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.


  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.

I’m back

I’m back! I’m fighting the worse jet lag I’ve ever experienced in my life. Yesterday I was up at 1:30am and today at 2:30. I figure, this is what @price_laborecon must feel like. Nonetheless, I’m stateside for a few days and going to crank out some original research and blog posts.

Here’s one picture for you, in my new saree. More on Kolkata and India and Bengali weddings later, I’m sure.

Time use and hindsight

I am in the midst of revising a paper that uses a very specific question from the Fragile Families Data set about reading to children. When I began writing the paper, I started looking for evidence with time-use surveys, such as the American Time Use Suvey (ATUS) which asks participants to record everything they do and for how many minutes on two given days (a weekday and a weekend, usually). I noticed, particularly at the PAA meetings this Spring, that there was a lot of controversy about these surveys. What, exactly, can they tell us about general effects, when we are looking at such a small sample of time for any given individual? More specifically, if we want to examine the effects of a particular policy, how does looking at one individual’s day give us a causal effect of a policy? Time use surveys are incredibly useful for seeing exactly how individual spends his time on any given day, and the possibilities for understanding the dynamics of child-rearing and marriage are far-reaching. The trade-off is that you have no way of knowing whether this is a typical day or not. On average, for the population, if we have a random sample of individuals and days are sufficiently randomly assigned, we should get an idea of what the population does, on average. But asking if a particular impetus leads to a specific behavioral change (for instance, does an increase in income mean you invest more in child’s education) is a little more problematic. The alternative is to ask questions in a survey setting about time-use behaviors without specifying the time. That’s what the Fragile Families does, and the question about how many days per week you read with your child has its own problems. I have long argued that when individuals answer the question, they must do some averaging over time. The question is not “how many days did you read with your child last week” as might be preferred or indicated by the literature on work (did you work last week?), but rather a sort of what do you usually do? I’ve been surprised at how much pushback I’ve received on this matter from discussants and reviewers. Most say the natural model to use is a count model, like negative binomial or Poisson, but I think it makes more sense to use an ordered probit, which allows for 4 to be more than 2, but not necessarily twice as much as 2. I don’t think the reading days answer is as firmly countable and identifiable as something like parking tickets, where a count model is the readily apparent model. I imagine the question is a lot like exercise. Over the weekend, I helped a friend with her profile and one of the questions is how many days a week do you exercise? For some, the answer is absolutely 7, every single day. For others, zero, not lifting a finger. For most, though, I’d guess it varies from week to week. One week, you go every day, the next week is busy at work, so you go less often. Perhaps you go on a whole-day hike and tell me two days instead of one because you don’t want to seem lazy. Thus, when I ask you the question of how many days a week you exercise, you’re not really giving me a straight answer, through no fault of your own. You’re averaging over the last couple of weeks, you’re perhaps adjusting your answer to reflect what you think the surveyor is looking for, and you’re partially giving an impression of how much you value exercise. I’m having a hard time making this same argument regarding time spent with children to discussants and reviewers, and I’m not sure what I’m missing in my explanation to make it more convincing.  

Fun stuff on infant health and taxes

I’m not a huge fan of the US tax code. I think it’s far too complicated and full of ridiculous things you can do to get around paying your taxes. This makes for rent seeking and a huge time suck. That said, I’m always interested in the types of incentives that certain taxes provide to change behavior, particularly when it comes to child health and investments in children. A new NBER working paper examines the relationship between infant health and the Earned Income Tax Credit.

Without having read the paper, my first thoughts are 1) why do we think the EITC would affect infant health specifically? and 2) those are pretty large effects for an increase in income. The authors argue that an exogenous increase in income means mothers will seek out more prenatal care, but it seems that a 10% reduction in the rate of low birth weight babies would require a large portion of the tax credit (increase in income) to go towards prenatal care for most mothers (or all for some and a small amount for others). Maybe they address it later on, but this, too, will make for some good plane and train reading this week.

The abstract is here:

This paper evaluates the health impact of a central piece in the U.S. safety net for families with children: the Earned Income Tax Credit. Using tax-reform induced variation in the federal EITC, we examine the impact of the credit on infant health outcomes. We find that increased EITC income reduces the incidence of low birth weight and increases mean birth weight. For single low education (<= 12 years) mothers, a policy-induced treatment on the treated increase of $1000 in EITC income is associated with 6.7 to 10.8% reduction in the low birth weight rate, with larger impacts for births to African American mothers. These impacts are evident with difference-in-difference models and event study analyses. Our results suggest that part of the mechanism for this improvement in birth outcomes is the result of more prenatal care and less negative health behaviors (smoking). We find little role for changes in health insurance. We contribute to the literature by establishing that an exogenous increase in income can improve health, and illustrating a health impact of a non-health program. More generally, we demonstrate the potential for positive external benefits of the social safety net.

Source: “Income, the Earned Income Tax Credit, and Infant Health.” Hilary W. Hoynes, Douglas L. Miller, David Simon. NBER Working Paper No. 18206, July 2012

Off to the land of sights and smells and senses, or a break

As you’re reading this, I’m likely on a plane, or sitting in one of many airports or train stations that is in my future over the next month and a half or so. Today, I’m headed to India to see my dear friend and colleague get married. It’s going to be a five-day, multicity affair, with an overnight train ride in the middle. En route, I’m stopping in Mumbai and Darjeeling to do some shopping (new saree!) and hiking and to see a bit more of this huge, incredible country. I was in India a few years ago and fell in love with it. It’s overwhelming, to be sure. The smells and the colors and the throngs of people are total madness, but I love it; it’s exhilarating to be somewhere out of my comfort zone. I’m not doing research this trip, though you can guarantee my eyes will be peeled for interesting things. I’m also not taking a computer, which means unless I can get wi-fi for my phone, I’m doing this trip old school. I’m going to read some books and journals, including Casualties of Credit by Wennerland and the CESifo journal issue on malnutrition, and some stuff for fun, like Just Kids and back issues of the New Yorker, but won’t be here or on twitter much. My 30th birthday present to myself is a real break from work, this means not thinking about the papers I have under review, or the one that’s due at the end of August, or the one I have to finish for the CNEH conference in Banff in October (so excited for Banff!). A break. I’m going to sit in a big, comfy chair on a tea plantation and stare at the Himalayas (or the clouds, given that it is monsoon season, but, details). If you want to read more about down time (or the lack thereof), take a few minutes for this piece in the NYT from last week on “busyness”, a phenomenon that I’ve been complaining about since my years at Duke, and suddenly everyone is talking about, or Bryce Covert’s piece in The Nation on work-family balance. If you know something I shouldn’t miss in Darjeeling, Kolkata or Ranchi, please do share. I’ll try to check email sporadically. I’ve also been designated honorary photographer and family blocker for this wedding by my advisors, fellow grad students, and professors in the Economics department at the University of Colorado, so I hope to have some crazy wedding pictures and experiences to share when I get back. Have fun! Talk to you all soon. Enjoy your July and thanks for reading. I forgot to acknowledge my blogiversary (sp?), but I’ve loved getting to know you all over the past year. Thanks for your comments and ideas and conversation and emails and shares and links. This has been an amazing learning experience for me and I’m so excited to keep it up over the next year (I promise not to torture you all too much with job market woes in the coming months. Feel free to chastise me if it gets out of hand.)

Long chain kidney donations

The NBER working paper series this week is giving me some plane reading for the next few days:

It has been previously shown that for sufficiently large pools of patient-donor pairs, (almost) effcient kidney exchange can be achieved by using at most 3-way cycles, i.e. by using cycles among no more than 3 patient-donor pairs. However, as kidney exchange has grown in practice, cycles among n > 3 pairs have proved useful, and long chains initiated by non-directed, altruistic donors have proven to be very eff ective. We explore why this is the case, both empirically and theoretically.
We provide an analytical model of exchange when there are many highly sensitized patients, and show that large cycles of exchange or long chains can significantly increase efficiency when the opportunities for exchange are sparse. As very large cycles of exchange cannot be used in practice, long non-simultaneous chains initiated by non-directed donors significantly increase efficiency in patient pools of the size and composition that presently exist. Most importantly, long chains benefit highly sensitized patients without harming low-sensitized patients.

I have a vague recollection of reading about kidney chains a few months ago, probably in the NYT, and getting a warm, fuzzy feeling inside about altruistic donors and how long chains helped to reach those who didn’t have an altruistic donor. I love it when economics comes together and puts everything in a neat little package for me. I’m excited to read this later.

Source: The Need for (long) Chains in Kidney Exchange (gated)
by Itai Ashlagi, David Gamarnik, Michael A. Rees, Alvin E. Roth NBER Working Paper 18202 (HC)


It’s kind of a big one, right? Today is the beginning of my next decade, and I’m happily in the mountains, riding my bicycle, watching moose, finding secret cabins, and spending time with friends. I hope everyone is having a safe and lovely week. Happy belated 4th and talk to you next week.

Child obesity, Latin America and a good reminder

A few weeks ago, Adam Ozimek and I of Modeled Behavior had a discussion in the comments section here about the soda ban in New York City and the debate around paternalism. When I was slow to respond, we continued over email, just proof that you’re never really going to end a debate with an economist.

Adam was kind enough to send me a link to a piece in the Atlantic, which I thought did a much better job of summing up the arguments against the soda ban and paternalism in general, which I had, up to that point, not seen as convincingly articulated. What I liked about the argument is that it alluded to culture and how creating laws that are both nonsensical and devoid of cultural understanding and social norms makes for really bad law. And this I can totally get behind.

With that in mind, I spent much of last week searching for recent programs in the developing world for adolescent girls. The scope of this new project is rather wide and includes programs aimed at increasing political and community participation by girls, delaying marriage and sexual debut, improving education, health status, and bargaining power, decreasing HIV and violence against women, and so much more. I was thumbing through websites on health and violence and found the program Agente F, partially sponsored by Telefonica, one of the major cell carriers in Latin America. It’s intended to teach kids about healthy eating habits and avoid obesity, which, apparently, is fast becoming a problem in Latin America. I didn’t know. I thought we were still dealing with hunger and poverty, but apparently I’m behind the times. I have been unable to ascertain how widely this program is used, or whether anyone has actually played the game, but it’s interesting in that it has a lot of institutional support, at any rate.

I consider myself somewhat adept at Latin American cultures, and some more than others, having lived and spent time in many Latin American countries. I tell people “buen provecho” when they’re eating and can sing happy birthday in Spanish, Portuguese and Venezuelan (it’s a different song). I know where it’s appropriate to wait in line and where you’ll never get your coffee if you don’t hustle your way to the counter. I can talk to you a little bit about Catholics and saints and am sure to take a shower immediately if I get wet in the rain (RIP, Tomas.). I’m not a native, by any means, and I surely make mistakes, but it’s not a completely foreign world to me.

So I was struck by how many of the questions on the Agente F game I was unable to answer. Not just the ones about how many bones are in the body or how many muscles. Those, I guessed on and mostly did fine. One question in particular asked what should you do to ensure a good night’s sleep? I said exercise, but the answer was take a cold shower before going to bed. I see the logic. Your body needs to cool down before going to bed, and it’s often hot in many Latin American countries, which can make it difficult to sleep, but I thought it was a very odd answer.

A few questions were in this vein. The answers seemed totally foreign to me and reminded me how important cultural context is in creating programs and legislation with the policy goals of influencing behavior and actions. Despite my experience living in Latin America, I’m not a native. I have no idea whether taking a cold shower before bed would sound like a reasonable thing to a Mexican or a Colombian; maybe it’s totally within the realm of reason. Heck, maybe it’s within the realm of reason for natives of the United States and I’ve totally missed the boat. Regardless, culture is an important element to take into consideration when designing programs and laws.

Compulsory education and girls in China

A new paper (gated) by a gaggle of economists (is this a new trend? I’ve never seen so many papers with five or six names on them than as of late), shows that compulsory schooling in China helped raise average educational attainment, and did a particularly good job of getting girls to stay in school. Girls stayed in school an average of 1.17 years longer, and boys an extra 0.4 years. I’ve yet to really get into this paper, but they use what looks like a neat instrument to identify the effect causally. The compulsory education policy was implemented at different times, so different regions were subject to the policy at different times.

The abstract:

As China transforms from a socialist planned economy to a market-oriented economy, its returns to education are expected to rise to meet those found in middle-income established market economies. This study employs a plausible instrument for education: the China Compulsory Education Law of 1986. We use differences among provinces in the dates of effective implementation of the compulsory education law to show that the law raised overall educational attainment in China by about 0.8 years of schooling. We then use this instrumental variable to control for the endogeneity of education and estimate the returns to an additional year of schooling in 1997-2006. Results imply that the overall returns to education are approximately 20 percent per year on average in contemporary China, fairly consistent with returns found in most industrialized economies. Returns differ among subpopulations; they increase after controlling for endogeneity of education.

“The Returns to Education in China: Evidence from the 1986 Compulsory Education Law.”
Hai Fang, Karen N. Eggleston, John A. Rizzo, Scott Rozelle, and Richard J. Zeckhauser
NBER Working Paper No. 18189, June 2012

CESifo Conference on Children

I think this looks pretty cool. Call for papers comes due on July 15. And I’ve never been to Germany!

CESifo Economic Studies and UCLS Conference on Families, Children and Human Capital Formation

From 19/Oct/2012 to 20/Oct/2012

Among the issues to be covered include the causes and (short-and long-run) consquences of child health, early-life interventions and events, education and familiy poilicies and divorce (including the role of the family more generally). The keynote lectures will be delivered by Anna Aizer (Brown University) and Kevin Milligan.

Scientific organiser(s):  Matz Dahlberg ,  Eva Maria Mörk and  Anna Sjögren

See call for papers 
Submit a paper
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