Tag: social norms

Peer effects, health behaviors and adolescents

Some months ago I was at a conference, listening to a presentation on breastfeeding initiation and the presenter cited a paper by Fletcher. My first and second thoughts were, “how did that person get my breastfeeding paper?” and then “I didn’t say that in my paper.” Thanks to my trusty smartphone, I went searching for the paper, thinking perhaps my Gettysburg colleague, Jean Fletcher, had actually written it (a source of endless confusion for students, believe me), but found instead that it was Jason Fletcher, at Yale’s School of Public Health. Since then, I’ve run into a number of his papers and today, one came out in the NBER Working Paper series (gated), a paper on adolescent health behaviors and network effects with Stephen L. Ross.

The paper seeks to identify the effect that adolescents’ peers’ choices have on an individual’s health. If that sounds complicated, you’re not alone. Basically, the idea is that we want to know how strongly a child’s friend’s choices affect the child’s choices. The problem of how to causally identify this effect has plagued researchers for some time. In particular, the issue is that ideally, we would want to observe one student’s choices in different peer groups. But even if we can identify an exogenous change in peer groups (or in peer groups’ choices, but most likely through a change in peer group), the change in peer group is generally coupled with a dramatic change in environment as well. For instance, Fletcher and Ross cite one paper that shows that children who move from high-poverty areas to lower poverty areas experience better outcomes. Clearly, their peer group changes because the kids in one area have access to different activities, different stimuli, etc, but also the general environment changes. Mothers of these children report reduced stress, for example, which in and of itself has been shown to improve outcomes for children (or more precisely, children in high-stress living situations have worse outcomes–memory is failing me at the moment, I’ll update when I recall a relevant paper). So, when the environment changes and the peer group changes, it’s difficult to separate out the effects.

Using Add Health, which is a really cool survey instrument, by the way, the authors identify the effect by arguing that there is rather little variation in cohorts within a grade, but friend groups that look similar (on characteristics observable to the researcher)

At any rate, I think it’s a pretty neat identification strategy. It rests on some pretty strong assumptions, primarily that when groups cluster on observable characteristics, they’re unobservable characteristics are also similar, but dissimilar on the characteristics that influence health behaviors. This assumption is a bit problematic, I think, but I’m resolving it in my head by thinking of the insertion of one student with a particular tendency to smoke (his older sister does it, perhaps?) into a peer group in 9th grade, while a similarly made-up peer group in 10th grade doesn’t receive that idiosyncratic shock. Thus, the two groups look pretty similar, but by virtue of being in different grades, they have exposure to different kids and thus end up with different health behaviors.

Neat, no?

One concern I do have, though, is the idea that these friend groups are really that separate. I’m not very familiar with the way Add Health identifies friend groups, but I seem to recall some issues arising for researchers given a) the definition changing, and b) there being a limit on the number of friends that could be identified. From my own experience (clearly the most relevant), there was also a lot of grade mixing of friends in high school, even more so in dating. Sports, off periods, electives, and activities all gave way to friends in classes above and below. I grant that I went to a rather unique high school (billed as a sort of mini college campus), but it seems like it might be even more pronounced in a small schools. The assumptions of separation might be easier to make with middle schoolers, although incidence of averse health behaviors are going to be lower there and perhaps harder to identify.

Sources:

  1. Jason M. Fletcher and Stephen L. Ross. Estimating the Effects of Friendship Networks on Health Behaviors of Adolescents. NBER Working Paper 18253. July 2012.
  2. Kling, J.R., J.B. Liebman, & L. Katz. (2007). Experimental Analysis of Neighborhood Effects. Econometrica 75(1): 83-119.
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No loo, No I do

A few weeks ago, a coauthor sent me a job market paper from an environmental economics student at Yale. Though in a very different department than me, we have similar interests and she thought I would find the paper interesting. Not only did I find it interesting, I found myself wishing it had been my job market paper. Apparently, so did a lot of people. The paper has been blowing up my twitter feed and was featured on the World Bank’s Development Impact Blog.

The paper evaluates the effects of a media campaign in Haryana, India designed to encourage women to make latrine presence a requirement for marriage. The project is particularly interesting because it allows for reasonable evaluation of a campaign targeting social norms without the the randomized control component so in vogue in economics right now. In addition, it provides real evidence as to the causal effect of skewed sex ratios. While we have speculated and reported on the effects of sex ratios, many of which I’ve discussed here, there is little statistical evidence. Now, we have some. It’s pretty great.

In summary, the paper shows that men of marrying age are more likely to build latrines when they live in areas with a more skewed sex ratio. Thus, a woman’s bargaining power in demanding a good that has an outsized benefit for her (privacy, sanitation, health) increases when she becomes relatively ‘scarce’ on the marriage market. While this doesn’t discount the other, more undesirable possible effects of a skewed sex ratio (bridenapping, increased violence against women, etc), it is certainly evidence that women are leveraging their bargaining power to improve their outcomes.

In addition, the means to test a social norms marketing campaign are huge. My own work on such campaigns directed at reducing gender-based violence showed the near impossibility of successfully and credibly evaluating their impact. The use of a sex ratio as a (somewhat?) exogenous measure of potential impact is novel, exciting, and I’m sure will be in use by many papers to come. There’s the obvious question of whether it’s plausibly exogenous, but perhaps we’ll save that conversation for another day.

The paper has two parts, one presents a theoretical model to explain the mechanism and the other presents empirical evidence from the program itself to show how a skewed sex ratio has increased women’s bargaining power, at least on this one dimension in Haryana, India. I have some nitpicky comments, like the theory section needs to be more thoroughly explained, or there are square brackets where there should be curly ones, but overall, I think it’s a great paper. It’s kind of wonkish, but you can download the paper here, if you’re interested. Good luck in Chicago, Yaniv!

Trafficking and how to fight it

One of the last things I did in Colorado before moving East was hike Longs Peak (no apostrophe, weird, I know). Longs is one the famous 14ers in Colorado, or a mountain whose summit lies higher than 14,000 feet above sea level. On my way down, I met up with a group who was climbing to raise awareness for an anti-trafficking organization, which warms my heart a little bit.

Whether to include trafficking, and particularly sex trafficking in a review I was working on was a particularly difficult decision. Trafficking is a problem that I feel is pretty understudied. It affects many diverse groups of people, so you don’t see women’s groups jumping on the larger problem–though plenty of them work on sex trafficking–and I don’t think there is much of a consensus on how to combat it. While a good thorough search yields numerous programs, advertising campaigns, raids, plays and more that aim to create awareness of trafficking, there’s not much analysis of their success. And truthfully, it would be very difficult to measure success. If we think domestic violence is an underreported problem that is difficult to measure, human trafficking is all the more so. For that reason, and likely others, economists have a hard time modeling it and so steer clear of it. Maybe I just have a blind spot. If economists haven’t tried to study it, I think it’s understudied.

So, we have no idea whether these work, but the NYT unveiled a collection of global anti-trafficking campaigns that is just really cool. In development work, people talk a lot about including local people in development plans, but it rarely happens as perhaps it should. For programs like these, that attempt to increase awareness or affect social norms, local direction is equally important, and sadly, often equally ignored.

Though I can’t speak to their veracity, the campaigns herein seem to reflect the cultures and unique problems that the countries face around trafficking. I like the Jamaican one, for instance, that equates trafficking to slavery–a historical and close-to-home reference–but encourages the reader to think about the problem in a more nuanced way.

It’s a shame, of course, that there’s no good way to measure the effectiveness of these programs. Or rather, now that they are in place, we cannot easily tell whether their dissemination had any effect on attitudes. The lack of good counterfactuals, the problem of measuring secondary effects versus primary effects, externalities, etc, all make for a nightmare of an econometrics problem. There might be room for good qualitative analysis, but again with the underreporting, etc.

Regardless, the visuals are pretty cool. I highly recommend you check them out.

More of them or more willing to say it?

Today’s NYT had an article on the cities with the highest proportion of gay couples. Interestingly, the list doesn’t include many high-density cities or the well-known gay neighborhoods. The lack of historical data and rapidly changing social norms make it difficult to differentiate between whether there are simply more gay couples living in places like Rehoboth Beach, DE, or whether they’re simply more visible and more willing to disclose their orientation.

While this limitation means we cannot make  statements about the changing demographics in these cities, I think it does say something pretty profound about standards of acceptable social behavior in small towns and, to some extent, all over the country.

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