Showing posts with label poverty. Show all posts
Showing posts with label poverty. Show all posts

Wednesday, September 4, 2013

This is a really big deal

From Yglesias
Most low-income Americans aren’t poor at all by global standards, so evidence from successful anti-poverty programs in the developing world are difficult to apply to domestic poverty. That’s why it’s so telling and fascinating that a study on the cognitive downsides of poverty would find identical results in New Jersey and Tamil Nadu. Much work on domestic poverty rightly emphasizes the idea of skills and “human capital” needed to navigate a complicated modern economy. This naturally leads to a focus on education, whether in the guise of various school-reform crusades or the push to bring high-quality, affordable preschool to more households. But adults need help, too, and the perception that poor adults—as opposed to presumably innocent children—are irresponsible often leads to reluctance to treat adults as adults who are capable of deciding for themselves how best to use financial resources.
This paternalistic notion that we should be relatively stingy with help, and make sure to attach it to complicated eligibility requirements and tests, may itself be contributing to the problem of poverty. At home or abroad, the strain of constantly worrying about money is a substantial barrier to the smart decision-making that people in tough circumstances need to succeed. One of the best ways to help the poor help themselves, in other words, is to simply make them less poor.

The causal ordering here is really important.  We see this dilemma with other variables that are difficult to randomize.  So, for example, it isn't 100% clear if lack of exercise contributes to obesity or if being heavy makes one less likely to exercise.  It can make a big difference in public policy if the causal arrow reverses direction (or if there is a positive feedback loop that goes between the two variables).

In this case, there seems to be evidence that making a stingier and more complex welfare state increases the long run poverty via decreased decision making due to financial stress.  If this is borne out in other context then it totally changes the optimal policy responses to poverty. 

Friday, July 29, 2011

Words of Wisdom -- Weekend Edition

Felix Salmon is unimpressed with Alan Greenspan and suggests a different perspective:

In fact, the opposite is true — ask anybody who has experienced both wealth and poverty. When you’re wealthy — when you have a nice capital buffer to absorb mistakes — you don’t worry so much about running risks, and you’re significantly happier than when you’re poor and you have to be much more worried about where your money might end up. Insurance improves living standards, it doesn’t detract from them. Let’s have more of it.

Monday, May 31, 2010

Robert Samuelson would not make a good statistician

Robert Samuelson is taking considerable heat for this column in the Washington Post complaining about the way we measure poverty. Dean Baker and Mark Thoma posted detailed and highly critical responses that listed several problems with Samuelson's argument. Both of them, however, skipped over at least one serious statistical flaw in the column.

Here's the quote from Samuelson:
Second, the poor's material well-being has improved. The official poverty measure obscures this by counting only pre-tax cash income and ignoring other sources of support. These include the earned-income tax credit (a rebate to low-income workers), food stamps, health insurance (Medicaid), and housing and energy subsidies. Spending by poor households from all sources may be double their reported income, reports a study by Nicholas Eberstadt of the American Enterprise Institute. Although many poor live hand-to-mouth, they've participated in rising living standards. In 2005, 91 percent had microwaves, 79 percent air conditioning and 48 percent cellphones.
The fallacy here is closely related to the phenomena of the wrong-way coefficient. You fit a model and you see a statistically significant variable with the wrong sign. For a fairly silly example, you build a model predicting how long it takes travellers to get from New York City to DC and you find that the indicator for being searched by a uniformed officer has a negative coefficient which would suggest that being searched somehow shortens your travel time. The explanation for this counterintuitive result is that there's a relationship between this variable and one or more of the other variables in your model. In this case there's a strong correlation between being searched and flying vs. driving.

For people living in residences with functioning kitchens, good ventilation and a land line, getting a microwave, an air conditioner and a prepaid cellphone clearly represents an increase in well being. If, however, there is an inverse relationship among the poor between having a stove/having a microwave, or ventilation/AC or land line/cell, then the high incidence rates could easily indicate a lower standard of living.

For an example of how not having a stove could make having a microwave more likely, check out this story from NPR:
So many immigrants, homeless people and others of limited means living in single-room occupancies (SROs) have no kitchens, no legal or official place to cook. To get a hot meal, or eat traditional foods from the countries they've left behind, they have to sneak a kind of kitchen into their places. Crock pots, hot plates, microwaves and toaster ovens hidden under the bed. And now, the latest and safest appliance, the appliance that comes in so many colors it looks like a modern piece of furniture: the George Foreman Grill. It is, quite literally, a hidden kitchen.
For me, a George Foreman grill would be a luxury purchase, but not having one doesn't mean I'm worse off than the next guy I see pushing a shopping cart with all of his belongings down the street.