Crowd-sourcing classroom blogging

So, I’ve made some work for myself this semester, I think. In light of the conversation a few weeks ago regarding blogging by academics, and a recent spate of blog posts on LSEImpact on social media, I decided that my students should be blogging.

In reality, I think they should be writing. A lot. And I think they should be reading each other’s writing. It’s amazing to me how many students go through college having had no one read their papers or other written work except their professors. Don’t get me wrong, I have faith in the ability of most professors to present an informed opinion on a work, but those students are missing significant opportunities to improve their skills of crafting an argument if they do not practice and put themselves out there. I can give an opinion on how to write something, but it’s merely one opinion.

It’s a good one, of course, but just one.

So, I have 25 students in two methods classes. They are going to blog about their research projects–still TBD for most, though a few have come to me with interesting ideas. They are going to blog about their reading assignments–mostly from Poor Economics or Freakonomics. Hopefully, they also blog about questions that come up in their textbooks. Hopefully, they blog about interesting things they find in the news. Hopefully, they start reading other blogs and commenting on them as well.

The course blog is here. It has three lists of links. One for each section of my class and one for several economics blogs. Some I read, some were just suggested to me. If your blog is not on there, and you think it should be, let me know. I’m happy to add it. I think the more examples they have, the better.

In addition, I’m totally open to ideas of how to make this work. Assignments that are particularly well-suited to blogging (with an economics or econometrics or research component preferred) are totally welcome. If it worked or if it didn’t, it it was an unmitigated disaster or a resounding success, I’d love to hear about it.

Duflo and Female Empowerment

When you volunteer with a left-leaning organization that requires forty-two hours of training on social justice and examining your own privilege and sensitivity, one of the first things you are taught is that empowerment is a silly word. Empowering, by definition, involves giving someone your power, which is, by this understanding of power, impossible. The idea is that we each have privilege and power that we didn’t necessarily earn, by way of our gender, skin color, or height, for example, and as we can’t give those things to another person; we can’t actually “empower” them.

The distinction seems like semantics, but it actually creates a very different outlook in social justice terms. There is a difference between trying to give someone your power–which is patriarchal in addition to futile–and creating an environment in which more people have access to power.

Hence, when I saw the title of Esther Duflo’s latest NBER working paper, I cringed a bit in anticipation of what might lie within. She and Abhijit Banerjee also sprinkle the term throughout their recent book Poor Economics, which I’ve recently finished, enjoyed, am excited to hear my students’ reactions. But I’m a proponent of presenting and discussing Duflo’s work, even if not always a proponent of the work itself, so I was willing to give it a try, hoping it was just a vocabulary issue.

Though I still think the term should be used more carefully, Duflo largely seems to be addressing issues of equality of treatment, investment, education, and salary in the developing world. It is a literature review, and a rather comprehensive one at that, covering the status of women all over the world and a number of experiments and papers that have sought to tease out the directionality of the relationship between gender equality and development.

For anyone interested in the state of women in the developing world and the relationship between equality and development, it’s a must-read.

Fads and RCTs and the job market

I spoke with a colleague last week whose university is hiring in Development this year. I was surprised, though perhaps I shouldn’t have been, that of six candidates they are flying out, five have job market papers using Randomized Control Trials. Maybe that’s an area that their department is trying to fill and thus that’s the kind of faculty they are interviewing, but it seemed odd along with a comment from another job market candidate.

A friend on the market, in development, told me that she felt she was having a hard time selling herself as a development economist. Without an RCT (and the requisite cash that accompanies these very-expensive projects), she didn’t feel like she was getting even enough attention to get a job. Her plan is to find a new line of research using US data in the next year to go on as a Labor economist.

I realize these are two very specific examples and might not be indicative of the market as a whole, but I do think that fads in economics are both fascinating and problematic. No single theoretical or empirical response to data issues is a panacea, and I wonder if we are putting too much stock in RCTs–and thus in those who were lucky enough or prescient enough–to get into them early. There’s still a lot of value in survey data, I think, and I hope we don’t lose those important results because of a love affair with RCTs.

Treating students differently

Education research seems to be teeming lately with the idea of the “threat of stereotype”, whereby women in particular don’t do as well on tests not because they are incapable but because they are faced with prejudice. If people think I’m going to do poorly, why work hard, or so goes the logic.

This article from the Daily Beast, which outlines much of the research on such ideas of late, struck me for its mention of how students are treated differently by their teachers.

In a study published last year, psychologist Howard Glasser at Bryn Mawr College examined teacher-student interaction in sex-segregated science classes. As it turned out, teachers behaved differently toward boys and girls in a way that gave boys an advantage in scientific thinking. While boys were encouraged to engage in back-and-forth questioning with the teacher and fellow students, girls had many fewer such experiences. They didn’t learn to argue in the same way as boys, and argument is key to scientific thinking. Glasser suggests that sex-segregated classrooms can construct differences between the sexes by giving them unequal experiences. Ominously, such differences can impact kids’ choices about future courses and careers.

I don’t teach single-sex classes, but in my principles classes, I’ve noticed that the men seem to ask questions–and answer questions–in a way that encourages debate. While women are perfectly willing to raise their hands when they have the right answer, they’re less likely to disagree with me or ask a question that seems to critically engage the subject matter.

Thankfully, this seems to diminish a little in upper division classes, where I see both men and women engaging the ideas and critiquing what is set before them. So at least anecdotally, I’d argue that all is not lost by middle school. But that doesn’t mean we shouldn’t work harder to get women to engage critically at every level.

MLK Day and Race

Today is Martin Luther King, Jr. Day, as I’m sure you know. MLK Day was the only federal holiday we got off at Duke, or at least the only one that fell during the semester. It was always marked with a big celebration and my dance group often performed. I always liked that celebration.

But I’ve gotten totally off-topic. An article this week in the NYT highlighted the issue of choosing a race, particularly on census forms, for Latinos in the US. Latinos, who are incredibly diverse in physiognomy and heritage, are, according to the article, choosing to mark ‘other’ instead of one or more of the categories provided.

The issue is of particular importance to economists because in most microeconomic work, we control for race. The implication of this, of course, is that by including someone’s race in a regression, we are separating out some aspect that is predictive of whatever behavior or outcome we’d like measure. And not only are we separating it out, we’re separating it out in a measured, specific way such that we think it applies to all respondents.

For example, we might see a regression that says, all other things equal, the average black person receives one more year of education than a white person. (I saw a statistic like this the other day, saying that black people of similar wealth and socio-economic status get more education than their white peers, I wish I could remember where it came from.) Though the statement is necessarily couched with “on average”, if a number of people are choosing other instead of white or black or some combination of these, we’re not actually seeing the true average. This is called measurement error, and can have pretty significant effects on esimation.

In my own work, for instance, black mothers and white mothers in the Fragile Families Data display different characteristics and decisions regarding investments in children when controlling for whether they’ve received a promise of financial support. But if I were able to capture more of the group that self-identifies their race as other, this effect may be reduced or even disappear.

The question of whether to even ask about race, or ethnicity, is a sticky one. It may give us information that gives different groups more “clout” as the NYT article argues, or it may reinforce stereotypes and feed the flames. Regardless, if research continues the way it currently goes, having a large group of people opt out because they don’t find something that fits them is problematic.

There’s still lots of thinking to be done about it, and perhaps today is a good day to mull it over a bit. I hope you enjoy your MLK Day!

–“The arc of the moral universe is long, but it bends towards justice.” -MLK, Jr.

Public Randomization

A significant issue in conducting randomized control trials in a community is the issue of fairness. The idea behind RCTs is to mimic the medical model by scientifically ascertaining just how useful a treatment might be. In the case of development economics, this could be a subsidy or an extra year of education, for example. In order to eliminate (or at least reduce) the effect of confounding factors, the researcher randomizes over the population, picking a representative sample to receive the treatment and compares their results to those who did not receive the treatment.

While in theory this should give us the best answer as to how to combat poverty, or get children to school, or determine the effect on whatever outcome we hope to affect, it’s also problematic. The process of randomization necessarily leaves some people out, essentially denying them help that could be life-saving or life-transforming. It might also provide benefits that researchers view as small, but that are capable of creating divisions in a community, or perhaps jealousy, suspicion, or bitterness.

Different RCTs deal with this in different ways. Some do nothing. Some hope the treatment group doesn’t notice. Some tell the control group that they will get the treatment after the analysis is done, some take this course but without informing the treatment or control groups. All of these solutions have their issues, which are dependent on the type of treatment. In some cases, control respondents might change their answers to certain questions to appear more sympathetic, or deserving of the treatment. Or they might anticipate how the treatment is going to affect them in the future and have their answers reflect their hopes rather than their actual state.

As in all survey data, the mere act of asking the question affects the answer.

Last week, Kim Yi Dionne, a professor at TAMU, posted on her blog about making the randomization process public. While I don’t think it solves the problem of people changing their answers to what they think they should be (either to make the treatment look better or worse), it does deal with the bitterness and competition that can often arise out of randomly selected treatment groups.

I especially love the education component of it.

[A Malawian research supervisor] posed a question to the audience: if he wanted to know how the papayas in the village tasted, would he have to eat every papaya from every tree (pointing to the nearby papaya trees)? Some villagers laughed, many said “ayi” (no) aloud. He said, instead he would eat one or two from one tree, then take from another tree, but probably not take one from every tree in the village so that he could know more about the papayas in this village.*

Every mentor I have had for research in the developing world has been adamant that we share findings with the community whose participation was requisite to our success. But rarely do we take the opportunity to educate about how we came to our conclusions, hoping the conclusions themselves will suffice.

I think it’s brilliant.

Blogging

There was a bit of discussion last week on the internet on blogging by academics. Particularly for economists, blogging is a relatively new venture and as there is as yet little demonstrated value in the academic job market, it’s a source of debate.

When I decided to start this blog, I started from a much different place than many other economics bloggers. I was still in the midst of writing my dissertation and my advisors were fairly adamant that I not blog. One pointed me to an economics blogger who had just left her university without tenure and with plenty of speculation that her blogging had contributed to that. She also left with a book deal. Call it what you will, but they were worried that blogging would be seen as taking time from serious academic work and would hurt my own chances for tenure and promotion down the line. One even tried to give me a number. Each blog post a week over a year was equivalent to one academic paper, or something like that.

That’s such an economist way to look at things, isn’t it?

Beyond my less-than-junior status, I’ve been blogging for a really long time. Since my first stint in Venezuela in 2003, I’ve kept a personal blog that I used to keep in touch with family and friends. I started that blog to try to stay sane while working as a journalist in Caracas and to make notes for a book project on Venezuelan women. One post, that was reprinted in my former editor’s blog and the Duke economics department bulletin (Oeconophile), is here. It’s over eight years old now. As that blog became more and more personal in nature, it also began to reflect my dual need to write about economics and about my own experiences with graduate school. In my move to a real job, it seemed to make sense to separate the economics-type posts from the personal ones, to use my writing about economics to create a public persona, a space just for economics. I could use it as a tool for organizing research, planning classes, and sharing my thoughts about what was going on in the world. The old one is still active (and private), though the number of posts I write there is lower now as the total is about split between here and there.

I don’t think that blogging is for everyone. I realize that most people are not compelled to write in the way that I am. Most people don’t have the habit of sharing their daily lives and musings–regardless of the topic–with a potentially large, unknown audience. Twitter is changing that, but the format is quite different.

I fully realize that this blog might hurt my chances at tenure, if and when I come to that point. I really hope that it doesn’t, though. I hope that the tenure process expands to include digital scholarship and outreach.

Even in my limited use of this blog and Twitter, I’ve made contacts with other researchers I likely never would have found otherwise. I’m grateful for this and hope that it continues, that it expands into greater opportunities for collaboration, discussion, and more. This blog might lead to other things. It might not.

But old habits die hard, and I can’t imagine not doing it, so here I go.

Chapter 2

I’m going a little out of order here because I’m trying to deal with something random on my first chapter that arose this week.

The second chapter of my dissertation has to do with expectations, incidentally the unifying theme of this year’s Nobel Prize in Economics.

Believe me, I’m not there.

In this chapter, (chapter2_health) I show that a mother’s expectations of financial support from her child’s father influence how she invests in her child’s health. In the Fragile Families and Child Wellbeing survey, women are asked a the birth of their child whether the father promised financial support. Around the child’s first birthday, they are asked when the child last went to the doctor and for long they breastfed. Interestingly, the promise of financial support is a significant predictor of whether the last doctor’s visit was in the last three months, but the effect is much more pronounced for black women. For white women, the promise of financial support is a significant predictor of how long a woman breastfed.

When I started this paper, I imagined I would be addressing a simple problem of financial (doctor’s visits) versus non-financial (breastfeeding) investments. The promise of support would make you feel richer and thus more likely to invest where you might feel constrained financially.

It turns out, however, that the effect is much more complicated that. The differences by race, which are largely differences of SES and class given the sampling strategy, indicate that a promise of support likely means very different things to people in different circumstances. The lack of distinction in terms of affecting financial versus non-financial investments also indicates that the question likely has a psychological or cultural angle that is not captured by the question itself.

In short, be careful with questions about expectations.

Dissertation

There is a large debate in the economics community about the value of putting out working papers. When a working paper creates significant buzz, whether in the media, on twitter, or even just among economists, the conclusions in the paper take hold. That first impression is shown to be very persistent, even when a later version of the paper comes up with opposite results.

At least as long as I’ve had this blog, I’ve had a note on my research page saying that links to working papers are forthcoming. I’ve completed my dissertation and am working on revising the chapters to submit to journals. I’m fairly certain that the big picture of these papers isn’t going to change and my advisors were insistent that each of my chapters was very close to that point. Consequently, revisions are small at this point, but that doesn’t mean that I can’t benefit from a little help from the internets.

Over the next few weeks, I will post each of the chapters of my dissertation here. Comments, suggestions, typos, criticism, etc. are welcome.

That is the point

I am in Colorado for what is an admittedly enviably long break from teaching classes. I have been spending time in various cities and this week had the pleasure of spending a day in the mountains with my dear friend from high school and her family.

B’s mom, M, and I were chatting a bit before we headed to breakfast (at the Butterhorn Bakery in Frisco. Love!) and she mentioned Yoram Bauman’s piece in the New York Times two weeks ago on his experiments to uncover the nature of economists’ stinginess. M was curious to hear my opinion on the matter, and so I thought I might share here what I shared with her.

At the heart of the paper is an experiment in which college students are asked whether they want to donate a nominal amount, $3, to one of two charities at the time of their class registration. One is a left-leaning group, WashPIRG, and the other a non-profit with the aim to reduce tuition rates, Affordable Tuition Now (ATN). The take-home message is that economics majors were less likely to contribute to either group and thus are “free-riding.” In addition, those who took economics classes but didn’t become majors were less likely to contribute than those who never took an economics class.

In his NYT piece, and in his paper, Bauman dismisses the type and name of the charities he employs in the experiment as rather meaningless to the outcome. “You may question whether these groups actually serve the common good, but that’s mostly beside the point.” It is my belief that the types and aims of charities are driving a lot the effect he sees, or at least have the potential to drive the effect.

For purely anecdotal purposes, I’ll tell you that I was an economics major, and I’m a little bit cheap, (have been my whole life), but that I also give to charity. Despite five years of impoverished grad student living, I still gave and will continue to give to charities I trust and admire. Now that I have a job and am feeling as though I’ve recuperated much of the year’s moving and dissertation writing losses, I’m also looking to expand that giving. Whether I give more to the charities I know or include new ones is to be determined, but you can bet that it will be a careful decision.

And I think that is where the problem comes in with Bauman’s experiment, carefulness. Research, thought, time, and emotional value all come into play when choosing charities to support. So do politics, often. And while I can’t say for sure that economics students are more careful about those decisions, if Bauman can’t account for that either, I don’t think he has a paper. Snap decisions about giving are likely very different than careful decisions about giving. And just because an economics class makes you less likely to give your money to an unknown organization with an unknown track record (or perhaps a known one that works for something that goes against some part of your belief system), I don’t think that makes us more stingy, it makes us more careful.

From an econometric standpoint, if the students who are more (or even less!) careful are the ones who are choosing not to donate–at least in that moment–then the effect you are attributing to stinginess is in fact not there. It’s what economists call an unobservable. The unobservable effect may be driving the difference in donations.

Even if economics students are not more careful, if there is any unobservable quality that is correlated with unwillingness to contribute, the effect is biased.

It’s also my experience that economics majors are more conservative–politically–than their arts and sciences counterparts. I have a hard time believing that right-leaning students would be inclined to donate to WashPIRG anyway, especially when they have likely spent a good deal of their college career dodging their canvassers in the street. (Maybe that’s just COPIRG.)

Overall, I disagree with the interpretation as much as the method. That taking an economics class leads to “loss of innocence” and thus not contributing is overly dramatic, patriarchal, and just plain silly. Aren’t we supposed to be educators? Since when is it my job to protect the innocence of college students? And why should we conflate giving with innocence?