Thank you, Joseph Stiglitz, for providing so much fodder for free-market economists to use in their classrooms this spring.
The fodder can be found in new research (with Bruce Greenwald) Stiglitz is touting. In it, he presents statistical relationships between technological improvements in agriculture and unemployment in the 1930s. He asks, What turned an otherwise normal market correction into a long, grueling depression characterized by persistent double-digit rates of unemployment? It was, he answers, at least in part, that damned agricultural technology causing all those workers to become displaced. Absent that, unemployment never would have skyrocketed, and the US job market could have maintained the halcyon days of the 1870s, when more than half of all workers worked on the farm. Surely, the economy of the 1930s — as we know it today — never would have occurred.
So goes mainstream neoclassical research, where truth is only what can be measured and then fit into mathematical models. The problem is that these models are only as good as their assumptions; when real, important information is not measurable, it is simply ignored — or assumed to exist in the error term and the corresponding vector or residuals.
This is the same problem that afflicted mainstream economics during the lead-up to the financial crisis. Again, many mainstream economists, including Stiglitz,1 were caught almost completely by surprise because their models did not pick up extremely relevant information pertaining to the housing and banking industries, because it wasn’t measurable. Meanwhile, those economists working with less empirical and more a priori approaches were very concerned about what was happening in both industries and were much less surprised by the crash. Many, in fact, predicted it.2
Note which approach — the mainstream empirics or the a priori — gets more heavily funded by the government. Note which approach is more likely to provide a theoretical justification for government action.
There is abundant evidence that Stiglitz’s findings reflect statistical correlations, and not causations. This is especially true because other countries made the transition from farming to manufacturing without significant employment stress. Stiglitz’s theory also lets the Hoover and Roosevelt administrations off the hook, whose policies hindered the price system from reallocating resources as efficiently as what took place in other countries.
Think about it. By the first half of the 20th century, there was a surplus of agricultural output for the first time in human history. This surplus, blessedly, placed a downward pressure on food prices. Then along came Hoover and FDR with policies to keep agricultural prices higher than they otherwise would have been, or at some level that reflects their price levels prior to the explosion in agricultural output. The economic results of these interventions are both predictable and disastrous:
The quantity demanded of farm output falls (because prices are kept high).
Agricultural unemployment skyrockets (because of reduced demand for output).
Many millions of people who would otherwise have been able to support themselves and their families working in agriculture then become dependent on the state.
Agricultural surpluses resulting from the artificial (and violently enforced) price increases lead to bizarre secondary interventions requiring the government to destroy food at a time when millions earned starvation wages, if any at all.
But such effects should be ignored, because the Great Stiglitz has found a correlation in the observable data!
We would do well to remember the context in which economic ideas are promulgated today. Remember, Stiglitz is paid well by the government to provide intellectual heft to market-failure arguments that justify an expansion of the government relative to the market. Even his 2001 Nobel Prize, which he shared with George Akerlof and Michael Spence, was for his work in the area of asymmetric information, which is used by many today to justify state regulation of all trade. So it perhaps makes sense that, today, he argues that technological improvements can lead to a decade-long depression at a time when many people are beginning to question the real practicality of unprecedented fiscal and monetary interventions during significant market corrections (both of which happened in the years following 1929 and 2008, respectively).
In the process, he damns technology (in the spirit of Ned Ludd, I’d add), ignoring the role of technological improvement to allow mankind to emerge from solitary, poor, nasty, and brutish lives. Technological improvements in the farm sector particularly caused much of the material progress in the 20th century, because it enabled the agricultural sector to maintain productivity with fewer workers, allowing surplus workers to move into the cities to work in other industries — industries that didn’t even exist 50 years earlier — and caused aggregate GDP to explode.
Absent this phenomenon, there would be no middle class today.
Yet, Stiglitz argues that technological improvements are a market failure, even though most of the transition from agriculture to manufacturing occurred 20–30 years prior to 1929. Like many in the mainstream, he focuses on the seen as opposed to the unseen effects of policy — because these effects, after all, can be easily inserted into elegant econometric models — and he ignores much economic theory and economic history to make his particular story work.
It’s hard to believe that so many argue in a similar fashion today that technological advances in the financial sector were the primary cause of the 2008 financial meltdown as well, thus absolving (say) the Federal Reserve’s interest-rate policy from 2002 to 2004, coupled with federal housing market manipulations.
It’s hard to believe such research is taken seriously simply because it highlights a supposed market failure and, by extension, justifies an even stronger role for government in the market.
- 1From Joseph E. Stiglitz, Jonathan M. Orszag, and Peter R. Orszag, “Implications of the New Fannie Mae and Freddie Mac Risk-based Capital Standard”: This analysis shows that, based on historical data, the probability of a shock as severe as embodied in the risk-based capital standard is substantially less than one in 500,000 — and may be smaller than one in three million. Given the low probability of the stress test shock occurring, and assuming that Fannie Mae and Freddie Mac hold sufficient capital to withstand that shock, the exposure of the government to the risk that the GSEs will become insolvent appears quite low. Given the extremely small probability of default by the GSEs, the expected monetary costs of exposure to GSE insolvency are relatively small — even given very large levels of outstanding GSE debt and assuming that the government would bear the costs of all GSE debt in the case of insolvency. For example, if the probability of the stress test conditions occurring is less than one in 500,000, and if the GSEs hold sufficient capital to withstand the stress test, the implication is that the expected cost to the government of providing an explicit government guarantee on $1 trillion in GSE debt is just $2 million.
- 2From Mark Thornton,“Who Predicted the Bubble? Who Predicted the Crash?”: It is especially noteworthy that the Austrian predictions all provided an economic explanation of the bubble and that their explanations were relatively consistent across the group. To generalize, they saw the Federal Reserve as following a loose money policy that kept interest rates before the rates that would have existed in the absence of inflationary monetary policy. Individual writers emphasized the willingness of the Federal Reserve to consistently bail out and rescue investors during the 1990s, thereby desensitizing investors to risk. As a result, a period of “exuberance” and wild speculation took place building into the hysteria of a stock market bubble. If the Austrian analysis is correct, this would suggest that the Federal Reserve is a significant source of financial and economic instability. It also suggests that the general bias to keep rates as low as possible can cause significant losses in the economy and that a better policy might be to let interest rates be determined by market forces, without the intervention of the Federal Reserve.
