Quantifying the pull of poverty traps
In yesterday’s New York Times Science section, there was an article called “Life in the Red” (hat tip Becky Jaffe) about people’s behavior when they are in debt, summed up by this:
The usual explanations for reckless borrowing focus on people’s character, or social norms that promote free spending and instant gratification. But recent research has shown that scarcity by itself is enough to cause this kind of financial self-sabotage.
“When we put people in situations of scarcity in experiments, they get into poverty traps,” said Eldar Shafir, a professor of psychology and public affairs at Princeton. “They borrow at high interest rates that hurt them, in ways they knew to avoid when there was less scarcity.”
The psychological burden of debt not only saps intellectual resources, it also reinforces the reckless behavior, and quickly, Dr. Shafir and other experts said. Millions of Americans have been keeping the lights on through hard times with borrowed money, running a kind of shell game to keep bill collectors away.
So what we’ve got here is a feedback loop of poverty, which certainly jives with my observations of friends and acquaintances I’ve seen who are in debt.
I’m guessing the experiments described in the article are not as bad as real life, however.
I say that because I’ve been talking on this blog as well as in my recent math talks about a separate feedback loop involving models, namely the feedback loop whereby people who are judged poor by the model are offered increasingly bad terms on their loans. I call it the death spiral of modeling.
If you think about how these two effects work together – the array of offers gets worse as your vulnerability to bad deals increases – then you start to understand what half of our country is actually living through on a day-to-day basis.
As an aside, I have an enormous amount of empathy for people experiencing this poverty trap. I don’t think it’s a moral issue to be in debt: nobody wants to be poor, and nobody plans it that way.
This opinion article (hat tip Laura Strausfeld), also in yesterday’s New York Times, makes the important point that listening to a bunch of rich, judgmental people like David Bach, Dave Ramsey, and Suze Orman telling us it’s our fault we haven’t finished saving for retirement isn’t actually useful, and suggest we individually choose a money issue to take charge and sort out.
So my empathetic nerd take on poverty traps is this: how can we quantitatively measure this phenomenon, or more precisely these phenomena, since we’ve identified at least two feedback loops?
One reason it’s hard is that it’d be hard to perform natural tests where some people are submitted to the toxic environment but other people aren’t – it’s the “people who aren’t” category that’s the hard part, of course.
For the vulnerability to bad terms, the article describes the level of harassment that people receive from bill collectors as a factor in how they react, which doesn’t surprise anyone who’s ever dealt with a bill collector. Are there certain people who don’t get harassed for whatever reason, and do they fall prey to bad deals at a different rate? Are there local laws in some places prohibiting certain harassment? Can we go to another country where the bill collectors are reined in and see how people in debt behave there?
Also, in terms of availability of loans, it might be relatively easy to start out with people who live in states with payday loans versus people who don’t, and see how much faster the poverty spiral overtakes people with worse options. Of course, as crappy loans get more and more available online, this proximity study will become moot.
It’s also going to be tricky to tease out the two effects from each other. One is a question of supply and the other is a question of demand, and as we know those two are related.
I’m not answering these questions today, it’s a long-term project that I need your help on, so please comment below with ideas. Maybe if we have a few good ideas and if we find some data we can plan a data hackathon.