The Economics of Structured Finance

For anyone interested in the financial crisis, I thought I'd try to summarize a paper I just read for my Empirical Macroeconomics and Finance course. The paper is called "The Economics of Structured Finance," by Coval, Jurek, and Stafford, 2009, in the Journal of Economic Perspectives, Volume 23, Number 1.

Structured finance is the pooling of economic assets and subsequent issuance of a prioritized capital structure of claims, called tranches, against these collateral pools. The prototypical example of a structured finance security is a collateralized debt obligation (CDO).

A reason that the practice of structuring securities arose was to allow the tranches to be rated by the credit rating agencies so that they could be comparable with single-name securities or corporate bonds. Securities involve a complex mix of risks. Adding the prioritization structure creates “safe” assets at the high priority senior tranches. Senior tranches only absorb losses after the junior claims have been exhausted, which allows senior tranches to obtain credit ratings in excess of the average rating for the whole collateral pool.

For example, consider two bonds, both with default probability p. Both pay $0 in case of default and $1 otherwise. You could pool them into a $2 fund, and then form a junior and senior tranche. The junior tranche pays $1 if both bonds avoid default and $0 if either bond defaults. The senior pays $1 if neither bond defaults or if only one out of two bonds defaults; it pays $0 if both bonds default.

The recent financial crisis involved the discovery that the “safe” manufactured tranches were actually far riskier than advertised. Even AAA rated securities defaulted with reasonable likelihood. When this was finally realized, in late 2007 and 2008, investors stopped buying structured finance products. How did the credit rating agencies get it so wrong?

Notice that in the example above, the risk of default for the senior tranche depends on the correlation between bond defaults. If the bond default probabilities are uncorrelated, then the senior tranche defaults with probability p²

Next, the authors look at the relation of structured finance to subprime. Government- sponsored agencies such as Fannie Mae, Freddie Mac, and Ginnie Mae were chartered to purchase mortgages originated by local banks that satisfy certain size and credit quality requirements. They repackage these conforming mortgages into mortgage-backed securities to be resold in capital markets with the implicit guarantee of the U.S. government. Mortgages that fall below the credit standard (“subprime”) were packaged into “private-label” mortgage-backed securities, which in turn were resecuritized into structured finance CDOs. So there were two levels of structuring, and a lot more correlations to worry about, which were not properly accounted for. The ratings also didn't take into account systemic risk, which structured finance was particularly susceptible to. Typically, securities that are correlated with the market as a whole should offer higher expected returns, since it is less valuable to have an asset that will pay well when times are good and pay poorly when times are bad, than vice versa. The systemic risk of the structured finance products was underestimated.

The authors don't place all the blame on the credit rating agencies. They partly blame some perverse incentives, and also a regulatory guideline saying that banks holding AAA-rated securities were required to hold only half as much capital as was required to support other investment-grade securities.This distorted the demand for AAA-rated securities, and fueled a lot of the effort to create an imprudently large volume of structured financial products.

After the Crisis

An interesting reading to kick off the semester warns of "the dangers of presuming a precision and degree of knowledge we do not have." The article, by Ricardo Caballero, is called "Macroeconomics after the Crisis: Time to Deal with the Pretense-of-Knowledge Syndrome," and appeared in the Fall 2010 Journal of Economic Perspectives.

Caballero, who is an MIT professor, writes that "On the methodological front, macroeconomic research has been in 'fine-tuning' mode within the local-maximum of the dynamic stochastic general equilibrium world, when we should be in 'broad-exploration' mode."

Basically, the general approach to macroeconomics these days is to begin with a stochastic neoclassical growth model-- a basic model of households and firms that everyone learns at the beginning of grad school-- and tack on some special effects, like money, monopolistic competition, or nominal rigidities. The problem is that "by some strange herding process the core of macroeconomics seems to transform things that may have been useful modeling short-cuts into a part of a new and artificial 'reality,' and now suddenly everyone uses the same language, which in the next iteration gets confused with, and eventually replaces, reality.
Along the way, this process of make-believe substitution raises our presumption of
knowledge about the workings of a complex economy."

We try to make incremental improvements to the model, adding a parameter here and there, but actually bring it further and further from reality by compounding absurd assumptions. "In realistic, real-time settings, both economic agents and researchers have a very limited understanding of the mechanisms at work. This is an order-of-magnitude less knowledge than our core macroeconomic models currently assume, and hence it is highly likely that the optimal approximation paradigm is quite different from current workhorses, both for academic and policy work. In trying to add a degree of complexity to the current core models, by
bringing in aspects of the periphery, we are simultaneously making the rationality
assumptions behind that core approach less plausible."

Caballero makes a distinction between uncertainty and Knightian uncertainty. The latter involves risk that cannot be measured and hence cannot be hedged--things you'd never think of thinking of. This is the kind of uncertainty that is involved in most crises and panics. In one sense, it is very discouraging that novelty and surprise is such a big part of financial crises, for then, how can we ever hope to model or understand them? On the other hand, there are nevertheless some insights: widespread confusion triggers panics which trigger demand for broad insurance (and a role for government). Macroeconomists need to embrace complexity and recognize that human reaction to the truly unknown is fundamentally different
from reaction to the risks associated with a known situation and environment.

Last semester, I took a course in Psychology and Economics with Matthew Rabin. The types of models we studied there captured things like belief-based or reference-dependent preferences, ego utility, social preferences, and framing and bracketing effects. All of these tweaks to the standard models are made for the sake of increased realism, but still, they are just tweaks. Usually they involve adding a nice Greek letter to the model. The standard model is a special case for which the Greek parameter is 0 or 1. Agents are allowed to have particular types of risk preferences, but the risks can always be measured, and in fact the models almost always impose rational expectations. Rational inattention is allowed, but Knightian uncertainty is not; agents are perfect Bayesian updaters with well-defined Bayesian priors. In this sense, as Professor Rabin describes in the syllabus, the course is "purposely, pointedly, persistently, proudly and ponderously mainstream."

Caballero says we need to go further from the mainstream and into areas like complex-systems theory and robust-control theory. In doing so we may need to "relax the artificial micro-foundation constraints imposed just for the sake of being able to generate 'structural' general equilibrium simulations."

This semester, I have one course that teaches precisely the methodology that Caballero so harshly criticizes. It's a theory-intensive course in macroeconomics, and the main textbook is Recursive Methods in Economic Dynamics by Stokey and Lucas. I'm excited to balance this course with a new course called Empirical Methods in Macroeconomics and Finance taught by Professor Atif Mian. This course will focus on new ways to integrate finance and macro. We will also get to learn about some new data sets and work at developing research ideas. Yet another complementary course will be Professor Barry Eichengreen's European Economic History course. Theory, empirics, and history sounds like a balanced mental diet for this semester.