a key cause of the housing crisis? AND the dangers in not understanding the limits of models and statistics

On the latter, you see this a lot in economic "analysis"-- even from economists. They rely too heavily on models, statistics, quantitative analysis, and graphs-- without understanding their limitations. This isn't to say that one should throw out the baby with the proverbial bath water. But one should understand the limitations and avoid squirrelly inferences.

From Michael Barone at TownHall.com...

Several economic blogs have pointed me to this excellent article by Felix Salmon in Wired on the Gaussian copula devised by mathematician David X. Li in 2000. This was a mathematical formula to quantify risk that "was adopted by everybody from bond investors and Wall Street banks to ratings agencies and regulators. And it became so deeply entrenched—and was making people so much money—that warnings about its limitations were largely ignored." It turns out that the formula underestimated the risk of many homeowners defaulting on mortgages at the same time....turned out to be unreliable.

I see a pattern here: the attempt to see quantitative patterns in human behavior can be misleading unless it is supplemented by acquaintance with the qualitative facts on the ground....

I have been a consumer of political and demographic numbers from the time my parents bought the 1951 edition of the World Book Encyclopedia, which contained results from the 1950 Census....But as I have grown older, I have come increasingly to believe that the numbers are just clues. Sometimes misleading clues. There's a reality on the ground that you're trying to understand, and the numbers help you make sense about it, help you develop theories of why things are happening or changing as they are. But you can become over-dependent on numbers, as Wall Street became over-dependent on David X. Li's Gaussian copula, and end up being really, really wrong about reality. And you have to constantly keep that in mind....