaber arguably offers the more detailed account; albeit one couched in technical language like emergent phenomena, ergodicity and computational irreducibility. In Chapter 10 he lays out the ways in which an agent based modelling approach to the problem of radical uncertainty would need to specify the complexity of the system in a structured way that takes account of the amount of information required to describe the system and the connectedness of its components. Bookstaber also offers examples of emergent phenomena in seemingly simple systems (e.g. Gary Conways’s “Game of Life”) which give rise to surprisingly complex outcomes.

I am not sure if either book makes this point explicitly but I think there is also an underlying theme in which the models that provide the illusion of control over an uncertain future create an incentive to “manage” risk in ways that increases the odds of bad outcomes based on insufficient resilience. That seems to be the clear implication of Kay and King’s discussion of the limits of finance theory (Chapter 17: The World of Finance). They acknowledge the value of the intellectual rigour built on the contributions of Harry Markowitz, William Sharpe and Eugene Fama but highlight the ways in which it has failed to live up to its promiseI .

We note two very different demonstrations of that failure. One is that the models used by regulators and financial institutions, directly derived from academic research in finance, not only failed to prevent the 2007–08 crisis but actively contributed to it. Another is to look at the achievements of the most successful investors of the era – Warren Buffett, George Soros and Jim Simons. Each has built fortunes of tens of billions of dollars. They are representative of three very different styles of investing.

Kay and King, Chapter 17 The World of Finance

I plan to do one more post exploring the ways in which we navigate a world of radical uncertainty.

Tony (From the Outside)

Worth reading – “Radical Uncertainty: Decision-Making for an Unknowable Future” by John Kay and Mervyn King

I have covered some of the ideas in the book in previous posts (here and here) but have now had the chance the read the book in full and can recommend it. I have included more detailed notes on the book here but this post offers a short introduction to some of the key ideas.

Kay and King cover a lot of ground but, simply put, their book is about

“… how real people make choices in a radically uncertain world, in which probabilities cannot meaningfully be attached to alternative futures.” 

One of the things that makes the book interesting is that they were once true believers in decision making models based on rational economic agents seeking to maximise or optimise expected value.

As students and academics we pursued the traditional approach of trying to understand economic behaviour through the assumption that households, businesses, and indeed governments take actions in order to optimise outcomes. We learnt to approach economic problems by asking what rational individuals were maximising. Businesses were maximising shareholder value, policy-makers were trying to maximise social welfare, and households were maximising their happiness or ‘utility’. And if businesses were not maximising shareholder value, we inferred that they must be maximising something else – their growth, or the remuneration of their senior executives.

The limits on their ability to optimise were represented by constraints: the relationship between inputs and outputs in the case of businesses, the feasibility of different policies in the case of governments, and budget constraints in the case of households. This ‘optimising’ description of behaviour was well suited to the growing use of mathematical techniques in the social sciences. If the problems facing businesses, governments and families could be expressed in terms of well-defined models, then behaviour could be predicted by evaluating the ‘optimal’ solution to those problems.

Kay and King are not saying that these models are useless. They continue to see some value in the utility maximisation model but have come to believe that it is not the complete answer that many economists, finance academics and politicians came to believe.

Although much can be learnt by thinking in this way, our own practical experience was that none of these economic actors were trying to maximise anything at all. This was not because they were stupid, although sometimes they were, nor because they were irrational, although sometimes they were. It was because an injunction to maximise shareholder value, or social welfare, or household utility, is not a coherent guide to action.

They argue that the approach works up to a point but fails to deal with decisions that are in the domain of radical uncertainty

But we show in this book that the axiomatic approach to the definition of rationality comprehensively fails when applied to decisions made by businesses, governments or households about an uncertain future. And this failure is not because these economic actors are irrational, but because they are rational, and – mostly – do not pretend to knowledge they do not and could not have. Frequently they do not know what is going to happen and cannot successfully describe the range of things that might happen, far less know the relative likelihood of a variety of different possible events.

There are many factors that explain the current state of affairs but a key inflexion point in Kay and King’s account can be found in what they label “A Forgotten Dispute” (Chapter 5) between Frank Knight and John Maynard Keynes on one side and Frank Ramsey and Bruno de Frinetti on the other, regarding the distinction between risk and uncertainty. Knight and Keynes argued that probability is an objective concept confined to problems with a defined and knowable frequency distribution. Ramsey argued that “subjective probability” is equally valid and used the mathematics developed for the analysis of frequency based probabilities to apply these subjective probabilities.

“Economists (used to) distinguish risk, by which they meant unknowns which could be described with probabilities, from uncertainty, which could not….. over the last century economists have attempted to elide that historic distinction between risk and uncertainty, and to apply probabilities to every instance of our imperfect knowledge of the future.”

Keynes and Knight lost the debate

Ramsey and de Finetti won, and Keynes and Knight lost, that historic battle of ideas over the nature of uncertainty. The result was that the concept of radical uncertainty virtually disappeared from the mainstream of economics for more than half a century. The use of subjective probabilities, and the associated mathematics, seemed to turn the mysteries of radical uncertainty into puzzles with calculable solutions. 

Ramsey and de Finetti laid the foundations for economists to expand the application of probability based thinking and decision making. Milton Friedman picked up the baton and ran with it.

There is a lot more to the book than interesting historical anecdotes on the history of economic ideas. The subject matter is rich and it crosses over topics covered previously in this blog including:

There are also overlaps with a book by Richard Bookstaber titled “The End of Theory: Financial Crises, the Failure of Economics, and the Sweep of Human Interaction”. I am yet to review this book but have some detailed notes here.

One quibble with the book is that I think their critique of the Bayesian method is a bit harsh. I understand their concern to push back on the idea that Bayes solves the problem of using probability to understand uncertainty. At times however it reads like Bayes has no value at all. Read “The Theory that Would Not Die: How Bayes’ Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy” by Sharon Bertsch McGrayne for an alternative perspective.

Bayes may not help with mysteries but its application in puzzles should not be undervalued. I don’t entirely agree with their perspective on behavioural finance either.

I want to come back to the topics of risk and uncertainty in a future post but it will take time to process all of the overlapping pieces. In the interim, I hope you found the overview above useful.

Tony (From the Outside)

Why the real economy needs a prudential authority too

Isabella Kaminska (FT Alphaville) offers an interesting perspective on ways in which prudential initiatives in the areas of capital, liquidity and bail-in that have strengthened the banking sector post GFC might be applied to the “real economy”.

The global financial crisis taught us that laissez-faire finance, when left to its own devices, tends to encourage extreme fragility by under capitalising the system for efficiency’s sake and making it far more systemically interdependent.

Pre-2008, banks operated on the thinnest of capital layers while taking extreme liquidity risk due to the presumption that wholesale liquidity markets would always be open and available to them. It was in this way that they saved on capital and liquidity costs and increased their return on equity.  

Regulatory responses to the crisis understandably focused on boosting resilience by hiking capital buffers, liquidity ratios and also by introducing new types of loss absorbing structures. While it’s still too early to claim regulatory efforts were a definitive success, it does seem by and large the measures have worked to stymie a greater financial crisis this time around.

But what the 2008 crisis response may have overlooked is that bolstering banks to protect the economy means very little if the underlying real economy remains as thinly spread and interconnected as the financial sector always used to be.

The assessment that these banking initiatives “means very little” is possibly overstating the case.  The problems we are facing today would be an order of magnitude greater if the banking system was not able to plays its part in the solution.

The core point, however, I think is absolutely on the money, the focus on efficiency comes at the expense of resilience. More importantly, a free market system, populated by economic agents pursuing their own interests shaped by a focus on relatively short term time horizons, does not seem to be well adapted for dealing with this problem on its own. The lessons prudential regulators learned about the limits of efficient markets and market discipline also apply in the real world.

Isabella looks at the way prudential capital and liquidity requirements operate in banking and draws analogies in the real economy. With respect to liquidity, she notes for example,

“… the just-in-time supply chain system can be viewed as the real economy’s version of a fractional reserve system, with reserves substitutable for inventories.  

Meanwhile, the real economy’s presumption that additional inventories can be sourced from third party wholesale suppliers at a price as and when demand dictates, is equivalent to the banking sector’s presumption that liquidity can always be sourced from wholesale markets.

Though there is obviously one important difference.

Unlike the banking sector, the real economy has no lender of last resort that can magically conjure up more intensive care beds or toilet paper at the stroke of a keyboard when runs on such resources manifest unexpectedly.  

So what are our options? Companies could increase their inventories (analogous to holding more liquid assets) or build excess capacity (analogous to building up a capital buffer) but it is very difficult for companies acting independently to do this if their competitors choose the short term cost efficient play and undercut them on price. The Prisoner’s Dilemma trumps market discipline and playing the long game.

Isabella frames the problem as follows:

short-term supply shortages can only be responded to with real world manufacturing capability, which itself is constrained by physical availability To that extent crisis responses can only really take two forms: 1) immediate investment in the build-up of new manufacturing capacity that can address the specific system shortages or, 2) the temporary reallocation of existing resources (with some adaptation cost) to new production purposes.

The problem with the first option is that it is not necessarily time efficient. Not every country has the capability to build two new hospitals from scratch in just 10 days. Nor the capacity to create unexpected supply just-in-time to deal with the problem.

New investment may not be economically optimal either. What happens to those hospitals when the crisis abates? Do they stand empty and idle? Do they get repurposed? Who will fund their maintenance and upkeep if they go unused? And at what cost to other vital services and goods?

Isabella’s proposal …

That leaves the reallocation of existing assets as the only sensible and economically efficient mitigatory response to surge-demand related crises like pandemic flu. But it’s clear that on that front we can be smarter about how we anticipate and prepare for such reallocation shocks. An obvious thing to do is to take a leaf out of banking regulators’ books, especially with regards to bail-inable capital, capital ratios and liquidity profiles.

Isabella offers two examples to illustrate her argument; one is power companies and the other is the health system.

She notes that power utilities manage demand-surge or supply-shock risk with interruptible contracts to industrial clients. She argues that these contracts equate to a type of bail-inable capital buffer, since the contracts allow utilities to temporarily suspend services to clients (at their cost) if and when critical needs are triggered elsewhere and supplies must be diverted.

I think she has a good point about the value of real options but I am less sure that bail-in is the right analogy. Bail-in is a permanent adjustment to the capital structure in which debt is converted to equity or written off. Preferably the former in order to maintain the loss hierarchy that would otherwise apply in liquidation. A contract that enables a temporary adjustment to expenses is a valuable option but not really a bail-in style option.

What she is identifying in this power utility example is more a company buying real options from its customers that reduces operating leverage by enabling the company to reduce the supply of service when it becomes expensive to supply. Companies that have high operating leverage have high fixed costs versus revenue and will, all other things being equal, tend to need to run more conservative financial leverage than companies with low operating leverage. So reduced operating leverage is a substitute for needing to hold more capital.

Isabella then explores the ways in which the liquidity, capital and bail-in analogies might be applied in healthcare. I can quibble with some of the analogies she draws to prudential capital and liquidity requirements. As an example of a capital requirement being applied to health care she proposes that …

“… governments could mandate makers of non-perishable emergency goods (such as medicines, toilet paper, face masks, hand sanitiser) to always keep two-weeks’ worth of additional supply on hand. And companies could also be mandated to maintain some share of total supply chain production capability entirely domestically, making them more resilient to globalised shocks”

 Two weeks supply looks more like a liquidity buffer than a capital buffer but that does not make the ideas any the less worth considering as a way of making the real economy more resilient. The banking system had its crisis during the GFC and the real economy is being tested this time around. There are arguments about whether the changes to banking went far enough but it is clearly a lot better placed to play its part in this crisis than it was in the last. The question Isabella poses is what kinds of structural change will be required to make the real economy more resilient in the face of the next crisis.

Another example of FT Alphaville being a reliable source of ideas and information to help you think more deeply about the world.

Tony (From the Outside)