Fed governor and Harvard Professor Jeremy Stein gave an
important speech on March 21, Incorporating Financial Stability
Considerations into a Monetary Policy Framework. I have a few minor
criticisms, specifically on standard errors, causal mechanism, and
Lucas critique. But it's great for Jeremy to think out loud this
way, and give me occasion to do the same. You should read the whole
Stein's bottom line:
...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.
This view has put Stein a bit in the camps of the hawks, meaning
simply those who for one reason or another think the time to raise
rates is sooner rather than later.
This is an interesting framing. Why did Stein say "forecast
shortfall of the path of the unemployment rate from its
full-employment level" and not just "more unemployment?" Stein is
pitching the argument, I think, at the other FOMC member's
sensitivity to unemployment. If the Fed ultimately cares about
unemployment a year from now, the probability of a shock that would
unexpectedly raise unemployment matters as much as the Fed's
expected value. His idea: a bit of tightening might raise the level
a bit, but lower the variance.
"How Do You Measure Financial Market Vulnerability?" Stein
thinks about leverage measures, and concludes they are not useful
in real time, that to the extent they can be measured, they are
better addressed with regulation rather than interest rates. Most
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.
He concludes that the Fed should watch risk premiums -- the
expected excess return on long term treasuries and corporates --
and be ready to tighten if risk premiums seem too low. Essentially,
the Fed should add a new term to the Taylor rule,
interest rate = phi_pi*inflation + phi_u*unemployment +
(my interpretation, not the speech.)
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.
But measuring the term premium is tricky stuff. It's not just
the spread between long bond and short bond yields. If long bonds
are 1.60% and short bonds are 0%, it might just be that everyone
expects interest rates to rise in the future, and expected returns
are the same for holding any type of bond. The "risk premium" is
how much of that spread exists over and above (or in this case,
under and below) people's expectations of rising interest
So how do you separate the yield spread into expectation and
risk premium components? Footnote 3:
The 10-year nominal rate hit 1.63 percent on May 2, 2013. An
estimate of the term premium based on the oft-cited methodology
of Kim and Wright (2005) was negative 0.78 percent on this
OK, how do Kim and Wright come to this conclusion? Basically, by
running regressions. They (we) examine, in the past, what
configuration of bond prices and other variables have been followed
by interest rate rises ("expectations hypothesis"), and what
configuration has been followed by good returns to bond investors
This is an imprecise business. Regressions have standard errors
big ones. Regressions vary even more by specification -- which
variables do you put on the right hand side. Having written two
papers on bond risk premiums, I can attest those standard errors
and specification uncertainties are large.
At a minimum, I think Stein would do all of us a favor if he
would include standard errors and specification errors. My guess
though is that they would be at least one if not two percentage
points. The risk premium was somewhere between negative 2 and
positive 2 percent, not -0.78%. That might undermine his case (!),
but perhaps the Fed can write an internal memo that everyone has to
quote numbers with standard errors. So, the natural rate of
unemployment is not 6.500%, but has at least a percent or two
uncertainty as well.
The same point holds for the much more important credit spreads.
If the BAA bond spread is 1%, does this mean a 1% chance of default
(including recovery)? Or does it mean that the price is temporarily
low and people holding BAA bonds will earn on average 1% more on
other assets? Solid research breaking out this spread, also by
examining historical correlations, is just beginning.
More deeply, the historical correlations come from a sample in
which the Fed was not affecting long rates. I don't think QE did
much to long rates, but the Fed does, with some sort of "friction"
or "segmented market" in mind. That would make those regressions
pretty useless now. If you force the weather forecaster to say it
will be sunny, the usual correlation between forecast and reality
More deeply still, there is a classic Lucas Critique problem.
Historical correlations can be counted on to move as soon as the
Fed exploits them for policy. If low short rates were correlated
with low credit spreads which were correlated with subsequent
financial turmoil in the past, will raising short rates raise
credit spreads and lower financial turmoil now?
The cure is to understand the causal structure, but here we're
all really at a loss. Everyone writes about how low interest rates
lead to a "search for yield" and low risk premiums, but how?
Economic theory pretty much divorces the level of interest rates
from the risk premium between different securities. If anything,
simple correlations go the other way: low interest rates have
happened in the depths of recessions, when risk premiums are
Stein knows all of this of course.
Of course, there are many caveats. Foremost among them is the
fact that the ability of increases in the EBP ["excess bond
premium"] 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.
So, if there is a correlation between the level of the short
rate, the term premium and the risk premium, and a correlation
between those and financial stability, it's not about fundamental
business cycle risk, it's something about frictions in the
intermediation system. We are awfully far from understanding that
process, and especially understanding it well enough to manipulate
This statement also somewhat contradicts Stein's earlier view
that we shouldn't watch and respond to leverage: "How, if at all,
does monetary policy influence the evolution of the [leverage]
ratio?" asked Stein above. But this is awfully speculative on how
monetary policy affects risk premiums, and through them financial
stability. Finally, frictions by definition don't last forever. We
are talking, not about a month or two of higher rates and higher
risk premiums, but about rates and premiums that last for years. Do
these frictions really last for years?
Stein is duly cautions
...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.
But understanding all this will take years. Do we really get to
wait? Is Stein really making speeches to spur a decade long
research agenda? Given the equally tenuous theorizing on the "dove"
side about the relation between low interest rates and long-term
unemployment or the employment-population ratio, should it wait?
How should the Fed act with so much uncertainty about basic cause
and effect? I'm glad I'm not on the hot seat.
I applaud the closing comment. Recessions are really about risk
...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. 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
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