Nobel laureate Paul Krugman wrote an interesting article about why economists were spectacularly ineffective during the financial meltdown.
By 1970 or so, however, the study of financial markets seemed to have been taken over by Voltaire’s Dr. Pangloss, who insisted that we live in the best of all possible worlds. Discussion of investor irrationality, of bubbles, of destructive speculation had virtually disappeared from academic discourse. The field was dominated by the “efficient-market hypothesis,” promulgated by Eugene Fama of the University of Chicago, which claims that financial markets price assets precisely at their intrinsic worth given all publicly available information. (The price of a company’s stock, for example, always accurately reflects the company’s value given the information available on the company’s earnings, its business prospects and so on.) And by the 1980s, finance economists, notably Michael Jensen of the Harvard Business School, were arguing that because financial markets always get prices right, the best thing corporate chieftains can do, not just for themselves but for the sake of the economy, is to maximize their stock prices. In other words, finance economists believed that we should put the capital development of the nation in the hands of what Keynes had called a “casino.”
These events, however, which Keynes would have considered evidence of the unreliability of markets, did little to blunt the force of a beautiful idea. The theoretical model that finance economists developed by assuming that every investor rationally balances risk against reward — the so-called Capital Asset Pricing Model, or CAPM (pronounced cap-em) — is wonderfully elegant. And if you accept its premises it’s also extremely useful. CAPM not only tells you how to choose your portfolio — even more important from the financial industry’s point of view, it tells you how to put a price on financial derivatives, claims on claims. The elegance and apparent usefulness of the new theory led to a string of Nobel prizes for its creators, and many of the theory’s adepts also received more mundane rewards: Armed with their new models and formidable math skills — the more arcane uses of CAPM require physicist-level computations — mild-mannered business-school professors could and did become Wall Street rocket scientists, earning Wall Street paychecks.
To be fair, finance theorists didn’t accept the efficient-market hypothesis merely because it was elegant, convenient and lucrative. They also produced a great deal of statistical evidence, which at first seemed strongly supportive. But this evidence was of an oddly limited form. Finance economists rarely asked the seemingly obvious (though not easily answered) question of whether asset prices made sense given real-world fundamentals like earnings. Instead, they asked only whether asset prices made sense given other asset prices. Larry Summers, now the top economic adviser in the Obama administration, once mocked finance professors with a parable about “ketchup economists” who “have shown that two-quart bottles of ketchup invariably sell for exactly twice as much as one-quart bottles of ketchup,” and conclude from this that the ketchup market is perfectly efficient. [More]
Well, the nation's mathematicians reacted swiftly and pretty darn belligerently (speaking relatively, of course). They weren't taking that kind of dissing sitting down.
One can argue tell one is blue that "humans are different" and that "economics is about Homo sapiens and therefore intractable" but if there is any hope for economics, it seems to me, it is not to retreat away from mathematical sophistication. Sure, I agree, fancy math can hide bad economics (same thing holds in physics.) But fancy/deep/beautiful math can also help you go where others have not been able to tread. Math arising from physics has an especially surprising way of being relevant beyond the laws of physics. So retreat not, economists, from the shouting hordes of anti-math naysayers at the gates, but head over to your physics, computer science, and math departments, sit in on a class with a subject you don't know, and maybe, just maybe, it will give you tools to understand why the hell my 401K got hammered last year. [More]
So, as I read it, it wasn't the math at fault, it was the ham-handed deployment by under-qualified economists.
At the heart of the issue however, is the efficient market hypothesis (EMH). True, it is a wonderful concept. If only it worked in real life. Lately we've been finding that disconnect has been hiding in plain sight.
Kraft Foods has made a $16 billion bid to acquire Cadbury PLC, maker of fine British chocolates. Naturally, Cadbury turned them down:
Prior to Kraft going public with its offer on Monday, Cadbury had already rebuffed the advance in private. In publicly rejecting it, Cadbury said the offer, a 31% premium to its closing share price on Friday, "fundamentally undervalues" the company.This is precisely what every company always says whenever someone offers to buy them: even though the offer price is 20% or 30% or 40% higher than the current stock price, it always "fundamentally undervalues" the firm.
In other words, corporate CEOs universally reject the efficient market hypothesis, and since Wall Street as a whole seems to agree, that means that essentially the entire finance industry rejects the EMH. So if that's the case, why should anyone else believe it? [More]
My thinking is the use of computers models will go through a period of highly skeptical consideration before we all fall back into line with portentous announcements from quants - who are now roaming in wild packs on Wall Street.
But if you think the misplaced faith in computer models is a investment banking problem, consider how often our complicated policy and economic issues are driven by arguably more questionable modeling and data. From FAPRI to CARD, I think it is safe to say the quality of the computer models being used to analyze agriculture economics is not demonstrably better than those used by people who could pay essentially any amount for brains and data.
To be sure, modeling results are best used to compare competing ideas, but the same issues that underlie the growing disaffection with elaborate computer models based essentially on rational expectations from investors are at work in our sector as well.
This would explain how wildly farm program cost projections miss, for one thing. It also helps explain how competing factions can easily come up with model outputs pointing in opposite directions. Until we incorporate some aspects of behavioral economics into our industry models, I think we will be at the same risk as the supremely confident investment houses.