A Better Way to Measure Systemic Risk
The economics profession has faced harsh criticism since the financial crisis of 2007-09 – not least from its own members –for relying on mathematical models that failed to foresee the crisis and in some cases abetted its onset.
These models rested on assumptions that have little to do with reality. For example, here is a description of the Dynamic Stochastic General Equilibrium model, the dominant macro model, from a U.S. House of Representatives sub-committee report on economic models in July 2010:
The agents populating DSGE models, functioning as individuals or firms, are endowed with a kind of clairvoyance. Immortal, they see to the end of time and are aware of anything that might possibly ever occur, as well as the likelihood of its occurring; their decisions are always instantaneous yet never in error, and no decision depends on a previous decision or influences a subsequent decision. Also assumed in the core DSGE model is that all agents of the same type – that is, individuals or firms – have identical needs and identical tastes, which, as “optimizers,” they pursue with unbounded self-interest and full knowledge of what their wants are. By employing what is called the “representative agent” and assigning it these standardized features, the DSGE model excludes from the model economy almost all consequential diversity and uncertainty – characteristics that in many ways make the actual economy what it is.
In his testimony at the hearing, Nobel laureate and Massachusetts Institute of Technology professor emeritus Robert M. Solow said the DSGE model has “essentially nothing to say” about the problems surrounding the financial crisis, despite its dominance at elite universities, central banks and influential policy circles.
Is the criticism justified, and what can be done about it?
The tradition of mathematical modeling in academia
Given the criticisms above, it is no wonder that the mathematical models of economics didn’t foresee the crisis. But are they as bad as they seem?
Purely theoretical exercises are not uncommon in academia. The findings of pure mathematics are intended to contribute to abstract mathematics and not to applied mathematics, which is often housed in an entirely different department at a university. The current fashionable model of physics, string theory, occupies much of physicists’ efforts but is criticized for being both untested against actual physical phenomena and untestable.
Economics suffers from the same disconnect between theory and application. Economist David Colander says in his textbook Economics, “Modern macroeconomists see their models as only indirectly relevant for policy. For example, when Robert Lucas, a Nobel Prize-winning modern macroeconomist at the University of Chicago, was asked what he would do if he were appointed to the Council of Economic Advisers, he said that he would resign.”
The justification for abstract models with unrealistic assumptions is that they remove the observer from the trees in order to assess the forest. Observing the forest from a distance can cause the viewer to miss many of the facts on the ground, but it can sometimes bring about a new perspective. If the new perspective helps uncover new principles, those principles can be taken back into the forest to improve its study.