The Big Short was released last week, and I took a small break from my research work to watch it with my wife. The movie theater was quite empty (looked more like a documentary about banking, mortgages, CDOs, Synthetic CDOs) but the movie has a nice IMDB rating (8.1/10).
The star-studded movie features Brad Pitt, Steve Carell, and many others, playing traders who figured out early on that Mortgage Backed Securities (MBSs) had AAA ratings that were too good to be true.
Some columnists (Forbes…) don’t like the movie: unhappy that regulators are not getting the blame for the mortgage crisis.
As with plane crashes, the 2008 crisis is not driven by one single incident that took down the economy. It’s a series of incidents happening at the same time:
- Households did have inflated expectations of house price increases. That’s well documented in the usual Shiller references. Households were wrong on the pace, probably not on the fact that some MSA supply can’t expand (e.g. San Francisco). Irrational exuberance was everywhere, but likely more in places where land is abundant but prices keep increasing. Look at the scary Case Shiller house price index in Dallas: St Louis Dallas TX House price index
- The securitization market has an asymmetric information problem: lemons are chasing the good products, a problem that was amplified by simple securitization rules (such as a minimum FICO requirement).
- Securitized products can be complex, very complex. But that’s a pretty fixable problem: loan-level data does exist, and it’s fairly easy to dig into the characteristics of the mortgages to check that the MBS is sound.
- Accounting rules such as the Basel agreements, give preferential capital treatment to securitized products. In plain English, they get a lower coefficient in the calculation of the capital ratios. That’s a substantial incentive to package products in CDOs.
- Once mortgages are packaged into a single securitized product, the price of the MBS depends on an evaluation of the risk. Takes some additional homework to figure out whether the price is right.
- Yes, pooling mortgages leads to a lower risk for the MBS as a whole, but that’s only true if the risks are roughly independent (that’s essentially an application of the central limit theorem in statistics). But that’s a wrong application of the central limit theorem if that leads people to think that packaging anything will lead to lower risk: if there are correlated shocks that affect all assets of the securitized product at the same time, packaging will do little to lower risk.
- Catastrophe was brewing when Fannie and Freddie withdrew from the market and the so-called Private Label Securitizers took their market share. You can see this quite easily using data I got from Blackbox.
- Adjustable rate mortgages (ARM) were OK as long as prices were rising. Households were not expecting to see the adjustable rate period kick in.
What about Fannie Mae and Freddie Mac’s housing goals?
Fannie and Freddie did have securitization goals (set by Congress) but these were for either underserved areas or low-income households. And careful estimation of the impact of these thresholds on mortgage supply suggests there isn’t much happening there. These housing goals don’t seem to be the reason the crisis. As mentioned earlier, it’s more that, when the GSEs withdrew, private label securitizers took the GSEs’ market share, with much less rigorous securitization practices.
What about monetary policy?
The fed started tightening around 2006 but no one can really say that a single interest rate can be the cause of this. The transmission channels of monetary policy are just too complex to be able to estimate the impact of nationwide interest rates on the housing market. Some markets didn’t heat up, after all.
So it’s got quite little to do with the GSEs Fannie and Freddie — it’s a story of capital ratios, PLS securitization markets, and overinflated household expectations. Doesn’t seem like we’ve done much on these topics since the crisis.
My work on the topic is forthcoming in the Review of Economics and Statistics.