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Diversity Professional Development Powerpoint (9–12 slides plus title and reference slides inserted into the final paper)

Create a professional development presentation to inform the staff in your school building or district regarding how to meet the needs of learners from diverse backgrounds.

Using evidence based practices and course resources, create a PowerPoint presentation (a minimum of 3 or 4 slides on each topic) to inform your staff of ways to better meet the needs of diverse students. At least one of your slides must discuss technology. Your professional development should specifically address each of the three following Walden Diversity Proficiencies:

Understanding the Learner
Learning Environment
Planning, Instruction, and Assessment

Oglethorpe University
Intermediate Macroeconomics (ECO 222)
Critical Review of Kuttner
Purpose
To allow students an opportunity to review the Federal Reserve’s (Fed) use of unconventional monetary policy in response to the Great Recession and to see how economists attempt to evaluate the ex post impact of the policy on the economy. The essays is intended to be complementary to the Cline essay on fiscal policy and is extra credit – see below.
Description
The review will be based on Kuttner (2018) and should include the following elements:
Describe one of the two major policy employed by the Fed: quantitative easing or forward guidance. Discuss the how the Fed formulated and then executed the policy and how it differs from the Fed’s conventional or traditional policy tools.
Explain the mechanism of how the policy was intended to impact the economy
Through what channels in the economy was the policy expected to work?
Present Kuttner’s evaluation of the policy: Kuttner reviews several studies that attempt to quantify the policy’s impact – this is rather technical and beyond the scope of this essay. Rather focus on his conclusions.
The written portion of the essay should be four to six pages long (typed, double spaced using normally sized fonts and margins). Your paper should begin with a cover page with your name, the title and date and a reference page.
I encourage you to include any appropriate figures – diagrams, charts or graphs of data – these does not count toward the page-minimum. I also would suggest using the equation editor in Word or some other software to present the equations. Please see me if you need help with the former.
Use Mankiw to support your discussion and analysis of the working paper.1 Cite Mankiw and Cline by using end-of-sentence citations, e.g. Mankiw (p. xx) or Kuttner (p. xx)
Due Date – Tuesday May 5, 2020 by 6:00 pm. Please send essay via email as an attached Word Document entitled (Your Last Name – Kuttner (2017) to pkower@oglethorpe.edu
A well written easy will raise the grade on your Cline essay up to one letter grade.
1 You may assume that your reader knows basic economic terms and definitions and thus do not use Mankiw to define these.
2
Evaluation of Writing
Be clear and concise and make sure your work is internally consistent (flows logically). Your paragraphs and sentences should be well constructed; choose your words carefully; grammar and spelling also matter. Please proof read your work carefully – this can be done by reading your paper out loud or have a friend or a classmate read your work.
If English is not your native language, I strongly recommend that you go to the Center for Academic Success for additional help.
Additional Notes – please do not use the word “feel”, as in the following clause. “I feel that interest rates are too high to stimulate the economy…” in your discussion. Reserve this word for other occasions, when describing a state, like I feel mad, happy, sad, glad…
Also, avoid using pronouns (in general), especially, “you” and “we”, and in the rhetorical devise, “…as one can plainly see.” or “…as we all know ….” You may, of course, use “I”
When describing a company or government agency the correct pronoun is “it”.
Do not use contractions.
Incentive is not a verb – please do not make it into one. A corporate tax cut may create an incentive for a firm to increase investment

American Economic Association
Outside the Box: Unconventional Monetary Policy in the Great Recession and Beyond
Author(s): Kenneth N. Kuttner
Source: The Journal of Economic Perspectives , Vol. 32, No. 4 (Fall 2018), pp. 121-146
Published by: American Economic Association
Stable URL: https://www.jstor.org/stable/10.2307/26513499
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Journal of Economic Perspectives—Volume 32, Number 4—Fall 2018—Pages 121–146
In November 2008, the Federal Reserve faced a deteriorating economy and a
financial crisis. The federal funds rate had already been reduced to virtually
zero. Thus, the Federal Reserve turned to unconventional monetary policies.
Through “quantitative easing,” the Fed announced plans to buy mortgage-backed
securities and debt issued by government-sponsored enterprises. Subsequent
purchases would eventually lead to a five-fold expansion in the Fed’s balance sheet,
from $900 billion to $4.5 trillion, and leave the Fed holding over 20 percent of
all mortgage-backed securities and marketable Treasury debt (as reported in the
Fed’s Z.1 release, table L.211, and Treasury Bulletin, table OFS-1). In addition, Fed
policy statements in December 2008 began to include explicit references to the
likely path of the federal funds interest rate, a policy that came to be known as
“forward guidance.”
The Fed ceased its direct asset purchases in late 2014. Starting in October 2017,
it has allowed the balance sheet to shrink gradually as existing assets mature. From
December 2015 through June 2018, the Fed has raised the federal funds interest
rate seven times.
Thus, the time is ripe to step back and ask whether the Fed’s unconventional
policies had the intended expansionary effects—and by extension, whether the Fed
should use them in the future.
Outside the Box: Unconventional
Monetary Policy in the Great Recession
and Beyond
■ Kenneth N. Kuttner is Professor of Economics, Williams College, Williamstown, Massachusetts, and Research Associate, National Bureau of Economic Research, Cambridge,
Massachusetts. His email address is kenneth.n.kuttner@williams.edu.
† For supplementary materials such as appendices, datasets, and author disclosure statements, see the
article page at
https://doi.org/10.1257/jep.32.4.121 doi=10.1257/jep.32.4.121
Kenneth N. Kuttner
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122 Journal of Economic Perspectives
The aim of this paper is to take stock of what we have learned about unconventional
monetary policy in the nine years since its inception, and to highlight some
open questions. It begins with a review of the key features of unconventional policy.
Next, it discusses the transmission of unconventional policy to financial markets,
institutions, and the economy more broadly. Then it addresses the question of effectiveness
with a selective survey of empirical work on the financial and economic
impact of these policies, and it takes up the issue of the policies’ unintended side
effects. The paper concludes with some thoughts on the shape unconventional
monetary policy might take in the future.
What Were the Unconventional Federal Reserve Policies?
Quantitative Easing
Quantitative easing refers to a set of four asset purchase programs: the three
Large-Scale Asset Purchases (LSAPs), commonly known as QE1, QE2, and QE3;
and the Maturity Extension Program (MEP), also known as the second “Operation
Twist.”1 Table 1 summarizes the key features of these programs.
QE1 was announced in November 2008.2 Initially, it was limited to purchasing
$100 billion of debt issued by the government-sponsored enterprises Fannie Mae,
Freddie Mac, and Ginnie Mae, plus $500 billion in agency-backed mortgage-backed
securities.3 Its stated purpose was to “reduce the cost and increase the availability
of credit for the purchase of houses . . .”4 On March 18, 2009, the Federal Open
Market Committee announced that it would expand its purchases of agency debt
and mortgage-backed securities, and would also purchase $300 billion of longer-
term Treasury securities “to help improve conditions in private credit markets”
more generally.5
QE2 was announced on November 3, 2010. The program entailed the purchase
of $600 billion in longer-term Treasuries, but no agency debt or mortgage-backed
securities.
The Maturity Extension Program was announced on September 21, 2011.
The program initially involved the purchase of $400 billion of 6- to 30-year Treasuries,
accompanied by the sale of the same quantity of 1- to 3-year securities, with
the intention “to put downward pressure on longer-term interest rates and help 1 The first “Operation Twist” was a short-lived episode in 1961.
2 Excluded from the list of quantitative easing episodes that follow are the assets acquired by the Federal
Reserve in its capacity as lender of last resort, such as the asset-backed commercial paper purchased as
part of the Commercial Paper Funding Facility, which was operated from October 2008 to February 2010
in an effort to avert a liquidity crisis.
3 To put this into perspective, in the five years prior to the crisis, the Fed would purchase $2.75 billion of
Treasury securities in a typical month.
4 Press Release, November 25, 2008, at https://www.federalreserve.gov/newsevents/pressreleases/
monetary20081125b.htm.
5 Press Release, March 18, 2009, at https://www.federalreserve.gov/newsevents/pressreleases/
monetary20090318a.htm.
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Kenneth N. Kuttner 123
make broader financial conditions more accommodative.”6 The Fed announced
an extension of the program June 20, 2012, which ultimately amounted to
$667 billion. In contrast to the three large-scale asset purchases, all of which
entailed balance sheet expansions, this program “sterilized” the asset purchases
with offsetting asset sales, leaving unchanged the overall size of the balance
sheet.
QE3, which commenced in September 2012, initially involved the purchase of
$40 billion per month of mortgage-backed securities in a renewed effort to “support
mortgage markets.” In December 2012, the program was expanded to include
$45 billion per month of Treasury securities. Unlike the other three quantitative
easing policies, QE3 was open-ended and did not set a dollar limit at the time of the
program’s launch.
These quantitative easing policies differ in clear ways from conventional
monetary policy. For example, Figure 1 shows that quantitative easing drastically
enlarged and altered the composition of the Fed’s System Open Market Account portfolio. In contrast, the quantitative aspects of conventional policy, in terms of the Fed’s balance sheet or the money supply, had always been negligible. The magnitude of the open market operations (essentially, temporary asset purchases) required to move the federal funds rate was vanishingly small—virtually undetectable in the Fed balance sheet (Friedman and Kuttner
2010).
6 Press Release, September 21, 2011, at https://www.federalreserve.gov/newsevents/pressreleases/
monetary20110921a.htm.
Table 1
Characteristics of the Four Asset Purchase Programs
Program Dates Assets purchased
Size (billions) Sterilized?
First LSAP (QE1) 11/2008 to 3/2009Agency debt $200 No
Agency MBSs $1,250
Treasuries $300
Second LSAP (QE2) 11/2010 to 6/2011Longer-dated Treasuries$600 No
MEP (“Twist”) 9/2011 to 12/2012 6- to 30-year Treasuries$667 Yes
Third LSAP (QE3) 9/2012 to 10/2014MBSs $40/month No
12/2012 to 10/2014 Longer-dated Treasuries$45/month
Note: Quantitative easing refers to a set of four asset purchase programs: the three Large-Scale Asset
Purchases (LSAPs), commonly known as QE1, QE2, and QE3; and the Maturity Extension Program
(MEP), also known as the second “Operation Twist.” The table summarizes the key features of these
programs. MBSs are mortgage-backed securities.
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124 Journal of Economic Perspectives
Another difference is that the goal of quantitative easing was not stated in
terms of an explicit interest rate target.7 And because a $100 billion purchase
of mortgage-backed securities is not necessarily equivalent to a $100 billion
sterilized purchase of 10-year Treasuries, it is not straightforward to distill the effects of the various quantitative easing programs into an interest rate
equivalent.
A common misconception is that the purpose of quantitative easing was to
increase bank reserves and the money supply. The Fed’s pronouncements clearly contradict this view. For example, in the December 16, 2008, meeting of the Federal Open Market Committee, then-Fed Chair Ben Bernanke characterized
the approach of the Bank of Japan as based on the theory “that providing enormous
amounts of very cheap liquidity to banks … would encourage them to lend and that lending, in turn, would increase the broader measures of the money
supply …” Contrasting this with the Fed’s approach, Bernanke stated, “[W]hat we are doing is different from quantitative easing because, unlike the Japanese focus
7 In this respect, the Fed’s version of quantitative easing differs from the Bank of Japan’s current “QQE
with Yield Curve Targeting” policy, and from a proposal originally floated by Ben Bernanke (2002).
Figure 1
The Composition of the Federal Reserve System Open Market Account Portfolio
(in trillions of dollars)
2007 20082009201020112012201320142015
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
MBS
5+ years
1–5 years
Bills
Crisis
QE1
QE2
MEP
QE3
Note: Excludes assets associated with temporary liquidity facilities and US Treasury floating rate notes.
“MBS” stands for mortgage-backed securities; “5+ years” stands for Treasuries with maturities of 5 or
more years; “1–5 years” stands for Treasuries with maturities of 1–5 years. QE1, QE2, and QE3 are three
quantitative easing programs. MEP is the Maturity Extension Program.
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Outside the Box: Unconventional Monetary Policy in the Great Recession and Beyond 125
on the liability side of the balance sheet, we are focused on the asset side of the
balance sheet.”8
Forward Guidance
The Fed’s conventional modes of communication were already providing
markets with a great deal of information relevant to forming expectations about
future policy expectations. Statements and minutes of the Fed Open Market
Committee included assessments of economic conditions, for example, along with
the economic projections of board members and regional bank presidents. What
distinguished forward guidance was its explicit reference to the likely path of the
target interest rate. The tactic sought to communicate a lengthening of the anticipated
period of time over which interest rates were likely to remain low.
The early forward guidance statements were qualitative and vague. The
December 16, 2008, statement said that rates were likely to remain low for “some
time.” The March 18, 2009, statement referred to an “extended period.” The statements
used the word “anticipate” and were conditioned on unspecified “economic
conditions.” In 2011, forward guidance began to involve calendar-based statements
and explicit time horizons. But the horizons were repeatedly extended as
the economy languished, and continued to be framed in terms like “are likely” and
conditioned on economic developments.
In the Federal Open Market Committee statement of December 12, 2012,
forward guidance became more explicit. It said that the low interest rate policy
would remain in place so long as unemployment remained above 6.5 percent and
the inflation forecast was below 2.5 percent.
With the unemployment rate at 6.7 percent in December 2013, the Federal
Open Market Committee began to include, in its policy statement, language indicating
its intention to keep the federal funds rate low “well past the time that the
unemployment rate declines below 6-1/2 percent.”9 As time progressed, the reversion
to qualitative, open-ended forward guidance led to considerable speculation
regarding the date of the first rate increase. “Lift-off” eventually occurred 18 months
after the unemployment rate crossed the 6.5 percent threshold, by which time the
rate had declined to 5 percent.
Monetary Policy Transmission
Actions by the Federal Reserve affect a constellation of interest rates and asset
prices, which in turn influence spending decisions by households and firms, and
8 Bernanke’s distinction notwithstanding, I will follow common usage in this paper in referring to the
Fed’s policies as “quantitative easing.” The transcript of the meeting is at https://www.federalreserve.
gov/monetarypolicy/files/FOMC20081216meeting.pdf.
9 Press Release, December 18, 2013, https://www.federalreserve.gov/newsevents/pressreleases/
monetary20131218a.htm.
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126 Journal of Economic Perspectives
lending decisions by financial institutions. Many of these mechanisms, although
not all, operate in the same way under conventional and unconventional monetary
policies. But the arrival of unconventional policies has prompted a reexamination
of the linkages between monetary policy and financial markets and led to renewed
interest in models characterized by imperfect substitutability between assets.
The Transmission of Conventional Monetary Policy
Before the federal funds rate was reduced to virtually zero in late 2008, it
was the sole tool of US monetary policy. However, little or no economic activity
depends directly on the funds rate, as it applies only to overnight borrowing and
lending between banks. Instead, the funds rate affects spending indirectly, through
a number of distinct channels.
One is through the interest rates on longer-maturity obligations, such as mortgages
and corporate bonds, which are more relevant to spending decisions than the
overnight funds rate. Interest rates also affect the prices of assets, such as equities
and houses, creating wealth effects that influence households’ spending decisions.
Similarly, interest rate changes affect imports and exports through their impact on
the exchange rate.
It is important to note that long-term rates, asset prices, and the exchange
rate depend on the market’s forecast of future short-term rates, not just the current
funds rate target. Therefore, Fed communication—announcements, speeches,
press conferences, and the like—will affect spending to the extent that they provide
information about the likely path of future policy.
Conventional policy can also affect spending through the banking system. In
the traditional bank lending channel advanced by Kashyap and Stein (1994), the
increase in bank reserves associated with expansionary policy increases loan supply.
Moreover, for a bank that finances long-term assets with short-term liabilities, a rate
reduction will increase the market value of its equity, promoting lending. (Working
in the opposite direction, lower rates crimp banks’ net interest margin, which tends
to reduce loan supply.)
Finally, in the credit channel described by Bernanke and Gertler (1995),
expansionary policy ameliorates informational frictions and reduces firms’ external
finance premiums, thus enhancing the real effects of rate cuts.
The Transmission of Forward Guidance
Forward guidance affects interest rates and asset prices by conveying information
about the likely trajectory of future interest rates. In that respect, it does
not differ qualitatively from other forms of Fed communication that hint at future
policy. The main difference is that the interest rate path communicated as part of
forward guidance was more explicit than under the conventional policy regime.
There are two reasons why forward guidance may affect interest rate expectations.
One interpretation, dubbed “Odyssean” by Campbell, Evans, Fisher, and
Justiniano (2012), is that forward guidance would commit the Fed to pursuing the
time-inconsistent policy of allowing the inflation rate to exceed the Fed’s objective
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Kenneth N. Kuttner 127
for some period of time. A credible commitment to higher inflation in the future
would reduce future short-term real interest rates (Eggertsson and Woodford 2003).
Odyssean forward guidance is therefore unambiguously expansionary.
Alternatively, forward guidance may convey information without implying
a commitment, the case Campbell et al. (2012) referred to as “Delphic.” There
are two possibilities as to the type of information that could be transmitted. One
possibility is that an expansionary forward guidance announcement reveals to the
private sector proprietary Fed information that the economy is weaker than previously
thought, which in turn implies that interest rates are likely to remain low for
a longer time. However, as noted by Woodford (2012), if current real expenditures
depended on expected future income, then an announcement that led to a more
downbeat view of the economy could be contractionary.
A second way in which forward guidance could affect expectations is by
communicating information about the Fed’s policy rule. This channel may be
especially important when markets had no clear sense of how economic conditions
would affect how long interest rates would remain near zero. Consistent with
this view, using information gleaned from the New York Fed’s surveys of primary
dealers, Femina, Friedman, and Sack (2013) showed that successive forward guidance
statements pushed back the date of the expected first interest rate increase.
Also consistent with this view is the finding by Swanson and Williams (2014) of
a decreased sensitivity, beginning in late 2011, of medium-term interest rates to
macroeconomic news.
The Transmission of Quantitative Easing
Quantitative easing entails the use of the Fed’s balance sheet to influence long-
term and private sector interest rates. This could occur through three mechanisms:
imperfect substitutability, signaling about future policy, and improvements in financial
balance sheets.
If assets are perfect substitutes, then arbitrage will mean that all assets have
equal expected returns. But with imperfect substitutability, each asset class has its
own downward-sloping demand curve, allowing changes in the relative supplies
of assets to affect prices and yields. This supply-and-demand mechanism is what
accounts for portfolio balance effects that were integral to macro models from the
1960s and 1970s, such as those developed by Tobin (1963).
Imperfect asset substitutability may arise from two sources. One comes from
the fact that the prices of long-maturity bonds are more sensitive to interest rate
fluctuations than those with shorter maturities. Investors with an aversion to interest
rate risk will require a higher expected return on long-term bonds, relative to what
they would have earned from investing in short-term debt (a “term premium”).
Using asset purchases to reduce the supply of long-term bonds should therefore
lower their yields by narrowing the term premium.
Market segmentation can also underpin imperfect substitutability. This may
arise from investors’ preferences for specific types of assets or “preferred habitats”
(as hypothesized by Modigliani and Sutch 1966), or by incentives that investors have
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128 Journal of Economic Perspectives
to hold a minimum share of portfolios in a certain form like securities free from
default risk. Vayanos and Vila (2009), for example, developed a model incorporating
features of both preferred habitat and portfolio balance models.
Quantitative easing could also affect interest rates by sending a signal about
future policy. The idea is that significant purchases of long-maturity bonds signal
the Fed’s intention to keep the policy interest rate near zero for a longer period of
time. As with forward guidance, there are both Delphic and Odyssean interpretations
of how the signaling channel could operate. One Delphic view is that asset
purchases reveal a downgrading of the Fed’s view of economic conditions, and thus
should lead to expectations of lower future rates. Another is that signaling conveys
information about a change in the Fed’s policy rule—for example, that it is placing
a higher weight on unemployment or lower-than-intended inflation. The Odyssean
interpretation is that a large balance sheet would provide a strong incentive for the
Fed to maintain a highly expansionary policy for a longer period of time than it
might otherwise have desired, perhaps because the Fed would want to sell off many
of the assets it owns before raising rates.
In addition to putting downward pressure on interest rates, asset purchases also
may have stimulated spending by increasing loan supply. The purchases effectively
raised banks’ capital ratios by increasing the value of the existing assets on their
balance sheets. In addition, the purchases of mortgage-backed securities (especially
under QE1, when many investors were anxious to reduce their exposure to
housing-related risk) increased the liquidity of the market for those securities. Both
mechanisms would have made banks more willing to lend.
Unconventional Monetary Policy and Interest Rate Effects
The main challenge in assessing the impact of monetary policy is isolating
exogenous policy changes that can be used to identify causal effects.10 In the study
of conventional monetary policy, the monetary policy “shocks” used to identify the
causal effects of changes in the federal funds rate are typically modeled as deviations
from the Fed’s normal response to economic conditions, most commonly derived
from a structural vector autoregression econometric model.
Assessing the impact of unconventional policy is more difficult than it is for
conventional policy, for at least two reasons. First, it is not clear what variable to
use as a summary measure of monetary policy, given the heterogeneity of the asset
purchases and differences in the framing of the forward guidance announcements.
Second, defining “shocks” is problematic. Because the financial crisis was such a
singular event, it is hard to know what the Fed’s “normal” response to it would have
been. And in any case, in gauging the macroeconomic effects of unconventional
10 See Nakamura and Steinsson (in the Summer 2018 issue of this journal) for an in-depth discussion of
the identification issues bedeviling efforts to measure the effects of monetary policies.
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Outside the Box: Unconventional Monetary Policy in the Great Recession and Beyond 129
policy, the comparison to a “no policy” counterfactual will be more relevant than
one that looks at deviations from the usual policy rule.
Given these obstacles, it is not surprising that research on quantitative easing
and forward guidance has tended to focus narrowly on how such policies affect
interest rates on Treasury bonds and mortgage-backed securities, rather than on
their ultimate macroeconomic impact.11 The two most common approaches to
assessing the interest rate effects are event studies using high-frequency data and
time series models of term premiums, both of which have their limitations.
Event studies
A typical event study for estimating the effects of unconventional monetary
policies on interest rates examines changes in bond yields over a one- or two-day
window around which the policies are announced. This approach relies on two
identifying assumptions. The first is that the announcement was unanticipated. This
seems plausible for the early stages of the first large-scale asset purchases. However,
lacking a market-based measure of financial markets’ expectations, such as the
prices of federal funds futures I used in Kuttner (2001), there is no satisfactory way
to confirm this. Subsequent large-scale asset purchases and the Maturity Extension
Program may have been anticipated to some extent, in which case, the measured
financial market reactions in the few days around the announcement of a policy
may understate their true effects.
The second key assumption is that the announcement was not interpreted as
revealing the Fed’s proprietary information about the state of the economy, which
in turn would have affected bond yields. This could be problematic, in light of
the Campbell et al. (2012) finding that expansionary policy surprises have historically
been associated with upward revisions in private-sector unemployment rate
forecasts.
Table 2 summarizes some estimates of cumulative effects from a selection of
event studies. The results vary somewhat across studies, due to differences in the
length of the event window, the choice of interest rate data, and the selection of
events, but all tell roughly the same story.
The most salient result is that the QE1 announcements had very large, negative
effects on long-term interest rates: approximately 100 basis points for Treasuries
and mortgage-backed securities and upwards of 150 basis points (depending on the
horizon) for agency issues. The reactions represent extreme tail events, the largest
one-day changes observed in the entire post-crisis period. The effects of subsequent
programs on yields were materially smaller. The estimated two-day effects of
the second large-scale asset purchase announcements are in the –30 to –40 basis
point range with comparable figures for the Maturity Extension Program. The QE3
announcements appear to have had only a small impact on yields.
11 The literature on the interest-rate and economic effects of unconventional monetary policy is vast,
and the studies mentioned here are intended to illustrate main themes, not to offer a literature review.
Bhattarai and Neely (2016) provide a more comprehensive survey.
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130 Journal of Economic Perspectives
Taken together, the event studies suggest that the four policies’ cumulative
effects on the 10-year Treasury yield totaled at least –150 basis points. The evidence
should be interpreted with caution, however. There are five reasons why the results
could be inaccurate or not fully generalizable to other situations.
First, QE1 was launched at a time of high stress levels in financial markets.
The initial November 25, 2008, announcement cited widening spreads on the debt
of government-sponsored entities and on the mortgages they guaranteed. It stated
that the action was being “taken to reduce the cost and increase the availability of
credit for the purchase of houses,” saying nothing about long-term interest rates
more broadly. Similarly, the December 16, 2008, minutes of the Federal Open
Market Committee called attention to soaring risk spreads on corporate bonds and
rising premiums for on-the-run (most recently issued) Treasuries, and described
the functioning of Treasury markets as “impaired.” Therefore, much of the impact
of the first large-scale asset purchases probably came from a restoration of market
functioning, rather than a reduction in either expected future interest rates or the
term premium.
Second, several announcements of quantitative easing also contained
forward guidance. Most conspicuously, the December 16, 2008, and March 18, 2009, announcements both stated an intention to keep the federal funds rate at
“exceptionally
low levels.” Some efforts to disentangle these effects are discussed
below. Table 2
Estimated Event-Study Interest Rate Effects
Study
Window
(days) Yield on:
QE1
(basis points)
QE2
(basis points)
MEP
(basis points)
QE3
(basis points)
Gagnon, Raskin,
Remache, and Sack
(2011)
1 T10–91***
Agency –156***
MBS –113***
Krishnamurthy and
Vissing-Jorgenson
(2011)
2 T10–107*–30***
Agency –200***–29***
MBS –88–13**
Ehlers (2012) 1 T10 –14 –27***
2 T10 –40*** –46***
Bauer and Neely
(2014)
1 T10–123**–23 –14
Notes: “T10” refers to the 10-year Treasury, MBS to the 15-year Agency mortgage-backed securities, and
“Agency” to the debt issued by Ginnie Mae, Fannie Mae, and/or Freddie Mac. QE1, QE2, and QE3
are three quantitative easing programs. MEP is the Maturity Extension Program. Asterisks indicate the
magnitude of the ratio of the observed event-day relative to the standard deviation of the yield changes
at the indicated horizon, as reported by the authors:
***denotes ratios greater than 2.58 in absolute value (1 percent tail),
**ratios greater than 1.96 (5 percent tail), and
*greater than 1.69 (10 percent tail).
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Kenneth N. Kuttner 131
Third, the paucity of announcements means that the results are sensitive to
individual observations. For example, the 51 basis point drop in the 10-year Treasury yield on March 18, 2009, is, by a wide margin, the largest in the past 20 years (the runner-up is only –28 basis points). Excluding this observation reduces the estimated impact of QE1 by more than half. Moreover, the small number of observations
is an invitation to “cherry pick” dates, and studies that that find a reason to exclude observations with small or perverse reactions are likely to be biased towards finding larger effects.
Fourth, the statistical precision of the event study approach is unclear. If one makes the dubious assumption of equal variance on event and non-event days, then it would be legitimate to use the variance of non-event-day changes in assessing the precision of the estimated effects. Dropping this assumption requires using
only event days to calculate the variance, which is problematic given the small
number of observations.12
Fifth, and perhaps most important, it can be hard for an event study to measure
persistence. It may take some time before changes in asset supplies are fully reflected
in prices and yields (Greenwood, Hanson, and Liao 2018). The dilemma is that an
event window of sufficient length to account for a gradual response will include
“noise” resulting from the arrival of additional information and events, making it
less likely to discern a statistically significant impact of the policy. The findings for
QE1 and QE2 summarized in Table 2 are so large, however, that they remain clearly
discernible (in the sense that the cumulative responses exceed two standard deviations)
for at least one or two weeks.
Assessing the policies’ persistence at longer horizons requires imposing a parametric
structure on the responses. In an effort to get at the persistence issue, Wright
(2012) estimated a vector autoregression on daily data encompassing all four of
the quantitative easing programs (but not distinguishing observations according
to whether they were associated with forward guidance statements). He detected
measurable responses over several weeks, but found that the effects wore off after
two to three months.
In another effort, Swanson (2017) addressed the issue of persistence by using
a two-factor model to differentiate between the effects of forward guidance and
quantitative easing, and also fitted an exponential function to the responses as a
way to parameterize the rate of decay. Like Wright (2012), he found that the effects
of both policies were relatively short-lived. He also found that dropping the outsize
reaction of March 18, 2009, significantly decreased the magnitude but increased
the persistence of the effects of the large-scale asset purchases (again illustrating the
fragility of results based on a small number of announcements).
12 For example, the standard deviation of the cumulative effect of the eight QE1 announcements on the
10-year Treasury yield is 58 basis points. Using the t-distribution with 7 degrees of freedom, this gives a
95 percent confidence interval ranging from –20 to 208 basis points.
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132 Journal of Economic Perspectives
Time Series Analysis of Term Premiums
Time series econometric methods can be also used to assess the effects of the
large-scale asset purchases on bond yields—and in particular on term premiums.
Term premiums cannot be observed directly, however, so estimating the policies’
effects requires the additional step of fitting a term structure model to the data.
The “affine term structure models” used for this purpose involve specifying
the vector of bond yields over different term structures as a function of a small
number of factors, which are assumed to follow a first-order vector autoregressive
process. The one-period risk-free interest rate is assumed to be a function of the
same factors. The structure means that all co-movements between bond returns of
different terms are attributed to the factors, and further implies that only the risk
associated with those factors is priced.
Figure 2 plots the fitted 10-year term premium, interpretable as an estimate
of the difference between the 10-year Treasury yield and the average of forecast short-term interest rates over the life of the bond, derived from the Kim–Wright (2005) method. Already quite low by historical standards prior to the financial
crisis, the term premium declined by approximately 200 basis points from
mid-2009 to mid-2012. The premium actually fell into negative territory, implying that investors were willing to sacrifice some return for the hedge provided by 10-year Treasuries. The yield and term premium fell more or less in lockstep over the quantitative easing period, and the correlation between monthly changes is
0.97. It seems that that a shrinking term premium accounts for almost the entire
QE1
QE2
MEP
QE3
2006 200720082009201020112012201320142015
–1
0
1
2
3
4
5
6
Term premium
Yield
Figure 2
Kim–Wright Estimated 10-year Term Premium and 10-year Treasury Yield
(percent)
Note: QE1, QE2, and QE3 are three quantitative easing programs. MEP is the Maturity Extension Program.
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Outside the Box: Unconventional Monetary Policy in the Great Recession and Beyond 133
decline in the yield of a 10-year bond, with very little attributable to falling interest
rate expectations.
The time series method has several advantages over the event study approach.
First, it makes use of more information. Rather than relying on a handful of
announcements, it uses the entire time path of interest rates and asset quantities.
The underling analytical structure makes possible a quantitative assessment—that
is, the yield change, in basis points, for a given $100 billion in asset purchases—
which is hard to do in an event study framework. Also, the effects of the policy can
be estimated regardless of whether asset purchase programs were anticipated.
The identifying assumption underlying this approach is that changes in
supplies of assets of a specific maturity result from factors such as the Treasury’s
debt management or Fed portfolio allocation decisions and are otherwise unrelated
to expected interest rates or term premiums. As an example, Greenwood and
Vayanos (2014) cite the drop in the average maturity of outstanding Treasury debt
in the 1960s and 1970s, which resulted from a 4.5 percent regulatory ceiling on
bonds’ coupon rates at that time. There is no evidence that either the Treasury or
the Fed (at least pre-quantitative easing) adjusted asset supplies in response to term
premiums, so it is probably legitimate to treat the supply variables as exogenous.
The identifying assumption would also be violated if asset supplies and term
premiums were both a function of an omitted variable, such as macroeconomic
conditions and/or the state of the financial system. This is a concern for the quantitative
easing period, when the Fed’s asset purchases were clearly an endogenous
response to the deteriorating state of the economy (just as the federal funds interest
rate was endogenous before quantitative easing). For this reason, studies taking this
approach generally fit the models to data before quantitative easing occurred.
Table 3 summarizes the findings from four well-known studies looking at the effects of quantitative easing policies on term premiums. Taken together, the studies suggest that the policies collectively reduced the 10-year term premium by
Table 3
Estimated Effects of Quantitative Easing on 10-year Term Premiums
(basis points)
Study QE1 QE2 MEP QE3
Gagnon, Raskin, Remache & Sack (2011) –38a
D’Amico, English, López-Salido & Nelson (2012) –35–45
Ihrig, Klee, Li, Schulte & Wei (2012) –40 –40–17–50b
Hamilton & Wu (2012) –27c
Notes: QE1, QE2, and QE3 are three quantitative easing programs. MEP is the Maturity
Extension Program.
a The smallest of the range of estimates reported.
b Estimated by Engen, Laubach, and Reifschneider (2015) using the Ihrig, Klee, Li, Schulte,
and Wei (2012) model.
c The reported impact of a $400 billion maturity swap, scaled up to the $667 billion size of the
Maturity Extension Program.
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134 Journal of Economic Perspectives
as much as 150 basis points—remarkably similar to event-study results surveyed previously. Gagnon, Raskin, Remache, and Sack (2011) and D’Amico, English, López-
Salido, and Nelson (2012) both used reduced-form regressions of the Kim–Wright
(2005) term premium on measures of relative asset supplies. The two studies’
regressions differ in several respects, such the construction of the supply measures
and the inclusion of control variables. Despite these differences, both studies have
QE1 subtracting at least 35 basis points from the 10-year term premium. D’Amico,
English, López-Salido, and Nelson (2012) put the impact of QE2 at –45 basis points.
Ihrig, Klee, Li, Schulte, and Wei (2012) extended an otherwise standard affine
term structure model to include asset supplies as additional factors. Their estimates
for QE1 and QE2 are quite similar to those just mentioned. They also report a
sizable –50 basis point effect of QE3, reflecting the very large magnitude of the
asset purchases at that time. The estimated Maturity Extension Program effects are
roughly half the size of the other programs. Also employing a modified affine term
structure model, Hamilton and Wu (2012) used measures of asset supplies to forecast the three factors on which the term premiums depend. They put the impact of the
Maturity Extension Program at –27 basis points—somewhat larger than the Ihrig et al.
(2012) estimate, but still smaller than the effect of the large-scale asset purchases.
There are several reasons to use caution in interpreting the time series results.
First, estimates of the term premium can differ a great deal across models, as
illustrated in Rudebusch, Sack, and Swanson (2007). Second, the confidence intervals
associated with the term premium estimates are wide. As Li, Meldrum, and
Rodriguez (2017) note, it is hard to estimate the long-run average yields and the
parameters characterizing the speed of mean reversion.13 Third, the term structure
models assume stable parameters, which may be unwarranted during a financial
crisis with unprecedented policy tools being introduced.
What Explains the Interest Rate Declines?
There are competing explanations for what channels were most important in
connecting unconventional monetary policy and falling interest rates. In late 2008
and early 2009, improvement in market functioning probably accounted for much
of the sharp initial drop in yields under QE1. Gagnon, Raskin, Remache, and Sack
(2011) argue this case by citing the large spreads between mortgage-backed security
and Treasury yields as symptomatic of market dysfunction prevailing at the time.
But remaining somewhat unsettled is the question of the importance of the
signaling channel, working through expectations of future short-term rates, and
the effects of large-scale asset purchases in leading to a rebalancing of portfolios,
which would have affected term premiums. Disentangling these two is inherently
difficult. Further complicating matters is the fact that several early announcements
13 Li, Meldrum, and Rodriguez (2017) also showed that the use of professional forecasts in the Kim–
Wright (2005) model ameliorates these problems.
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Kenneth N. Kuttner 135
of large-scale asset purchases, the ones associated with the most extreme market
reactions, coincided with forward guidance statements.
Some inferences can be drawn using direct market-based measures of interest
rate expectations. Gagnon, Raskin, Remache, and Sack (2011) found that there was
no change in the one-year-ahead forward rate on December 16, 2008; and that the
28 basis point drop on March 18, 2009, was reversed shortly thereafter. Thus, they
attributed the change in the yields to the large-scale asset purchases, rather than
forward guidance. Similarly, Swanson’s (2017) model attributed most of the March
18 yield decline to the large-scale asset purchase factor.
However, looking at the overall impact of QE1, Krishnamurthy and Vissing-
Jorgenson (2011) ascribed a larger share of the market reaction to the signaling
channel. Observing that the announcements were collectively associated with a
40-basis-point reduction in the two-year federal funds futures rate, they concluded
that the signaling effect accounted for a nonnegligible 20–40 basis points of the
107-basis point drop in the 10-year Treasury yield. Bauer and Rudebusch (2014)
reached a similar conclusion using Eurodollar futures.
Another way to address the relative importance of signaling and the expected
future short-term rate, versus portfolio balance effects from large-scale asset
purchases and term structure effects, is to look at the results implied by an affine
term structure model. Using the Kim–Wright estimates of the term premium, Bauer
and Rudebusch (2014) calculated that 22 percent of the QE1-induced reduction
in the 10-year yield was attributable to signaling, with 78 percent coming from the
term premium. However, the estimated impact of QE1 on conventionally estimated
term premiums was very imprecise, and much larger signaling effects could not be
ruled out. Their favored model (with restricted risk prices) put the contribution of
the signaling effect at 36 percent (and in the 30–56 percent range), which suggests
that the majority of the yield decline can be attributed to a reduction in the term
premium.
An additional question relating to the transmission mechanism has to do with
whether it is the stock of outstanding assets that affects yields, stemming from market
segmentation; or the flow of asset purchases, which could result from transitory
liquidity or market functioning effects. In an effort to address this issue, D’Amico
and King (2013) study how the purchase of a specific bond affected its price, as well
as those of close substitutes. Comparing yields pre- and post-QE1 and aggregating
over the relevant set of bonds, they estimated a “stock effect” yield reduction of
30 basis points. Transitory “flow effects” of bond purchases were also detectable in
daily data, but of a much smaller magnitude. Significantly, this micro-level evidence
does not speak to the aggregate effect of reducing the supply of long-term interestsensitive
bonds (“removing duration”), implying that the overall impact of QE1 is
likely to have been larger. On the other hand, the authors note that market segmentation
was likely to have been stronger during the period of QE1, when financial
markets were under a great deal of stress, and consequently that supply effects are
likely to have been smaller during subsequent large-scale asset purchases. Using
methods similar to those employed by D’Amico and King (2013), Meaning and
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136 Journal of Economic Perspectives
Zhu (2011) found that QE2 shifted the Treasury yield curve down by roughly 20
basis points—a smaller “bang for the buck,” given that the volume of Treasuries
purchased was twice that of QE1.
Unconventional Monetary Policy and Effects on Economic
Outcomes
The evidence discussed so far points to a meaningful impact of unconventional
monetary policy. But lowering interest rates is not an end unto itself; it matters
only to the extent that it affects the decisions of financial institutions, firms, and
households.
In the context of unconventional monetary policy, it is especially important to be cautious about treating interest rate reductions as an end in themselves. First,
in an environment of financial stress, uncertainty, and scarce investment opportunities,
it is not a foregone conclusion that interest rate reductions will have the
same effects on spending as at other times. Perhaps in a time of economic stress, the cost of funds is of second-order importance for potential borrowers. Second,
a change in term premiums may have a smaller effect than a lowering of the
expected path of future short-term interest rates. Stein (2012) argues that a riskneutral
firm might adjust its capital structure to take advantage of the lower term premium without altering its real economic decisions. Indeed, Kiley (2014) finds,
using a quantitative macro model, that term premium reductions had substantively
smaller expansionary effects than reductions of expected future interest rates.
Thus, in this section we discuss evidence about the effects of unconventional
monetary policies on bank lending and firm behavior, and also consider some
studies that try to model the overall macroeconomic effects.
Bank Lending
Two recent papers have uncovered micro-level evidence that quantitative easing
increased bank lending. Rodnyansky and Darmouni (2017) used a difference-indifference
model to study the effects of large-scale asset purchases on bank lending.
They regressed loan growth on indicator variables for large-scale asset purchases,
which do not vary across banks, interacted with a measure of exposure of each bank
to mortgage-backed securities. They found that banks with higher initial holdings of
mortgage-backed securities were more likely to increase lending following QE1 and
QE3, both of which (and unlike QE2 and the Maturity Extension Program) entailed
significant purchases of mortgage-backed securities.
Luck and Zimmerman (2017) provide parallel findings for total loan growth.
Using data on mortgage originations and small business lending data reported
by banks to comply with the Home Mortgage Disclosure Act and the Community
Reinvestment Act, they were able to distinguish the policies’ effects on mortgage
refinancing versus commercial and industrial lending. While QE1 and QE3 both
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Outside the Box: Unconventional Monetary Policy in the Great Recession and Beyond 137
encouraged banks to extend credit, only QE3 increased commercial and industrial
lending. They also exploited spatial variation in banks’ holdings of mortgage-backed
securities to assess the effects of the large-scale asset purchase on county-level employment
growth. The main finding is that counties whose banks had relatively large
holdings of mortgage-backed securities tended to experience more rapid employment
growth following QE3, relative to those with smaller exposures. The same was
not true for QE1, however, whose effects were limited to mortgage refinancing.
Firm behavior
Using firm-level micro data, Foley-Fischer, Ramcharan, and Yu (2016) found
empirical support for the hypothesis that the reduction in bond yields resulting from
the Maturity Extension Program materially affected firms’ financing and investment
decisions. They used a difference-in-difference approach, with firms’ long-term debt
levels before the Maturity Extension Program as the treatment variable—the idea
being that those relying more on long-term debt would have benefitted more from
reductions in long-term interest rates. The identifying assumption is that firms’
preference for long-term debt is exogenous, and unrelated to any factors that might
have affected their response to interest rates generally, or the Maturity Extension
Program specifically.
Additionally, they found that firms with a relatively heavy reliance on long-term
debt experienced positive excess stock returns on September 22, 2011, the day of
the announcement of the Maturity Extension Program. The program also seems to
have affected firm’s financing decisions. In the year following the commencement
of the Maturity Extension Program, firms with high levels of long-term debt tended
to issue even more of it. More importantly, a greater reliance on long-term debt was
associated with larger increases in capital spending and employment following the
Maturity Extension Program. The asset purchases therefore appear to have affected
firms’ real economic decisions, not just their capital structure.
Macroeconomic Impact
Ultimately, we care about the effect of quantitative easing on macroeconomic
variables like GDP and the unemployment rate. A first step towards gauging its
macroeconomic implications is to translate the decline in bond yields into an equivalent
reduction in the federal funds rate. Previous studies, such as Kuttner (2001),
have found that a 100 basis point surprise cut in the funds rate target results in a
reduction in the 10-year yield of approximately 33 basis points. Using this as a rule
of thumb, it would have taken 450 basis points of funds rate cuts to produce the
150 basis point reduction in the Treasury yield that seems to have resulted from
quantitative easing.
A more rigorous approach is to use a term structure model to back out the
value of the (negative) latent federal funds rate that is consistent with the observed
behavior of the term structure of interest rates. Wu and Xia (2016) propose a model
of the “shadow federal funds rate” by truncating from below the distribution of
forward interest rates, thus introducing a nonlinearity into what would otherwise
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138 Journal of Economic Perspectives
have been a linear relationship between forward rates and the underlying factors.
According to their calculations (reported at https://www.frbatlanta.org/cqer/
research/shadow_rate.aspx), the shadow federal funds rate reached a nadir of
–3 percent in May 2014.
Wu and Xia (2016) then used a factor-augmented vector autoregression to
assess the impact of shocks to the shadow funds rate on various measures of real
activity. According to their calculations, the reduction in the shadow rate reduced
the unemployment rate by a full percentage point from July 2009 to December
2013, relative to a counterfactual with no quantitative easing.
Using a very different econometric model, Engen, Laubach, and Reifschneider
(2015) obtained results similar to those of Wu and Xia (2016). Feeding the 120-basis-
point reduction in term premium from Ihrig, Klee, Li, Schulte, and Wei (2012) into
the Federal Reserve Board’s FRB/US model, they concluded that the four quantitative
easing policies combined reduced the unemployment rate by 1.2 percentage
points relative to what it would have been in the absence of quantitative easing.
Yet another approach to gauging the policies’ aggregate effects is to use dynamic
stochastic general equilibrium models that incorporate some sort of financial friction.
In Gertler and Karadi (2013), the friction takes the form of limited arbitrage,
either between risk-free government and privately issued risky assets, or across
different maturities of risk-free assets. Quantitative easing is modeled as a policy
in which the central bank steps in and performs intermediation between different
assets that private financial institutions are unwilling to do. Under the assumption
of a zero short-term interest rate, their calibration indicates that QE1 reduced the
magnitude of the GDP contraction by 3.5 percentage points (quite substantial, relative
to the actual peak-to-trough contraction of 4.3 percent), with QE2 increasing
GDP by 1 percent within the span of a year. Quantitative DSGE results can be sensitive
to model specification, however. For example, the simulations in Chen, Cúrdia,
Vasco, and Ferraro (2011) put the impact on GDP of QE3 at only 0.4 percent, with
considerably more market segmentation required to obtain larger effects.
Side Effects of Unconventional Monetary Policy
The evidence summarized to this point supports the view that the Fed’s unconventional
policies largely achieved their purpose of reducing long-term interest
rates and stimulating economic activity. Concerns have been raised about the possibility
of adverse unintended consequences, such as inflation, financial instability,
and international spillovers, but such outcomes seem to have been modest.
Two Nonissues
One concern was that the vast expansion in bank reserves and the monetary
base would be inflationary. A number of prominent economists went so far as to write
in 2010 an open letter to Ben Bernanke predicting that QE2 would risk “currency
debasement and inflation” (e21 Staff 2010). This outcome did not occur, of course.
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Kenneth N. Kuttner 139
Another concern was that the large balance sheet might complicate the process
of “normalizing” monetary policy—that is, switching back to the use of the federal
funds interest rate as the short-term interest rate. This fear also turns out to have
been misplaced. As discussed by Ihrig, Meade, and Weinbach (2015), paying interest
on reserves has allowed the Fed to raise short-term interest rates, even with banks
holding $2.5 trillion of excess reserves.
Risk-taking
Less easily dismissed is the concern that unconventional monetary policy
encouraged excessive risk-taking by firms and financial intermediaries. For
example, while acknowledging that low interest rates are intended to encourage
some risk-taking, Fed Chair (then Governor) Jerome Powell (2017) raised the question
of whether or not “low rates have encouraged excessive risk-taking through the
buildup of leverage or unsustainably high asset prices.”
Excessive risk-taking is especially relevant to institutions, such as insurance
companies, with commitments to streams of fixed future payments (Rajan 2005). It
also applies to money market mutual funds, which require an interest margin of sufficient
size to cover management fees. Such institutions may feel compelled to “reach
for yield,” investing in riskier assets in order to hit targets for investment income.14
Several recent studies examining the effects of quantitative easing on financial
institutions find little reason for concern over additional risk-taking. Foley-Fischer,
Ramcharan, and Yu (2016) found that spreads narrowed between A– rated corporate
bonds and Treasury yields after the Maturity Extension Program, suggesting
that insurance companies were shifting towards somewhat riskier (but still highquality)
assets. (It may also have been the case that the A– securities were perceived
to have become less risky as a result of the expansionary policy.) Importantly, the
effect did not extend to lower-rated bonds, which typically imposed on institutional
investors a more stringent capital requirement. Thus, while some reaching-for-yield
may have occurred, it certainly didn’t qualify as reckless.
Focusing on banks, Kurzman, Luck, and Zimmerman (2017) found that those
with higher initial holdings of mortgage-backed securities were more likely to relax
lending standards following QE1 and QE3. On the face of it, this suggests riskier
behavior by banks. However, observing that QE1 resulted in relatively larger gains
in the value of banks laden with mortgage-backed securities, they attributed the
increased lending to the improvement in the banks’ capital positions. Increased
liquidity of mortgage-backed securities resulting from QE3 also seems to have
played a role. There is nothing to indicate that the risk-taking was excessive.
Looking at several different types of financial institutions, Chodorow-Reich
(2014) examined how large-scale asset purchases might affect risks. In an event study
framework, he found that for insurance companies and bank holding companies,
14 An extensive literature, too rich to do justice to here, has examined how low interest rates affect the
risk-taking of financial institutions in contexts that do not involve quantitative easing; for a survey, see De
Nicolò, Dell’Ariccia, Laeven, and Vaencia (2010).
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