I don’t think the analogy holds. With aircraft, yes, everything is modeled. But the corner points of the model get tested in real physical systems. They fly the AC into stall, to make sure that those numerical aerodynamic models work. They break a wing to check that the structure models work. In the end, they can do experiments to make sure they match the physical world. This blocks the race to the bottom; fancy justifications don’t fly :-) when the wing breaks at less than its design point. This is enforced both by FAA regulation and by the threat of liability. The organization doing the rating is exposed if something goes wrong, and has an incentive to play it straight.

Economic models don’t generally have this ability. Bloomberg had a two part article “Bringing Down Wall Street as Ratings Let Loose Subprime Scourge” discussing how the ratings agencies altered their models to boost ratings. There was definitely some relaxation of the risk correlation factor and requirements for diversity in the models. This relaxation was driven by the desire to give high ratings and please the customers paying to have their products rated. So there was definitely a race to the bottom, as the customers could go elsewhere. And the rating agency and to some extent the bank packaging the deal weren’t planning to keep any of the assets, so weren’t really exposed to the downside.

In other words, they may be pursuing this care for reasons other than health maintenance, and if the claims are great enough, lack of evidence is minimalized. Also, a thick envelope of “alternative” spirituality usually accompanies the product; its therapeutic value cannot be determined by mere rationality.

Uninsured credit-default swaps, how can this work? (not to mention the side bets placed on them) Who cares, when the promises are nearly infinite; don’t be so negative and bourgoise in your demands for evidence…

Normalization of deviance is a real problem with anything bubble-related, because, even though it’s really not that hard to tell when you’re in a bubble if you’re sensitized to the signs, it’s virtually impossible to predict when bubbles will end. It’s almost a disadvantage to be sharply attuned to bubble behavior. You’re just a Chicken Little act to everyone around you, after a while. You’re not wrong. Catastrophe is coming. But you’re just a drag, and everybody comes to hate seeing your sorry depressive ass looming in the hallway.

Interestingly, Vaughan’s earlier work on how couples break up (Decoupling) provided her an invaluable clue for understanding the Challenger launch decision (and the Columbia disaster later—it was the same damned social process, just eating away at a different part of the vehicle hardware.) Couple breakups can take a long time, but isn’t it funny how you can sometimes tell with a particular couple that it’s happening, even if it seems they don’t? It’s because you’re getting a snapshot of what, for them, is a gradual process of “normalizing” increasing differences in their relationship.

I live in Japan, visiting the U.S. now and again. I would come back one year and see, “Wow, 0% financing for cars, something’s wrong here.” Another year, another visit, “Wow, 0% financing for mortgages, this is nuts!”

I had two advantages, however: (1) I’d seen a couple of housing bubbles already, and I’d had friends and family lose their shirts in them, and (2) I was getting time-lapsed snapshots. Without the “benefit” (?) of both, it might be arrogant of me to assume I could have seen what was happening.

The result is that aircraft design indeed has much smaller safety margins than most engineering disciplines, and a much higher reliance on modelling to get every bit of performance out of a design. Still, aircraft have become extremely safe, while the financial world has completely lost control. It might be interesting to think why this difference exists.

My suspicion is the lack of (non-oligopolic) competition in aircraft industry. If there were a thousand aircraft manufacturers, including “hedge manufacturers” that rebuild existing planes to other specs, some more safe than others, a race to the safety bottom would be much more likely. As it is, companies gladly oblige the strongest safety regulations, because they know their competitors and know they adhere to the same rules, so they can pass on the cost to customers. The downside is massive overspending on safety, on the order of dozens of millions of dollars per life saved, much more than in most sectors.

Another aspect is PR: the aircraft industry knows that if flying was as safe as driving a car,
there would be massive crashes every few days, hurting the image of flying beyond repair. The financial world seems to fear such bad PR a lot less, perhaps because there are no human lives directly at stake, or perhaps it is less clear where to put the blame for financial crises.

I suppose when someone builds an airplane, they rather err on the side of caution. The same did (and does) not apply to financial models – as someone wrote up-thread, the model wouldn’t sell if it is too cautious (leverage makes slight differences in risk assessment into potentially large differences in returns).

By the way, saying “the models didn’t take the human factor into account” is of course absurd on its face – the models are produced, and employed, by humans in the first place, after all.

Fannie’s business people overrode the risk managers when making the decision to keep reserves too low. The models were right.

This sounds oddly reminiscent of the Challenger (yes, the space shuttle). The engineers were concerned about cold-weather performance of the solid-rocket-booster seals, but were overruled by the managers, who decided to launch anyway. Boom (literally). And the whole thing (well, not the disaster itself, but the decisionmaking that led up to it) might have been covered up if not for one oddball physicist.

Imagine you are working for an investment bank and you put together a new model in, say, 2005, predicting that within a few years, declining real estate prices will prevent the continuous refinancing of these complex loan instruments, leading to higher default rates and an industry-wide death spiral of securities devaluation. Your bank is currently exposed enough to become insolvent if this happens. Do you take that model to your boss? How do you expect he would react if you did? Fire you and look for someone with a positive attitude who works well with others, would be my guess.

Maybe we need to give a little more respect to negativity.

P.S. HTML blockquote doesn’t show up in the instant preview, so I added the quote tag too. We’ll see how it comes out when posted.

I agree. Part of the problem is that the market gives no hint how much the future should be discounted.

The best way to prevent this kind of crash is better regulation of the market.

Then we depend on good regulation. I’d like to see a clear basic explanation about how to do good regulation and how to avoid bad regulation. We need an excellent philosophy of regulation or else we’ll keep doing it badly.

Here’s a very quick sketch of a start at that. Economies and markets are games, played by rules. The legal system does not regulate such things well at all—taking someone to court is like an act of war, you can’t much hope to come out ahead, the best you can hope for is to hurt the other guy worse than you get hurt yourself. Libertarians who want to allow people to do pretty much what they want subject to lawsuit in courts similar to US courts, are being disingenuous.

One good way to regulate things would involve setting up clear rules for the game. The rules should be simple enough that people understand them easily. They should be easy to enforce. Players of the game should have an incentive to turn in cheaters, while at the same time they should have little incentive to falsely turn in innocents as cheaters.

The game and all its parts should be designed to promote the values we want, which include among others productivity, fairness, the continued existence and prosperity of the game, and an open invitation to those who are not playing or who are not playing hard to get more involved.

I would suggest as one minor detail that fractional-reserve banking should be illegal when performed by private entities rather than the government. When a US state charters a bank they give that bank a license to steal. As another minor detail, there should be careful study when it is better to have private monopolies that manage markets, versus government agencies whose job is to manage those markets. What are the important criteria to decide this question?

Also models tend to be tuned to particular risks. When the market is terribly competitive and things are good, focussing on tail risk might well lose you money in the short term. In the past that would have been fine for investment banks because they would have been long gone by the time there was trouble but that changed in the last few years and it is possible that the situation changed faster than the use of models. Pricing and risk management aren’t exactly the same.

The whole point about overcollateralisation is that if the definition of a credit rating of X is a probability of default of Y per cent, and the average default probability of the loans in your bucket is Z (where Z < Y), you add (Y-Z) per cent more loans to the pool over and above the face value of the security.

I can’t remember off the top the name of the bridge failure which caused Eads to change his models of iron bridge stress (and the Roeblings to be far more conservative in their design of the Brooklyn Bridge), but the defenses here of the financial models used from 2000-2008 strike me as if the Eads, Roeblings, etc had ignored every physical (and lifetaking) failure before them and barged ahead with their preferred models regardless of the actual physical world. That didn’t happen; Eads in particularly was known to have absorbed and learned extensively from previous failures.

Of course he was dealing with the immediate physical world, a concept which seems to have disappeared from Wall Street about 1990. “Outlier event”? I drove through the Inland Empire from 2002-2006 scratching my head and wondering exactly how the number of 1200 sq ft townhouses built on desert scrubland and priced at $450,000 could continue growing at 5 times the rate of Los Angeles’ population and job growth. But I guess no one who worked on these “models” bothered to check little things like your objective reality.

I put “models” in scare quotes because it is quite clear (and was clear at the time) that these “models” were just cream-skimming fraud justification machines. Which in all honesty did their job quite nicely: the Wall Street princes who caused this mess are safely off in the Connecticut mansions with $100 million in Swiss accounts. Too bad about us working stiffs.

Cranky