Regulating complexity I: Ashby, Perrow, Haldane

The word “complexity” is being used a lot lately in discussions of the financial system, particularly when it comes to regulation. The severity of the financial crisis seems to have opened a space for new ideas about the relationship between the complexity of the financial system and the complexity of regulation, with some of the most interesting proposals calling for greater simplicity in one or both of these areas.

The counterintuitive idea of simplicity as a tonic for complex problems is very attractive. It strikes me as common sense that attempting to control complex institutions with increasingly complex regulation often only makes things worse – it creates incentives for cheating, drives destructive “innovation” designed to exploit gaps, and often arms regulators to fight the last battle rather than preventing problems.

But I also think it’s worth taking a step back to think more clearly about the problem of regulating complexity from a number of perspectives before zeroing in on specific proposals in detail. Working from the purely conceptual to the purely applied, the remainder of this post looks at the problem from the perspectives of biology, social systems and banking.

Ashby and the law of requisite variety

Ross Ashby was one of the godfathers of systems theory and cybernetics, and developed a famous concept called the law of requisite variety. I haven’t read his book yet (free pdf here) but he followed it with a fairly accessible paper in 1958 that laid out the central idea.

In the paper, Ashby approaches the question of how to regulate a system from the perspective of biology and engineering, where a “regulator” can be an enzyme, an overflow valve, or anything that acts to counteract disturbances to the system. Using set theory, he defines successful regulation as a set of regulatory responses (the plural is important) that reduce the space of possible outcomes from a set of disturbances to an acceptable subset.

The key takeaway is that the success of regulation in a complex system is a function of the relationship between the set of regulators and the set of disturbances. More precisely, because no single regulatory response will be effective across all possible disturbances, the success of a set of regulations is in part a function of the match between the variety of disturbances and of responses (hence the law’s name).

Working with Roger Conant, Ashby followed this paper with another in 1970 that reached an even more dramatic conclusion, namely that (to quote the title) “every good regulator of a system must be a model of that system.” The conclusion of the paper, which must please economists to no end, is that the only way to regulate a system effectively is to build a comprehensive model of its internal dynamics.

The abstract appeal of these concepts runs aground when they confront the messy reality of real-world social systems, with two important implications for regulating finance. First, if no single regulation can be uniformly effective across a dynamic range of problems, then attempting to regulate using law becomes much more problematic. I’d imagine that this (along with lobbying for loopholes) is one of the main reasons regulation has become complicated in tandem with the growth of finance – if one rule can’t work, the natural implication is that you write more of them, and add to the set as more problems manifest. But by definition, a single set of rules will never be robust to every possible event.

Second, the need for a model implies that the designer of the set of regulators has to have deep knowledge of all aspects of the system, and to understand the non-linear dynamics of interconnected systems. But our regulatory framework for finance is set up in such a way that this is impossible. Banks alone are regulated by multiple agencies, each focusing on a different part of the business, while various types of markets have their own overseers, and none of these effectively reach beyond national borders. New meta-regulators like the Financial Stability Oversight Council in the US and the Financial Stability Board globally are attempting to get there, but it is much too early to know how well they are doing.  Worse still, even the most sophisticated model will be prone to similar problems as law – by dealing with known risks, models by definition don’t take into account risks that lie beyond the designer’s awareness or ability to simulate.

So if effective regulation requires a perfect model of the financial system that is so complicated that seemingly no one has handle on the whole thing, let alone an ex-ante understanding of all possible bad events, how should we deal with the real-world complexity of the financial system?

Perrow: eliminate complexity in the system itself

The most rational answer is to make the system less complex. A simpler financial system is will presumably be less likely to fail catastrophically, while also reducing the scale of necessary regulation.

Charles Perrow wrote nearly three decades ago that complex systems, which he identifies as those marked by tight coupling and complex interactions, are inherently vulnerable to failure by accidents.  In fact, these accidents are so predictable that he named them “normal accidents” (the title of his landmark study).

Since the financial system is a textbook case of tight coupling and complex interactions, the natural question is how best to reduce the risk of accidental system failure. Perrow’s more recent book addresses this question, though not before Perrow asserts that the financial crisis was a result of malfeasance that was abetted by the complexity of the system itself, rather than an inevitable system accident. Moreover, he points to the concentration of economic power as a key faultline to be addressed since it creates dangerous dependencies (a pernicious form of tight coupling) and creates power dynamics that work against regulation.

Perrow’s recommendations for reducing risk in complex systems are consistent with his normal accident framework. He points to the need for effective regulation as the most important factor, but he also acknowledges the difficult politics that are likely to make reform a long and difficult process. Given that, he calls instead for two related measures to reduce the vulnerability of complex systems. First, a reduction in the concentration of power is crucial in order to lessen systemic risk (an idea echoed by Hansen, as I discussed here). Replacing one-way relationships of dependency, which tie individuals and companies to more powerful organizations, with more equal and reciprocal arrangements is also necessary.

So what would a Perrow-esque (Perrovian?) financial system look like? He doesn’t say, but I’d have to think it would be consistent with the rising chorus of demands to break up the biggest banks roughly along the lines of Glass-Steagall. Doing so would reduce the complexity of individual institutions, and would also significantly reduce the concentration of economic power these organizations currently enjoy.

That’s the easy part. What is less clear is how to address the problem of interconnectedness. One of Perrow’s insights is that tight couplings eliminate slack (the extra capacity that absorbs energy) in densely connected systems, and are the primary reason that bad outcomes can propagate so quickly across them. So while an industry of smaller banks and trading firms would be good, those firms would remain embedded in trading networks. As former Chancellor of the Exchequer Alasdair Darling wrote in this week’s FT, Lehman Brothers was a standalone investment bank that nonetheless had a disastrous global impact when it failed.

While it is difficult to imagine a financial system with smaller banks in the current political environment, it is impossible to imagine it with fewer connections. By implication, structural fixes to the system itself are unlikely to go far enough to eliminate the scope for normal accidents so long as the financial system remains so tightly interconnected.

Haldane: eliminate complexity in the regulatory framework

The Bank of England’s Andrew Haldane approaches the problem from the other side, by focusing on reducing complexity in regulation rather than in the financial system it governs.

This is not to say that Haldane argues against simplifying the banks – quite the opposite. In an inversion of Perrow’s approach, Haldane notes toward the end of this typically erudite 2012 speech (summary) that restructuring of banking institutions along the clear lines of Glass-Steagall would be ideal, but that the political reality is that debate over mandating  “has reached a stalemate.”

Instead, Haldane focuses more closely on the ways in which regulation could be restructured to be simpler in order to be more robust to the unexpected and less subject to model error. He provides a number of proposals for how this might work, including using simpler metrics to reduce regulators’ reliance on banks’ own risk models (a terrible legacy of the roaring 1990s) and recalibrating the role of the regulator to include more judgment from experience rather than box-ticking. He also proposes a sort of complexity tax to be levied on institutions large enough to create “complexity externalities.”

There is much more to say about Haldane’s ideas, and they will be central to the next complexity post. Until then, I’ll close by noting that none of these views is well-represented in our current regulatory environment. While we do have an increasingly complicated (some would say Byzantine) regulatory framework for banks, the complexity of the institutions themselves has far oustripped the ability of regulators to keep up, let alone create a perfect Ashby model. And while there is mounting political pressure to break up the banks, it has yet to overcome the political power of the banks themselves to resist this change, let alone to address the problem of tight coupling. Meanwhile, Haldane remains a bit of a lone voice, though that is changing.

Up next: the failure of expertise, and a potential solution

Soon

I had a clever post on complexity and regulation all worked out in my head but in researching it I kept coming across interesting new things, which made the post much too (of course) complex. I’m still working out some ideas and will have something more in the next day or so. 

It must be nice on Planet Davos (but for the rest of us, not so much)

In researching another project yesterday, I came across two articles about the economy that seemed to describe completely different realities. The first was by Joe Weisenthal of Business Insider, and described a general consensus among the great and good of Davos that “the economic crisis is over.” Wiesenthal refers to Mohamed El-Erian of PIMCO who coined the term “the new normal” to describe the post-crash economic malaise. Apparently, even El-Erian now sees a possible end to our woes.

But you wouldn’t know that from reading sociologist Erin Hatton’s Opinionator post this weekend at the NY Times, which described the economic “new normal” on the planet where the rest of us live:

… According to the Census Bureau, one-third of adults who live in poverty are working but do not earn enough to support themselves and their families.

A quarter of jobs in America pay below the federal poverty line for a family of four ($23,050). Not only are many jobs low-wage, they are also temporary and insecure. Over the last three years, the temp industry added more jobs in the United States than any other, according to the American Staffing Association, the trade group representing temp recruitment agencies, outsourcing specialists and the like.

Low-wage, temporary jobs have become so widespread that they threaten to become the norm.

This would be easy to dismiss as another case of the 1% vs. the 99%, but I think it’s worth looking at exactly how this split has developed, and what reinforces it.

The first thing to bear in mind is that the people who go to Davos have one thing in common – all of them have benefited enormously from the financialization of the global economy, whether through their stock price of the company they run, the portfolio they built after selling their company, or (more often) by virtue of working directly in finance. So for these people, the economy matters to the extent that it affects their portfolio.

So what have these people seen since the crisis? This is a pretty good indicator:

The stock market has more or less regained everything it lost. So if your sense of well-being is tied up in financial markets, you have to be feeling pretty good.

The infuriating part, of course, is the reason why stock prices are so high, which is where Hatton’s work enters the picture. The media has been full of reports about corporate profits hitting record highs, which is true, but here again they don’t get at the components of that. To grossly oversimplify, we can disaggregate corporate profits into revenue minus costs. And since there are any number of ways to specify those, I’m going to keep it simple and use proxies.

If we assume that revenue is a function of overall economic activity, then GDP seems a decent place to look. And here the picture is surprisingly strong – not great in terms of percentage growth, but in terms of the dollar amount of output (shown here), there is consistent growth since the bottom in 2009.

The other side – costs – is where things get ugly. I took as proxies here the yield spread of the BAA corporate over Treasuries, which measures how much extra a company with this credit rating has to pay to issue bonds (there are other ratings, but the downward pattern is the same), as well as the change in the average wage. If we treat these as proxies for the costs of capital and labor then the pattern is quite clear:*

What is especially frustrating is just who is paying these costs. In terms of capital, the Fed has made it clear that its various policies involving purchasing mortgage and Treasury bonds are intended to drive down yields across the market. Those policies are connected to their decision to maintain short-term rates – and thus the yields for savers – at extraordinarily low levels. So while the exact amount is hard to quantify, it seems fair to assume that savers are subsidizing both corporate profits (through lower borrowing costs) and financial portfolio returns (through falling yields, which are synonymous with rising prices).

The picture with labor is more direct. With companies needing fewer and fewer employees, and hiring more and more of those as temps or contractors, the pressure to raise wages just isn’t there in the aggregate. So here again, the rest of us (just by virtue of needing to work) are bearing the cost of lower wages that in turn support record profits.**

So if I had to capture the real “new normal” in a single graph, I think it would be the one below. The red line is GDP growth, and the blue line is wage growth, both relative to the year prior (this is why I can get away with putting them on the same graph). What we have is an economy that is growing twice as fast as wages are growing, and that’s only for those who have a job – you don’t even show up if you’re unemployed.

Doesn’t look like grounds for optimism to me, but then I don’t live on Planet Davos.

* Yes, this is a fudge to use rate of change in wage rather than the underlying wage, but using the base amount wasn’t informative without doing a lot of fiddling.

 ** There wasn’t room in this post, but it’s always worth looking at U6 unemployment rather than the number they give in the news. U6 takes into account those who are working part-time but don’t want to be, as well as those who have given up looking for work (though I don’t think it takes into account temps). The graph for that is here and tells the same story of stagnation at a very uncomfortable level.

Sentiment should not be the new horizon in journalism

Cross-posted at mathbabe.org.

Nate Silver’s high-profile success in predicting the 2012 election has triggered a wave of articles on the victory of data analysts over pundits. Cathy has already taken on the troubling aspects of Silver’s celebrity, so I’d like to focus instead on the larger movement toward big data as a replacement for traditional punditry. It’s an intriguing idea, especially given the sad state of political punditry. But rather than making things better, it’s entirely possible that the methods these articles propose could make things even worse.

There’s no question that we need better media, especially when it comes to politics. If we take the media’s role to be making sure that voters are informed, then they’re clearly doing a poor job of it. And one of the biggest problems is that political coverage has largely abandoned any pretense of getting to the truth in favor of “he said/she said” and endless discussion of the horse race, with the pundits being the worst offenders. Instead of “Will this be good for citizens?” we get “Will this be good for the Democrats/Republicans in the next poll?”

This is where the big data proposals enter the picture, and where I think they go wrong. Rather than addressing the accuracy or usefulness of the information being provided to us as voters, or working to shift the dialogue away from projections of how a given policy will play in Iowa, the proposals for big data revolve around replacing pundits’ subjective claims about shifting perceptions with more objective analysis of shifting perceptions.

For example, this piece from the Awl convincingly describes the potential for the rapid analysis of thousands or even millions of articles as a basis for more effective media criticism, and as a replacement for punditry by “anecdata.” A more recent post from the Nieman Journalism Lab at least acknowledges some methodological weaknesses even as it makes a very strong case for large-scale sentiment analysis as a way of “getting beyond pundits claiming to speak for others.” By aggregating and analyzing the flow of opinion across social media, the piece argues, journalism can deliver a more finely tuned representation of public opinion.

It’s true that perceptions in a democracy matter a lot. But it’s also true that getting a more accurate read on perceptions is not going to move us toward more informative coverage, let alone toward better politics. Worse still, these proposals ignore the fact that public perception is heavily affected by media coverage, which implies that pulling public perception more explicitly into the coverage itself will just introduce reflexivity rather than clarification.

In other words, we could end up with a conversation about the conversation about the conversation about politics. Is that really what we need?

As I see it, there are two precedents here, neither of which is encouraging. Financial markets have been treated as a source of perfect information for a very long time. The most famous justification for this was Hayek’s claim that the price system inherent in markets acts as “a system of telecommunications” that condenses the most relevant information from millions of agents into a single indicator. Even if we accept this as being true when Hayek wrote his essay in 1945 (which we shouldn’t), it’s certainly not true now. That’s in part because financial markets have attracted more and more speculators who base their decisions on their expectations of what others will do rather than introducing new information. So rather than informational efficiency, we get informational cascades, herding and periodic crashes.

The other example is consumer markets, which have the most experience with sentiment analysis for obvious reasons. In fact, this analysis is only the latest service offered by an enormous industry of advertising, PR and the like that exists solely to engineer and harness these waves of sentiment and perception. Their success proves that perception doesn’t exist in some objective void, but is closely shaped by the process of thinking about and consuming the very products it’s attached to. Or to be wonky about it, preferences can be more endogenous than exogenous in a consumer society.

Which is ultimately my point. If we want to treat the information provided by the media – the primary source of information for our democracy – as a more and more finely tuned consumer good whose value is determined by how popular it is, then this sort of analysis is emphatically the way to go. But we should not be surprised by the consequences if we do.

Regulating systemic risk

The Hansen framework I offered in the last post remains a good starting point for thinking about sources of systemic risk, and points to some of the problems regulators face in regulating systemic risk. This is not to say that Hansen’s list offers (or even claims to offer) a complete set of risk factors. But his three dimensions of Concentration, Interconnectedness and Behavior provide a useful basis for thinking about the individual threads that combine to create the complexity that makes systemic risk such a problem.

But before I get to that, I think it would be useful to consider some of the ways regulators have tried to address each of the three sources of risk.

As the table shows, treating each risk separately leads to very different regulatory approaches. If regulators focus on concentration, then the obvious solution is to limit both the absolute and relative size of a given organization. This rational solution has been rendered a non-starter due to the political power of the financial sector (though the Fed’s Fisher is trying).

Instead, regulators have considered a range of policies designed to increase the resiliency of institutions to losses by raising credit and liquidity standards, layering on shock-absorbing buffers, and other features. In the wake of the failure of Lehman Brothers, regulators have also been focused on developing guidelines and clarifying jurisdiction in terms of winding down or “resolving”  a failing institution as a worst case.

By contrast, focusing on interconnectedness implies a completely different regulatory response that emphasizes controlling, reducing or even eliminating the linkages between institutions. Doing this is much easier said than done, given the lack of data on the networks created by transactional flows both across and within national banking systems (as this Vox paper by Cerutti et al. explains).

An even greater challenge is that these linkages can span regulatory jurisdictions, requiring a level of harmonization that seems impossible to achieve even within a single country. The ongoing tussle between the SEC and the CFTC over the regulation of index swaps – a structure that ties together securities, futures and swap markets – is only one of several examples.

The final source of risk is notably the only one that stems from the behavior of people, rather than the structure of the overall system. The policy response is also different in that it imposes costs directly on individuals while generally letting the institutions that benefit from their business off the hook.

The real value of this three-part framework, in my view, is the way it reduces the welter of new regulation into some more easily understandable. It also shines a light on what regulators choose not to regulate when claiming to address systemic risk, which can be especially useful.

That’s a lot easier to see in the context of a specific example.

Example: Money Market Funds

The recent push by regulators to address systemic risk emanating from money market funds (MMFs) is a case in point. One of the ugliest surprises of the 2008 credit crisis was the extent to which the financial sector relied on borrowing in  short-term markets to fund its longer-term investment activity. Money market funds are the biggest single source of funding for these markets, so the run on these funds in the wake of the collapse of Lehman shone a spotlight on the fragility of this aspect of the financial system.

Although it’s not necessary to go into all of the details, a brief list makes the extent of the problem quite clear – MMFs look bad in all three dimensions:

Data source: Financial Stability Oversight Council

Regulators have taken a few passes at controlling these risks. The first measures were emergency plans put in place by the Fed and Treasury in 2008, though these were temporary, and have since expired.

The next pass at reform came in 2010, when the SEC took the “de-risking” approach I described above by implementing a series of measures aimed at making the funds themselves more resilient to market shocks (MoFo offers a helpful summary). These reforms tightened the rules for credit quality, liquidity and other features inherent in MMF portfolios.

While these rules were a necessary step forward, they left unaddressed the instability created by the illusion of a “stable” NAV. More important, they left the overall concentration of the industry untouched, and did not address the dense linkages between MMFs and the broader financial system.

More recently, the SEC attempted but failed to address the remaining structural issues with two proposals. The Financial Stability Oversight Council (FSOC) then stepped in with its own proposal, which is currently in an extended comment period.

This is already a very long post so I won’t go into too much detail, but there are several characteristics of the FSOC’s document that merit discussion. First, it includes a comprehensive overview of the risks related to various aspects of the industry, including its size, scale and interconnectedness. Second, it distils these into two central problems of instability and uncertainty relating to the illusion of  a stable NAV, as well as the lack of loss-absorption capacity of MMFs.

The remainder of the document can be seen as a sort of menu of possible policy alternatives to address these problems, either alone or in combination. It will be fascinating to see how the rules end up being implemented, because each menu choice only addresses one risk. For example, imposing liquidity fees would put all the costs on shareholders and only addresses behavioral risk, while creating a capital buffer to absorb instead puts all the costs on fund companies (more or less), and offsets some of the concentration risk in the Hansen framework.

The proposal is also interesting in terms of what it leaves unaddressed. After describing them in great detail in the introduction, the proposed rules don’t mention the concentration of the MMF industry or its tight linkages to the financial system again. Not only does this narrow the policy space of possible solutions – it also makes clear what is and sn’t politically possible when creating new rules for the investment industry.

There’s much more to say about MMFs but that’s of interest to a tiny group of people, so I will end here. Up soon – complexity.

Defining systemic risk

Systemic risk is a big topic these days for obvious reasons – the near collapse of the financial system has had profoundly bad effects on people around the world, and its continued instability is a major source of concern. Finding a way to measure and control threats to the stability of the entire system – and by extension, the rest of the world – is an important step toward making sure this doesn’t happen again.

Given that, it’s surprising that there remains no coherent, commonly understood definition of systemic risk, let alone a single way of measuring it. As Lars Peter Hansen notes in a recent NBER paper, this has implications for regulatory policy in the absence of meaningful analysis. Hansen focuses on the dangers of government enacting “discretionary” policies based on political urgency, though the opposite is more likely – if we treat the financial system as too complex to understand, then every problem simply becomes a “normal accident” that couldn’t possibly be mitigated by regulation.

Although Hansen has interesting things to say about modeling, what I find most useful in the paper is the way he groups together the various sources of systemic risk. Hansen uses three primary categories, which I paraphrase as:

Concentration: Some firms are either so large, or play such a central role in the financial system, that their failure can pose a risk to the entire system. The obvious example here is the too big to fail (TBTF) banks.

Interconnectedness: This clumsy word has become the term of art (see only the latest example here) for describing the density of linkages between financial institutions, as well as to the broader economy.  Hansen is sharp in observing that the connections can have two damaging effects. First, they can transmit volatility across networks of institutions simply by virtue of their being connected. Worse still, the structure of the network itself can make the spread of risk worse by magnifying its effects, particularly in the case of the failure of an institution that is both densely interconnected and very large.

The big banks are an obvious example here as well, given the daisy chains of liabilities created by swaps, repo agreements and other transactions that link them.

Behavior: If enough investors become worried about solvency, the resulting sell-off can become “a modern-day counterpart to a bank run triggered by liquidity concerns,” as Hansen puts it. A less innocent example is what William Black calls the “epidemic of control fraud” in mortgage lending and securitization, which was so widespread that it arguably threatened the entire system.

In reality, none of these risks exists in isolation, and they are best thought of as the ingredients that recombine to create emergent systemic risks. A bank run, for example, only becomes systemic to the extent that it affects institutions that are linked to other institutions, or are sufficiently large to create problems, or both. Or consider ETFs and the Flash Crash. Trading in index ETFs affected index futures, individual stock prices and the ETFs themselves (interconnectedness), resulting in an electronic stampede (behavior).

This intermingling of sources of risk is one of the primary challenges facing regulators, who are operating (as Hansen notes) without sufficient data or analysis in the face of heavy resistance from industry and Congress. I think Hansen’s three-part framework can also help clarify how regulators are approaching this challenge, which is the subject of the next post.

Two questions for Fed Governor Tarullo

Bloomberg this morning included an article on recent comments by Fed Governor Daniel Tarullo on a push by regulators to require banks to fund themselves more appropriately:

Federal Reserve Governor Daniel Tarullo is pushing an agenda to regulate banks beyond the restraints in the Dodd-Frank Act, including making them fund more of their assets using long-term borrowing.

The Fed and the Federal Deposit Insurance Corp. are holding preliminary discussions on a rule that would require holding companies for the largest U.S. banks to maintain a minimum amount of long-term debt that would aid in winding them down in case they fail, FDIC spokesman Andrew Gray said.

Mr. Tarullo explained the general dynamics of this shift in a speech in December at a Brookings Institution conference:

The basic idea is that the maintenance of minimum levels of long-term debt at the top holding company level will allow a resolving authority to transfer operating subsidiaries of the failed firm to a functioning bridge entity, while leaving behind in a receivership the equity and sufficient long-term debt to absorb the original firm’s losses. Eventually, the resolving authority could recapitalize the bridge entity by exchanging claims of the long-term unsecured creditors of the parent for equity, long-term debt of the bridge, or both.

In plain English, Tarullo is saying that requiring banks to fund themselves with a threshold level of long-term bonds would give regulators room to re-engineer the banks’ capital in the event of another crisis. Restructurings impose significant short-term losses on the holders of those bonds. Exposing bondholders to this risk would give them the “skin in the game” that regulators like to talk about so much, and would in theory give banks an incentive to control their own risks better.

But that incentive only makes sense if there are risks attached. Put another way, there can’t be “market discipline” without the stick of penalties. And the Fed itself has shown that it is almost pathologically unwilling to allow bank bondholders to incur losses.  This is a point that fund manager John Hussman has been making since early 2008, when he wrote the following after Timothy Geithner (then president of the NY Fed) testified to the Senate Banking Committee about the end of Bear Stearns:

Among those [question asked] was a question by the Committee to the effect that while it was clear that Bear Stearns’ shareholders had not been “bailed out,” the same could not be said for Bear Stearns’ bondholders – didn’t this send a signal to the credit markets that could encourage excessive risk taking in the belief that the government stood behind the bonds of private companies? Geithner gave a general response that credit spreads among financial companies remained relatively wide, so the market had not been provided with that sort of confidence. There was no follow-up question.

Hussman later expanded on this point with some data on just how much losses could have been absorbed by a failing Lehman Brothers if the Fed had not stepped in to protect the bond holders:

In Lehman’s case, $20 billion in shareholder equity is a very thin pool of funds to eat through when you’re not confident in the true market value of the $600 billion in assets held by the company. But it’s crucial to recognize that if you include both shareholder equity as well as Lehman’s debt (bonds and subordinated debt), you’ve got a $143 billion cushion to eat through before any customer or counterparty would be at risk. With that kind of cushion, the issue is not, and probably will never be whether customers or counterparties are at risk. The only issue is whether you save the bondholders.

Indeed, although Tarullo’s quote in the Bloomberg piece implies that banks need to issue more long-term debt, the reality is that they have already done so. As Hussman noted in 2011:

The amount of bondholders and equity coverage [among large financial institutions] varies somewhat, but in virtually every case, bondholder and shareholder capital of these institutions are more than sufficient to absorb any losses without the need for public funds, provided that the objective of government policy is to protect the people and the long-term viability of the economy, rather than defending the existing owners, bondholders, and managements of these institutions.

Tarullo echoed this point in his December speech, when he described it as “notable that, at present, large U.S. firms have substantial amounts of long-term debt on their balance sheets.”

With that in mind, I have two questions for Mr. Tarullo:

1. If the banks already have “substantial” levels that (per Mr. Hussman) are “more than sufficient to absorb any losses,” then how would a rule requiring them to do what they are already doing help?
2. How can we be sure that the rule will be meaningful if the implicit promise of the government to step in and fund these banks remains in force?

Tarullo’s remit within the Federal Reserve system is one of its most important – defining, measuring and controlling systemic risk. It’s hard to have much confidence that his work will be meaningful as long as the Fed and the Treasury reserve the right to prop up banks at their own discretion.