By Ed Walker, who writes as masaccio at Firedoglake. You can follow him at Twitter at @MasaccioFDL, and here’s his author page at Firedoglake.
The field [economics] is filled with anxious introspection, prompted by economists’ feeling that they are powerful but unloved, and by robust empirical evidence that they are different.
The Superiority of Economists, by Marion Fourcade, Etienne Ollion and Yan Algan.
I feel bad for these lost souls, the unloved economists, so I’ll try to help them understand why people don’t love them. It’s obvious that the principal reason is that economists refuse to take any responsibility for the Great Crash, despite the fact that it was their policy recommendations and justifications that led to the dismantling of the regulatory structure that worked for decades to prevent such massive disasters. They could have confessed that that they didn’t do a proper cost benefit analysis of the risks associated with their policies getting rid of Glass-Steagall, and ending aggressive enforcement of securities and commodities laws, and that they had absolutely no idea what might happen as a result.
But they didn’t. What they did was to define the debate over their failures as a question about their models. Here are some examples: Noah Smith, finance professor at SUNY Stony Brook, David Andolfatto at the St. Louis Fed, and Chris Dillow, economist and writer. Here’s one from December 2010, an interview with the neoliberal Gary Becker.
The gist of the defense is that it’s not fair to ask that their models predict disasters like the Great Crash. Here’s David Andolfatto:
But seriously, the delivery of precise time-dated forecasts of events is a mug’s game. If this is your goal, then you probably can’t beat theory-free statistical forecasting techniques. But this is not what economics is about. The goal, instead, is to develop theories that can be used to organize our thinking about various aspects of the way an economy functions. Most of these theories are “partial” in nature, designed to address a specific set of phenomena (there is no “grand unifying theory” so many theories coexist). These theories can also be used to make conditional forecasts: IF a set of circumstances hold, THEN a number of events are likely to follow. The models based on these theories can be used as laboratories to test and measure the effect, and desirability, of alternative hypothetical policy interventions (something not possible with purely statistical forecasting models).
That’s a pretty good description of the behavior of economists as described by Fourcade et al. They set up models and then tell politicians, central banks, legislators, regulators and all the rest of us how to behave and what policies are best.
But it turns out that not only are their models not going to give “time-dated forecasts of events” like the Great Crash, there are no circumstances under which their models will predict a financial crash until it’s upon us. Consider this paper from the staff of the International Monetary Fund. The abstract tells us “[t]his paper presents the theoretical structure of MAPMOD, a new IMF model designed to study vulnerabilities associated with excessive credit expansions, and to support macroprudential policy analysis.” They explain
As has been emphasized in a number of recent theoretical and empirical studies by the world’s leading policy institutions (see for example Macroeconomic Assessment Group, 2010), the critical macroprudential policy tradeoff is between reducing the risks of very costly financial crises and minimizing the costs of macroprudential policies during normal times.
The obvious implication is that economists never thought of using their models to figure out any of the circumstances under which those models would predict a crash. Worse, they didn’t use their models to estimate the cost generated by crashes until several years after their favored policies wrecked the financial system.
In this paper by Del Negro et al. of the New York Fed, the authors describe tweaks they made to a standard DSGE model and the addition of data as late as Fall 2008. Here’s their conclusion:
We show that as soon as the financial stress jumps in the Fall of 2008, the model successfully predicts a sharp contraction in economic activity along with a modest and more protracted decline in inflation. Price changes are projected to remain in the neighborhood of one percent. This result contrasts with the commonly held belief that such models are bound to fail to capture the broad contours of the Great Recession and the near stability of inflation.
The paper tells us that if you put in the data about a crash, their modes can predict the outcome. Of course, no one thought of doing that in the 20th Century when these guys were busy tearing down the regulatory structure. This model wasn’t even created until after the Great Crash, and it still won’t predict a crash; the authors had to put the crash into the data.
The plain fact is that economists converged on a set of ideas, perhaps because of the way the field is organized, as explained by Fourcade et al. Those ideas furthered the personal and corporate interests of the rich and of Wall Street, and drew their enthusiastic support. To these economists and their self-interested supporters, economic efficiency was so important that it wasn’t useful or reasonable to evaluate the costs of a crash. The US and other countries adopted their favored macroprudential policies, like getting rid of New Deal financial regulation. The result was trillions of dollars of damage. And how much were the gains from purported economic efficiency? And precisely who reaped those gains? And who paid the price? No surprises here: the gains, whatever they were, went to the rich and their friends on Wall Street, and the price was paid by the rest of us.
The problem is not that models created by economists didn’t predict this Great Crash. The problem is that the models are not designed to predict crashes. And even worse, they weren’t set up to evaluate the costs of events like the Great Crash. That means it was in utter ignorance of the costs of failure that economists told policy makers it would be great to get rid of the entire New Deal regulatory structure.
That’s one reason why people don’t love economists.