Jeremy C Stein: Incorporating financial stability considerations into a
monetary policy framework
Speech by Mr Jeremy C Stein, Member of the Board of Governors of the Federal Reserve
System, at the International Research Forum on Monetary Policy, Washington DC, 21 March
2014.
* * *
I would like to talk today about how one might explicitly incorporate financial stability
considerations into a monetary policy framework.1 Doing so involves tackling two questions -
one that is relatively easy and one that is much harder. The easier question is, should
financial stability concerns, in principle, influence monetary policy decisions? To be specific,
are there cases in which one might tolerate a larger forecast shortfall of the path of the
unemployment rate from its full-employment level than one would otherwise, because of a
concern that a more accommodative policy might entail a heightened risk of some sort of
adverse financial market outcome? This question is about theory, not empirical magnitudes,
and, in my view, the theoretical answer is a clear "yes." I will say a bit more about why
shortly, but let me stress that I am not breaking any new conceptual ground here; the basic
argument has been laid out by a number of others, including Woodford and Kocherlakota.2
The second question is, how does one operationalize the theory? What sorts of data should
one look to, and what sorts of empirical methods should one use, to calibrate by how much
the stance of monetary policy should be altered relative to the case in which financial stability
considerations are completely set aside? This question is very difficult. In the interests of
advancing the conversation, I will venture some tentative thoughts on one possible approach,
which is somewhat different than what I have seen in other recent work on this topic. While I
hope to convince you that this path is worth exploring, I cannot say that I know yet exactly
where it will lead - and, in particular, whether it will ultimately deliver monetary policy
prescriptions that differ in a quantitatively meaningful way from those offered by our current
models. So I do not intend anything that follows as a comment on the current stance of our
policy.
Before getting too deep into the details, let me preview my bottom line. I am going to try to
make the case that, all else being equal, monetary policy should be less accommodative -
by which I mean that it should be willing to tolerate a larger forecast shortfall of the path of
the unemployment rate from its full-employment level - when estimates of risk premiums in
the bond market are abnormally low. These risk premiums include the term premium on
Treasury securities, as well as the expected returns to investors from bearing the credit risk
on, for example, corporate bonds and asset-backed securities. As an illustration, consider
the period in the spring of 2013 when the 10-year Treasury yield was in the neighborhood of
1.60 percent and estimates of the term premium were around negative 80 basis points.3
Applied to this period, my approach would suggest a lesser willingness to use large-scale
asset purchases to push yields down even further, as compared with a scenario in which
term premiums were not so low.4
The informal intuition I have in mind is that there is a cost associated with pushing risk
premiums too low, because doing so increases the likelihood that they may revert back in a
way that hinders the Federal Reserve's ability to achieve its mandated objectives. In what
follows, I will try to make this intuition more precise and to generalize its applicability.
Do financial stability considerations belong in a monetary policy framework?
However, let me start with the conceptual question of whether financial stability
considerations belong at all in a monetary policy framework. As I said earlier, I think the clear
in-principle answer here is "yes." The generic argument rests on three assumptions. First,
suppose that the Federal Reserve focuses only on its traditional dual mandate of maximum
employment and price stability. To keep things simple, suppose further that these two goals
are not in conflict with one another - say, because aggregate demand is weak, depressing
both employment and inflation - so that we can boil things down to one objective: keeping
unemployment close to target. With the usual quadratic loss objective function, this
assumption would say that the Federal Reserve cares about minimizing the expected value
of (U - U*)2. A little bit of algebra shows that this objective function can in turn be
decomposed into two pieces: (1) an "expected shortfall" term, given by the squared deviation
of expected unemployment from the target level of U*; and (2) a "risk" term, given by the
variance of realized unemployment, U.5
Second, the argument assumes that there is some variable summarizing financial market
vulnerability - I will be abstract for the moment and just call it FMV - which is influenced by
monetary policy. That is, easier monetary policy leads to increased vulnerability as measured
by FMV. Moreover, when FMV is elevated, there is a greater probability of an adverse event
- some kind of financial market shock - that, if it were to occur, would push up the
unemployment rate, all else being equal.6
The third and final assumption is that the risks associated with an elevated value of FMV
cannot be fully offset at zero cost with other nonmonetary tools, such as financial regulation.
To be clear, this assumption does not imply that regulation is not helpful in reducing financial
vulnerabilities - it only says that regulation is not a perfect instrument. These imperfections
could stem from regulatory arbitrage; political-economy constraints; or the fact that too much
regulation can also impede economic growth, just like overly restrictive monetary policy.7
Thus one way to think of my construct of FMV is that it is a stand-in for the level of financial
vulnerabilities that remain after regulation has done the best that it can do, given the existing
real-world limitations.
4
Again, I stress that this statement is directional, not quantitative - I am not claiming that the magnitude of the
adjustment one would want to make is large, or that the policy we had in place at the time was miscalibrated in
any absolute sense. Rather, my point is just that the financial stability costs of asset purchases are likely to
loom larger when term premiums are more negative, and that this consideration belongs in the discussion.
5
Kocherlakota (2014) emphasizes the same decomposition of the Federal Reserve's loss function. Note that, in
focusing only on mean and variance, this functional form sets aside what may be another important aspect of
vulnerabilities: tail risks that are not well captured in variance as opposed to higher moments.
6
If I had introduced an explicit time dimension, it might be more natural to assume that easier monetary policy
today raises the probability of an adverse event at some medium-run future date, even while reducing the
probability in the short run. In this case, there might be an interesting set of intertemporal tradeoffs to be
considered, particularly if the economy were in a very vulnerable position today. In any event, these are just
assumptions at this point, meant to illustrate the logic of the argument.
7
See, for example, Stein (2013) for an elaboration of these points.
In this setting, even with inflation concerns entirely set aside, monetary policy faces a
tradeoff. Consider a situation in which unemployment is above target. A more
accommodative policy has the usual benefit of lowering expected unemployment and thus
reducing the expected shortfall term in the objective function.If, however, it also raises the
conditional variance of the unemployment rate via an elevated-FMV channel - thereby
increasing the risk term in the objective function - then there is a cost to be weighed
alongside the benefit. And importantly, this is true even when financial stability is not a
separate objective in and of itself; as I have framed it, financial stability matters only insofar
as it affects the degree of risk around the employment leg of the Federal Reserve's
mandate.8
To be sure, absent a concrete measure of FMV, as well as some sense of the
responsiveness of FMV to monetary policy, this discussion is all pretty theoretical and
nonoperational. So I will turn to measurement in a moment. But it is worth noting one useful
qualitative observation that emerges just from the logic and from the nature of a quadratic
loss function. In making the tradeoff I just described, the marginal benefit of using easier
policy to reduce the expected unemployment gap is greater when the gap itself is large - that
is, when unemployment is far above target. In this case, even a quite high level of financial
vulnerability may not imply a much different stance of monetary policy than would fall out of a
more traditional analysis. However, as the unemployment gap shrinks, financial stability risks
loom larger in relative terms, so an analysis that takes them on board may lead to more of an
adjustment in the stance of policy.
Okay, but how do you measure financial market vulnerability?
Financial sector leverage
At an abstract level, the framework that I have sketched corresponds closely to that in
Woodford's work, although his model is much more fully articulated. When it gets down to
implementation, Woodford suggests that the most natural measure of financial market
vulnerability is a variable that captures "leverage in the financial sector." In other words,
faced with unemployment above target, he would have monetary policy be less
accommodative, all else being equal, when financial-sector leverage is high. This
recommendation rests on three key premises. First, when financial-sector leverage is high,
the probability of a severe crisis in which multiple large intermediaries become insolvent is
elevated - that is, we are more likely to have a replay of what happened in 2008 and 2009.
Second, easy monetary policy is asserted to increase the incentives for the financial sector to
lever up. And, third, focusing on leverage as opposed to asset prices avoids putting the
central bank in the position of having to "spot bubbles": Even if it is impossible for the central
bank to know when an asset class is overvalued, the risks to the economy associated with
overvaluation are presumably greater when intermediaries are highly levered.9
In my view, these are generally sensible arguments, and an approach of the sort that
Woodford outlines may well turn out to be fruitful. At the same time, this leverage-centric
approach also has some drawbacks, which suggest that there is likely to be value in a
parallel exploration of other tracks. For one thing, the effective degree of leverage in the
financial system is not easy to measure in a comprehensive fashion. One can certainly look
at things like banks' capital ratios, but some of the important action, from a financial stability
perspective, is likely to be in subtler forms of leverage that are either outside of the traditional
banking sector or more prone to shape shifting. More to the point, recall that, for the
purposes of informing monetary policy, one wants to focus on those sources of financial
vulnerability that are least effectively dealt with via regulation. And the more reliably a form of
leverage can be measured, the better a candidate it is for being handled with a regulatory or
supervisory approach. In other words, if we were to see signs that banks' capital ratios were
in danger of eroding, we would certainly want to do something, but it is hard for me to
imagine that the something should involve monetary policy - the obvious first line of defense
in this case would be to turn to our regulatory and supervisory tools.
In response to this critique, one might instead seek to focus the attention of monetary
policymakers on broader measures of private-sector leverage that are outside the reach of
traditional financial regulation. For example, Borio and Drehmann document that the ratio of
credit to the private nonfinancial sector relative to gross domestic product (GDP), once
suitably detrended, has substantial predictive power for financial crises, so perhaps it might
make sense for monetary policy to condition on this kind of broad credit-to-GDP ratio.10
However, if one goes this route, another measurement challenge arises: How, if at all, does
monetary policy influence the evolution of the ratio? Without an answer to this question, it is
hard to say how much one would want to alter the stance of policy when, say, the ratio is
abnormally high relative to trend. And the measurement problem is likely to be a difficult one,
given that the credit-to-GDP ratio is a slow-moving variable: Unlike with asset prices, there is
no scope for doing an event-study analysis of the effect of a change in policy on the item of
interest.11
Risk premiums in the bond market
Motivated in part by these observations, I would like to spend the rest of this talk exploring an
alternative, albeit potentially complementary, approach to the problem. Rather than focusing
primarily on some measure of intermediary leverage as an input into the monetary policy
framework, my suggestion is to also look at estimates of risk premiums in the bond market.
Thus, at a broad thematic level, I am taking a capital-markets-centric view of financial
stability, as opposed to a purely intermediary-centric view. This is, of course, not to suggest
that shocks to large leveraged intermediaries are not as important - if not more so - as those
that play out primarily in capital markets. Rather, the premise is simply that disruptions
originating in the capital market can be of consequence in their own right, and that they may
be less amenable to being dealt with via financial regulation. In this regard, I am echoing a
point made recently by Feroli and others, who have emphasized the fragilities related to bond
fund flows.12
Let me start by being clear on terminology: By the "risk premium" on an asset category, I
mean the ex ante expected return, based on an objective statistical model, that an investor
can anticipate earning on the asset in excess of that on short-term Treasury bills. So I will
use the words "risk premium" and "expected return" interchangeably in what follows. And, for
the sake of concreteness, I will focus on two of these bond market risk premiums in
particular: the so-called term premium, which is the expected excess return on longer-term
Treasury bonds relative to short-term bills, and the credit risk premium, which is the expected
excess return on bonds with credit risk (for example, corporate bonds, or asset-backed
securities) relative to safe Treasury securities.
With all of the rhetorical heat that gets generated about whether the Federal Reserve can or
should try to spot bubbles, it is worth keeping some uncontroversial facts in mind. It is widely
accepted among researchers in finance that there is an economically large amount of
predictable variation in the risk premiums on a wide range of assets classes.13 For example,
Cochrane and Piazzesi document that the excess returns on longer-term Treasury securities
can be predicted one year ahead with a simple model that delivers an R-squared in excess
of 40 percent.14 Analogously, Greenwood and Hanson show that the returns on junk bonds
relative to Treasury securities over two- to three-year horizons can also be forecast with
Rsquared values in the ballpark of 30 to 40 percent, in this case by using two intuitively
appealing forecasting variables: credit spreads and the high-yield share, which is the fraction
of total bond issuance that comes from the high-yield category.15 Figure 1 illustrates the
timeseries variation in estimates of both of these risk premiums.
Again, these sorts of findings are largely undisputed. Where there is more controversy is
over the interpretation of these patterns, with some arguing that they reflect waves of
irrational investor sentiment and others taking the view that they come from more rational
factors, such as time variation in either the risks facing investors or their tolerance for bearing
such risks. Here is where one can get into hard-to-resolve debates about bubble spotting and
about whether one can expect the Federal Reserve to be smarter than other market
participants. However, at least for some purposes, these debates are beside the point. In
particular, the implications for monetary policy that I have in mind do not seem to depend
critically on the difficult question of why there is so much time variation in expected bond
market returns; they only require that this variation exists, as we know it does. In other
words, there may be scope to make considerable practical progress while remaining largely
agnostic about the whole metaphysical are-there-bubbles question.16
Okay. So let's stipulate that risk premiums in the bond market move around a lot. The next
observation to throw into the mix is that monetary policy is one of the factors that have an
important influence on these movements. An emerging body of empirical work finds that an
easing of monetary policy - even via conventional policy tools in normal times - tends to
reduce both the term premiums on long-term Treasury securities and the credit spreads on
corporate bonds.17 That is, monetary policy always tends to work in part through its effect on
capital market risk premiums, perhaps through a risk-taking or reaching-for-yield
mechanism.18
13
See Cochrane (2011) for a recent survey of what is by now an enormous literature.
14
See Cochrane and Piazzesi (2005).
15
See Greenwood and Hanson (2013).
16
This statement admittedly sweeps some important subtleties under the rug. More precisely, I suspect that, if
one takes the Federal Reserve's legal mandate as given - and, more specifically, takes as given an objective
function such as minimizing the expected value of (U - U*)2 - then one can remain agnostic about the source
of variation in risk premiums and still reach the kinds of conclusions that I do in what follows. However, if one
asks whether such a mandate is itself normatively optimal in a fully micro-founded model, my intuition is that
the source of variation may matter quite a bit. For example, I would conjecture that it might be more
normatively appropriate, holding fixed the consequences for aggregate activity and unemployment, to lean
against a sharp reduction in risk premiums that is driven by investor sentiment rather than against one that is
driven by a rational response to changes in the risk environment.
17
See, for example, Hanson and Stein (2012); Gertler and Karadi (2013); and Gilchrist, Lopez-Salido, and
Zakrajsek (2014).
18
Note that, as an econometric matter, it is easier to establish a causal effect of monetary policy on risk
premiums than on broad measures of leverage, because asset prices can be measured on a daily or even
intraday basis. So they can be directly related to innovations in the stance of policy, as proxied for by, for
However, while this empirical observation sheds some interesting light on how monetary
policy influences the real economy, it does not by itself suggest that there is any financial
stability dark side - that is, any meaningful increase in what I have been calling FMV - to the
lowered risk premiums that go with monetary accommodation. For there to be such a dark
side, there would have to be some sort of asymmetry in the unwinding of the effects of
monetary policy on these risk premiums, whereby the eventual reversal either happens more
abruptly, or causes larger economic effects, than the initial compression.
Let's take an example. Suppose that initially, the credit risk premium on high-yield bonds is
400 basis points, and that, because the unemployment rate is well above target, the Federal
Reserve wants to add monetary accommodation. Suppose further that doing so lowers the
credit risk premium to 200 basis points temporarily but also increases the odds that this risk
premium will, at some point in the next couple of years, revert sharply, moving back in the
direction of 400 basis points. What is the downside here? Given a desire for accommodation,
is it not better to have credit risk premiums pushed down to a lower on-average level, even if
that potentially involves a more volatile down-then-up path? Again, the answer depends
critically on whether there is some kind of asymmetry, whereby the eventual increase in
spreads either is more abrupt, or has a larger effect on the real economy, than the initial
compression.
In table 1 and figure 2, I present some new evidence that bears on this asymmetry. To do so,
I build directly on recent work by Gilchrist and Zakrajsek (hereafter, GZ).19 GZ show that
changes in credit risk premiums have substantial predictive power for measures of economic
activity like GDP and unemployment. More specifically, GZ construct a variable called the
excess bond premium (EBP). The EBP at any point in time is, roughly speaking, a measure
of marketwide credit spreads minus an estimate of the expected default losses on bonds.
Hence, it can be thought of as a proxy for the excess return that bondholders can expect to
earn, net of defaults, on a going-forward basis - very much in the spirit of the risk premium
concept to which I have been referring. Not surprisingly, the EBP exhibits considerable
timeseries variation, reaching a peak in the wake of the Lehman Brothers bankruptcy. Moreover,
in simple forecasting regressions, changes in the EBP are associated with significant
movements in GDP and unemployment one year later. In other words, an increase in the
EBP - that is, a widening of the non-default-related component of credit spreads - portends
a decline in economic activity and employment a year later.
The specifications of GZ are linear, so they impose the assumption that increases in the EBP
have an effect that is symmetric to decreases. In table 1 and figure 2, I look explicitly for
asymmetries, with a specification that allows an upward move in the EBP to have a different
effect on the economy than a downward move. The results, which come from a sample
spanning the period from January 1973 to December 2012, are striking. Upward moves in
EBP - again, those corresponding to a widening of credit spreads - are very informative
about the future evolution of the real economy. The coefficient estimates imply that an
increase of 50 basis points in the EBP in a single quarter, which is roughly a
once-every-fiveyears kind of move, is associated with a two percentage point slowing of GDP growth over
the next four quarters and slightly more than a one percentage point increase in the
unemployment rate over the same interval.20 These effects are, by any standard,
economically important. By contrast, declines in the EBP have no discernible effect at all on
economic activity.
Putting it all together, this reasoning suggests that the credit risk premium - as measured,
say, by a forecasting model like that of Greenwood and Hanson - may be an operationally
useful measure of financial market vulnerability. When this risk premium is low, there is a
greater probability of a subsequent upward spike in credit spreads and the EBP. Moreover,
such upward spikes, when they do occur, are associated with significant adverse economic
effects. To be clear, we are not necessarily talking about once-in-a-generation financial
crises here, with major financial institutions teetering on the brink of failure. Nevertheless, the
evidence suggests that even more modest capital market disruptions may have
consequences that are large enough to warrant consideration when formulating monetary
policy. If so, the indicated directional adjustment would be to be less aggressive in providing
monetary accommodation in the face of above-target unemployment, all else being equal,
when risk premiums are abnormally low.
Of course, there are many caveats. Foremost among them is the fact that the ability of
increases in the EBP to predict future economic activity may not reflect a causal link from the
former to the latter. Perhaps there are economic slowdowns that are caused entirely by
nonfinancial factors, and, when investors see one on the horizon, they get skittish, causing
the EBP to rise. If so, it would be wrong to conclude that easy monetary policy - even if it
does, in fact, cause lower risk premiums - has any causal effect on the probability of a future
slowdown. So at this point, the evidence that I have reviewed can only be thought of as
suggestive.
Making progress on these difficult issues of causality will likely require a clearer articulation
of the underlying mechanism that leads to such pronounced asymmetries in the relationship
between credit spreads and economic activity. If a causal link is, indeed, present, what is
there about it that leads increases in spreads to have a much stronger effect on the economy
than decreases? I suspect that the answer has to do with something that mimics the effect of
leveraged losses to financial intermediaries - and the attendant effect on credit supply. For
example, GZ document that their EBP measure is closely correlated with the credit default
swap spreads of broker-dealer firms. The reason could be that losses on their inventories of
risky bonds erode the capital positions of these firms, which might in turn compromise their
ability to provide valuable intermediation services. Alternatively, a similar mechanism may
play out with open-end bond funds, whereby losses cause large outflows of assets under
management, again compromising the intermediation function and aggregate credit supply.21
Conclusion
To restate my main point, I believe that measures of bond market risk premiums - for
example, estimates of the expected excess returns on long-term Treasury securities relative
to Treasury bills and on credit-risky bonds relative to Treasury securities - may turn out to be
useful inputs into the monetary policy framework. These variables have the potential to serve
as simple proxies for a particular sort of financial market vulnerability that may not be easily
addressed by supervision and regulation. Again, however, let me emphasize the conjectural
nature of these remarks. Even if this broad way of thinking about the problem turns out to be
useful, there is a ways to go - in terms of modeling and calibration - before it can be used to
make quantitative statements. Thus, at this early stage, I would not want to claim that one is
likely to get policy prescriptions that differ significantly from those of our standard models.
We will have to do the work and see what emerges.
Finally, a more general theme that has been lurking in the background here is the sharp
difference in perspective that subfields of economics sometimes bring to a given question. As
I noted earlier, one of the central and most widely shared ideas in the academic finance
literature is the importance of time variation in the risk premiums (or expected returns) on a
wide range of assets. At the same time, canonical macro models in the New Keynesian
genre of the sort that are often used to inform monetary policy tend to exhibit little or no
meaningful risk premium variation.22 Even if most of the specifics of what I have had to say in
this talk turn out to be off base, I have to believe that our macro models will ultimately be
more useful as a guide to policy if they build on a more empirically realistic foundation with
respect to the behavior of interest rates and credit spreads.
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