Data inanities

I feel like half the time I read something from one of these data news explainer sites, I want to blog about how silly it is. So while I’ve been wrestling with what to write here regarding a series of terrible NYT op-eds (no, I won’t link to them, but you know which ones I’m talking about), I will take a minute to call out 538 for publishing this article complaining that giving students free lunch is going to make data analysis difficult.

It’s absolutely true that students receiving free lunches is a proxy for student poverty. In fact, in my own teaching, we talk about proxy variables by examining a data set of school characteristics and students achievement scores. We actually run regressions where I encourage students to think about socioeconomic status and poverty through school lunch programs (along with other measures). But it’s also a rather coarse measure. In the way that school lunch programs have traditionally been applied, if you fail to meet some income threshold, you get free lunch, and in some cases, free breakfast. In Colorado, for a family of four, it’s $44,123. While it’s useful for looking at broad categories, it doesn’t tell you anything about the heterogeneity within those categories. The number of kids qualifying for free lunch could be the same at two different schools, but if one school is in a relatively homogenous district with most families hovering around the cutoff point and the other pulls from one very rich area and one very poor area, looking at those schools as the same actually “muddies” the waters” more than diluting the program.

So, it’s not actually a great measure, anyway, which we’ve kind of already covered by calling it a “proxy.” So why not look for better measures? The article mentions education levels of parents; that’s a good one. Or economic variables of the surrounding districts could work. Property values, for instance, are widely available and could be linked to school district. This is a little more work perhaps, because often these variables aren’t automatically linked to school quality data.

It’s true; we don’t like change. And changing a commonly used measure of poverty means looking for new answers, and that trends over time will be a bit difficult to determine for awhile, but with a little hard work and ingenuity, the new answers should be better. Decrying the end of a poor measure of socioeconomic status when its expansion will actually help a lot of kids at the margin is just not very useful. Why not spend a little more time thinking about how we can make data better, answer questions more fully, and ultimately improve school experiences for kids?

The second life of RCTs and implications for child development

In the last few weeks, I’ve come upon two research programs (each with a few related papers) that utilize a combination of an RCT or phased-in intervention and follow-up data 7-10 years on to examine new research questions. They both happen to be focused on the lasting effects of childhood health and wellbeing initiatives, but I doubt that this trend will be confined to child health and literacy. Barham, Macours and Maluccio have a few papers (gated) that use the phasing in of a conditional cash transfer program in Nicaragua to test later childhood cognitive and non-cognitive outcomes, distinguishing effects by timing of the intervention. A working paper out last week shows that deworming programs in Uganda not only increased short-term anthropomorphic outcomes, but also contributed to children’s numeracy and literacy several years later.

In short, we’re seeing more evidence that these early health and wellbeing interventions can have profound impacts not just on the immediate outcomes–Under-5 mortaility, school attendance, etc–but also on future outcomes. I think it’s a neat use of experimental design to examine questions we might not have thought about when the programs were first put in place.

India-bound!

It’s (almost) official! I think I actually have a ticket and am leaving for India and the Philippines for the rest of the summer on Friday. I’ll post updates here as the mood strikes me, but feel free to follow @ekfletch and @EPoDHarvard on twitter for more frequent (and perhaps less related) content (pictures of all the momos I’m going to eat? Anyone?).

For now, I’ll leave you with the World Bank’s new project to determine the economic cost of child marriage, a well-funded, but really huge undertaking:

What is the economic cost of child marriage? We don’t really know. Studies – including those by the World Bank – suggest a range of negative impacts of child marriage on human development outcomes. For example, Bank staff have estimated that in sub-Saharan Africa child marriage may account in some countries for up to one-fifth of drop-outs among girls at the secondary level, and each additional year of delay in the age of (child) marriage could potentially increase the likelihood of literacy and secondary school completion by several percentage points for the affected girls. Another study published a few years ago in the Journal of Political Economy suggests similar impacts in the case of Bangladesh.

Breastfeeding and mommy wars

Last week, a paper came out in a relatively obscure journal and got a lot of attention (or at least got its own #slatepitches headline). A sociologist at Ohio State published a study saying that the positive effects of breastfeeding essentially disappear if you look at within-sibling differences. That is to say if you compare two siblings from the same parents, one of whom was breastfed and one of whom wasn’t, there isn’t much in the way of statistically significant differences in their educational achievement, health status, or intelligence as measured by standardized tests.

In many ways, this isn’t surprising. We already know that the vast majority of our later life outcomes are determined by our parents’ incomes and education levels, where we grow up, how many words are said to us before we can even talk, and the myriad investments our parents make in our parents’ health. That breastfeeding doesn’t make a very big difference among siblings shouldn’t surprise us.

Perhaps even more important though, and this is really the kicker when trying to identify the effects of early childhood interventions, is that we don’t know what else the parents did differently for these two children. Given what we know about mothers who breastfeed—they tend to be wealthier and more educated, they get more assistance with breastfeeding education, they tend to have more flexible jobs that allow them to breastfeed for longer, or are staying at home with their kids, they’ve been told for years, etc.—we also expect them to be conscientious if they for some reason are not breastfeeding one of their children. Colen’s analysis can only control for time-invariant, mother-specific characteristics. An important omission is that she can’t control for mothers who supplement bottle-feeding with additional doctor’s visits, vitamins, extra care, more time spent together, or any other activity or characteristic that would act as a complement to breastfeeding. It ignores anything that might cancel out the fact the child isn’t getting the extra nutrients and other stuff that we ascribe to breastfeeding.

This omission is only important if it’s correlated with breastfeeding, and in all likelihood, it is. If you thought your child was missing out by not being breastfed, mothers with the ability to might try to compensate by increasing other investments.

It’s also worth noting that there are other studies using the same methodology that do find within-family effects for breastfeeding. This one, for instance, by Rees and Sabia.

Ultimately Colen wants to use the results to push for more family-friendly social policy, like increased maternity leave and more. But this is not the last word on breastfeeding. One momy blogger called it a “suspect methodology.” It’s not, it’s a perfectly valid methodology, but we need to be careful about what it’s actually showing.

Cited:

Rees, Danial and Joseph Sabia. 2009. “The Effect of Breastfeeding on Educational Attainment: Evidence from Sibling Data.” University of Colorado at Denver Working Paper 09-03.

Colen, Cynthia and DM Ramey. 2014. “Is Breast Truly Best?:Estimating the effects of breastfeeding on long-term child health in the United States using sibling comparisons.”Social Science and Medicine.

Hart, B. & Risley, T.R. “The Early Catastrophe” (2004). Education Review, 77 (1), 100-118.

Cognitive effects of poverty

A new paper by Anandi Mani, Sendhil Mullainathan, Eldar Shafir, and Jiaying Zhao shows some pretty profound effects of poverty on cognition and decision making. The paper says that poverty is equivalent to pulling all-nighters in terms of its effect on your ability to perform routine tasks and make good decisions. It reminded me of a conversation I had with Mark Hecker, director of Reach, Inc., a nonprofit working on literacy in DC, about children who’ve been abused. He asked me to think about that feeling of indigence and anger that shoots up when someone bumps into you. It’s startling, difficult to process, and affects everything we do next. Children who’ve suffered abuse feel that way all the time, which puts additional stress on them to make good decisions, to concentrate in school, and more.

It’s a good reminder that putting ourselves in someone else’ shoes is often impossible; someone who has grown up middle class never worrying about money is not going to approach large expenditures the same way that someone who grew up poor will. Analyzing decision making of poor and disadvantaged individuals is subject to so many more constraints that we realize.

Reading to girls

An Atlantic piece today outlines some current research that is very much in line with my own.

The researchers found a gender difference in what they call “teaching activities” that build cognitive skills in children as young as nine months old. Girls, not boys, in all three countries received more time from parents on three activities: reading, storytelling, and teaching letters and numbers. Baker and Milligan scrutinized data for first-born children, to control for differences arising when parents slack off after baby number two or three arrives. They also examined parents’ time spent with boy-girl twins and again found boys receiving less time than girls on the three teaching activities.

I’ve found a small, but statistically significant difference in the amount of time parents spend reading to girls at ages one, three, and five as part of a paper focused on relationship quality and investments in children.

They’ve got a very economist-y explanation for the behavior: “It is just more costly to provide a unit of reading to a boy than to a girl because the boy doesn’t sit still, you know, doesn’t pay attention,” Michael Baker told NPR (on his research with Kevin Milligan).

Costs are not just about money, people.

More on adolescent girls, because, yeah

I just realized that I never shared this work with you all. This post was written almost four months ago, but I think it’s still relevant. And even more so now as the papers are all live on the Girl Effect website. I hope you enjoy it!

My coauthor and I spent the last week finishing up our issues paper on adolescent girls for DFID and the Nike Foundation. It’s been this super crazy, whirlwind kind of project where I’ve learned so much and met so many amazing people. It’s exciting, but it sure was exhausting. I’m really excited to be able to share our findings, here they are!

So, what do we find? For the most part, programs that seek to use social norms to reduce societal discrimination against adolescent girls aren’t very well-studied. With the exception of a very small number of programs, both quantitative and qualitative analysis are lacking; overall there has been little effort to sufficiently randomize participants and perform rigorous pre- and post-intervention analysis. Thus the ability to causally identify statistically significant effects of these programs is incredibly limited.

There are a few rays of light, however. We found three programs–Tostan, Meena Communication Initiative, and Promises–that promote gender-equitable behaviors and discourage violence and discrimination against adolescent girls using social norms language or methods. All three of these programs employ multifaceted interventions. That is to say that while each has a goal of reducing discrimination or ending FGM/C, the actual process includes community conversations, social norms marketing through popular culture medium such as comic books and television shows, community declarations, school programming and more.

It seems that this is the way programs in the developing world are going. Recently, Markus Goldstein posted about his new paper on a child club program to promote the status and welfare of adolescent girls in Uganda. Though it doesn’t seem to have a strong social norms component, ELA is multifaceted, and thus multi-outcome.

In terms of sexual behavior, the girls who participate in the clubs show significantly better HIV and pregnancy knowledge than the control group.   They are also 12.6 percentage points more likely to report always using a condom when they have sex (which matches up with a reduction in those reporting often or occasional use of a condom).   They also experience a striking reduction in fertility – at follow up, treatment girls are 2.7 percentage points less likely to have a kid (26 percent of the baseline mean).   Now since they also report no increase in use of other forms of contraception, these things taken together strongly suggest that they are markedly reducing their risk of exposure to HIV.

My favorite part of reading this paper was this interactive effect. It’s very cool and I think will provide an strong template going forward for programs that wish to engage communities and have profound, lasting effects. Both Markus’ research and ours suggest that the narrowly focused, difficult-to-replicate, difficult-to-scale-up RCTs such as those heralded in Poor Economics and More Than Good Intentions have some growing to do.

Lean In, Dad, if you can

I’m in that period of my life where my friends are starting to have babies. The wedding invitations that filled my mailbox up until last year have been replaced with baby announcements and family photos. It’s hard to believe that I have no weddings to attend this year. Like an actual zero.

I’m not sure if it’s the labor economist in me, but I ask pretty much everyone what their parental leave policy is. How much time are you taking off? How much time is your partner taking off? How much is paid, how much is unpaid? I just learned Gettysburg offers a one-course reduction for “secondary caregivers” (I must say, I do like the gender neutral language, even if it is implied that the dad is the secondary). There are all sorts of restrictions about when you can take it and how often, because I’m sure that parents are going to time their childbearing to maximize the number of classes they can get out of (no, they’re not; that’s ridiculous). Sometimes people just offer the information:

The fact remains that there isn’t a lot of support for two-parent caregiving, at least in this country. I am impressed, though, with how many of my male friends and colleagues have taken time off, even if unpaid, and have taken the time to actually caregive, as opposed to using it for personal or professional gain. 

Catherine Rampell has an op-ed in the NYT today on increasing parity among caregivers’ leave policies. She suggests that parental leave, or rather paternal leave, is an important aspect of not only equity in the workplace and ensuring that we continue to chip away at the gender pay gap, the glass ceiling, and other forms of discrimination. In addition, she suggests that mere exposure to full-time caregiving in the early stages of a child’s life might lead to more equitable distribution of household and caregiving work as the child ages. It’s actually a big deal!

This might not sound like such a big deal, but social scientists are coming around to the notion that a man spending a few weeks at home with his newborn can help recast expectations and gender roles, at work and home, for a long time. A striking new study by a Cornell graduate student, Ankita Patnaik, based on a new paid paternity-leave quota in Quebec, found that parents’ time use changed significantly. Several years after being exposed to the reform, fathers spent more time in child care and domestic work — particularly “time-inflexible” chores, like cooking, that cut into working hours — than fathers who weren’t exposed to the reform. More important, mothers spent considerably more time at work growing their careers and contributing more to the economy, all without any public mandates or shaming.

Perhaps the most amusing part of the article is that the comments section is filled with screeds against “procreators.” Yes, I get it. The planet has a lot of people on it and you’ve made a personal decision not to procreate. But, two things. One, individuals don’t make the decision to put hundreds of thousands of dollars into a child because they’re going to get two weeks off. If you think that, you need to take an economics class. And two, if you want to reduce population growth, donate to programs that work to educate children, improve access to contraception and family planning services, reduce child mortality, and give young women jobs, all of which are actually proven to reduce fertility rates.

Children’s health and recall

One of the primary problems with survey research is that it relies on recall of past events. In as much as humans are subject to forgetting things (and we are actually designed to forget things), asking someone about how often they perform an activity or how often something has happened in the past few weeks or how much they paid for something is problematic. This is before we even factor in the cultural norms and expectations around the behavior. We probably exaggerate the things we’re proud of of or that match social norms and downplay the incidence of events we’re ashamed of. Econometrically, we tend to say this kind of error is only a problem if it is systematic. That is, if some people overestimate and some people underestimate (with mean zero and some constant standard deviation), it won’t affect our estimates. However, if everyone underestimates, this causes our parameter estimates to be biased. In simpler terms, we don’t accurately assess the relationship between two variables because we’re missing a lot of information about at least one.

A paper explains this problem as it relates to diarrhea incidence recall by parents and definitions (which also gets me thinking about language, and education, but that’s another post or two or three).

Several methodological issues may have an impact on the incidence rates of childhood acute diarrhea reported by community-based studies. This study was performed to assess the impact of parental recall ability and definition of diarrhea on the estimate of incidence of acute diarrhea. Eighty-four children younger than 40 months were randomly selected and visited every other day for four weeks and the occurrence of diarrhea was registered. On the last day of the study, another visit was performed and the informants were inquired about the occurrence of diarrhea during the previous four weeks. Data gathered during the four weeks were compared to those obtained on the last visit. Additionally, the informants’ definition of diarrhea was investigated and compared to the one adopted by this study. During the observation period, 33 children suffered diarrhea, but only 10 (30.3%) informants reported the occurrence of diarrhea. Although 42.4% of those informants reported that their children had been ill over that period, they did not report diarrhea. Further, 60.6% children who had diarrhea suffered at least one episode in the two weeks prior to the visitation. The same definition of diarrhea used in this study was adopted by 52.1% of the informants inquired. Parental recall is an unreliable method to estimate the incidence of diarrhea and studies with a short interval between the visits should be necessary to correctly evaluate this important health problem. Moreover, assessing the informants’ own definition of diarrhea is a significant contribution to the interpretation of the results.

The rub is that we’re not very good at recalling past events, even when we’re being constantly reminded of them. As a separate, but related question, I wonder whether our ability to recall changes over time, or more specifically, over the course of an intervention. I wonder if the percentage of recall changes when you’ve been a recipient of an education program or a new latrine or whether that percentage stays constant. Depending on what the answer is, it could have a large impact on how we evaluate the effectiveness of health and sanitation interventions.

So many NBER papers I want to read today

Good thing I’m traveling this afternoon. (All gated, sorry.)

  1. Long-Term Neighborhood Effects on Low-Income Families: Evidence from Moving to Opportunity Abstract: We examine long-term neighborhood effects on low-income families using data from the Moving to Opportunity (MTO) randomized housing-mobility experiment, which offered some public-housing families but not others the chance to move to less-disadvantaged neighborhoods. We show that 10-15 years after baseline MTO improves adult physical and mental health; has no detectable effect on economic outcomes, youth schooling and youth physical health; and mixed results by gender on other youth outcomes, with girls doing better on some measures and boys doing worse. Despite the somewhat mixed pattern of impacts on traditional behavioral outcomes, MTO moves substantially improve adult subjective well-being.
  2. New Evidence on the Impacts of Access to and Attending Universal Childcare in Canada Abstract: In Canada, advocates of universal child care often point to policies implemented in Quebec as providing a model for early education and care policies in other provinces. While these policies have proven to be incredibly popular among citizens, initial evaluations of access to these programs indicated they led to a multitude of undesirable child developmental, health and family outcomes. These research findings ignited substantial controversy and criticism. In this study, we show the robustness of the initial analyses to i) concerns over whether negative outcomes would vanish over time as suppliers gained experience providing child care, ii) concerns regarding multiple testing, and iii) concerns that the original test measured the causal impact of childcare availability and not child care attendance. A notable exception is that despite estimated effects stemming from the policy indicating declines in motor-social development scores in Quebec relative to the rest of Canada, our analyses imply that on average attending childcare in Canada leads to a significant increase in this test score. However, our analysis reveals substantial heterogeneity in program impacts that occur in response to the Quebec policies and indicates that most of the negative impacts reported in earlier research are driven by children from families who only attended childcare in response to the implementation of this policy.
  3. Profitability of Fertilizer: Experimental Evidence from Female Rice Farmers in Mali Abstract: In an experiment providing fertilizer grants to women rice farmers in Mali, we found that women who received fertilizer increased both the quantity of fertilizer they used on their plots and complementary inputs such as herbicides and hired labor. This highlights that farmers respond to an increase in availability of one input by re-optimizing other inputs, making it challenging to isolate the returns to any one input. We also found that while the increase in inputs led to a significantly higher level of output, we find no evidence that profits increased. Our results suggest that fertilizer’s impact on profits is small compared to other sources of variation. This may make it difficult for farmers to observe the impact of fertilizer on their plots, and accordingly this affects their ability to learn about the returns to fertilizer and could affect their decision to adopt even in the absence of credit constraints.