The Downside of Asset Screening for Market Liquidity

• Date: 01 October 2017
• Author: VICTORIA VANASCO
• DOI: http://doi.org/10.1111/jofi.12519
• Published date: 01 October 2017

THE JOURNAL OF FINANCE •VOL. LXXII, NO. 5 •OCTOBER 2017

The Downside of Asset Screening for Market

Liquidity

VICTORIA VANASCO∗

ABSTRACT

This paper explores the tension between asset quality and market liquidity. I model

an originator who screens assets whose cash flows are later sold in secondary markets.

Screening improves asset quality but gives rise to asymmetric information, hindering

trade of the asset cash flows. In the optimal mechanism (second-best), costly retention

of cash flows is essential to implement asset screening. Market allocations can feature

too much or too little screening relative to second-best, where too much screening gen-

erates inefficiently illiquid markets. Furthermore, the economy is prone to multiple

equilibria. The optimal mechanism is decentralized with two tools: retention rules

and transfers.

SECONDARY MARKETS FOR ASSETS PLAY an important role in providing lending

capacity to the financial industry and the real economy, by allowing finan-

cial institutions to raise funds through asset sales. In 2007 more than 25% of

outstanding consumer credit in the United States was financed through the

securitization of consumer loans.1Following the financial crash of 2008, how-

ever, issuance of securitized assets collapsed, adversely affecting financial in-

stitutions and, in turn, firms and consumers’ access to credit (Chodorow-Reich

(2014), Mondragon (2015)). In response, policy makers geared their efforts

∗Victoria Vanascois from the Graduate School of Business, Stanford University. I thank Bruno

Biais (Editor), the Associate Editor, and two anonymous referees. I am also thankful to Vladimir

Asriyan, Mitch Berlin (discussant), Peter DeMarzo, Sebastian Di Tella,Darrel Duffie, Dana Foarta,

Alex Frankel, William Fuchs, Pierre-Olivier Gourinchas, Brett Green, Laurie Hodrick, Amir

Kermani, Arvind Krishnamurthy, Ulrike Malmendier, Takeshi Murooka, Aniko ¨

Oery, Christine

Parlour,Giorgia Piacentino, Demian Pouzo, David Romer, Nancy Wallace, and YaoZeng for insight-

ful discussions and suggestions; seminar participants at UC Berkeley Department of Economics,

Haas School of Business, GSB at Stanford University, The Fuqua School of Business, University

of Maryland, Universita Bocconi, EIEF Rome, CREI and Universitat Pompeu Fabra, University

of Toronto, HEC Paris, Columbia Business School, Wharton School of Business, the New York and

Richmond Federal Reserves, the Federal Reserve Board, and the European Central Bank; and

conference participants at the FTG Meeting at UCLA (2014), the Econometric Society Meetings

in Madrid (2014), FIRS (2015), and UTDT Economics Conference (2015). I acknowledge financial

support from The Clayman Institute for Gender Research and I declare that I have no relevant or

material financial interests related to the research in this paper. All errors are my own.

1Securitization is the practice of creating and selling securities whose payoffs are derived from

and collateralized by a specified pool of underlying assets. Some common examples include (com-

mercial) mortgage-backed securities ((C)MBS), collaterilized loan obligations (CLO), and asset-

backed securities (ABS).

DOI: 10.1111/jofi.12519

1937

1938 The Journal of Finance R

toward reviving these markets.2Two key market frictions have been brought

to light. First, the ability to sell loan cash flows in secondary markets (directly or

through securitization) has been associated with a decline in lending standards

(see Berndt and Gupta (2008) for the syndicated loan market, and DellAriccia,

Igan, and Laeven (2012), Elul (2016), Jaffee et al. (2009), Keys et al. (2010), and

Mian and Sufi (2009) for the mortgage market). Second, originators have used

private information about loan quality when choosing which loans to securi-

tize (Downing, Jaffee, and Wallace (2008), Calem, Henderson, and Liles (2011),

Agarwal, Chang, and Yavas (2012), Jiang, Nelson, and Vytlacil (2014)). There

is a problem of incentives at the asset origination stage followed by a problem

of asymmetric information that may limit the ability to trade these assets (i.e.,

that reduces asset liquidity). This raises two questions: how should originators

be incentivized to screen asset quality while preserving liquidity in secondary

markets for these assets, and is there a need for policy intervention?

To address these questions, I develop a theoretical framework to study the

trade-off between an asset’s quality and liquidity. In the model, an originator

can exert costly effort to improve the quality of an asset, the cash flows of

which can be sold in secondary markets. The key feature of the model is that

both the level of the screening effort and the quality of the originated asset

are the originator’s private information. This setup aims to capture the fact

that not all of the information that is acquired while screening or monitoring

can be easily conveyed to outside investors.3Asset screening may therefore

expose the originator to illiquid secondary markets for the asset due to her

private information. This is costly when there are gains from trade with outside

investors. In this setting, I explore the resulting tension between productive

efficiency—the quality of originated assets—and allocative efficiency—the final

allocation of asset cash flows.

This framework is general and can be applied to many economic settings.

The premise is that an agent’s hidden action determines the distribution of

output and gives the agent superior information about the realization of this

output. This superior information can, in turn, affect the liquidity of claims

on this output. All originators of informationally sensitive financial assets face

this trade-off. This tension is also present in nonfinancial settings where an

agent, such as a venture capitalist (VC) or a CEO with stock options, can

exert effort to improve a firm’s cash flows. When monitoring generates private

information, too much monitoring may impact the liquidity of the agent’s stocks

(Faure-Grimaud and Gromb (2004)) or exit options (Aghion, Bolton, and Tirole

(2004)). Other examples include the relationship between firm control and its

impact on stock market trading (Coffee (1991), Bhide (1993), Dewatripont and

Tirole (1994), Maug (1998), Medrano and Vives (2004)).

2The 2010 report of the Financial Stability Board to G20 leaders stated “re-establishing secu-

ritization on a sound basis remains a priority in order to support provision of credit to the real

economy and improve banks’ access to funding” (FSB (2010)).

3See Qian, Strahan, and Yang (2015) for evidence on how incentives and communication costs

affect information production in banking.

The Downside of Asset Screening for Market Liquidity 1939

Turning back to the setting of interest here, the model has three periods

and features a manager and market investors. The manager can finance and

manage one risky project that pays off in the final period. In the first period,

she exerts costly effort to screen projects to increase the likelihood of finding

a “good” project. If a “good” project is found, it is financed; if not, an average

project from the pool of potential projects is financed. Both the screening effort

and the quality of the financed project are the manager’s private information.

In the intermediate period, the manager can exploit gains from trade with

investors, who are more patient, by selling securities that are backed by the

project’s cash flows. The cash flows that are not sold are retained by the man-

ager. In the first-best of this economy, the manager (i) chooses screening effort

in the first period such that the social marginal benefit of asset screening equals

its social marginal cost—full productive efficiency, and (ii) sells all of her asset

cash flows in the intermediate period to investors—full allocative efficiency.

Full productive and allocative efficiency cannot be achieved in the presence

of information frictions. I thus characterize the optimal mechanism that max-

imizes ex ante efficiency (second-best). I then describe the equilibrium alloca-

tions and study the conditions under which they differ from the second-best

allocations. Under the optimal mechanism, retention of cash flows is essential

to implement positive effort. Ex ante efficiency is maximized with differen-

tial retention levels—managers with poor-quality assets should not retain as

much as those with good-quality assets. In contrast, equilibrium allocations

can feature either too little or too much screening effort relative to the second-

best. While the presence of asymmetric information is essential to sustaining

the equilibrium with positive effort, too much effort may generate inefficiently

illiquid assets.

The predictions of the model shed light on the observed booms and busts in

origination and securitization of some asset classes around the 2008 to 2009

financial crisis. First, as gains from trade increase, which can be interpreted

as an increase in liquidity needs, trade in secondary markets increases while

the quality of underlying asset cash flows decreases. Second, when gains from

trade are large enough, investors’ beliefs about the manager’s screening effort

become self-fulfilling, which increases market fragility. A second equilibrium

with no asset screening and no cash flow retention arises. This behavior is in

line with the observed trend in the United States of certain securitized assets,

such as nonagency MBS, that featured a boom in the years leading up to the

crisis that was accompanied by a decrease in the quality of the underlying loans

(Mian and Sufi (2009)).

Under the optimal mechanism, while retention of cash flows is essential to

implement positive screening effort, it reduces gains from trade. As a result,

effort is optimally chosen to trade off the social benefit of asset screening with its

social cost, which includes the indirect cost of the cash flow retention required to

implement it. This indirect cost generates a wedge between the first-best and

the second-best allocations. The notion that cash flow retention incentivizes

asset screening is consistent with evidence in Ashcraft, Gooriah, and Kermani

(2014) that an increase in the amount of cash flow retention is correlated