Should you move to a better county?

5/06/2015 09:49:00 AM
That said, for the marginal family on the verge of moving, this looks about right.
A fun and interesting post/app about economic mobility at the NYT Upshot blew up twitter a couple days ago. At least, it blew up my section of twitter, which consists mostly of phd economists tweeting how important this research is. The post was about a paper by Raj Chetty and Nathaniel Hendren, "The Impacts of Neighborhoods on Intergenerational Mobility: Childhood Exposure Effects and County-Level Estimates" which used a unique identification strategy to tease out the causal effect of moving to each county in the US on children's outcomes.

I'm going to make a bold claim: the paper is actually not that important to the general public. It's certainly interesting from an academic perspective, but I'll argue that it has very limited policy implications and the research literature isn't really ready for popular press.

Chetty and Hendren obtained estimates of the effects various counties have on kids outcomes. The interpretation that the NYT Upshot piece drew from this is that if you move to a county like, say, Warren county Ohio, your kids will end up earning $2,500 more per year, on average, whereas moving to Hamilton county Ohio would them to earn $800 less. What policy conclusions can we draw from this? It's unclear. The Upshot also noted that research found that policies that actually paid poor people to move to nicer neighborhoods failed to achieve the desired result, so the policy implication would seem not to encourage people to move from "bad" counties to "good" ones. Even ignoring the previous negative result, there would still be tons of work to do before we begin proposing such a plan--moving people from county to county involves substantially higher costs and more serious consequences than merely paying for apartments in nicer buildings as the previous programs did. More realistically, this paper is merely a continuation of the line of research, and Chetty and Hendren conclude with their recommendation for the next step:
"We hope these data facilitate future work exploring the mechanisms through which neighborhoods have causal effects on intergenerational mobility."
That's a long ways off from any actionable policy advice. More realistically, what Chetty and Hendren have done is constructed an index of county effects on child outcomes, which can then be used in future papers as an instrument to identify things that improve outcomes for poor children. As of right now, we really don't have a good idea on what causes the effects Chetty and Hendren measured, or even if they correctly measured those effects. Hence, the research literature really isn't ripe for public consumption.1

So why were all the twitter economists tweeting how "important" this paper is? That remains unclear to me. As Brian Albrecht pointed out, it's not as if the paper upsets old paradigms No one really doubted that location matters before. What Chetty and Hendren did--something that Chetty is freakishly good at--is found a novel identification strategy for teasing out causal effects from the overall correlation between movement and child outcomes. Mere correlation could have been caused by endogeity bias, but Chetty and Hendren were able to extract a component that we can be reasonably confident is causal.

But "causal" is a nebulous construct. Let's examine their identification strategy. They have a dataset in which families have moved from county to county, and they have data on the child outcomes in these various counties. The problem with simply regressing the one on the other is that people don't just move at random, they move at least in part because of how good they think these counties will be for their children. What Chetty and Hendren did was look instead at the ages of the kids when they moved, and--taken literally--found that the younger the kids are when they moved, the bigger the correlation is between county and their outcomes. Intuitively, if a family has two kids of different ages when they move to a "good" county, the younger child does better later in life than the older child. If you are willing to assume that the reasons for moving to these counties, by and large, is unrelated to the ages of their children, then we can interpret this correlation as the causal effect of the county on child outcomes. If we were just observing upwardly mobile families moving to these counties, instead of the counties making them upwardly mobile, then the correlation should be the same for both the older and younger child. So the estimate is "causal." But what is causing what for whom?

This is far from a clear result. And the results themselves were often very strange: It's quite possible here that Chetty and Hendren have a ceteris parabis problem with their data. The big secret with these causal inference models is that they are all about 10 percent statistics and 90 percent picking the right control group. By using younger and older siblings in families that moved, the paper tries to mimic an RCT where the treatment group is families who moved and the control group is families with identical income who haven't moved yet move to an average county instead (Update: something didn't quite make sense here. ht Salim Furth for the edit). But as Salim Furth noted, there's no particular reason to suppose that moving from a bad county to a good county you'll be able to keep the same income.

Chetty and Hendren needed to include income as a control variable because otherwise they'd have omitted variables bias, because income is correlated both with the reasons people move and child outcomes. Methodologically, this was probably the best approach. But as I've written previously, control variables are a sign of weakness, and can reintroduce endogeneity even in otherwise "clean" identification strategies. In other words, if moving to a good county also causes family income to decline, then it doesn't really make any sense to say that the county "causes" better child outcomes--yes that causal mechanism may be there, but does not exist in isolation.

Even ignoring the issues of endogeity, Furth's critique can be thought of as a question of generality: Chetty and Hendren's dataset includes only families that voluntarily chose to move under the status quo. The fact that they chose to move suggest that they had something to gain from the move, such as, for example, relatives or a lucrative job opportunity--things that would benefit the kids. Take those away, and it's not clear that moving actually does benefit kids. I mean, surely, there exists someone who is better off living in Hamilton county than Warren.

So when it comes to the actual policy question that readers think the Upshot piece was about--should they move to a better county--the answer remains, at best, "It depends" and the truth is that Chetty and Hendren don't shed much light on whether you are one of the families who would benefit or not from moving.

1. What I mean to say here is that the research question remains far from answered. I don't object to popular press readers following along the research process, but it is unfortunate that the Upshot presented this as a settled question when in fact we are only at an intermediate stage.
Luna 5/11/2015 03:37:00 PM
Maybe the lesson is something like: If you hate where you live and are determined to move out, you'd better look for opportunities in nice areas, rather than average areas.