Financial institutions can create frictions. Until recently, economic theory had paid relatively little attention to this possibility. For example, asset pricing theory often assumes that prices are set directly by the "representative household", treating the finance sector as an efficient pass-through. As a result of the global financial crisis, economists are thankfully becoming more aware of the need to account for the real world complication of delegation to agents (Buiter 2009, Kirman 2009, and Kobayashi 2009).
Delegation enables financial agents to capture rents
The past decade has seen a surge of new products and strategies, such as hedge funds, securitisation, private equity, structured finance, CDO's and credit default swaps. Each came to be regarded as a worthwhile addition that helped to "complete" markets and spread risk-bearing by offering investors and borrowers new ways of packaging risk and return.
Ominously, most of these innovations have been accompanied by increased opacity, creating the scope for elevated moral hazard. Hedge funds shroud themselves in mystery as to strategies, holdings, turnover, costs, and leverage. It is hard to monitor the diligence and competence of their managers in the absence of information on the sources of performance. The growth of structured finance and CDS's has meant greater reliance on over-the-counter trades that circumvent the discipline of open markets and regulation.
In a recent paper, we present a framework for thinking about how competitive agents are able to extract rents from the provision of services to principals even when all expectations are rational (Biais et al. 2009). We describe the evolution of a financial innovation and show how rents rise progressively to the point where the agents end up capturing the bulk of the return from the innovation. The key assumption of the model is the presence of information asymmetry; the agent has more information than the principal and the agent's interest and objectives are not necessarily aligned with those of the principal.
Despite being based on a single innovation, our analysis can be used as a metaphor for the financial sector as a whole. The model also shows how innovations and rents carry the seeds of their own destruction to the point where principals are no longer receiving an adequate return and refuse to support the innovation, which then collapses. Perhaps in line with the global financial crisis, the model suggests that high and rising rents of agents offer a lead indicator of crisis.
The model: Asymmetric information is key
First consider the frictionless benchmark case in which principals and agents have access to the same information. The principals are a set of rational, competitive investors and the agents are a set of similarly imbued fund managers. A financial innovation is introduced but there is uncertainty about its viability.
As time goes by, investors and managers learn about this by observing the profits that come from adopting the new technique. If it generates a stream of high profits, this raises confidence that the innovation is robust. This leads to an increase in the scale of its adoption and therefore the size of the total compensation going to managers. Because of the symmetry of information, these gains are competitively determined at normal levels and the innovation flourishes.
Alternatively, profits may deteriorate, market participants come to learn of its fragility and the innovation withers on the vine. In both cases, while learning generates dynamics, with symmetric information there is no crisis.
This differs from previous analyses of industry dynamics under symmetric information where the learning model was specified so that certain observations could trigger crises (see Barbarino and Jovanovic 2007, Pastor and Veronesi 2006, Zeira 1987 and 1999). In our framework however, it is information asymmetries and the corresponding rents earned by agents which precipitate the crisis.
In reality, innovative sectors are plagued by information asymmetry. It is hard for the outsider to understand everything the insiders are doing and difficult to monitor their actions.
We explore the implications of this lack of transparency and oversight using optimal contracting theory. Our model assumes that managers have a choice:
- They can exert effort to reduce the probability that the project fails even though such effort is costly.
- Alternatively they can cut corners and “shirk” – the term used by economists and familiar to every schoolboy meaning to avoid work. When agents shirk they fail to carefully evaluate and control the risks associated with the project.
The handling of portfolios of CDO's in the run-up to the recent crisis illustrates this well. Fund managers had the option of diligently scrutinising the quality of the underlying paper or they could shirk by relying on a rating agency assessment and pass the unopened parcel on to the investor. While securitisation is a potentially valuable innovation, it also requires costly effort to implement properly.
Our model also assumes that managers have limited liability. The inability to punish gives rise to the moral hazard that characterises finance at every level from individual traders to the banks that employ them (our simple moral hazard model is in line with that of Holmstrom and Tirole 1997).
This combination of opacity and moral hazard is the core of the agency problem. Investors have to pay highly to provide managers sufficient incentive to exert effort, and the greater the moral hazard, the larger are likely to be the rents. Our model shows the probability of shirking is higher when the innovation is strong than when it is weak. After a period of consistently high profits, managers become increasingly confident that the innovation is robust. They are tempted to shirk and it becomes correspondingly harder to induce them to exert continuing effort. As the need for incentives grow, the point is reached where agents are capturing most of the gains from the innovation.
Investors then become frustrated at the rents being earned by the agents and at their own poor return and eventually give up on incentives. The dynamics are such that when confidence in the innovation reaches a critical threshold, there is a shift from equilibrium effort to equilibrium shirking. The innovation collapses as managers cease to undertake the necessary risk assessment to maintain the viability of the innovation. In the end, an otherwise robust innovation is brought down by the weight of rents being captured.
Relating the model to the real world
Our theoretical results are consistent with the empirical findings of Philippon and Reshef (2008). Their study observes a burst of financial innovation in the first half of this decade and rapid growth in the size of the finance sector, accompanied by an increase in the pay of managers. They estimate that rents accounted for 30 to 50% of the wage differential between the finance sector and the rest of the economy. Philippon and Reshef point out that the last time this happened on a similar scale was in the late 1920's bubble – also with calamitous consequences. It is significant that a high proportion of the net revenues of banks and other finance firms went to the staff rather than shareholders. Referring back to our model, this suggests that rent extraction was occurring at all operating levels within the institutions.
Our model's second prediction is that innovations under asymmetric information are vulnerable to collapse. The current crisis seems to validate this prediction since structured credit, CDO's and CDS's were the immediate cause of the global financial crisis.
The policy imperatives are to reduce opacity both in the functioning of capital markets and in the actions of individual institutions. Trades should be conducted in transparent markets, so that investors can use price, trades and quotes information to monitor and discipline agents. Transactions should be cleared in open markets with clearing houses requiring call margins and security deposits. This would enable principals and regulators to monitor the risky positions of agents and prevent excessive risk-taking. Risky conditions and portfolio structure should also be disclosed to investors and regulators. Hedge funds and private equity need to be clearer and more “above board” about what they are doing and why.
Moral hazard can also be reduced by extending the period over which performance of portfolios and of individual traders is measured, and compensation is determined. Three or four years would be a reasonable horizon.
Policymakers are always looking for ways to anticipate trouble in time. Our model shows how a combination of high confidence in finance sector innovations and high rents for finance managers might act as a lead indicator of crisis. If warning signs are showing, policymakers should demand an increase in transparency.
Barbarino, Alessandro, and Boyan Jovanovic (2007), "Shakeouts and market crashes", International Economic Review, 385-420.
Biais, B., J.C. Rochet & P. Woolley, 2009, "Rents, learning and risk in the finance sector and other innovative industries," Working paper, PWC London School of Economics.
Buiter, Willem (2009), “The unfortunate uselessness of most ‘state of the art’ academic monetary economics”, VoxEU.org, 6 March.
Kirman, Alan (2009), “Economic theory and the crisis”, VoxEU.org, 14 November.
Kobayashi, Keiichiro (2009), “Why this new crisis needs a new paradigm of economic thought”, VoxEU.org, 24 August.
Holmstrom, Bengt, and Jean Tirole (1997), "Financial intermediation, loanable funds and the real sector", Quarterly Journal of Economics, 663-692.
Pástor, Lubos., and Pietro Veronesi (2006), "Was there a Nasdaq bubble in the late 1990s?", Journal of Financial Economics, 81:161-100.
Philippon, Thomas, and Ariell Reshef (2008), "Skill biased financial development: education, wages and occupations in the U.S. financial sector", Working paper, New York University.
Zeira, Joseph (1987), "Investment as a process of search", Journal of Political Economy, 204-210.
Zeira, Joseph (1999), "Informational overshooting, booms and crashes", Journal of Monetary Economics, 237-257.