Reputation and signaling in asset sales☆
Introduction
On April 16, 2010, the US Securities and Exchange Commission (SEC) filed a complaint against Goldman Sachs (GS) alleging that the investment bank had misled investors in the Abacus 2007–AC1 collateralized debt obligation (CDO). In response, GS raised at least two important points that seem to be in line with financial economic theory. First, during GS’s first quarter earnings conference call in 2010, Gregory Palm, general counsel for GS, stated that “a significant point missing from the SEC’s complaint was the fact that Goldman Sachs retained a significant residual long position in the transaction.... We certainly had no incentive to structure a transaction that was designed to lose money” (Palm, 2010). In other words, GS maintained some skin in the game in the Abacus deal. Second, in a supplemental submission to the SEC, attorneys for GS asserted: “Nor is there any basis to suggest that Goldman Sachs would have intentionally jeopardized its own reputation and relationship with established customers and counterparties.... Goldman Sachs had no reason to mislead anyone” (Klapper et al., 2010). That is, GS would not intentionally mislead investors because doing so could damage its reputation.
The skin-in-the-game defense could follow from the notion that informed issuers reveal their information through costly signaling by maintaining a stake in their issue and that such a stake should be a sufficient statistic for all private information (Leland, Pyle, 1977, Nachman, Noe, 1994, DeMarzo, Duffie, 1999, DeMarzo, 2005). The reputation defense could follow from the idea that concern for future business can lead issuers to be truthful when making public statements about their issues, such as in marketing materials or a deal prospectus. Considered separately, these defenses make some economic sense, although the interactive effects of signaling and reputation need further exploration. This paper fills that gap and shows that the interaction between reputation and signaling can cause issuers to have a greater incentive to mislead investors. These findings reveal that reputation can improve allocative efficiency, as well as provide for incentives to misrepresent asset quality.
In this paper, I consider an infinitely repeated asset sales game. In each period, a risk-neutral issuer is endowed with an asset to sell. Nature chooses the quality of the asset, which can be either high or low. Asset quality denotes expected cash flow at the end of the period. Patient risk-neutral investors compete to buy the fraction of the asset that is sold. The issuer can perfectly observe the type of the asset, but this information is not available to investors. Thus, a classic lemons problem arises as in Akerlof (1970). The issuer publicly reports the type of asset in a prospectus, but this report need not be truthful. In addition, the issuer can signal asset quality by retaining a fraction of it. Such a signal is credible because the issuer finds it more costly to engage in fractional asset retention when selling a low-quality asset.
Reputation concerns for the issuer arise due to asymmetric information over issuer preferences for honesty. The issuer could be one of two types. The honest-type issuer is committed to truthfully reporting the asset’s quality in the prospectus. The opportunistic-type issuer chooses a reporting strategy that maximizes payoffs. Both types optimally choose a fraction of the asset to retain. The issuer’s reputation is the probability that the investors place on the issuer being the honest type, as in Kreps and Wilson (1982), Milgrom and Roberts (1982), and Mathis et al. (2009). By mimicking an honest issuer (i.e., truthfully reporting asset quality in the prospectus), an opportunistic-type issuer’s reputation can be improved, thereby reducing the lemons discount on the fraction of the asset sold to investors.
A central focus of this paper is the degree to which the issuer’s concern for her reputation can improve allocative efficiency. In a static version of my model, under some parameter restrictions, the only equilibrium is the classic least cost separating equilibrium (LCSE). In this equilibrium, the issuer retains just enough of every high-quality asset she sells to signal its quality. This retention leads to forgone gains from trade. Reputation effects impact this result in three ways. First, if gains from trade are high enough, the concern for future reputation leads the opportunistic-type issuer to truthfully report, making retention as a signal of asset quality unnecessary. Second, when the issuer has a higher reputation, investors perceive that a greater chance exists that the issuer is mechanically honest. This raises the price of an asset following a high-quality report even if investors anticipate that the opportunistic-type issuer will pool her low-quality assets with high-quality assets. In effect, a higher reputation means that there is a greater chance that an asset is high quality given a report of high quality. This allows for pooling equilibria with greater allocative efficiency even when they would not exist in the static game. Third, when reputation is too low to sustain a full pooling equilibrium, concern for reputation can leave the opportunistic-type issuer indifferent between truthfully reporting and misrepresentation. In this case, a partial-pooling equilibrium obtains in which the issuer retains some of the asset when she reports that it is high qualty, but not as much as she would if she had zero reputation.
The fact that reputation concerns can lead to a pooling equilibrium gives rise to a criticism of the claim that reputation is the core self-disciplining mechanism for markets, such as that for asset-backed securities (ABS). If one ignores the possibility that issuers can signal asset quality through costly retention, reputation certainly provides some incentives for issuers of ABS to truthfully reveal their private information. However, in a pure costly signaling setting, the issuer would perfectly reveal her information via retention. When reputation and costly signaling interact, the issuer can engage in retention yet misreport at the same time. This feature of the model is appealing given the alleged prevalence of opportunistic behavior in many ABS markets, even though issuers often maintain a position in the assets they sell. For example, Piskorski et al. (2015) show that mortgage-backed securities (MBS) issuers misrepresent important information about the quality of mortgages underlying the securities they sell. Although this type of misrepresentation does not negatively affect the allocative efficiency for the agents in my model, it can have implications for real outcomes outside of the model. For example, misrepresentation in the market for MBS could have led to excessive lending in the primary mortgage market. As such, it is important to understand MBS issuer incentives to misreport.
My theoretical results give rise to new empirical predictions that apply to any financial market with asymmetric information between issuers and buyers, frequent issuances, and observable issuer retention. A good example is the ABS market, although the model can also be applied to other markets such as the repurchase agreement (repo) or asset-backed commercial paper markets. The first empirical prediction is that when discount rates are low or gains from trade are high, there would be no issuer retention and a large dispersion in prices. When discount rates are high or gains from trade are low, the issuer retains a fraction of the asset only when her reputation is low. Retention will decrease as issuer reputation improves because costly signaling and reputation act as substitutes. As such, issuer retention should decrease with good past performance and increase with bad past performance. In the ABS market, this translates to the issuer retaining a larger equity tranche when more of her past tranches have been downgraded. In the repo market, this could translate to larger haircuts when past collateral turns out to be of lower quality than expected. This relation implies that an improvement in issuer reputation will initially decrease the investor’s beliefs about the probability that the issuer will truthfully reveal asset quality when reputation is low and increase that probability when reputation is high. In equilibrium, the issuer’s actual strategies must be consistent with this belief. Thus, prices should be more sensitive to retention for low-reputation issuers than for high-reputation issuers. The differential sensitivity of prices to issuer retention can help explain why some researchers, for example, Garmaise and Moskowitz (2004), find that price is insensitive to issuer retention.
To close the paper, I demonstrate that reputation can lead to a pooling equilibrium even when imposing a standard refinement criterion for signaling games. In a static setting, pooling equilibria are typically eliminated by the D1 refinement criterion of Banks and Sobel (1987) and Cho and Kreps (1987). When reputation effects are considered, the issuer’s preferences no longer satisfy a single crossing property. As a result, a pooling equilibrium with reputation concerns can survive elimination by D1. The intuition is that opportunistic-type issuers selling low-quality assets can be more willing to sacrifice reputation and, hence, investors must ascribe off-equilibrium actions to those types of issuers.
This paper relates to the literature on adverse selection in financial markets. In his seminal paper, Akerlof (1970) shows that private information can cause important distortions in markets. Since Leland and Pyle (1977) and Myers and Majluf (1984), this idea has also been applied to the markets for financial securities. In these markets, informed agents often can take actions that reveal their private information (Spence, 1973). Leland and Pyle (1977) show that informed issuers of financial securities can retain a fraction of a security to signal quality. DeMarzo and Duffie (1999) and DeMarzo (2005) build on this idea to show that when such sellers can signal via retention, issuing a debt like claim backed by assets can be optimal. The signaling mechanism I consider in this paper is similar to that of Leland and Pyle (1977), DeMarzo and Duffie (1999), and DeMarzo (2005).
This paper also relates to the literature on reputation effects in repeated games. Intuitively, agents involved in repeated games could try to acquire a reputation for a certain characteristic in the early stages of the game if that characteristic improves payoffs in later stages. Kreps and Wilson (1982) and Milgrom and Roberts (1982) introduce the notion that imperfect or asymmetric information about player preferences can provide such a mechanism. By observing a given player’s previous actions, other agents update their beliefs about that player’s type. These beliefs then serve as a form of reputation. In two seminal papers, Diamond (1989) and Diamond (1991) show that reputation can act as an important incentive mechanism in firm financing and investment decisions. Recently, Mathis et al. (2009), Josephson and Shapiro (2012), and Griffin et al. (2013) show that a high reputation can lead informed sellers or intermediaries to misrepresent asset quality. Winton and Yerramilli (2015) consider issuer moral hazard in a repeated setting and find that issuers retain less as their reputation improves. In their model, issuer retention solves an ex ante moral hazard problem. In my model, retention serves as a signaling device to overcome an adverse selection problem. This difference means that, in their model, good behavior monotonically increases with reputation; in my model, the effect is non-monotonic. Chari et al. (2014) consider a reputation model of loan sales with a persistent adverse selection problem. They find that reputation effects can lead to partial pooling equilibria similar to those I consider.
The remainder of the paper proceeds as follows. Section 2 lays out the setup of the model. Section 3 provides an equilibrium analysis of the model. Section 4 introduces novel empirical predictions that follow from the equilibrium analysis. Section 5 examines the application of D1 to the framework of the model. Section 6 concludes. All proofs appear in Appendix C.
Section snippets
The model
In this section, I introduce the economic environment of the model and define the equilibrium concept and refinement criteria I use to analyze the model.
Equilibrium analysis
In this section, I characterize equilibria of the game as well as analyze their properties.
Empirical implications
As is common in signaling games, my model admits multiple equilibrium. To make empirical predictions in a consistent way, I select an equilibrium based on allocative efficiency. I apply the following equilibrium selection in Case I and Case II based on parameters:
Case I:. The truth-telling equilibrium is selected as it is perfectly allocatively efficient.
Case II:. The partial pooling equilibrium of Proposition 3 is selected as it features greater allocative
D1 refinement and pooling equilibria
In static signaling games, pooling equilibria are typically eliminated by applying the D1 refinement criterion. D1 requires that investor beliefs in response to a given off-equilibrium issuer action must reflect those types who would gain under the largest possible set of beliefs in response to that action. It typically eliminates pooling because higher types usually stand to benefit from breaking a pool for a broader set of belief responses. In the model I present above, this result can be
Conclusion
In this paper, I present a model of an informed securities issuer that unifies signaling and reputation effects. A lemons problem arises due to asymmetric information about the quality of assets. Partial asset retention by the issuer is a credible signal of asset quality, as the issuer is impatient relative to investors causing such retention to be costly. Imperfect information over issuer preferences induces a market reputation for the issuer. A high reputation can increase payoffs for the
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I gratefully acknowledge financial support from the Fisher Center for Real Estate and Urban Economics, the White Family Foundation, and the Institute of Business and Economics Research. I wish to thank the editor Bill Schwert, the anonymous referee, Darrell Duffie, Bruce Carlin, Zhaohui Chen, Willie Fuchs, Mark Garmaise, Simon Gervais, Sebastian Gryglewicz, Dwight Jaffee, Dmitry Livdan, Chris Mayer, Marcus Opp, Christine Parlour, Chester Spatt, Avanidar (Subra) Subrahmanyam, Steve Tadelis, Alexei Tchistyi, Nancy Wallace, Bill Wilhelm, Bilge Yılmaz, Geoffery Zheng, and seminar and conference participants at Georgetown University, the Federal Reserve Board of Governors, Boston University, Duke University, University of Chicago, the Federal Reserve Bank of Boston Massachusetts, University of Houston, Columbia University, University of British Columbia, University of North Carolina, UCLA Anderson School of Management, Wharton, University of Virginia, the Summer Real Estate Symposium (2011), and the Texas Finance Festival (2012) for helpful conversations and comments.