Recently, my favorite radio show teamed up with NPR news to do an in-depth collaboration on exactly what went wrong with the US sub-prime mortgage crisis. It turns out to be a perfect example of how a complex system can go wrong. So I thought I'd give a summary of what they found, and discuss how it relates to what we know about complex systems in general.
The whole thing started with what our radio hosts call "the global pool of money." In the early 2000's, there ended up being a whole lot of people around the globe with lots of money to invest. The amount of money looking to be invested had doubled in the past xxx years, due in part to growing economies in other countries.
The wealth holders of this money needed somewhere to invest this money, to keep it safe and growing. A large subset of them wanted safe investments, where the return on their money would be moderate but reliable. So they and their brokers looked around for safe investments to make.
While this was happening, Alan Greenspan was trying to help the US economy out of the post-internet bubble slump. He did this by setting interest rates extremely low: around 1%. This means that US treasury bonds, one of the safest investments historically, would be getting extremely low returns for a long time. So the pool of money had to look elsewhere.
The lack of traditional safe investment options meant that the brokers had to get creative. So they looked around and they saw this:
All over the country, retail banks (the kind of banks you and I use) were loaning money to homeowners, who were repaying the money with interest. These were safe investments on the banks' part because historically, very few homeowners default on their mortgages. The brokers wanted to get in on this action, but mortgages are too small and detailed to get involved with on an individual level. So they set up a system like this:
The retail banks would lend money to homeowners, and then sell these mortgages to investment banks. The investment banks would buy tons of these mortgages and organize them into "bundles" of hundreds at a time. These bundles would be sold to Wall Street firms, who would create "mortgage-backed securities" out of the bundles, and sell shares in these securites to the global pool of money.
This system worked fine for a while. But by 2003 or so, virtually every credit-worthy indvidual with a home had already taken a mortgage. There were no more mortgages to be bought. But the global pool of money had seen how effective these mortgage-backed securities were, and they demanded more. This sent an echoing voice all the way down the chain saying "GIVE US MORE MORTGAGES!"
To fill this incredible demand, the retail banks started relaxing the standards for who they loaned to. The radio show tells the fascinating story of how every week, one requirement after another was dropped, until they reached rock bottom: the NINA loan. NINA stands for "No Income, No Asset." It means you can get a loan without even claiming to have a job or any money in the bank whatsoever. In the words of one former mortgage banker "All you needed was a credit score, and a pulse."
In the old system, no bank would ever think of giving a loan without verifying the borrowers income and assets. This is because the bank had an interest in seeing that it got its money back. But under the new system, the banks would just sell the mortgage up the chain and wash their hands of it. If the borrower defaulted two months later, it would be someone else's problem.
Still, you would think that someone would realize that an investment system built on no income, no asset loans was bound to fail. And indeed, many people did realize it. But the money kept flowing in from the global pool, and everyone in the chain was getting rich in the process. Saying "no" to the system seemed like ignoring a pot of gold right in front of your face.
Two additional factors prevented reason from prevailing. First, the computer models used by the investment banks and Wall Street firms were telling them that everything was going fine. No one made the connection that the models were using data from pre-2003, when loans were made on the basis of actual assets. Second, housing prices in the US were going up. If a borrower defaulted, then the bank would own the house, which as long as prices were rising would be worth more than the bank loaned originally.
Of course, housing prices didn't keep going up. And the Wall Street firms noticed at some point that some of the mortgages they were investing in were defaulting on the very first payment. So they stopped buying these bundled mortgages. At that point, the middlemen in the system (the retail and investment banks) were left holding mortgages that no one up the chain wanted, and that would almost certainly be defaulted from the bottom of the chain. And they went bankrupt en masse.
That's enough writing for today. Next time we'll use this crisis as a case study for some general complex systems principles.
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in The Biology Files
Pirates are even cooler than we thought!
So this is mostly a "I saw this and thought it was cool" kind of post: An article in Sunday's Boston Globe describes the research of Peter Leeson and Marcus Rediker claiming that pirates were practicing democracy aboard their ships in the 1600's, well before America or Europe ever got around to it.
Before each voyage, pirates voted on a captain and a quartermaster, whose main job was to be a check on the captain's power. Either officer could be "recalled" at any time. Ground rules were laid out in a written charter. They also had primitive forms of trial and workmen's compensation.
The researchers differ on the motivation for this democracy. Leeson sees it as a necessary organizational system for a cadre of criminals who have to work together without killing each other. Rediker sees it as a political reaction to despotic organization of commercial ships, wherein captains hold absolute power and floggings were routine and often deadly. Pirates, according to Rediker, tried to create a utopian alternative.
Inasmuch as there is a single motivation for anything, I'm inclined to agree with Leeson's point of view. The success of a pirate ship depends on the ability of its members to work together. There is a natural check on any one pirate's power in that any other pirate could pretty easily kill him in his sleep. Unlike the case of commercial ships, pirate society is not tied to any larger land-based social structures.
The question then becomes, what is the based way to maintain organization in a small self-contained society where no individual can dominate the others through force? I think the best and perhaps only workable answer in the long term is democracy, or something like it.
Before each voyage, pirates voted on a captain and a quartermaster, whose main job was to be a check on the captain's power. Either officer could be "recalled" at any time. Ground rules were laid out in a written charter. They also had primitive forms of trial and workmen's compensation.
The researchers differ on the motivation for this democracy. Leeson sees it as a necessary organizational system for a cadre of criminals who have to work together without killing each other. Rediker sees it as a political reaction to despotic organization of commercial ships, wherein captains hold absolute power and floggings were routine and often deadly. Pirates, according to Rediker, tried to create a utopian alternative.
Inasmuch as there is a single motivation for anything, I'm inclined to agree with Leeson's point of view. The success of a pirate ship depends on the ability of its members to work together. There is a natural check on any one pirate's power in that any other pirate could pretty easily kill him in his sleep. Unlike the case of commercial ships, pirate society is not tied to any larger land-based social structures.
The question then becomes, what is the based way to maintain organization in a small self-contained society where no individual can dominate the others through force? I think the best and perhaps only workable answer in the long term is democracy, or something like it.
Life's Universal Scaling Law
It ain't easy being green. Biology has long suffered under the label "soft science," a term used (often disparagingly) to draw a contrast with the "hard sciences" of physics and chemistry, whose laws are guaranteed with the certainty of mathematics. But this picture is not altogether true. While biological processes are more complex than physical ones, making simple mathematical formulas harder to come by, there are yet some mathematical rules that hold with a remarkable degree of consistency.
One famous example is the relationship of a animal's mass to its metabolism (the rate at which it expends energy). This relationship is expressed in the simple formula
R = R0M3/4,
where R is the metabolic rate, R0 is a constant, and M is the mass of the organism.
Separate laws exist for mammals, birds, unicellular organisms, and even living structures like mitochondria within cells. The values of R0 are
different for each law, but the mysterious 3/4 exponent stays the same.
These laws have been observed since 1930, but the reason for the 3/4 exponent has been a mystery until recently. The discovery by Geoff West et al of a mechanism underlying this law was a major triumph for the complex systems movement: a universal law of life explained by complex systems principles.
Specifically, West showed that the 3/4 exponent comes from the way a living thing distributes its resources. If the cells in an animal acted like independent beings, each gathering and consuming its own food, the metabolic rate would be a simple multiple of the mass, that is
R = R0M
with no exponent. But the cells of an animal aren't independent. They work together to collect, process, and consume energy. To do this they need networks (such as blood vessels) to move resources around. West and his collaborators showed that the 3/4 exponent is determined by the requirements that the network a) reach every part of the animal's body, and b) waste as little energy as possible.
Extending this approach, they were able to explain other scaling laws like the relationship between heart rate and mass. Currently, West is investigating scaling laws in large-scale living communities, such as forests and cities.
I haven't talked much about network theory (a topic for another time perhaps) but West's work suggests the great potential of this complex systems subfield to explain some of life's mysteries.
One famous example is the relationship of a animal's mass to its metabolism (the rate at which it expends energy). This relationship is expressed in the simple formula
R = R0M3/4,
where R is the metabolic rate, R0 is a constant, and M is the mass of the organism.
Separate laws exist for mammals, birds, unicellular organisms, and even living structures like mitochondria within cells. The values of R0 are
different for each law, but the mysterious 3/4 exponent stays the same.
These laws have been observed since 1930, but the reason for the 3/4 exponent has been a mystery until recently. The discovery by Geoff West et al of a mechanism underlying this law was a major triumph for the complex systems movement: a universal law of life explained by complex systems principles.
Specifically, West showed that the 3/4 exponent comes from the way a living thing distributes its resources. If the cells in an animal acted like independent beings, each gathering and consuming its own food, the metabolic rate would be a simple multiple of the mass, that is
R = R0M
with no exponent. But the cells of an animal aren't independent. They work together to collect, process, and consume energy. To do this they need networks (such as blood vessels) to move resources around. West and his collaborators showed that the 3/4 exponent is determined by the requirements that the network a) reach every part of the animal's body, and b) waste as little energy as possible.
Extending this approach, they were able to explain other scaling laws like the relationship between heart rate and mass. Currently, West is investigating scaling laws in large-scale living communities, such as forests and cities.
I haven't talked much about network theory (a topic for another time perhaps) but West's work suggests the great potential of this complex systems subfield to explain some of life's mysteries.
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