IMES DISCUSSION PAPER SERIES

Monetary Policy, Financial Conditions, and Financial Stability

Tobias Adrian and Nellie Liang
Discussion Paper No. 2014-E-13

INSTITUTE FOR MONETARY AND ECONOMIC STUDIESBANK OF JAPAN
2-1-1 NIHONBASHI-HONGOKUCHOCHUO-KU, TOKYO 103-8660
JAPAN

You can download this and other papers at the IMES Web site:

http://www.imes.boj.or.jp
Do not reprint or reproduce without permission.

NOTE: IMES Discussion Paper Series is circulated inorder to stimulate discussion and comments. Views
expressed in Discussion Paper Series are those of
authors and do not necessarily reflect those of
the Bank of Japan or the Institute for Monetaryand Economic Studies.

IMES Discussion Paper Series 2014-E-13
December 2014

Monetary Policy, Financial Conditions, and Financial Stability

Tobias Adrian * and Nellie Liang **Abstract
In the conduct of monetary policy, there exists a risk-return tradeoff between
financial conditions and financial stability, which complements the traditional
inflation-real activity tradeoff of monetary policy. The tradeoff exists even ifmonetary policy does not target financial stability considerations independently of
its inflation and real activity goals, as the buildup of financial vulnerabilities frompersistent accommodative monetary policy when the economy is close to potential
increases risks to future financial stability. We review monetary policy
transmission channels and financial frictions that give rise to this tradeoff between
financial conditions and financial stability, within a monitoring program acrossasset markets, banking firms, shadow banking, and the nonfinancial sector. We
focus on vulnerabilities that affect monetary policies’ risk- return tradeoff including(i) pricing of risk, (ii) leverage, (iii) maturity and liquidity mismatch, and (iv)interconnectedness and complexity. We also discuss the extent to which structuraland time-varying macroprudential policies can counteract the buildup ofvulnerabilities, thus mitigating monetary policy’s risk-return tradeoff.
Keywords: risk taking channel of monetary policy; monetary policy transmission;monetary policy rules; financial stability; financial conditions;macroprudential policy
JEL classification: E52, G01, G28*Federal Reserve Bank of New York (E-mail: Tobias.Adrian@ny.frb.org)**Board of Governors of the Federal Reserve System (E-mail: JNellie.Liang@frb.gov)
This paper has been previously published as “Federal Reserve Bank of New York Staff Report,
Number 690, September 2014.” We thank Kathryn Boiles and Benjamin Mills for excellent
research assistance and Fernando Duarte, Rochelle Edge, Thomas Eisenbach, Simon Gilchrist,
Luca Guerrieri, Jamie McAndrews, Frank Packer, Jeremy Stein, Skander Van den Heuvel, andMichael Woodford for helpful comments. The views expressed in this paper are those of theauthors and do not necessarily reflect the official views of the Bank of Japan, the Board ofGovernors of the Federal Reserve, the Federal Reserve Bank of New York, or the Federal
Reserve System.

Table of Contents
1.

Introduction ............................................................................................................................. 2

2.

Conceptual Framework ........................................................................................................... 3

3.

4.

5.

Monetary Policy Transmission and Financial Stability ............................................................ 5

A. Asset Markets ...................................................................................................................................... 6
B. Banking Sector ..................................................................................................................................... 8
C. Shadow Banking ................................................................................................................................. 10
D. Nonfinancial Sector............................................................................................................................ 13

Financial Stability Considerations for Monetary and Macroprudential Policies ................... 14

A. Asset Markets .................................................................................................................................... 16
B. Banking Sector ................................................................................................................................... 17
C. Shadow Banking ................................................................................................................................. 20
D. Nonfinancial Sector............................................................................................................................ 21

Conclusion ............................................................................................................................. 23

Literature ...................................................................................................................................... 24
Data Sources ................................................................................................................................. 32
Tables and Figures ........................................................................................................................ 33

1

1. Introduction
Accommodative monetary policy eases financial conditions, but may also contribute to the buildup offinancial vulnerabilities and hence increase risks to financial stability. Risks to financial stability are thepotential for widespread financial externalities, such as from asset sales and contagion, that can result inlarge negative outcomes for output. In this paper, we argue that macroprudential and monetary policy
transmission channels are intertwined, and central banks should consider effects on both financial
conditions and financial stability when setting monetary policy. The basis for this argument is a growing
body of research advancing a risk-taking channel of monetary policy. This literature suggests that in
non-crisis periods when the economy is expanding, accommodative monetary policy interacting withfinancial frictions can lead to a buildup of financial vulnerabilities. Vulnerabilities, such as compressedrisk premiums, and excessive leverage or maturity and liquidity transformation in the financial system,
can increase the probability of a financial crisis and severe recession in the future.
We provide a review of transmission channels of monetary policy, focusing not just on financial
conditions, but also on the financial stability consequences via financial vulnerabilities. Looser monetary
policy may introduce a risk-return tradeoff, where accommodative policy improves financial conditions
by reducing risk premia and increasing incentives for risk taking. Financial frictions include agency costs,
institutional investor sticky nominal return targets, or financial firms’ risk models and limited liability.
The frictions introduce an inter-temporal tradeoff when the economy is close to potential, because thefrictions may lead to greater vulnerabilities, which will amplify shocks with negative consequences for
economic activity in the future.
We also review research that asks to what extent macroprudential policy or monetary policy
should respond to financial vulnerabilities. Macroprudential policies—both structural through-the-cycle
and cyclical time-varying—are usually viewed as the primary tools to mitigate vulnerabilities andpromote financial stability. These regulatory and supervisory tools, such as bank capital requirements or
sector-specific loan-to-value ratios, can shore up the resilience of the financial system to possible
adverse shocks. However, the impact of macroprudential policies may be limited because financial
intermediation can move away from more regulated entities to shadow banking, and the incentives tomove may increase as financial conditions become more accommodative and risk-taking behavior
increases. At the same time, macroprudential tools targeted at specific sectors may be politicallyunpopular if they are viewed as government-imposed credit allocation. Monetary policy can be a timevarying macroprudential tool, but cannot be targeted, since it will affect funding conditions for all
intermediaries, regulated and unregulated, and all sectors. As a consequence, it may have greatercollateral consequences than more sector-specific policies.
This paper builds on the financial stability monitoring framework described by Adrian, Covitz,
Liang (2013), as summarized in Table 1. It focuses on specific financial vulnerabilities—A) pricing of risk,B) leverage, C) maturity and liquidity transformation, and D) interconnectedness and complexity—acrossfour sectors—1) asset markets, 2) the banking sector, 3) shadow banking, and 4) the nonfinancial sector.
Adrian, Covitz, Liang (2013) explain how financial vulnerabilities can be systematically monitored
following this matrix approach, and discuss some policy implications, primarily focusing on2

macroprudential policy. This paper is an extension, and focuses specifically on how monetary policy canlead to buildups of vulnerabilities through an endogenous increase in risk-taking, and the efficacy ofmonetary policy or macroprudential policies to mitigate in each of the four sectors. The monetary policy
transmission channels in the four sectors of the financial system can be summarized as follows (seeTable 2):
1) Asset markets: Easier monetary policy improves financial conditions by lowering the risk-freeterm structure, but also compresses risk premiums.
2) Banking sector: Easier monetary policy increases loan supply, but also contributes to higher
leverage of banks and broker-dealers and greater risk taking (more credit to riskier firms).
3) Shadow banking: Easier monetary policy increases dealer-intermediated leverage that facilitates
maturity and credit risk transformation, and securitization, without an explicit government
backstop, but contributes to higher leverage and lower risk premiums.
4) Nonfinancial sector: Easier monetary policy eases borrowing constraints and boosts credit
growth, but reduces underwriting quality and increases debt burdens of riskier borrowers.
Macroprudential tools that can be used to mitigate the vulnerabilities in these four sectors
include capital, liquidity, and risk weight requirements, as well as supervisory guidance and exposure
limits for regulated firms, margins and haircuts for securities, and loan-to-value (LTV) and debt-toincome (DTI) ratios for borrowers (see Table 3).
The remainder of the paper is organized as follows. Section two provides a conceptual
framework for the relationship between monetary policy, financial conditions, and financial
vulnerabilities, also considering macroprudential policy. Section three provides a literature review of
the transmission channels of monetary policy, particularly focusing on the potential buildup of financial
vulnerabilities. Section four discusses how financial vulnerabilities can be addressed withmacroprudential policy tools, and the extent to which monetary policy should take financial
vulnerabilities into account explicitly. Section five concludes.

2. Conceptual Framework
One channel for monetary policy is the credit channel, where interest rate changes affect loan supply
through credit market frictions, such as asymmetric information between borrowers and lenders thatgives rise to an external finance premium. The size of the external finance premium depends on thebalance sheet conditions of the borrower, which vary with the level of interest rates. When interest
rates rise and asset values fall, borrowers are less able to borrow (balance sheet channel), and banks
may not be able to easily replace deposits with non-deposit funding, and reduce the supply of loans(bank lending channel).
The risk-taking channel posits that accommodative monetary policy will lead to an increase inrisk taking by financial institutions and investors that will boost economic activity. If the increase in risk
3

taking, because of financial frictions, also substantially increases the vulnerability of the financial system
to shocks, then the risk-taking channel will increase risks to financial stability. This effect onvulnerabilities can operate through asset prices or financial firms, or both. Low interest rates could
incent investors who may target a nominal return that is higher than current returns to reach for yield.
Low rates could pressure profit margins of banks and incent them to hold riskier assets, or higher asset
values could lead them to underestimate risk. Low rates that boost asset values also may incent carrytrades based on short term funding, often secured by the assets, and allow for excessive maturity
transformation. Similarly, higher net worth of borrowers arising from higher collateral values allows for
greater debt accumulation.
This tradeoff between financial conditions and financial vulnerabilities is typically not consideredin the literature on monetary policy. In traditional monetary policy settings, the inflation-real activity
tradeoff determines the stance of financial conditions, without giving consideration to financial
vulnerabilities. For example, in typical new Keynesian models, the Taylor rule—which determines the
stance of monetary policy with respect to inflation and real activity—is derived by taking first orderapproximations around the steady state, thus explicitly abstracting from downside risk considerations.
Furthermore, financial vulnerabilities that can lead to systemic risk are usually not modeled explicitly.
The lack of explicit consideration does not imply that financial stability objectives areinconsistent with the objectives of monetary policymakers. For example, suppose policymakers set
interest rates in order to keep output (and inflation) close to target. With a simple quadratic loss
objective function, policymakers would minimize the square of the expected value of the gap between
output and potential output, and the variance of output (Kocherlakota, 2014; Stein, 2014). Financial
stability risks are reflected in the variance term (a more complicated model could incorporate downsiderisk rather than just variance). When the gap between actual and potential is large, the variance around
output would have less weight in the objective function. Moreover, when the gap is large with output
well below potential, looser monetary policy might also reduce the variance term, by strengthening thebalance sheets of borrowers and lenders. 1 However, when the output gap is close to zero, financial
stability considerations would have greater weight in reducing variance. In this situation, a trade-off
may emerge as loose financial conditions to continue to promote current economic growth could lead toa build-up of vulnerabilities that increases the variance of output because of an increased likelihood ofan economic downturn in the future due to the realization of financial instability.
The risk-return trade-off for monetary policy is affected by the stance of macroprudential policy.
A tighter macroprudential stance alters the risk-return tradeoff of monetary policy in two ways. Tighter
macroprudential policy reduces financial vulnerabilities for any level of monetary policy, and may also
flatten the risk-return tradeoff, indicating that monetary policy faces a less severe tradeoff whenmacroprudential policy is more forceful. The trade-off for monetary policy exists because it is likely thatmacroprudential policies cannot adequately reach all vulnerabilities, given the limited reach of policies
to regulated sectors, and policies themselves provide incentives to move activities to shadow banking.
In the U.S., shadow banking is extensive. One estimate, which includes securitizations and net assets
1

For example, in a financial crisis, the positive impact of looser policy on risk taking can improve financial stability.

4

funded by short-term liabilities that are not issued by the regulated banking sector, hit a peak in 2008 at
100 percent of GDP, equivalent to the liabilities of the banking sector (see Adrian, Covitz, Liang, 2013).
A dimension that should be emphasized is the intertemporal nature of the tradeoff between
financial conditions and financial vulnerabilities. More accommodative policy eases current financial
conditions, allowing businesses to borrow immediately at lower rates. However, if borrowing were tocontinue at a rapid rate, borrowers and lenders would over time become more leveraged and more
vulnerable to an adverse shock. In addition, the impact of monetary policy on economic outcomes via
financial conditions is on expected economic outcomes. In contrast, monetary policy affects thebuildup of vulnerabilities that raise the potential for systemic risk. This tail risk to future macroeconomic
outcomes manifests itself only in some states of the world, when adverse shocks are realized. These
dimensions are important because they greatly complicate efforts to incorporate financial stability in thedetermination of monetary policy. Policymakers would need to look beyond expected conditions forpotential downside risks in the future, when uncertainty about expected conditions is alreadyconsiderable.
The distinction between risks and vulnerabilities is a fundamental one, representing animportant organizing framework for this paper. We refer to amplification mechanisms due to financial
frictions as vulnerabilities, which amplify adverse shocks. Risks are realizations of adverse shocks. Whilethe dimensionality of risks is very high—and risks are thus difficult to monitor and assess—theassessment of vulnerabilities is more manageable. The paper thus focuses on the tradeoff between
financial conditions and financial vulnerabilities.

3. Monetary Policy Transmission and Financial Stability
Before turning to specific transmission channels of monetary policy, it is helpful to review stylized facts
about monetary policy, financial conditions, and financial vulnerabilities. We present preliminary
suggestive empirical analysis on the risk-return tradeoff of monetary policy and the risk taking channel
by looking at the relationship between the stance of monetary policy, financial conditions, and financial
vulnerabilities. We first look at the relationship between monetary policy and financial conditions, andnext at the relationship between monetary policy and financial vulnerabilities.
Exhibit 1 show correlations between monetary policy and measures of financial conditions andvulnerabilities from 1987 to 2007, before the zero lower bound became a binding constraint. 2 Figures 1
and 2 show that monetary tightening is associated with tightening of funding conditions in fixed income
markets, specifically with an increase in a longer-term Treasury yield and an increase in the expectations
component of the 10-year Treasury yield (computed from the term structure model of Adrian, Crump,
Moench, 2013).
The risk taking channel of monetary policy is also present when the zero lower bound constraint is binding, sinceother tools such as forward guidance or asset purchases that reduce rates to support financial conditions also
impact financial vulnerabilities.

25Stylized facts about the relationship between the stance of monetary policy and future financial
vulnerabilities are presented in Figures 3 to 6. We relate the one-year lag of Taylor rule residuals tomeasures of vulnerabilities in financial markets. 3 In general, the stylized facts suggest an inverse
relationship between looser financial conditions (negative lagged Taylor rule residual) and declines inrisk premiums and increases in financial sector leverage and short-term funding. Looser policy tends tobe followed by tighter risk premia, both in equity markets and for interest rates (Figures 3 and 4).
Furthermore, we see that looser policy tends to be associated with future higher leverage for securities
broker-dealers (figure 5), and the amount of maturity transformation as proxied by the ratio of
wholesale short term funding to GDP tends to increase following looser monetary conditions (Figure 6).
Of course, the evidence presented here is only suggestive, and the remainder of this section
reviews rigorous empirical and theoretical studies about the linkages between monetary policy, financial
conditions, and financial stability. 4 We provide a review of the literature regarding the effect ofmonetary policy on financial conditions and the buildup of vulnerabilities for the four sectors previously
mentioned: A. asset markets, B. banking, C. shadow banking, and D. nonfinancial sector. The economic
mechanisms are summarized in Table 2.

A. Asset Markets
Accommodative monetary policy can lead to stronger economic growth by increasing financial
asset prices and improving financial conditions, either by lowering the risk-free discount rate or bylowering risk premia. The most direct transmission channel of monetary policy is via the expected pathof future short rates. Changes to the current level of rates may affect the path of expected future short
rates, and pass through directly to longer-term rates if not offset by changes to term premiums.
Changes in risk neutral longer-term yields, that remove risk premia from long term yields using a modelof the term structure of interest rates, appear to be directly related to changes in current short rates.
Monetary policy also impacts the pricing of risky assets, such as in equity, credit, housing, andother risky asset markets. Monetary policy may also impact expected cash flows. Bernanke and Kuttner(2005) document that positive monetary policy surprises generate negative stock returns, mostly
through increases in risk premia (higher expected returns), rather than through higher expected real
rates. In addition, others have shown that easing of monetary policy tends to reduce credit risk
premiums on corporate bonds (Greenwood and Hanson, 2012; Gertler and Karadi, 2013; Gilchrist,
Lopez-Salido, Zakrajsek, 2014). Bekaert, Hoerova, and Lo Duca (2013) find based on the dynamics of the
VIX that tightening shocks lead to increases in investor risk aversion.
3

Taylor rule residuals measure movements in the federal funds rate that are orthogonal to inflation and real
activity, thus allowing us to capture the impact of monetary policy on financial vulnerabilities independently of thecontemporaneous state of the macroeconomy. We use Taylor rule residuals for Figures 3 to 6 as we want toillustrate the correlation of the stance of monetary policy with indicators of risk taking in a manner that is
orthogonal with the state of the macroeconomy.
4
In addition, the relationship between monetary policy and financial vulnerabilities is state contingent, likely
changing signs in the depth of financial crises.

6But the link from monetary policy to asset prices does not necessarily suggest that loose policy
increases risks to financial stability. For that to happen, risk premiums would have to become
compressed, which can arise because of frictions in financial markets, and the unwinding of risk
premiums is asymmetric. We turn to a discussion of these issues next.
Financial Stability
For Treasury securities, looser monetary policy, combined with asset manager behavior, canlead to lower real term premiums than can be justified by fundamentals. Hanson and Stein (2012)provide evidence that monetary policy shocks induce variation in real forward term premiums,
consistent with yield-oriented investors who prefer current income to a holding period return. Whenmonetary policy loosens, these investors may rebalance to longer-term bonds, so as to mitigate adecline in current yields, thereby boosting longer-term bond prices and reducing term premiums. Thismechanism is similar to unconventional monetary policy, such as asset purchases of Treasury securities,
which work by lowering term premiums.
Changes in the stance of monetary policy combined with financial frictions may also compress
risk premiums for other assets. Rajan (2005, 2006) argues that low interest rates can lead tocompressed risk premiums because they increase the incentives for investors to reach for yield. This
incentive arises because some investors operate with constraints, such as fixed nominal rate targets tied
to their liabilities, or asset managers have contractual arrangements in which their compensation isbased on returns above a nominal level.
More broadly, monetary policy could contribute to a compression of risk premiums byincreasing risk taking at financial institutions. Allen and Gale (2000, 2003, 2007) provide models wherebubbles in real estate prices can arise because of agency problems between investors and lenders (risk
shifting because lenders do not observe the risky investment), and as credit expands. Low interest rates
can encourage investors to purchase a risky asset, boosting its current price. The expectation of futurecredit expansion will also raise current prices, though at the same time increase the likelihood of afuture crisis. They argue that expectations about future credit are determined by monetary policy.
Adrian and Shin (2008) also focus on the relationship between lending and asset prices. In
particular, looser monetary policy increases the ability of intermediaries to take on leverage, which inturn impacts the pricing of risk (Adrian, Etula, Muir, 2012 and Adrian, Moench, Shin, 2010). In addition,
low risk premia and low volatility may contribute to a buildup in imbalances, due to the “volatility
paradox” (Brunnermeier and Sannikov, 2014).
Morris and Shin (2014) and Feroli et al (2014) posit that unlevered asset managers who areevaluated based on their relative performance provide a channel for monetary policy to generate sharp
rises in risk premia not related to changes in fundamentals. Loose monetary policy may lead to greaterflows to funds that are managed by asset managers, who want to avoid being the worst performer sinceinvestors can redeem assets. Fund flows lead to increases in prices, generating momentum and a
feedback loop between flows and prices. But when investors believe monetary policy may tighten, the7aversion by asset managers to underperformance can create a sharp jump in risk premia. They
document this channel for risky bonds, though they do not find empirical support in Treasuries or
equities. Even so, more work is needed to determine if the jumps in risk premia are sufficiently large topose a threat to financial stability in the absence of high leverage and maturity transformation in the
broader financial system.
A number of studies have documented that the majority of movements in asset prices reflects
movements in the equilibrium compensation for risk. For example, the time variation in Treasury
returns primarily is due to changes in the pricing of risk rather than to changes in expectations of future
short rates (see Campbell and Shiller, 1984, Cochrane and Piazzesi, 2005, Cochrane, 2011). Similarly, themajority of variation in credit spreads is due to investors’ compensation for the risk of potential credit
losses in the future rather than expected losses (see e.g., Elton, Gruber, Agrawal, and Mann, 2001, and
Huang and Huang, 2012). For equity prices and house prices, valuation measures such as the dividend
payout or the price-to-rent ratio tend to exhibit large, persistent swings, again indicating that risk
premia vary over time (see Campbell and Shiller, 1988 for equity returns, and Case and Shiller, 2003, andCampbell, Davis, Gallin, Martin, 2009 for house prices). Risk premia are time varying, so that periods ofcompressed risk premia can be expected to be followed by a reversal of valuations. Another welldocumented feature of asset prices is their asymmetric conditional density: asset price declines tend to
be more violent than asset price appreciations (Harvey and Siddique, 1999 and 2000). This property isoften referred to as conditional skewness. The cyclical nature of risk premia combined with the negativeskewness in asset returns suggests that asset price booms associated with periods of accommodative
monetary conditions potentially pose a financial stability threat.

B. Banking Sector
Besides its impact on asset valuations, monetary policy has traditionally been viewed to workthrough the banking sector, mainly as lower policy rates lead to an increase in the volume of lending(see Peek and Rosengren, 2013 for a review). The bank lending channel posits that easier policy relaxes
borrowing constraints of banks, shifting credit supply (Bernanke and Blinder, 1988; Kashyap and Stein
1994). Bernanke and Blinder (1992), Kashyap, Stein and Wilcox (1993), and Bernanke and Gertler (1995)
provide empirical support for the bank lending and balance sheet channels, based on aggregate data, asmonetary policy tightening lead banks to shrink lending. Kashyap and Stein (1995, 2000) show thatbanks that are small and less liquid, and have fewer margins to adjust to a loss of reservable deposits,
reduce loans by more when policy tightens. While many studies support the lending channel, recent
developments in financial markets, such as growth of securitization, suggest the channel may havebecome less of an amplification channel for monetary policy (Loutskina and Strahan, 2009).
Capital requirements may influence the impact of monetary policy on bank lending. Peek andRosengren (1995) show that an adverse capital shock that makes a capital constraint binding will cause
banks to shrink assets and liabilities. When comparing capital-constrained to unconstrained banks, theunconstrained were more able to increase loans in response to an easing of policy.

8

Financial Stability
An increasing number of papers have focused on the link between the stance of monetary policy
and the risk-taking behavior of banks, which establishes a connection to financial stability. Loose
monetary policy can encourage banks to take on more risk on both the asset side and the liability side.
On the asset side, banks can reach for yield (Rajan, 2005), which will increase the share of risky assets.
On the funding side, loose monetary policy increases incentives to use more short term funding. Stein(2012, 2013) and Adrian and Shin (2010) show that increases in policy rates are associated with declines
in short term liabilities.
Recent papers provide cross-sectional evidence of the risk-taking channel, in which monetary
policy affects not just the quantity but the quality of credit. The risk taking effects depend importantly
on the amount of bank capital, where higher levels of capital mitigate incentives to reduce the quality ofcredit. Jiménez et al (2012) use detailed credit register data in Spain to show that lower rates leads togreater risk taking, more credit to riskier firms, and this effect is greater at banks with lower capital.
Dell’Ariccia, Laeven, and Suarez (2013) look at this channel in the US, and find a relationship between ex
ante riskiness of loans and bank capital. Paligorova and Santos (2012) evaluate loan spreads on
syndicated loans in the US and find that required spreads for more risky to less risky borrowers is lower
in periods of looser monetary policy, and is stronger for banks with greater risk appetite. Maddaloni and
Peydro (2011) find that low rates lead to softer lending standards in both the US and Euro area, which isgreater if rates have been low for an extended period, supervision is weaker, and securitization activity
is greater. Altunabas, Gambacorta, and Marques-Ibanez (2010) show unusually low rates for an
extended period led to a sharper rise in expected default probabilities for banks, consistent with greaterrisk taking.
Drechsler, Savov, and Schnabl (2014) model the effects of monetary policy through financial
institutions by affecting the external finance spread that banks pay to leverage. Easing of monetary
policy leads to lower leverage costs for banks, which increases risk taking and lowers risk premia. They
document that an external finance spread for banks (the funds rate – Tbill rate) moves closely with the
fed funds rate. Monetary policy can be viewed as altering bank leverage by affecting this spread.
Adrian and Shin (2010, 2014) document that broker dealer leverage is endogenous and highly
procyclical, owing to the way in which risk management is conducted. In booms, asset market volatility
is endogenously low, loosening risk-based capital constraints for broker dealers. When adverse shocks
occur, broker dealers sell assets, fueling a decline in asset prices, and a rise in market volatility, further
tightening risk management constraints. This procyclical balance sheet management has aggregate
consequences. Adrian, Etula, and Muir (2013) show that the cross section of asset returns acrossvarious asset classes is well explained by covariation with broker-dealer leverage. Adrian, Moench andShin (2013) further document that pricing of risk varies with broker dealer leverage over time.
Adrian and Shin (2011a and 2009a) link the procyclical leverage to monetary policy, showingthat tighter monetary policy tends to lower risk taking of broker dealers, leading to an increase in thepricing of risk, with associated contractionary macro consequences. In addition, Adrian, Moench andShin (2009, 2010) link leverage management to aggregate economic activity, and show that shocks to9dealer leverage impact macro activity through the pricing of risk. Adrian and Boyarchenko (2012) andNuño and Thomas (2014) provide theories that rationalize these facts within dynamic stochastic generalequilibrium models. In Adrian and Boyarchenko (2012), higher leverage is further associated with anincrease in financial vulnerability in the form of systemic risk. Adrian and Shin (2011b) show thatprocyclicality of dealers is apparent at the largest bank holding companies that own substantial brokerdealer subsidiaries. The procyclical leverage behavior is thus present in the largest U.S. and global
banking organizations.
Schularick and Taylor (2012) document the impact of the procyclicality of bank credit for real
activity using a historical dataset that covers almost 140 years across 14 developed countries. They findthat lagged credit growth is a highly significant predictor of financial crisis. Financial stability risks tend
to increase with the size of the financial sector, and equity market fluctuations have more adverse real
economic consequences in more financially-developed economies. Schularick and Taylor also documentthat while post-World War 2 monetary policy has generally stabilized money growth in the face ofadverse financial developments, it has not been able to prevent collapses in credit growth.

C. Shadow Banking
Shadow banking can be defined as maturity transformation, liquidity transformation, and credit
risk transfer outside of institutions with direct access to government backstops such as depository
institutions (see Adrian, Ashcraft, Cetorelli, 2014 for a recent overview). This intermediation takes placein an environment where prudential regulatory standards and supervisory oversight are either not
applied or are applied to a materially lesser or different degree than is the case for regulated banks. The
shadow banking system decomposes credit intermediation into a chain of wholesale-funded,securitization-based lending. 5
The shadow banking system transforms risky, long term loans (mortgages, for example) into
seemingly credit-risk-free, short term, money-like instruments. The creation of money-like shadow bankliabilities complements traditional forms of money creation (Gorton and Metrick, 2012). High-poweredmoney can be created only by central banks. Commercial banks create broader forms of money, such as
demand deposits. Shadow bank money creation occurs primarily in the commercial paper market andthe repo market, and is funded by money market funds and short term investment funds. Shadow bankliabilities can substitute for money in the private sector’s asset allocation. Sunderam (2012) shows thatshadow banking liabilities respond to money demand shocks. Gallin (2013) provides a comprehensive
map of the amount of short term funding from the shadow banking system to the real economy, basedon the flow of funds statistics. Short term money creation by the shadow banking system also furthers
monetary policy transmission.
Shadow credit intermediation is performed through chains of nonbank financial intermediaries in a multistep
process that can be interpreted as a “vertical slicing” of the traditional banks’ credit intermediation process into
seven steps. Pozsar, Adrian, Ashcraft, and Boesky (2013) explain the seven steps of shadow bank credit
intermediation in detail. The seven steps involve 1) loan origination, 2) loan warehousing 3) pooling andstructuring of loans into term asset-backed securities (ABS), 4) ABS warehousing, 5) pooling and structuring of ABS
into CDOs, 6) ABS intermediation, and 7) funding in wholesale funding markets by money market intermediaries.

510

Money creation in the shadow banking system is at the root of the breakdown of monetary
relationships in the U.S. Until the early 1980s, the relationship between money growth and nominal
output growth was very stable, a fact usually labeled as stable velocity of money. Schularik and Taylor(2012) document that credit began to grow rapidly and decouple from broad money since the early
1970s, via a combination of increased financial risk and leverage outside of non-monetary liabilities atbanks. Since the shadow banking system became a quantitatively important contributor to credit
intermediation, shadow bank money creation has led to a highly time-varying velocity of money. This
reflects the feature of the shadow banking system that it responds quickly to changing financial,economic, and regulatory conditions.
Financial Stability
The presence of shadow banking steepens the risk-return tradeoff that monetary policy makers
face. The shadow banking system, which is less constrained by prudential regulation, leads to a greatertransmission of monetary policy to financial conditions via a larger degree of endogenous risk taking.
The greater risk taking may be evident in higher leverage, and greater maturity and liquidity
transformation, allowing the system to operate at higher levels of risk taking and increasing thepotential for systemic financial crises. The presence of shadow banking thus steepens the risk-return
tradeoff relative to an economy with only traditional banking, making monetary transmission faster, butalso riskier.
A generic model of shadow bank intermediation that features such a steepening in theaggregate risk-return tradeoff has been proposed by Moreira and Savov (2012). Intermediaries create
liquidity in the shadow banking system by levering up the collateral value of their assets. However, theliquidity creation comes at the cost of financial fragility as fluctuations in uncertainty cause a flight toquality from shadow liabilities to safe assets. Gorton and Metrick (2012) document the run on the
shadow banking system at the beginning of the financial crisis of 2007-09, as investors began toquestion the value of subprime mortgage collateral. Covitz, Liang, and Suarez (2013) show that runs on
ABCP programs were more likely if they had weaker liquidity and credit support, as commercial paper
investors are especially sensitive to being paid in full and on time. Moreover, for programs with thesecharacteristics that were able to issue paper, spreads were wider and maturities were shorter, pointing
out their inherent fragility and source of financial instability. ABCP since 2004 was—at least in part—
attributable to regulatory arbitrage triggered by a change in capital rules. Acharya, Schnabl, and Suarez(2013) document that the majority of guarantees were structured as liquidity-enhancing guarantees
aimed at minimizing regulatory capital, instead of credit guarantees, and that the majority of conduits
were supported by commercial banks subject to the most stringent capital requirements.
The financial frictions that lead to excessive risk taking and exacerbate credit losses during
downturns also interact with the fragility of funding. Per definition, funding sources for shadow banking
activities are uninsured and thus runnable. In many ways, the fragility of shadow banks due to the runability of liabilities resembles the banking system of the 19th century, prior to the creation of theFederal Reserve and the FDIC. During that time, bank runs were common, and they often had severe
consequences for the real economy. The shadow banking system’s vulnerability to runs bears
11resemblance to bank runs as modeled by Diamond and Dybvig (1983). Shadow banks are subject to runs
because assets have longer maturities than liabilities and tend to be less liquid as well. In a run, shadowbanking entities have to sell assets at a discount, which depresses market pricing. Martin, Skeie, andvon Thadden (2012) provide a model for a run in repo markets. In their model, repo borrowers faceconstraints due to the scarcity of collateral and the liquidity of collateral. Under sufficiently adverse
conditions, self-fulfilling runs can occur. Duarte and Eisenbach (2013) quantify repo runs and find large
systemic effects.
Another source of financial stability risk emanating from shadow banking is related to theperception of tail risk. Misperceived tail risk matters for monetary policy as it impacts estimates ofdownside risk to real activity and inflation. An early paper warning of the financial system’s exposure tosuch tail risk was presented by Rajan (2005) who asked whether financial innovation had made theworld riskier. Rajan (2006) later notes that financial intermediaries have incentives to show superior
performance in periods when financing is ample, which leads them to take on tail risk. Shadow banking
activity is often tailored to take advantage of mispriced tail risk, making the shadow banking system
particularly sensitive to tail events. Such tail risk might be mispriced ex-ante, either due to irrational or
due to rational reasons. Gennaioli, Shleifer, and Vishny (2013) posit that actors neglect risk based on
behavioral evidence. When investors systematically ignore the worst state of the world, overinvestment
and overpricing during the boom and excessive collapse of real activity and the financial sector during
the bust are generic features of shadow credit intermediation. Coval, Jurek, and Stafford (2009) pointout that the AAA tranches of private label asset backed securities behave like catastrophe bonds thatload on a systemic risk state. Neglected risk also manifests itself through over-reliance on credit ratings
by investors. For example, Ashcraft, Goldsmith-Pinkham, Hull, Vickery (2011) document that subprime
MBS prices are more sensitive to ratings than ex post performance, suggesting that funding is
excessively sensitive to credit ratings relative to informational content. Merrill, Nadauld, Strahan (2014)
show that life insurance companies exposed to unrealized losses from low interest rates in the early
2000s increased their holdings of highly rated securitized assets, assets which offered higher yield perunit of required capital. The results are only evident in accounts subject to capital requirements and at
firms with low levels of ex ante capital.
Chodorow-Reich (2014) investigates the impact of monetary policy during and since the financial
crisis on the tradeoff between financial conditions and financial stability by focusing on the behavior of
financial institutions. He documents that the accommodative policy led to a rise in asset values that
reduced market-based default risk measures for bank holding companies and life insurers, thus helping
to stabilize the financial sector. In terms of testing for reach for yield, Chodorow-Reich documents formoney market funds that the interaction of low nominal interest rates and administrative costs forced
the funds to waive fees; funds with higher costs reached for higher returns in 2009-11, but notthereafter. Chodorow-Reich also shows that private defined benefit pension funds with shorter
duration of liabilities or worse funding status increased their risk taking beginning in 2009, but that such
behavior largely dissipated by 2012. However, he does not relate behavior to whether the funds havetarget returns that exceeded current market rates.

12

D. Nonfinancial Sector
The balance sheet channel is a standard transmission channel for monetary policy, whichemphasizes the impact of policy on the net worth of borrowers (the seminal contribution by Bernanke
and Gertler (1989) was further extended by Kiyotaki and Moore (1997), and Bernanke, Gertler andGilchrist (1999)). Empirical evidence on the balance sheet channel, often referred to as the “financial
accelerator,” is extensive. For example, Levin, Natalucci, and Zakrajsek (2004) find a sharp rise inexternal finance premiums for businesses during the 2001 recession, and Iacoviello (2005) showschanges in home equity affects household borrowing and spending by more than a conventional wealtheffect. The literature generally finds that large shocks are needed for the accelerator to matter.
Furthermore, in the financial crisis of 2007-09, borrower balance sheet frictions alone were notsufficient to explain the large observed amplification. As a result, the literature has been evolving to
combine borrower frictions with additional frictions, such as financial constraints of lenders, or asset
price bubbles.
Financial Stability
Increases in net worth will increase access to credit, but frictions in financing markets could leadto excessive debt growth that increases the likelihood that borrowers will default. Lorenzoni (2008)
generates excessive borrowing ex ante and excess volatility in investment ex post, due in part to limited
ability to commit to future payments. Borrowers have limited access to outside funds, so when hit bybad shocks, they are forced to fire sell assets. Inefficiencies arise because borrowers do not consider thegeneral equilibrium of fire sales on asset prices. Korinek and Simsek (2014) in a model of deleveraging,show that borrowers do not take into account the negative externalities of leverage on aggregate
demand, which leads to excessive leverage. In their model, tight monetary policy could be used toaddress aggregate demand externalities caused by leverage.
Research has identified excessive credit in the private nonfinancial sector as an important
indicator for the buildup of systemic risk (see Borio, Drehmann, Tsatsaronis (2011), Borio, Furfine, Lowe(2001), Borio, White, (2003)). A first-order transmission channel for a systemic financial crisis to affectthe real economy is via wealth effects of the household and nonfinancial business sectors. The leverageof these sectors, as well as their reliance on short term nonbank deposits for funds, can amplify thewealth effects. As highly indebted households and nonfinancial businesses are less able to withstandnegative shocks to incomes or asset values, they may have to sharply curtail spending in ways that canreinforce the effects of the shocks.
In the household sector, more highly-levered households are less able to absorb, for example,
the shock of a house price decline. Mian and Sufi (2009) show that a rise in household leveragemeasured at the county level, likely due to an increase in the supply of credit, is a strong predictor ofrecession severity. Mian and Sufi (2012) suggest that lower demand driven by the deterioration inhousehold balance sheets is responsible for a large share of job losses during 2007-09. For businesses,
insurance companies’ reach for yield behavior coincides with greater bond issuance by riskier firms,
suggesting ex post greater systematic risk and volatility (Becker and Ivashina, 2013). In addition,businesses that default or violate loan covenants as net worth declines are forced to cut back on

13

investment and employees, potentially amplifying the initial declines in spending if cutbacks arewidespread (Opler and Titman, 1994; Chava and Roberts, 2008; Falato and Liang, 2013).
Losses among households and businesses also can lead to mounting losses at financial
institutions. Such losses that impair capital adequacy of regulated banks and shadow banks can restrict
credit availability and further reduce aggregate demand through an adverse feedback loop in which lessaggregate demand reduces the value of collateral and makes it more difficult for the nonfinancial sector
to service their debt, further increasing losses to the financial sector (He and Krishnamurthy, 2012c,
Brunnermeier and Sannikov, 2012)

4. Financial Stability Considerations for Monetary and Macroprudential Policies
We have reviewed papers where in periods of economic expansions, accommodative monetary policy
can lead to buildups in financial vulnerabilities and increase risks to financial stability. However, since
tightening monetary policy to reduce vulnerabilities could have undesirable consequences for
macroeconomic activity, we turn next to the question of what macroprudential tools could be used. In
this section, we review papers that focus on the use of macroprudential tools, and interactions ofmacroprudential and monetary policy to mitigate asset overvaluations, rapid credit growth, and excessleverage and maturity transformation.
There are a variety of macroprudential tools that could be used, depending on the type ofvulnerability and in which sector of the financial system vulnerabilities occur. A categorization by theCommittee on the Global Financial System (2012) includes countercyclical capital buffers, sectoral
capital requirements, countercyclical liquidity requirements, margins and haircuts, and LTVs and DTIs.
However, some of these countercyclical tools are new and most of the other tools have not been usedwidely; thus their effectiveness in mitigating vulnerabilities is unknown. An empirical study by Kuttner
and Shim (2012) of the use of macroprudential tools in 57 countries from 1980 to 2012 identifies the useof sectoral risk weights, exposure limits, loss provisioning, LTVs, and DTIs. They find that LTVs andexposure limits can mitigate increases in house prices, and DTIs can reduce credit growth. Kuttner andShim (2012) document 662 actions, but about one-third were used by only five countries, so theirfindings may not be applicable broadly, given the diversity of financial systems across countries.
Macroprudential policies can tilt the risk-return tradeoff for monetary policy by pre-emptively
lowering vulnerabilities of the financial system. Supervisory and regulatory tools can target the stabilityof individual institutions or if there are externalities, aimed at the stability of the system as a whole. For
example, short-term funding fragilities can be addressed partly by removing the first-mover advantage
in the fixed net asset value of money market mutual funds; and risk shifting by insufficiently capitalizedbanks that leads to lower quality loans can be addressed by increasing capital requirements. Suchstructural macroprudential policies can be considered to be set exogenously for monetary policy, as
they typically do not vary with the business cycle. In contrast, cyclical macroprudential policies may
adjust endogenously with monetary policy. A simple approach to the interaction between cyclical14

macroprudential policy and monetary policy would be to think of them as being separable, invoking theTinbergen principle. The argument goes as follows: Monetary policy should narrowly focus on
macroeconomic objectives, i.e. the inflation-real activity trade off. Conditional on the stance ofmonetary policy, macroprudential policy would be used to mitigate vulnerabilities to achieve an
acceptable level of systemic risk.
However, this argument overlooks two important interactions between macroprudential andmonetary policies.6 On the one hand, cyclical macroprudential policies do not only impact
vulnerabilities, but also financial conditions, thus influencing the stance of monetary policy. For
example, if loose monetary policy causes reach for yield behavior, which could motivate tighter
macroprudential policy tools, such as a higher countercyclical capital buffer, the higher capitalrequirement would not only counteract the reach for yield vulnerability, but would tighten financial
conditions in a way similar to monetary policy tightening. A second interaction arises because of
shadow banking. Macroprudential policies imposed on the regulated sector could generate potentiallysizable regulatory arbitrage responses, pushing intermediation to shadow banking, which could offset
the tightening at regulated firms, leaving unclear the net effect on financial conditions.
As a result of the interactions between macroprudential and monetary policy transmission, andthe interdependencies between the risk-return and inflation-real activity tradeoffs when the economy isexpanding, monetary and macroprudential policies should be considered jointly. Decisions to
implement policies require policy makers to assess how quickly financial fragilities can build and how
costly it would be to financial stability in the event of a large adverse shock. These considerations
suggest a continuum for pre-emptive macroprudential actions, to deploy lower cost tools more
frequently and before there is strong evidence of excesses, if by doing so, it can reduce the odds of abuild up invulnerabilities with systemic consequences. Potential policies vary widely in their costs ofimplementation: Increased supervisory scrutiny targeted to specific firms and activities,
communications by authorities, or public recommendations by financial stability coordinating or
decision bodies (such as FSOC in the U.S. or the FPC in the U.K.) to regulators, financial institutions, ormarket participations are relatively inexpensive actions. At the other end of the cost spectrum, acountercyclical capital buffer could imply significant capital raising and international cooperation, andmonetary policy would affect all risk taking.
The interdependence between macroprudential and monetary policy has been examined by
Farhi and Tirole (2009, 2012). In their setting, financial intermediaries make private choices about
leverage and maturity transformation, taking into account anticipated monetary policy responses.
Loose interest rate policies increase the likelihood of future crises because they provide incentives for
greater maturity mismatch because central banks ex ante cannot commit not to inject liquidity after acrash, leading to excessive risk taking in the aggregate. Farhi and Tirole (2012) argue that pre-emptive
macroprudential policies, such as limits on short-term debt that mitigate excessive valuations due to risktaking would increase welfare.

The International Monetary Policy Fund (2013) proposes a complementary discussion of the interaction between
monetary and macroprudential policies.

615More broadly, a theory of the interdepence of macroprudential, fiscal, and monetary policies isprovided by Brunnermeier and Sannikov (2011, 2014). Their I-Theory stresses the importance of
spillover effects that link price stability, financial stability, and fiscal stability, and the difficulties ofseparation of the stability concepts. For example, financial instability prompts financial intermediaries
to shrink their balance sheets and create less inside money. Consequently the money multipliercollapses and Fisher deflation pressure emerges. This increases the real value of banks’ liabilities andworsens financial instability. Also monetary policy redistributes wealth to the ailing sector by changing
the relative value between government debt and money in order to stabilize the overall economy.
Of course, the consideration of both financial conditions and financial stability in the conduct ofmonetary policy is not without possible costs. Firstly, monetary policy tightening can result in risk
shifting incentives for intermediaries, leading them to take on more, not less risk (Landier, Thesmar,
Sraer, 2011). Furthermore, without clear priorities, incentive problems between price stability andfinancial stability could arise (Smets, 2013). For example, ex post monetary policy easing in a credit bustto inflate away some of the debt overhang could generate an inflation bias. If there are politicalpressures not to lean too hard, or to not engage in credit allocation, policy makers have incentives touse monetary policy ex post, which can then risk price stability.
In the remainder of this section, we discuss considerations for the use of monetary policy andmacroprudential policy to address financial vulnerabilities in the four sectors considered in the previous
section: asset markets, the banking sector, the shadow banking system, and the nonfinancial sector.
Table 3 summarizes existing macroprudential tools for each of these sectors.

A. Asset Markets
Macroprudential tools that can be used to mitigate risks from overvalued assets, such as poor
quality loans and mortgages, include tightening underwriting standards such as LTVs and DTIs, to theextent the debt is originated or distributed through firms subject to prudential regulations. Other tools
include countercyclical capital buffers, or higher risk weights or sectoral capital buffers for regulated
firms. In addition, if asset prices are being fueled by leverage, standards could be tightened on implicit
leverage through securitization or other risk transformations, or by limiting the debt provided toinvestors in either unsecured or secured funding markets by raising margins and haircuts.
Empirical evidence of the effectiveness of macroprudential tools on asset prices is scarce, andlimited to effects on house prices. Kuttner and Shim (2012) find that LTVs and exposure limits atfinancial institutions may help to reduce house price growth, using a sample of actions in 57 countries.
Looking at recent specific cases, the use of LTV limits combined with other actions in Hong Kong, Korea,
and Canada may have mitigated some growth in house prices.
Bernanke and Gertler (1999) analyze the extent to which monetary policy should react to asset
valuations. Bernanke and Gertler argue that monetary policy should target inflation flexibly and takeasset prices into account only to the extent that they impact the inflation-activity tradeoff. Some haveaccepted Bernanke and Gertler’s view with respect to equity market bubbles, as the burst of the late1990’s tech bubble, which was not fueled by credit provision by leveraged financial institutions,16

appeared to be successfully offset with changes in the stance of monetary policy. Others have moved
from this view. For example, Christiano, Ilutz, Motto, and Rostagno (2010) document that stock market
booms tend to be accompanied by low inflation. As a result, interest rate rules that focus narrowly on
inflation targets will destabilize asset markets and the broader economy. Interest rate rules should thus
be adjusted for asset valuations, for example by allowing an independent role for credit growth, toreduce the volatility of output and asset prices.
Gilchrist and Zakrajšek (2011, 2012) study monetary policy rules that augment the Taylor rulewith a credit spread. Gilchrist and Zakrajšek use a new New Keynesian model—augmented with thestandard Bernanke, Gertler, Gilchrist (1999) financial accelerator mechanism—which is capable ofproducing the dynamics of the U.S. economy during the recent financial crisis. The benefits of amonetary policy rule that incorporates credit spreads arise as asset prices anticipate the beneficial
effects of such a rule in mitigating the financial frictions. In a calibration of the model to U.S. data, thespread-augmented policy rule dampens the negative consequences of financial disruptions on real
economic activity, while engendering only a modest increase in inflation.
There is some empirical evidence suggesting that monetary policy in the U.S. does take the priceof risk into account. Bekaert and Hoerva (2013) estimate a Taylor rule that is augmented with measuresof financial market risk and uncertainty. They decompose equity-implied volatility as measured by the
VIX into a risk and an uncertainty component and find that Taylor rule residuals are particularly strongly
correlated with the uncertainty component of the VIX. Adrian, Moench, and Shin (2009) estimate a“macro risk premium” from a GDP tracking portfolio. In a reduced form vector autoregression, Adrian,
Moench and Shin find that monetary policy shocks significantly impact the macro risk premium, which inturn significantly forecasts real activity. Furthermore, the fed funds target depends significantly on themacro risk premium, even after taking account of inflation and output.
There is a strong case for pre-emptive monetary policy action to reduce over-valuation in credit
and housing markets as these assets are closely intertwined with the leverage and risk taking of thefinancial and the nonfinancial sectors. Still there needs to be some evaluation of whether monetary
policy would be effective, given the financial frictions such as asymmetric information or
mismeasurement of tail risks that lead to overvaluations, and whether other macroprudential tools canbe pre-emptive or can mitigate risk of fallout. Dokko et al (2009) show that deviations from the Taylor
rule explain only a small part of the rise in house prices in the U.S. leading up to the financial crisis.
Kuttner and Shim (2013) show for a cross-section of 57 countries that low short-term interest rates
contribute to house price increases and credit growth, but cannot account fully for the booms and busts.

B. Banking Sector
Macroprudential tools that could offset excessive risk taking in banking include the new Basel III
countercyclical capital buffer, which can be built up in boom times when the cost of equity is relatively
cheap, and deployed in downturns when the accumulation of capital is expensive. A build-up duringextended boom times would result in a higher capital buffer, leaving banks better equipped towithstand large adverse shocks. A release of the countercyclical capital buffer in a downturn would
17

mitigate pressures for banks to deleverage, thus mitigating the potentially adverse amplification offorced deleveraging during an economic downturn. In principle, the build-up and release of the buffer
would be a function of the pricing of risk, whereas capital required for microprudential objectives would
be a function of physical default risks. A tool that is similar to countercyclical capital requirements, butthat works in a more targeted fashion, is sectoral capital requirements. Sectoral capital requirements
would be built and released like a countercyclical buffer, but higher or lower capital charges would be
for specific asset classes.
Other policy tools include supervisory guidance and stress tests. Supervisory guidance, which
could be used to signal a need to improve risk management practices around potential future risks, is bydesign, flexible. Supervisory stress tests can address emerging vulnerabilities by adjusting the severityof the macroeconomic and financial scenarios, in practice working to offset pro-cyclicality inherent incapital regulations (Liang, 2013). Stress tests can also highlight potential salient risks, such as a sharp
rise in term premiums when interest rates have been low for an extended period. However, because
excessive tightening of prudential regulations for banks can be expected to push financial
intermediation into the shadow banking system, especially when the pricing of risk is low,macroprudential policies aimed at SIFIs should be complemented by prudential policies for the shadowbanking system.
Rigorous analysis of macroprudential tools in the presence of banking frictions withinequilibrium models is rapidly developing. For example, Kiley and Sim (2012) examine a setting wherebanks face an external finance premium. Modigliani-Miller is assumed to fail so that debt is cheaper
than equity and outside equity is the most expensive form of funding. The key friction in Kiley and Sim is
the pecuniary fire sale externality across banks, reflecting bank balance sheet problems. Kiley and Sim
evaluate policies to lean against credit growth, against asset prices, and against loan spreads. In
particular, they analyze a pro-cyclical capital buffer (interpreted as a tax on leverage) aimed at closing
the gap between private and social costs of bank debt. In their setting policies for loan spreads work
best. While Kiley and Sim feature a monetary policy rule, they do not look at the interaction of themonetary policy rule with the macroprudential instruments.
The prior to the 2007-09 financial crisis, the monetarist view that that inflation was always andeverywhere a monetary phenomenon had been largely replaced by New Keynesian theories wheremoney and credit played little role (see Woodford, 1998). However, even prior to the crisis, Christiano,
Motto, Rostagno (2006) argued that monetary policy which focuses narrowly on inflation may
inadvertently contribute to welfare reducing boom-bust cycles in real and financial variables. 7 The
authors showed that a policy of monetary tightening when credit growth is strong can mitigate suchproblems. The New Keynesian literature following the financial crisis has focused on incorporating
financial vulnerabilities into monetary policy models. Gertler and Kiyotaki (2011) develop a canonicalframework to analyze credit market frictions and aggregate economic activity in the context of the
2007-09 crisis, augmenting Bernanke and Gertler (1989) and Bernanke, Gertler, Gilchrist (1999) with afinancial sector. Gertler and Kiyotaki (2013) add a banking sector that features bank net worth and7

See Adrian and Shin (2006) and Gertler (2006) for related arguments.

18liquidity mismatch, which gives rise to bank runs, as in Diamond and Dybvig (1983). Woodford (2010)
proposes a Keynesian IS-LM model augmented with financial intermediary frictions, based on Curdia andWoodford (2010). In that setting, the financial intermediation friction gives rise to a state variable inaddition to inflation and real activity. That state variable can be mapped into credit spreads (loan lesspolicy rate), which in turn enters into the optimal monetary policy rule. Optimal policy is thus explicitly
dependent on credit supply conditions. Woodford (2011) studies optimal monetary policy in a settingwith financial crises and finds that inflation targeting rules should consider explicitly the possibility offinancial crises.
Gambacorta and Signoretti (2014) examine the performance of augmented Taylor rules that
adjust the policy rate in response to asset prices and credit indicators, comparing them to more
standard rules with flexible inflation targeting. They also use the setting of Curdia and Woodford (2010),
and additionally analyze the impact of high household leverage and a risk taking channel. Gambacorta
and Signoretti’s key result is that even if financial stability is not an explicit target for monetary policy,
monetary policy rules that enhance financial stability are desirable in the presence of supply shocks.
This is because financial frictions through borrower balance sheets and credit supply affect the tradeoffs faced by monetary policy. In particular, pre-emptive monetary policy enhances welfare.
While the first order effect of the risk taking channel of monetary policy is that tighter policy
reduces risk taking, there is a secondary effect that goes in the opposite direction. Tighter monetary
policy might bring institutions closer to the default boundary, resulting in risk shifting incentives. Thishas been documented by Landier, Sraer, Thesmar (2011) for the subprime crisis. In particular, Landier,
Sraer and Thesmar investigate the lending behavior of New Century Financial Corporation, a large
subprime lender in the run-up to the 2007-09 crisis. As the Fed began tightening rates in 2004, theincrease in rates led to a large, adverse shock in the value of the loan portfolio that New Century held
for investment purposes. New Century reacted to this loss to the value of its assets by lowering
underwriting standards and issuing deferred amortization mortgages. These loans were riskier, andmore sensitive to housing valuations, substantially increasing risk taking. New Century’s shareholders
thus gambled for resurrection, as their equity value was low, and their risk taking incentives (due tolimited liability) were large.
The potential presence of gambling for resurrection in the face of rising rates has important
implications for the conduct of monetary policy, as it suggests that increases in rates following
prolonged periods of low rates can generate the perverse effect where tighter rates lead to increased
risk taking, going against the traditional mechanism of the bank lending channel. In fact, in the U.S., theworst subprime mortgages were originated between 2005 and 2007, while the Fed was alreadytightening. The presence of risk-shifting incentives suggests that 1) macroprudential policy is apreferred tool, and 2) tightening should occur early. A theoretical setting that studies this second orderrisk shifting effect is presented by Dell’Ariccia and Marquez (2013) and Dell’Ariccia, Laeven, Marquez(2014). While risk shifting is theoretically possible in that setting, it is usually dominated by the firstorder effect which links rising rates to lower risk taking, when capital constraints are not binding.
However, in practice, under certain conditions such as when capital is constrained, the risk shifting
effect might be the dominant one.
19

C. Shadow Banking
Regulatory capital and accounting rules in the pre-crisis period had created significant incentives
for banks to shift assets off balance sheet into shadow bank special purpose entities (SPEs). Since then,bank regulatory and accounting reforms have been adopted to restrict regulatory arbitrage. For
example, Basel III reforms have increased the capital charge for providing explicit support to shadowbanks, assuming a higher drawdown rate under the LCR for credit and liquidity facilities, and the
Financial Accounting Standards Board adopted new rules that require sponsors to consolidate many
previously off-balance-sheet transactions. These reforms should help reduce shadow banking that isdone for the purpose of regulatory arbitrage. That said, more stringent banking regulations could also
increase incentives to move some activities away from banks, especially if demand for credit or for cashlike assets strengthens.
Macroprudential policy tools that affect shadow banking are not well defined, and are very
heterogeneous across entities and activities. Adrian (2014) reviews financial stability policies for the
shadow banking system, pointing out that the nature of policies differ widely across shadow banking
activities. While shadow banking activities are often regulated for market conduct and market
functioning, most shadow banking entities and activities are not subject to prudential regulation. As aresult, the availability of macroprudential policies for shadow banking is limited, though there is aninternational effort underway to improve shadow banking regulation. 8
One possible tool to address pro-cyclical incentives in secured funding markets, such as repo
and sec lending, is minimum standards for haircut practices, to limit the extent to which haircuts would
be reduced in benign markets. Margins and haircuts effectively set the maximum amount of leveragethat borrowers can take on. Margins and haircuts are set by exchanges, clearing houses, brokersdealers, and in repo transactions. In practice, however, such margins and haircuts are set from a purely
microeconomic risk management perspective. Macroprudential considerations would promote higher
through-the-cycle margins because they could materially reduce the ability of shadow banking
participants to take on excessive leverage in expansions.
Goodhart, Kashyap, Tsomocos, Vardoulakis (2012, 2013) consider the impact of margin
constraints on shadow banks, capital and liquidity requirements on banks, and loan-to-value limits on
borrowers in a dynamic equilibrium setting. The presence of a shadow banking sector generates firesale externalities on the banking sector and the household sectors, as haircuts tend to rise in times ofstress. Limiting shadow bank leverage by setting margins pre-emptively can mitigate this fire sale
externality, but comes at the cost of reduced credit intermediation in the boom. Goodhart et al do not
The Financial Stability Board, as directed by the G20 Leaders, has been developing policy recommendations tostrengthen the oversight and regulation of the shadow banking sector. The set of proposals attempt to: 1) limit
the spillover of shadow banking risks to the banking sector, 2) reduce or eliminate the first-mover advantage in
U.S. money market mutual funds that makes them vulnerable to runs, 3) assess and mitigate risks of other shadowbanking entities, 4) assess and align the incentives in securitization, and 5) dampen risks and the pro-cyclicalincentives in secured financing.
8

20

find countercyclical capital requirements on banks to be particularly useful at preempting systemic riskin the presence of shadow bank intermediaries, as the shadow banking system can arbitrage theincreased capital requirement. However, the joint usage of countercyclical capital requirements andcountercyclical margin setting can be more effective. A constraint on the effectiveness of capital
policies is the fact that collateral values are increasing in asset price booms, making capital constraints
ineffective as preemptive tool, though they are still useful as a prudential instrument. For pre-emptive
purposes, Goodhart et al find liquidity requirements to be more effective in constraining risk taking.
However, the tightness of liquidity requirements is tightly linked to the stance of monetary policy, andsafe asset availability more generally.
The currently limited availability of macroprudential policy tools for the shadow banking system,and the large share of credit intermediation in the shadow banking system leaves monetary policy as animportant instrument. Stein (2012) studies monetary policy in the presence of shadow bankintermediation. In Stein’s setting, shadow bank intermediaries create money-like short term debt. Dueto an externality, shadow banks issue too much short term debt, creating excess vulnerability tofinancial crises. Stein points out that balance sheet policies of the central bank can be a usefulcomplement to open market operations, as balance sheet policies affect the value to the shadowbanking system of issuing short term debt, and hence regulate the magnitude of excess vulnerability inthe shadow banking system.

D. Nonfinancial Sector
Macroprudential tools to address emerging imbalances in the nonfinancial sector aim primarily
at improving underwriting standards. For example, increasing loan-to-value (LTV) ratios or debt-toincome (DTI) ratios on mortgages can limit the exposures of households and businesses to a collapse in
prices, thereby bolstering their resilience. Goodhart et al (2012) study LTV limits in conjunction withcapital and liquidity regulations. In their model, LTV tools are relatively ineffective in the presence ofasset price booms. One reason is that as the rise in asset prices boost collateral values, it becomes
relatively easier to satisfy LTV constraints.
Kuttner and Shim (2013) provide evidence based on a cross-section of 57 countries that limits on
debt service-to-income ratios can help to restrain housing credit, thereby moderating the cycle, while
LTVs are less successful at restraining credit growth since credit can increase with real estate values. In
the U.S., there is some evidence that the use of LTVs and maturity caps in the early 1950s, as imposedby the Federal Reserve Board, were effective in reducing housing starts, but Congress removed that
authority, partly reflecting uneasiness with the Fed targeting particular types of credit growth (Elliott,
Feldberg, and Lehnert, 2013).
Because of significant differences across countries in financial system structures that couldchange the effectiveness of macroprudential tools, it will be instructive to examine case studies. In
recent years, a number of countries have increased loan-to-value ratios on residential mortgages to limit
an increase in exposures of households to a collapse in prices, and to lean against rising real estate
prices. For example, Hong Kong has increased LTVs multiple times on residential mortgages in the past21

decade to mitigate the house price boom. As prices have continued to rise, they have also “stresstested” borrowers for resilience to increases in interest rates. Korea imposed LTV and DTI limits onhouseholds, which appears to have reduced mortgage loans, housing transactions, and house prices inthe six months after implementation. The Bank of Israel took several steps between 2009 and 2011 torein in a housing boom, including a supplementary reserve requirement for banks’ mortgage loans withhigh LTVs, increased capital requirements for mortgages with floating rates and high LTVs, andrestricting the adjustable interest rate component of mortgage loans. Canada has employed a mix of
LTV and DTI restrictions, in addition to maturity caps and mortgage insurance limits, to restrain a buildup in household leverage and house prices.
The role for monetary policy to reduce leverage in the nonfinancial sector is unclear, as is the
combined effects of higher rates on the nonfinancial sector and the financial sector. Korinek and Simsek(2014) consider a setting where borrowers do not take the negative aggregate demand externality ofleverage into account, resulting in excessive risk taking. Monetary policy is constrained at the zero
lower bound, giving rise to a shortfall in aggregate demand. Debt limits (or mandatory insurance) can
improve welfare. An interesting result of their model is that it highlights different possible effects formonetary policy. The conventional view to mitigate a buildup in leverage would be to raise interest
rates. However, a rise in rates could prompt a recession, and borrowers may want to borrow even more
to smooth consumption. In addition a rise in rates transfers wealth from borrowers to savers, providing
another incentive to borrow. Thus, Korinek and Simsek (2014) find macroprudential policies to be more
efficient than monetary policies for reducing excessive leverage. Efficiency requires setting a wedge
between borrowers’ and lenders’ relative incentives to hold bonds, whereas interest rate policies createa different inter-temporal wedge that affects all incentives equally.

22

5. Conclusion
The stance of monetary policy is transmitted to the real economy via multiple channels. In asset
markets, the pure expectations channel is complemented by the risk-taking channel, which operates via
changes in the pricing of risk. Risk taking is conducted in asset markets, by the banking sector, theshadow banking system, and nonfinancial sectors. As financial intermediation has become increasingly
market based, the risk-taking channel has become more important, particularly in the shadow banking
system. When the economy is close to potential, the risk taking associated with expansionary monetary
policy tends to cause the buildup of vulnerabilities that can generate systemic financial crises whenadverse shocks hit.
Macroprudential policies are the first order defense against such buildups of vulnerabilities.
However, macroprudential policies only impact a limited set of financial institutions due to shadowbanking, have limited international reach, and are potentially subject to long implementation lags.
Monetary policy, on the other hand, impacts funding conditions for all intermediaries, almost
immediately, and has some global reach.
If monetary policy takes financial vulnerabilities into account, it would not imply thatmacroeconomic and macroprudential objectives are necessarily in conflict. For example, during therecovery phase following a recession or crisis, macroeconomic objectives are likely aligned withmacroprudential objectives as inflation and real activity tend to be suppressed at the same time as risktaking in the financial sector is low. Similarly, in a crisis, expansionary monetary policy that increases
risk taking might be beneficial to financial stability. At other times a conflict might arise if inflation
remains at target, real activity is close to potential, but financial vulnerabilities are building as risk
appetite and asset valuations become elevated. In the latter scenario, conditional on the stance ofmacroprudential policy, a relatively tighter monetary policy might be chosen than one implied by asimple Taylor rule, as estimates of downside risk to future outcomes will have increased due to thebuildup of these vulnerabilities.
When financial vulnerabilities increase downward tail risk, these tail risks may not only dependon the current output gap, but also additional state variables. For example Stein (2014) has recently
argued that estimated credit risk premia provide valuable information about the amount of tail risk,
while Kocherlakota (2014) has argued that monetary policy should take financial vulnerabilities into
account once estimated future tail risk is beyond a threshold. Dudley (2010) argues that monetary
policy should take asset bubbles into account to the extent that they are associated with excessive
leverage. Woodford (2010) also uses variables such as credit spreads as additional variables in a Taylor
rule, while Gambarcorta and Signoretti (2014) argue that indicators of financial sector leverage should
directly enter into an augmented Taylor rule. We note again that financial stability objectives arecompatible with the dual mandate as the buildup of financial vulnerability increases tail risks to inflation
and real activity mandates.

23

Literature
Acharya, Viral, Philipp Schnabl, and Gustavo Suarez (2013). "Securitization Without Risk Transfer,"
Journal of Financial Economics 107(3), 515-536.
Adrian, Tobias (2014). “Financial Stability Policies for Shadow Banking,” Federal Reserve Bank of New
York Staff Reports 664.
Adrian, Tobias and Adam B. Ashcraft (2012a). “Shadow Bank Regulation,” Annual Review of Financial
Economics 4(1), 99-140.
Adrian, Tobias and Adam B. Ashcraft (2012b). “Shadow Banking: A Review of the Literature,” Palgrave
Dictionary of Economics.
Adrian, Tobias, Adam B. Ashcraft, and Nicola Cetorelli (2013). “Shadow Bank Monitoring,” Federal
Reserve Bank of New York Staff Reports, 638.
Adrian, Tobias, Daniel Covitz, J. Nellie Liang (2013). “Financial Stability Monitoring,” Federal Reserve
Bank of New York Staff Report 601, and Board of Governors of the Federal Reserve Finance andEconomics Discussion Series 2013-21.
Adrian, Tobias, and Nina Boyarchencko (2012). “Intermediary Leverage Cycles and Financial Stability,”
Federal Reserve Bank of New York Staff Report 567.
Adrian, Tobias, Richard K. Crump, and Emanuel Moench (2012). “Pricing the Term Structure with Linear
Regressions,” Federal Reserve Bank of New York Staff Report 340.
Adrian, Tobias, Erkko Etula, and Tyler Muir (2012). “Financial Intermediaries and the Cross-Section ofAsset Returns,” Journal of Finance, Forthcoming.
Adrian, Tobias, Emanuel Moench, and Hyun Song Shin (2010). “Financial Intermediation, Asset Prices,
and Macroeconomic Dynamics,” Federal Reserve Bank of New York Staff Report 422.
Adrian, Tobias and Hyun Song Shin (2006). “Money, Liquidity, and Financial Cycles,” paper presented at
the fourth ECB Central Banking Conference, The Role of Money: Money and Monetary Policy in the
Twenty-First Century," Frankfurt, November 9-10, 2006.
http://lasil-sladi.org/files/live/sites/iheid/files/shared/iheid/research/projects/historical_imagination/roleofmoneyen2008en.pdf

Adrian, Tobias and Hyun Song Shin (2008). “Financial Intermediaries, Financial Stability, and Monetary
Policy, “ Federal Reserve Bank of Kansas City Jackson Hole Economic Symposium Proceedings, 287-334.
Adrian, Tobias and Hyun Song Shin (2009a). “Money, Liquidity and Monetary Policy,” American
Economic Review Papers & Proceedings 99 (2), 600-609.
Adrian, Tobias and Hyun Song Shin (2009b). “Prices and Quantities in the Monetary Policy Transmission
Mechanism, “ International Journal of Central Banking 5 (4), 131-142.
Adrian, Tobias, and Hyun Song Shin (2010). “Liquidity and Leverage,” Journal of Financial Intermediation
19(3), 418-37.
Adrian, Tobias and Hyun Song Shin (2011a). “Financial Intermediaries and Monetary Economics,”
Handbook of Monetary Economics 3A, ch. 12, ed. by Benjamin Friedman and Michael Woodford, 601650.
Adrian, Tobias and Hyun Song Shin (2011b). “Financial Intermediary Balance Sheet Management,”
Annual Review of Financial Economics 3.
24Adrian, Tobias, and Hyun Song Shin (2014). “Procyclical Leverage and Value-at-Risk,” Review of Financial
Studies 27(2), 373-403.
Allen, Franklin and Douglas Gale (2000), “Bubbles and Crises,” Economic Journal 110, 236-255.
Altunbas, Yener, Leonardo Gambacorta, and David Marques-Ibanez (2010). “Bank Risk and Monetary
Policy,” Journal of Financial Stability 6(3), 121-129.
Angelini, Paolo, Stefano Neri, and Fabio Panetta (2012). “Monetary and Macroprudential Policies,”
European Central Bank Working Paper 1449.
Angeloni, Ignazio, and Ester Faia (2013). “Capital Regulation and Monetary Policy with Fragile Banks,”
Journal of Monetary Economics 36(11), 311-324.
Ashcraft, Adam, Paul Goldsmith-Pinkham, Peter Hull, and James Vickery, J. (2011). “Credit Ratings andSecurity Prices in the Subprime MBS Market,” American Economic Review: Papers & Proceedings 101(3),115-119.
Becker, Bo, and Victoria Ivashina (2013). “Cyclicality of Credit Supply: Firm Level Evidence,” Journal of
Monetary Economics, forthcoming.
Bekaert, Geert, and Marie Hoerova (2013). “The VIX, the Variance Premium and Stock Market Volatility,”
Journal of Econometrics, forthcoming.
Bekaert, Geert, Marie Hoerova, and Marco Lo Duca (2013). “Risk, Uncertainty and Monetary Policy,”
Journal of Monetary Economics 60(7), 771-788.
Bernanke, Ben S., and Alan S. Blinder (1988). “ Credit, Money, and Aggregate Demand,” American
Economic Review 78(2), 435-439.
Bernanke, Ben S., and Alan S. Blinder (1992). “The Federal Funds Rate and the Channels of Monetary
Transmission,” American Economic Review 82(4), 901-921.
Bernanke, Ben, and Mark Gertler (1989). “Agency Costs, Net Worth, and Business Fluctuations,”
American Economic Review 79(1), 14-31.
Bernanke, Ben, and Mark Gertler (1995). “Inside the Black Box: The Credit Channel of Monetary Policy
Transmission,” Journal of Economic Persepctives 9(1), 27-48.
Bernanke, Ben S., Mark Gertler, and Simon Gilchrist (1999). “The Financial Accelerator in a Quantitative
Business Cycle Framework,” Handbook of Macroeconomics 1: 1341-1393.
Bernanke, Ben, Mark Gertler, and Simon Gilchrist (1999). “The Financial Accelerator in a Quantitative
Business Cycle Framework,” Handbook of Macroeconomics 1, 1341-1393.
Bernanke, Ben S., and Kenneth N. Kuttner (2005). “What Explains the Stock Market's Reaction to Federal
Reserve Policy?” Journal of Finance, 60(3), 1221-1257.
Bianchi, Javier, and Enrique Mendoza (2011). “Overborrowing, Financial Crises and Macroprudential
Policy,” IMF Working Paper 11/24.
Borio, Claudio, Mathias Drehmann, and Kostas Tsatsaronis (2011). “Anchoring Countercyclical Capital
Buffers: The role of Credit Aggregates,” International Journal of Central Banking 7(4), 189-240.
Borio, Claudio, Craig Furfine, and Philip Lowe (2001). “Procyclicality of the Financial System and
Financial Stability: Issues and Policy Options,” BIS Working Paper 1.

25

Borio, Claudio, and William White (2003). “Whither Monetary and Financial Stability? The Implicationsof Evolving Policy Regimes,” Proceedings of the Kansas City Fed Economic Symposium.
Brunnermeier, Markus K., and Lasse Heje Pedersen (2009). “Market Liquidity and Funding Liquidity,”
Review of Financial Studies, 22(6), 2201-2238.
Brunnermeier, Markus, and Yuliy Sannikov (2012). “A Macroeconomic Model with a Financial Sector,”
Princeton University Working Paper.
Brunnermeier, Markus, and Yuliy Sannikov (2011). “The I Theory of Money,” Princeton University
Working Paper.
Brunnermeier, Markus, and Yuliy Sannikov (2014). “Monetary Analysis: Price and Financial Stability,”
Paper presented at the ECB Forum on Central Banking, 26 May 2014, Sintra, Portugal.
Campbell, Sean D., Morris A. Davis, Joshua Gallin, and Robert F. Martin (2009). “What Moves Housing
Markets: A Variance Decomposition of the Rent–Price Ratio,” Journal of Urban Economics 66(2), 90-102.
Campbell, John Y., and Robert J. Shiller (1984). “A Simple Account of the Behavior of Long term Interest
Rates,” American Economic Review 74(2), 44-48.
Campbell, John Y., and Robert J. Shiller. (1988) “The dividend-price ratio and expectations of future
dividends and discount factors,” Review of Financial Studies 1(3), 195-228.
Case, Karl, and Robert J. Shiller (2003). “Is There a Bubble in the Housing Market?“ Brookings Papers on
Economic Activity 2003(2), 299-362.
Chava, Sudheer, and Michael R. Roberts (2008). “How Does Financing Impact Investment? The Role ofDebt Covenants,” Journal of Finance, 63(5), 2085-2121.
Chodorow-Reich, Gabriel (2014). ‘’Effects of Unconventional Monetary Policy on Financial Institutions,”
Harvard University Working Paper.
Christiano, Lawrence, Cosmin Ilut, Roberto Motto, Massimo Rostagno (2010). “Monetary Policy andStock Market Booms,” Federal Reserve Bank of Kansas City Jackson Hole Symposium.
Christiano, Lawrence, Roberto Motto, Massimo Rostagno (2006) “Two Reasons Why Money and Credit
May be Useful in Monetary Policy,” paper presented at the fourth ECB Central Banking Conference, The
Role of Money: Money and Monetary Policy in the Twenty-First Century," Frankfurt, November 9-10,
2006. http://lasil-sladi.org/files/live/sites/iheid/files/shared/iheid/research/projects/historical_imagination/roleofmoneyen2008en.pdf
Christensen, Ian, Césaire Meh, and Kevin Moran (2011). “Bank Leverage Regulation and Macroeconomic
Dynamics,” Bank of Canada Working Paper 2011-32.
Cochrane, John H (2011). “Presidential Address: Discount rates,” Journal of Finance 66)4), 1047-1108.
Cochrane, John H., and Monika Piazzesi (2005). “Bond Risk Premia,” American Economic Review 90(1),138-160.
Committee on the Global Financial System (2012). “Operationalizing the Selection and Application ofMacroprudential Instruments,” CGFS Paper 48.
Coval, Joshua, Jakub Jurek, and Erik Stafford (2009). “The Economics of Structured Finance,” Journal of
Economic Perspectives, 3-26.
Covitz, Daniel, Nellie Liang, and Gustavo A. Suarez (2013). “The Evolution of a Financial Crisis: Collapse of
the Asset‐Backed Commercial Paper Market,” Journal of Finance 68(3), 815-848.

26

Curdia, Vasco, and Michael Woodford (2010). “Credit Spreads and Monetary Policy,” Journal of Money,
Credit and Banking 42(1), 3-35.
Danielson, J., Hyun Song Shin, and Jean-Pierre Zigrand (2012). “Procyclical Leverage and Endogenous
Risk,” London School of Economics Working Paper.
Dell'Ariccia, Giovanni, and David Marquez (2012). “The Role of Real Interest Rates on Bank Leverage andRisk Taking,” International Monetary Fund Working Paper.
Dell'Ariccia, Giovanni, and David Marquez (2012). “Interest Rates and the Bank Risk taking Channel,”Annual Review of Financial Economics Vol. 5: 123–141.
Dell'Ariccia, M. G., Laeven, M. L., and Suarez, M. G. (2013). “Bank Leverage and Monetary Policy's Risk
taking Channel: Evidence from the United States,” International Monetary Fund Working Paper 13-143.
DellʼAriccia, Giovanni, Luc Laeven, and Robert Marquez (2014). “Real Interest Rates, Leverage, and Bank
Risk taking,” Journal of Economic Theory 149, 65-99.
Diamond, Douglas W., and Philip H. Dybvig (1983). “Bank Runs, Deposit Insurance, and Liquidity,” The
Journal of Political Economy 401-419.
Dokko, Jane, Brian Doyle, Michael Kiley, Jinil Kim, Shane Sherlund, Jae Sim, and Skander Van den Heuvel(2009). “Monetary policy and the Housing Bubble,” Federal Reserve Board Finance and Economics
Discussion Series 2009-49.
Drechsler, Itamar, Alexi Savov, and Philipp Schnabl (2014). “A Model of Monetary Policy and Risk
Premia,” New York University Working Paper.
Duarte, Fernando, and Thomas Eisenbach (2013). “Fire-sale Spillovers and Systemic Risk,” Federal
Reserve Bank of New York Staff Report 645.
Dudley, William (2010). “Asset Bubbles and the Implications for Central Bank Policy,” Remarks at the
Economic Club of New York, April 7, 2010. http://www.newyorkfed.org/newsevents/speeches/2010/dud100407.html
Elliott, Douglas J., Greg Feldberg, and Andreas Lehnert. (2013) “The History of Cyclical Macroprudential
Policy in the United States,” Federal Reserve Board Finance and Economics Discussion Series 2013-29.
Elton, Edwin, Martin Gruber, Deepak Agrawal, and Christopher Mann (2001). “Explaining the Rate
Spread on Corporate Bonds,” Journal of Finance 56(1), 247-278.
Falato, Antonio, and Nellie Liang (2013). “Do Creditor Rights Increase Employment Risk? Evidence from
Loan Covenants,” Working Paper.
Farhi, Emmanuel, and Jean Tirole (2009). “Leverage and the Central Banker's Put,” American Economic
Review Papers & Proceedings 99(2), 589-593.
Farhi, Emmanuel, and Jean Tirole (2012). “Collective Moral Hazard, Maturity Mismatch, and Systemic
Bailouts,” American Economic Review 102(1), 60-93.
Feroli, Michael, Kermit L. Schoenholtz, and Hyun Song Shin (2014). “Market Tantrums and Monetary
Policy,” U.S. Monetary Policy Forum Report No.8, Initiative on Global Markets, University of Chicago.
Fostel, Ana, and John Geanakoplos (2008). “Leverage Cycles and the Anxious Economy,” American
Economic Review 98(4), 1211-1244.
Gallin Joshua (2013). “Shadow Banking and the Funding of the Nonfinancial Sector,” Federal Reserve
Board Finance and Economics Discussion Series 2013-50.

27

Gambacorta, Leonardo, and Federico Signoretti (2014). “Should Monetary Policy Lean Against the
Wind?: An Analysis based on a DSGE Model with Banking,” Journal of Economic Dynamics and Control,
forthcoming.
Geanakoplos, John (2003). “Liquidity, Default, and Crashes: Endogenous Contracts in General
Equilibrium,” Advances in Economics and Econometrics: Theory and Applications, Eighth World
Conference, Volume II, Econometric Society Monographs.
Geanakoplos, John (2010). “The Leverage Cycle,” in NBER Macroeconomics Annual 2009, ed. D
Acemoglu, K Rogoff, M Woodford. Chicago: University of Chicago Press.
Gennaioli, Nicola, Andrei Shleifer, and Robert W. Vishny (2013). “A Model of Shadow Banking,” Journalof Finance, 68(4), 1331-1363.
Gertler, Mark (2006). “Incorporating Real and Financial Sector Data Within an Inflation Targeting
Framework,” paper presented at the fourth ECB Central Banking Conference, The Role of Money: Moneyand Monetary Policy in the Twenty-First Century," Frankfurt, November 9-10, 2006. http://lasilsladi.org/files/live/sites/iheid/files/shared/iheid/research/projects/historical_imagination/roleofmoneyen2008en.pdf

Gertler, Mark, and Peter Karadi (2013). “Qe 1 vs. 2 vs. 3...: A Framework for Analyzing Large-scale Asset
Purchases as a Monetary Policy Tool,” International Journal of Central Banking, 9(1), 5-53.
Gertler, Mark, and Nobuhiro Kiyotaki (2010). “Financial Intermediation and Credit Policy in Business
Cycle Analysis,” Handbook of Monetary Economics 3(11), 547-599.
Gertler, Mark, and Nobuhiro Kiyotaki (2012). “Banking, Liquidity, and Bank Runs in an Infinite Horizon
Economy,” National Bureau of Economic Research Working Paper 19129.
Gilchrist, Simon, David López-Salido, and Egon Zakrajšek (2014). “Monetary Policy and Real Borrowing
Costs at the Zero Lower Bound,” Boston University Working Paper.
Gilchrist, Simon, and Egon Zakrajšek (2011). “Monetary Policy and Credit Supply Shocks,” IMF Economic
Review 59(2), 195-232.
Gilchrist, Simon, and Egon Zakrajšek (2012). “Credit Supply Shocks and Economic Activity in a Financial
Accelerator Model,” in Rethinking the Financial Crisis, ed. Alan Blinder, Andrew Lo and Robert Solow,
Russell Sage Foundation, 37-72.
Gilchrist, Simon, and Egon Zakrajšek (2012). “Credit Spreads and Business Cycle Fluctuations,” American
Economic Review 102(4), 1692-1720.
Goodhart, Charles, Anil K. Kashyap, Dimitrios P. Tsomocos, and Alexandros Vardoulakis (2012).
“Financial Regulation in General Equilibrium,” National Bureau of Economic Research Working Paper
17909.
Goodhart, Charles, Anil K. Kashyap, Dimitrios P. Tsomocos, and Alexandros Vardoulakis (2013). “AnIntegrated Framework for Analyzing Multiple Financial Regulations,” International Journal of Central
Banking 9(1), 109-143.
Gorton, Gary, and Andrew Metrick (2012). “Securitized Banking and the Run on Repo,” Journal of
Financial Economics, 104(3), 425-451.
Greenwood, Robin, and Samuel G. Hanson (2012). “Share Issuance and Factor Timing,” Journal of
Finance 67(2), 761-798.
Hanson, Samuel G., Anil K. Kashyap, and Jeremy C. Stein (2011). “A Macroprudential Approach to
Financial Regulation,” Journal of Economic Perspectives 25(1), 3-28.
28

Hanson, Samuel G., and Jeremy C. Stein (2012). “Monetary Policy and Long term Real Rates,” Board ofGovernors of the Federal Reserve Finance and Economics Discussion Series 2012-46.
Harvey, Campbell R., and Akhtar Siddique (1999). “Autoregressive Conditional Skewness,” Journal of
Financial and Quantitative Analysis 34(4), 465-487.
Harvey, Campbell R., and Akhtar Siddique (2000). “Conditional Skewness in Asset Pricing Tests,” Journalof Finance 55(3), 1263-1295.
Haughwout, Andrew, Donghoon Lee, Joseph Tracy, and Wilbert van der Klaauw (2011). “Real Estate
Investors, the Leverage Cycle, and the Housing Market Crisis,” FRB of New York Staff Report 514.
He, Zhiguo, and Arvind Krishnamurthy (2012a). “A Model of Capital and Crises,” Review of Economic
Studies 79(2), 735-777.
He, Zhiguo, and Arvind Krishnamurthy (2012b). “Intermediary Asset Pricing,” American Economic
Review 103(2), 1-42.
He, Zhiguo, and Arvind Krishnamurthy (2012c). “A Macroeconomic Framework for Quantifying Systemic
Risk,” Working Paper.
Huang, Jing-zhi, and Ming Huang (2012). “How Much of the Corporate-Treasury Yield Spread is Due toCredit Risk?“ Review of Asset Pricing Studies 2(2), 153-202.
International Monetary Fund (2013). “The Interaction of Monetary and Macroprudential Policies,” IMF
Policy Paper http://www.imf.org/external/np/pp/eng/2013/012913.pdf
Jiménez, Gabriel, Steven Ongena, José-Luis Peydró and Jesús Saurina (2012). “Credit Supply andMonetary Policy: Identifying the Bank Balance-Sheet Channel with Loan Applications,” American
Economic Review 102(5), 2301-26.
Kashyap, Anil, Richard Berner, and Charles Goodhart (2011). “The Macroprudential Toolkit,” IMF
Economic Review 59(2), 145-161.
Kashyap, Anil K., and Jeremy C. Stein (1994). “Monetary Policy and Bank Lending,” in Monetary Policy,edited by N. Gregory Mankiw, University of Chicago Press, 221-256
Kashyap, Anil K., and Jeremy C. Stein (1995). “The Impact of Monetary Policy on Bank Balance Sheets,”
Carnegie-Rochester Conference Series on Public Policy 42, 151-195
Kashyap, Anil K., and Jeremy C. Stein (2000). “What Do a Million Observations on Banks Say about theTransmission of Monetary Policy?“ American Economic Review 90(3), 407-428.
Kashyap, Anil, Jeremy Stein, and David Wilcox (1993). “The Monetary Transmission Mechanism:
Evidence From the Composition of External Finance,” American Economic Review 83(1), 78-98.
Kiley, Michael and Jae Sim (2012). “Intermediary Leverage, Macroeconomic Dynamics, andMacroprudential Policy,” Board of Governors of the Federal Reserve Working Paper.
Kiyotaki, Nobuhiro, and John Moore (1997). “Credit chains,” Journal of Political Economy 105(21), 211248.
Kim, Don H., and Jonathan H. Wright (2005). “An Arbitrage-Free Three-Factor Term Structure Modeland the Recent Behavior of Long term Yields and Distant-Horizon Forward Rates,” Finance andEconomics Discussion Series 2005-33.
Kiyotaki, Nobuhiro and John Moore (1997). “Credit Cycles,” Journal of Political Economy 105(2), 211248.
29

Kocherlakota, N. (2014). Discussion of 2014 USMPF Monetary Policy Report. In speech delivered at the
US Monetary Policy Forum, a conference sponsored by the Initiative on Global Markets at the Universityof Chicago Booth School of Business, held in New York, February (Vol. 28).
http://www.minneapolisfed.org/news_events/pres/speech_display.cfm?id=5272

Korinek, Anton, and Alp Simsek (2014). “Liquidity Trap and Excessive Leverage,” NBER Working Paper
19970.
Krishnamurthy, Arvind, Stefan Nagel, and Dmitry Orlov (2012). “Sizing Up Repo,” NBER Working Paper
17768.
Kuttner, Kenneth, Ilhyock Shim (2012), “Taming the Real Estate Beast: The Effects of Monetary andMacroprudential Policies on House Prices and Credit,” in Property Markets and Financial Stability,
Reserve Bank of Australia.
Kuttner, Kenneth, Ilhyock Shim (2013), “Can non-interest rate policies stabilize housing markets:
evidence from a panel of 53 economies,” BIS working paper, No. 433, November.
Landier, Augustin, David Sraer, and David Thesmar (2011). “The Risk-shifting Hypothesis: Evidence from
Subprime Originations,” Toulouse School of Economics Working Paper 11.
Liang, Nellie (2012). “Financial Stability: Lessons Learned From the Recent Crisis and Implications for theFederal Reserve,” in The Role of Central Banks in Financial Stability: How Has It Changed? D.Evanoff,
G.Kaufman, C.Holthausen and M.Kremer, Editors. World Scientific Publishing Co. Pte. Ltd, New Jersey,
Forthcoming.
Liang, Nellie (2013). “Implementing Macroprudential Policies,” Conference on Financial Stability
Analysis, Federal Reserve Bank of Cleveland and Office of Financial Research, May 31, 2013.
Lorenzoni, Guido (2008). “Inefficient Credit Booms,” Review of Economic Studies 75(3), 809-833.
Loutskina, Elena, and Philip E. Strahan (2009). “Securitization and the Declining Impact of Bank Financeon Loan Supply: Evidence from Mortgage Originations,” Journal of Finance 64(2), 861-889.
Maddaloni, Angela, and José-Luis Peydró (2011). “Bank Risk taking, Securitization, Supervision, and Low
Interest Rates: Evidence from the Euro-area and the US Lending Standards,” Review of Financial Studies
24(6), 2121-2165.
Martin, Antoine, David Skeie, and Ernst-Ludwig Von Thadden (2012). “Repo Runs,” Federal Reserve Bankof New York Staff Report 444.
Merrill, Craig, Taylor Nadauld, Philip Strahan (2014). “Final Demand for Structured Finance Securities,”
SSRN Working Paper 2380859.
Mian, Atif, and Amir Sufi (2009). “The Consequences of Mortgage Credit Expansion: Evidence from the
US Mortgage Default Crisis,” The Quarterly Journal of Economics 124(4), 1449-1496.
Mian, Atif, and Amir Sufi (2010). “Household Leverage and the Recession of 2007–09,” IMF Economic
Review 58(1), 74-117.
Mian, Atif, and Amir Sufi (2011). “House Prices, Home Equity-Based Borrowing, and the US Household
Leverage Crisis,” American Economic Review 101(5), 2132-2156.
Mian, Atif, and Amir Sufi (2012). “What explains high unemployment? The aggregate demand channel,”
National Bureau of Economic Research Working Paper 17830.

30

Moreira, Alan, and Alexi Savov (2013). “The Macroeconomics of Shadow Banking,” Yale University
Working Paper.
Morris, Stephen, and Hyun Song Shin (2014). “Risk taking Channel of Monetary Policy: A Global GameApproach,” Princeton University Working Paper.
Nuño, Galo and Carlos Thomas (2014). “Bank Leverage Cycles,” Bank of Spain Working Paper 1222
Opler, Tim C., and Sheridan Titman (1994). “Financial Distress and Corporate Performance,” Journal of
Finance, 49(3), 1015-1040.
Paligorova, Teodora and João Santos (2012). “Monetary Policy and Bank Risk taking: Evidence from the
Corporate Loan Market,” Federal Reserve Bank of New York Staff Report.
Peek, Joe, and Eric Rosengren (1995). “Bank Regulation and the Credit Crunch,” Journal of Banking &Finance, 19(3), 679-692.
Peek, Joe, and Eric S. Rosengren (2013). “The Role of Banks in the Transmission of Monetary Policy,”Federal Reserve Bank of Boston Public Policy Discussion Paper 13-5.
Piazzesi, Monika and Martin Schneider (2011). “Trend and Cycle in Bond Premia,” Stanford University
Working Paper.
Pozsar, Zoltan, Tobias Adrian, Adam Ashcraft, and Hayley Boesky (2010). “Shadow Banking,” Federal
Reserve Bank of New York Staff Report 458.
Rajan, Raghuram G. (2005). “Has Financial Development Made the World Riskier?” Proceedings of theFederal Reserve Bank of Kansas City Economics Symposium: 313—69.
Rajan, Raghuram G. (2006). “Has Finance Made the World Riskier?” European Financial Management,
12(4), 499-533.
Schularik, Moritz and Alan M. Taylor (2012) “Credit Booms Gone Bust: Monetary Policy, Leverage
Cycles, and Financial Crisis, 1870-2008. American Economic Review, 102(2), 1029-1061.
Stein, Jeremy C. (2012). “Monetary Policy as Financial Stability Regulation,” Quarterly Journal of
Economics 127(1), 57-95.Stein, Jeremy (2013). “Overheating in Credit Markets: Origins, measurement,
and policy responses,” Federal Reserve Bank of St. Louis, St. Louis, Missouri.
http://www.federalreserve.gov/newsevents/speech/stein20130207a.htm
Stein, Jeremy (2014). “Incorporating Financial Stability Considerations into a Monetary Policy
Framework,” Speech delivered at the International Research Forum on Monetary Policy, Washington,
D.C., March 21, 2014. http://www.federalreserve.gov/newsevents/speech/stein20140321a.htm
Sunderam, Adi (2012). “Money Creation and the Shadow Banking System,” Harvard Business School
Working Paper.
Taylor, John B. (1993). “Discretion Versus Policy Rules in Practice,” Carnegie-Rochester Conference Series
on Public Policy 39, 195-214.
Woodford, Michael (1998). “Doing without Money: Controlling Inflation in a Post-Monetary World,”
Review of Economic Dynamics 1(1), 173-219.
Woodford, Michael (2010). “Financial Intermediation and Macroeconomic Analysis,” Journal of
Economic Perspectives 24(4), 21-44.
Woodford, Michael (2011). “Monetary Policy and Financial Stability,” Columbia University Working.

31Data Sources
Variable:
Units:
Source:Data Conversion:
Notes:

Real federal funds rate
Percent
Federal Reserve Board, BLS
Raw data is monthly, converted to quarterly using EOP values
The effective federal funds rate minus CPI inflation (year-over-year percentage change)
for all items, less food and energy (Haver: YPCUSLFE@USECON)

Variable:
Units:
Source:Data Conversion:
Notes:

Taylor Residuals
Percent
Federal Reserve Board, Bureau of Economic Analysis, Haver Analytics
Raw data is monthly, converted to quarterly using EOP values
Difference between federal funds target rate and the hypothetical target implied by the
Taylor (1993) rule, using output gap and PCE inflation (Haver: FTRULE1@USECON)

Variable:
Units:
Source:Data Conversion:
Notes:

Risk Neutral Yield
Percent
Federal Reserve Bank of New YorkRaw data is monthly, converted to quarterly using EOP values
Risk neutral expectation component of yields based on the Adrian, Crump, Moench(2013) term structure model and calculated by the NY Fed

Variable:
Units:
Source:Data Conversion:
Notes:

Equity Risk Premium
Percent
Federal Reserve Bank of New YorkRaw data is monthly, converted to quarterly using EOP values
First principal component of 29 equity risk premium models reported by Duarte andRosa (2013) calculated at the NY Fed

Variable:
Units:
Source:Data Conversion:
Notes:

Term Premium
Percent
Federal Reserve Bank of New YorkRaw data is monthly, converted to quarterly using EOP values
Based on the Adrian, Crump, Moench (2013) term structure model and calculated by the
NY FedVariable:
Units:
Source:Notes:

Broker Dealer Net Leverage
Ratio
Flow of Funds (Z.1 Release)
Security brokers and dealers, Ratio of total financial assets to equity capital

Variable:
Units:
Source:Notes:Net Short Term Debt of Financial Sector to GDP
Ratio
Flow of Funds (Z.1 Release)
Net short-term wholesale debt of financial sector to GDP, FOF Z.1 Items:((fof'FL703069175.Q + fof'FL703067005.Q) - (fof'FL703135005.Q +fof'FL702150005.Q +fof'FL763178005.Q + fof'FL704110005.Q)) /(us'gdp.q*1000))*100

32

Tables and Figures
Table 1. Monitoring Vulnerabilities in Different Sectors (Adrian, Covitz, Liang 2013)(1) Asset markets

Price of risk

Leverage

Risk premiums andnon-price terms inequities, credit,
real estate

Investor leverage

Risk taking in credit
and rates
Underwriting
standards
SLOOS

Interconnections
and complexity
Derivatives andcounterparties

Carry trades
Mutual funds

Term premiums for
rates(2) Banking sector

Maturity/ liquidity
transformation
Dealer-based
finance

Regulatory capitalratios, banks andbroker-dealers

ETFs
Financial firm
liabilities,
maturities

Market measures ofrisk and capital

Secured andunsecured funding

Post-stress capitalfrom stress tests

Systemic risk
measures
Intra-financial
assets and liabilities
Common asset
holdings, correlatedrisks
Size, critical
functions, TBTF

(3) Shadow banks,
Financial markets

Securities issuance
Underwriting
standards
SCOOS(4) Nonfinancial
sectorUnderwriting
standards (LTVs,
DTIs)

Securitization
tranches

Agency REITs

CCPs

ABCP conduits

New financial
products

Regulatory capital
arbitrage

Repo markets

Hedge funds

Sec lending

Use of derivatives
to mimic leverage

MMFs

Debt-to-GDP

Use of short-termor floating rate
debt

Leverage and debt
service burdens ofhouseholds,
business, andgovernment

STIFs

33

Table 2. Monetary Policy Transmission on Financial Conditions and Financial Stability in
Different Sectors(1) Asset markets

Financial conditions
Risk free term structure
Higher asset prices
Lower risk premiums

Financial stability
Compressed risk premiums• Reach for yield because of nominal targets• Supported by leverage from an externalfinance premium, asymmetric information• Asset managers that prefer yield income orare evaluated based on relative performanceLow volatility and low risk premiums• Procyclical risk management practices• Mismeasurement of risk

(2) Banking sector

Credit channel

Pro-cyclical leverage of banks and dealers• Procyclical risk management practices andinflated collateral values
Risk-shifting channel reduces the quality of credit• Low bank capital(3) Shadow banking

Securitization
Liquidity creation

Pro-cyclical dealer intermediated leverage• Procyclical risk management practices andinflated

Maturity transformation by
nonbank intermediaries

Excessive maturity transformation• Short-term funding fragilities
Regulatory arbitrage(4) Nonfinancial
sectorBorrowing conditions
Balance sheet channel
Credit growth (credit/GDP)

Deterioration in underwriting standards
Excess leverage• Fire sale externalities• Negative demand externalities

34

Table 3. Macroprudential Policy Tools in Different Sectors(1) Asset markets

Financial stability
Compressed risk premiums• Reach for yield because of
nominal targets• Supported by leverage from anexternal finance premium,asymmetric information• Asset managers that preferyield income or are evaluatedbased on relative performanceLow volatility and low risk premiums• Procyclical risk management
practices• Mismeasurement of risk

(2) Banking sector

Pro-cyclical leverage of banks anddealers• Procyclical risk management
practices and inflated collateralvaluesRisk-shifting channel reduces thequality of credit• Low bank capital

Macroprudential Tools
Underwriting standards for debt, like LTVs
and DTIs
Sectoral risk weights at banks
Countercyclical capital or liquidity buffers
Margins and haircuts
Limits on short-term collateralized funding

Higher capital and liquidity requirements
Countercyclical capital and liquidity
requirements
Sectoral risk weights
Supervisory guidance, exposure limits
Supervisory stress tests(3) Shadow banking

Pro-cyclical dealer intermediatedleverage• Procyclical risk management
practices and inflated

Monitor for regulatory arbitrage andreduce regulatory and accounting
incentives to move activities from
regulated sector

Excessive maturity transformation• Short-term funding fragilities

Higher minimum haircuts or margins
Tighter standards on securitizations

Regulatory arbitrage(4) Nonfinancial
sectorDeterioration in underwriting standards
Excess leverage• Fire sale externalities• Negative demand externalities

Limits on underwriting standards, such as
LTVs and DTIs
Limits on adjustable rate loans forborrowers, stress test borrowers for rising
rates

35

Exhibit
Monetary Policy and Financial Conditions

Monetary Policy and Financial Stability

36