September 29, 2008. The Dow Jones Industrial Average is down 777.68 points. The biggest single-day loss in the index’s history. An economic catastrophe roaring to life. What followed was the worst financial crisis since the Great Depression, in which a “perfect storm” of economic variables synced up with one another and launched a surprise attack on Wall Street. So, what happened during the 2008 financial crisis?
Let’s set the stage. We start out with 3 groups of people: homeowners with mortgages for their homes, investors with money from mutual funds (where people pool their money for investing purposes) or insurance companies, and banks/brokers who bring together these 2 groups. But before the investors were investors, they were once people with a lot of money, looking to turn that money into more money. Ordinarily, they’d go to the US Federal Reserve and buy Treasury bills (basically Treasury bonds with short maturity terms, from 4 weeks to a year), but their interest rates were lowered to 1% in the early 2000s, so investors lost enthusiasm as 1% is an insultingly low return!
On the other hand, this means banks can borrow money from the Fed with only a 1% interest fee, and so naturally, banks start borrowing more money and go crazy with what’s called leverage - when you borrow money to buff up the outcome of a deal in your favor. How does this work? For example, John buys something for $100 and then sells it to someone else for $110, thereby earning a $10 profit - nice, simple business. But Susan, also with only $100 on hand, is eyeing something worth $1000. So what does she do? She borrows $900 from the bank, buys the $1000 item, and then sells it for $1200.
She pays back her loan with $50 interest, meaning her final profit is $150 ($1200 - $1000 - $50). This process is a major way banks make money. Investors also want a piece of the action, so here’s what happens: a family looking to buy a house contacts a mortgage broker, who then connects them to a mortgage lender, who then lends them a mortgage bond, with the broker earning commission for their work. One day, an investor buys not just that particular mortgage bond but thousands of others using borrowed money and puts them all into a collateralized debt obligation (a pool of mortgage bonds to be bought and sold).
Since the CDO is divided into 3 sections, the senior, mezzanine, and equity tranches, a few homeowners defaulting on their mortgages would result in less money flowing into specifically the equity tranche. That’s the riskiest chunk of the asset, and so it offered the most returns. Even though the senior tranche is the safest one, banks wanted to be extra sure and started insuring it through credit default swaps, where other investors would pay insurance premiums in exchange for insurance money in case things went bust.
The nice thing about dividing the CDO into sections is that the owner can sell them individually to investors with varying levels of risk tolerance, thus generating even more money and allowing the CDO owner to repay his loans. This process essentially rinses and repeats itself: the investor buys more mortgages, puts together more CDOs, and sells more CDO sections. From nearly every stakeholder’s point of view, the procedure worked well since the risk carried with owning mortgages was simply sold off to whoever wanted to buy them.
But what happens when the mortgage broker can’t find anyone to sell the mortgage bond to? The broker starts lowering his standards for who the mortgages can be lent to. In other words, they build risk. So the broker switches from prime mortgages, which are ones lent to responsible homeowners, to subprime mortgages, ones lent to…less than responsible homeowners. And here is where things begin to change. For the worse, of course.
The mortgage broker goes through the same process described above with their new, subprime mortgage borrowers. To everyone’s surprise, the subprime homeowners default on their loan, turning one of the banker’s monthly payments into a house (since defaulting on a mortgage typically means you give up the house to the bank). This isn’t a huge problem in and of itself, as the banker can simply sell off the home. But if more and more of his monthly payments end up becoming homes, which then results in more and more of them being put up for sale on the market, this creates an excess supply of housing relative to demand.
According to the law of demand, if supply exceeds the people’s ability and willingness to buy it, the price goes down. In the case of housing, prices went way down:
For homeowners especially, this is a big problem. They’re wondering why they have to pay a $300,000 mortgage for a house that’s now worth less than half of that. It literally makes no sense to continue paying even if you could afford to. So now even the prime mortgage borrowers start defaulting on their loans. Mortgage default rates suddenly go through the roof:
The CDO owner now just has a bunch of worthless houses instead of a flow of money - which is needed to pay off the loans that they used to buy the CDO in the first place. And it’s not like the CDO could just be sold to someone else for a high fee, as everyone now knows that they no longer generate money. With that, big banks start going bankrupt, triggering worry and fear among American investors. Since it’s ultimately investor prospects that drive the financial markets, we end up with a financial crisis.
Econ IRL
With the Russian-Ukraine conflict sending gas prices soaring, the idea of electric vehicles has in turn become more popular. It shouldn’t be any surprise to hear that there is currently a strong push towards adopting EVs over diesel and hybrid vehicles. But to determine the effectiveness of policies regarding this goal, we must first understand how drivers choose to refuel their vehicles and their preferences in doing so. Recognizing the lack of information on that end, this week’s paper uses GPS data on driving routes, refueling stops, and gas station prices to get a clear picture of drivers’ fueling preferences.
Although it may not seem like much, the authors were able to extrapolate a lot information from the aforementioned data:
Which stations drivers actually visited, as well as which stations within their travel routes they could have visited
Drivers’ value of travel time, which is inferred from their willingness to travel further in exchange for a lower expected gas price. The researchers find that drivers value their time at around $27.54/hr, meaning that drivers are willing to drive to a gas station an hour away only if the gas prices at that station saves them at least $27.54
How drivers guess various station prices, in which it’s found that drivers rely primarily on long-run average prices when estimating the price they’ll have to pay as they pull over towards a given gas station. Interestingly enough, drivers with more information regarding gas station prices increase their consumer surplus by only about 2 cents per gallon, which makes sense when considering the point above, namely that driving further, even to cheaper stations, is costly. In other words, drivers don’t really gain much from learning about stations’ prices located further from their route. From a policy perspective, this means that mandating price disclosure will in fact result in limited benefits to consumers
‘Till next time,
SoBasically