The Macroeconomics of Shadow Banking

• DOI: http://doi.org/10.1111/jofi.12540
• Date: 01 December 2017
• Author: ALEXI SAVOV,ALAN MOREIRA
• Published date: 01 December 2017

THE JOURNAL OF FINANCE •VOL. LXXII, NO. 6 •DECEMBER 2017

The Macroeconomics of Shadow Banking

ALAN MOREIRA and ALEXI SAVOV∗

ABSTRACT

We build a macrofinance model of shadow banking—the transformation of risky as-

sets into securities that are money-like in quiet times but become illiquid when uncer-

tainty spikes. Shadow banking economizes on scarce collateral, expanding liquidity

provision, boosting asset prices and growth, but also building up fragility. A rise in

uncertainty raises shadow banking spreads, forcing financial institutions to switch to

collateral-intensive funding. Shadow banking collapses, liquidity provision shrinks,

liquidity premia and discount rates rise, asset prices and investment fall. The model

generates slow recoveries, collateral runs, and flight-to-quality effects, and it sheds

light on Large-Scale Asset Purchases, Operation Twist, and other interventions.

RECENT ECONOMIC PERFORMANCE HAS BEEN the story of a boom, a bust, and a slow

recovery. The rise and fall of shadow banking plays a central role in that story.

In the boom years, shadow banking transformed risky loans into short-term

money-like instruments held by households, firms, and institutional investors.

These instruments traded at low spreads over traditional money-like instru-

ments such as Treasury bills, indicating a high level of liquidity. This liquidity

evaporated, however,with the onset of the financial crisis, when spreads opened

up and shadow banking all but shut down, causing both liquidity and credit to

contract sharply.1Shadow banking can thus be interpreted as fragile liquidity

∗Alan Moreira is with the University of Rochester. Alexi Savov is with New York University and

NBER. We thank Ken Singleton (the Editor), the anonymous Associate Editor, two referees, Nick

Barberis, Markus Brunnermeier, Douglas Diamond, Marco Di Maggio, Sebastian Di Tella, Itamar

Drechsler, Gary Gorton, Valentin Haddad, Zhiguo He, John Ingersoll, Arvind Krishnamurthy,

Matteo Maggiori, Gustavo Manso, Andrew Metrick, Holger Mueller, Tyler Muir, Fabio Natalucci,

Cecilia Parlatore, Thomas Philippon, Philipp Schnabl, Vish Viswanathan,Michael Woodford, Ariel

Zetlin-Jones, and Shengxing Zhang for feedback. We also thank seminar participants at Yale

SOM, NYU Stern, Kellogg, Wisconsin Business School, Princeton, Columbia GSB, LSE, LBS, and

the European Central Bank, as well as conference participants at the Kellogg Junior Finance

Conference, NBER Monetary Economics, NBER Asset Pricing, the Macro Finance Society, the

WesternFinance Association, the Society for Economic Dynamics, the Tel Aviv Finance Conference,

the Atlanta Fed’s Financial Markets Conference, the Bank of England, the Richmond Fed, and the

NBER Mathematical Economics Conference. We have read the disclosure policy of the Journal of

Finance and have nothing to disclose.

1Bernanke (2013) writes that “Shadow banking . . . was an important source of instability during

the crisis . . . . Shadow banking includes vehicles for credit intermediation, maturity transforma-

tion, liquidity provision .. . . In the run-up to the crisis, the shadow banking sector involved a high

degree of maturity transformation and leverage. Illiquid loans to households and businesses were

securitized, and the tranches of the securitizations with the highest credit ratings were funded by

DOI: 10.1111/jofi.12540

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2382 The Journal of Finance R

transformation: it extends credit to riskier borrowers and provides liquidity to

investors, liquidity that is as good as any other during quiet times but that

disappears when the environment becomes more uncertain. Under this view,

shadow banking presents us with a trade-off between stability and growth. In

this paper, we build a dynamic macrofinance model of shadow banking as frag-

ile liquidity transformation. We show how it boosts asset prices and economic

growth while at the same time exposing the economy to changes in uncertainty.

We also show how it builds financial and economic fragility, how it sets up slow

recoveries, and how a number of policy interventions interact with these effects.

The model works as follows. Investors use liquid securities to take advantage

of high-value opportunities that require them to trade quickly and in large

amounts. Intermediaries create liquid securities by tranching assets. The top

tranche is safe, which makes it fully insensitive to any private information

about asset values and allows investors to trade it without fear of adverse

selection (Gorton and Pennacchi (1990)). A safe security is thus always liquid.

By contrast, the bottom residual tranche is risky, which makes it sensitive to

private information and hence illiquid. Its role is to provide a cushion for the

liquid securities.

The middle security tranche takes a loss only if a large shock called a crash

hits. This loss is limited and rare enough to make the security insensitive

to private information and thus liquid most of the time. However, there is

a small probability that a crash becomes much more likely, in which case it

becomes profitable to trade the security based on private information. The

presence of privately informed trading creates adverse selection, causing the

security to become illiquid. A security with limited crash exposure is therefore

liquid most of the time, but not always. We call it fragile-liquid.

In sum, intermediaries can issue securities that are liquid most of the time

by limiting their crash exposure and securities that are liquid all of the time by

making them safe. The overall amount of liquid securities is thus constrained by

the value of intermediaries’ assets in a crash, that is, by their collateral value.

Since fragile-liquid securities have a higher crash exposure than always-liquid

securities, they require less collateral, which enables intermediaries to provide

investors with a lot more liquidity overall. Investors can thus have a lot of

liquidity most of the time, or a little liquidity all of the time.

We call the safe, always-liquid security “money.” Examples include tradi-

tional bank deposits, government money market funds, and general collateral

repurchase agreements. We call the fragile-liquid security “shadow money.” Ex-

amples include large uninsured deposits, prime money market funds, private-

label repurchase agreements, financial-backed commercial paper, and asset-

backed commercial paper (ABCP), and other forms of short-term wholesale

very short-term debt, such as asset-backed commercial paper and repurchase agreements (repos).

The short-term funding was in turn provided by institutions, such as money market funds, whose

investors expected payment in full on demand . .. . When investors lost confidence in the quality

of the assets . . . they ran. Their flight created serious funding pressures throughout the financial

system . . . and inflicted serious damage on the broader economy.”

The Macroeconomics of Shadow Banking 2383

funding. We interpret shadow banking as the process of creating shadow

money.2

Shadow banking expands liquidity provision and raises asset prices in times

of low uncertainty. Intuitively, investors are willing to rely on shadow money

for their liquidity needs as long as it is likely to remain liquid. This is the case

when a crash is unlikely,that is, when uncertainty is low. Low uncertainty thus

results in a low spread between shadow money and money. The low spread

makes shadow money an attractive source of funding for intermediaries. Its

low collateral requirement enables them to make liquidity more abundant.

Abundant liquidity allows investors to deploy their wealth when it is most

valuable, which lowers their required return on savings and boosts asset prices.

The prices of riskier assets rise the most because their low collateral values

make them more reliant on shadow money funding. A boom in investment

and growth ensues, but fragility builds up over time as the investment is

concentrated in riskier assets.

A period of low uncertainty (e.g., the “Great Moderation” of the 1990s and

early 2000s) thus induces a shadow banking boom similar to the one that pre-

ceded the 2008 financial crisis: spreads are narrow, shadow banking securities

crowd out traditional money-like instruments, liquidity is abundant, and asset

prices are high. The shadow banking boom in turn induces an economic boom:

investment and growth are high, especially in riskier sectors. Consistent with

this dynamic, the shadow banking boom that preceded the crisis led to a large

expansion in residential and commercial real estate loans, as well as in auto,

student, and credit card loans, all of which contributed to employment and eco-

nomic growth. Moreover, the credit expansion was heavily concentrated among

riskier borrowers (Mian and Sufi (2009)).

A rise in uncertainty brings the shadow banking boom to an end. Households

are less willing to hold shadow money because its liquidity might evaporate.

The spread between shadow money and money opens up, as did the spreads on

shadow banking instruments in the summer of 2007. Intermediaries respond

by sharply contracting shadow money (e.g., the collapse of the ABCP market)

and switching to money. Since money requires a lot more collateral, intermedi-

aries must also issue a larger illiquid residual tranche (equity). The supply of

liquidity shrinks, more so given the low collateral value of the assets created

during the boom. The liquidity contraction raises discount rates and lowers

asset prices, and as a result investment falls and growth turns negative. In

short, the liquidity cycle drives the macrocycle.

While uncertainty remains high, intermediaries invest only in safe, high

collateral-value assets that they can fund primarily with money. Over time,

this “collateral mining” makes the economy’s capital stock safer, which allows

2Pozsar (2014) shows that the shadow banking system met the large and growing demand for

highly liquid instruments of institutions such as asset managers and corporations whose holdings

of such instruments tripled in size from $2 trillion to $6 trillion between 1997 and 2013. Sunderam

(2014) further shows that ABCP issuance responds strongly to changes in liquidity premia.