A few self-links

  1. This morning I posted “What a new preschool study tells us about early child education – and about impact evaluation” over at Development Impact, about an interesting study “Cognitive science in the field: A preschool intervention durably enhances intuitive but not formal mathematics,” which is a randomized controlled trial in Delhi, India.
  2. You can also just watch the researchers explain that paper below.

3. The French version of my post, “A Framework for Taking Evidence from One Location to Another,” based on the work of Mary Ann Bates and Rachel Glennerster, is now available:  Comment déterminer si un projet avec de bons résultats dans un pays fonctionnera ailleurs ?

4. The Portuguese version of my post, “Are good school principals born or can they be made?” based on the work of Roland Fryer and others, is now available: Os bons diretores da escola nascem ou podem ser criados?

A history of Liberia’s women? A review of Helene Cooper’s Madame President: The Extraordinary Journey of Ellen Johnson Sirleaf

madame presidentIn 2005, Liberia elected its first woman president. Ellen Johnson Sirleaf was also Africa’s first elected woman president. (Guinea-Bissau and Burundi both briefly had women as acting presidents.)

In Madame President: The Extraordinary Journey of Ellen Johnson Sirleaf, Helene Cooper recounts the story of Ellen Johnson Sirleaf’s life: from precocious child to teen mom to victim of domestic violence to Harvard graduate to international financier and — ultimately — to head of state.

But of course, any such biography also gives a history of the country, and here Cooper does something special. As she tells individual stories to make broader movements more concrete, she chooses stories of women. She tells the stories of
  • “Josephine, who cooked every day for the Taylor soldiers who raped her,” and
  • “a terrified Mary Warner [who] strapped her four-year-old son on her back and ran from place to place, finally pressed up against a gate outside the United Nations compound, desperately seeking shelter,” and
  • Louise Yarsiah, who was leading a group of women in prayers for peace when Charles Taylor’s security chief showed up. Yeaten’s soldiers drew their guns, and Yarsiah’s women kept praying. Ultimately, the soldiers stood down.

Cooper also demonstrates how women organizing women brought about Sirleaf’s election and then re-election. She tells of other powerful women within Sirleaf’s government, like Mary Broh, mayor of Monrovia. This is not just the extraordinary journey of Ellen Johnson Sirleaf, but also the story of thousands of other extraordinary Liberian women. Cooper imagines how Liberia’s brutal history grew a generation of women activists: “Little girls do not come out of the womb vowing to become activists for female power. They don’t spend their childhood thinking about how they will repair the indignities, large and small, that bleed women daily. It’s a series of things that multiply and turn ordinary women into movements of female determination.”

As Johnson Sirleaf achieves gains in the country over the course of her presidency, I couldn’t help but feel a growing dread, knowing that the devastating Ebola epidemic of 2014-2015 was on its way. I actually met the author, Helene Cooper, during the Ebola epidemic, when we appeared on the same news program after she had returned from a trip to Liberia and I had worked on estimates of the potential economic impact of the epidemic. She was deeply knowledgeable, and it shows in her reporting here.

This is a sympathetic biography; Jina Moore wrote in the New York Times that it “valorizes Johnson Sirleaf rather than complicates her.” But Cooper also doesn’t whitewash: Johnson Sirleaf’s supporters aren’t above buying voter cards from their opponent’s supporters for booze money in the run-up to an election, and Johnson Sirleaf appoints her own son to a key government position.

I listened to the audiobook, wonderfully narrated by the author’s sister Marlene Cooper Vasilic. As Audiofile puts it, the narration makes the story “all the more powerful. … Vasilic’s facility with pidgin makes the few direct quotes come alive.”

Even if technology improves literacy, is it worth the cost?

Ben Piper reports on insightful work that he and co-authors have done comparing various education technology intervention in Kenya in terms of both effectiveness (do they improve reading ability?) and the cost-effectiveness (what’s the cost per reading gain?).

I recommend his full post (or the research paper it’s based on). Here are a couple of highlights:

When compared to traditional literacy programs, the more intensive ICT interventions did not produce large enough gains in learning outcomes to justify the cost. This is not to say that each of the ICT interventions did not produce improvements in students’ reading ability…. [But] the cost-effectiveness of all of these programs might still be significantly lower than a clear investment in high quality literacy programs…. In additional to monetary cost, an opportunity cost existed…. Many of the teachers, tutors, and students lacked exposure to technology and the time and energy spent on learning how to use the technology reduced the amount of time for instructional improvement activities. 

When costs are considered, there are non-ICT interventions that could have larger impacts on learning outcomes with reduced costs; one such option could include assigning the best teachers to the first grade when children are learning how to read, rather than to the end of primary school as many schools do.

Economists will disagree with the standard errors if I understand the specification right: Randomization is at the district level and I don’t believe the authors cluster the standard errors. 

But I don’t think that will change the fundamental message here: Even if there are some gains from education technology, we have to ask when they will be most likely to be worth the cost.

Economic Development in 20 minutes to middle schoolers

Earlier this week I had 20 minutes each to speak to four classes of middle schoolers about my career. I talked about economic development. I used a presentation (available in full here). Given that it was the antepenultimate day of school, the students and teachers appeared very engaged.

  1. I showed the students four families from Gapminder’s Dollar Street initiative — one from India, one from Burundi, one from Ukraine, and one from Colombia, and I had students vote (by raised hands) on which family they expected was poorest and which was wealthiest.

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2. Then I introduced the four families in turn, and I expressed their monthly income in terms of the price of school lunches at the middle school where I was speaking. (The Ukrainian family’s monthly income was the equivalent of 3,100+ school lunches, more than the most insatiable student should ever consume.)

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3. Having highlighted the massive gaps in income between families, I invited the students to vote (again, by raised hands) on the number of people in the world currently in extreme poverty. Hint: According to the latest estimates from Cruz et al. (2015), we’re at 700 million.

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4. Then I showed — in two ways — how much poverty has decreased over time. First I showed the figure below from Our World in Data. I also showed the evolving chart on income and life expectancy from Gapminder. (Technical difficulties precluded showing the actual evolution over time, but at least I could show screenshots of the beginning and the end.)

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5. I then highlighted geographical concentrations of poverty.

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6. Then I gave two very simple definitions of economics:

  • Macro: Why are some countries rich and others poor
  • Micro: How can poor families get out of poverty?

7. What does economic growth look like? Here’s some of the variation, where countries on the top left are those that grew the most: low income in 1960, high income in 2014.

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8. I then invited the students to suggest what makes countries grow. We talked about a few possibilities.

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9. We then returned to the growth map and differentiated between two high-growth countries: South Korea, which produces goods for trade (I had all the students with Samsung devices raise their hands) versus Equatorial Guinea, which produces a natural resource for trade (oil). We talked about the different implications for inequality.

10. I then talked through the two objectives of the World Bank: to encourage growth and to end extreme poverty. (To be more precise, the “twin goals” are to encourage “shared prosperity” — growth that benefits the bottom 40% of the population — and to end extreme poverty.)

11. Then, since education is an area I work in actively, I highlighted the relationship between learning and economic growth, using data from Hanushek et al. (2008).

slide 18a

12. I then asked how many of the 7th graders could read a sentence: All of them claimed that ability. I then showed data from the Early Grade Reading Barometer on the percentage of 2nd graders in various countries who couldn’t read a single word, which of course predicts future literacy.

13. I talked about what I do specifically, with a few examples (including a few funny stories).

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14. And finally, I talked them through how I got to my current job and reminded them that it’s not just economists working in international development.

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Many thanks to all those who gave suggestions. I used several of them and would have enjoyed using others if I’d had more time (either to prepare or with the classes).

The next day, I received a number of thank you notes from students. This one took the cake.

thank you

The impact of student performance labels on later schooling

One key feature of test-based accountability systems in the U.S. is that every student receives not only a test score but also a label based on their performance. Massachusetts, the state that we study, assigns students labels of Failing, Needs Improvement, Proficient, or Advanced by determining cut-points with which it divides the finer-grained test-score distribution into performance regions. … These labels provide no additional information beyond the test scores on which they are based; they are simply coarse summaries of a student’s performance. We focus on responses to labels that have no state-defined consequences for students.

This, from a paper by John Papay, Richard Murnane, and John Willett, in the Journal of Human Resources.

Using a regression-discontinuity design, we find persistent effects of earning a more positive label on the college-going decisions of urban, low-income students.

Here’s an open-access, earlier version of the paper. And here’s the key figure, on the left comparing students with an “advanced” versus a “proficient” label, and on the right, comparing the “proficient” to the “needs improvement” label:

advanced-proficient cutoff


To improve educational outcomes, help households to smooth consumption throughout the year

A new paper by Paul Christian and Brian Dillon poses this question: “Does a consistently seasonal diet during childhood have long-run effects on human capital formation?” They use Tanzania’s Kagera Health and Development Survey — a 19-year panel survey — to answer the question. As you can see from the figure below, Tanzania has dramatic seasonality: Children have very different access to food in some parts of the year than in others.

histogram of seasonality

Christian and Dillon develop a structural model — which you can read all about in the paper — and use the household data to estimate it.

Here is a taste of the results:

We find a robust, negative relationship between consumption seasonality and human capital formation. Across specifications, the negative relationship between seasonality and human capital is 30-60% of the magnitude of the positive relationship between average consumption and human capital (in the same units). … The effects of seasonality on height is greatest for children in utero and during infancy, during the critical first 1,000 days of life. Effects on education are most pronounced for older children, suggesting that behavioral channels such as dropping out of school to help on the farm are more important in this sample than early life impacts on cognitive performance. When we further allow for heterogeneity by both age and gender, we see that the height effects during infancy are concentrated among girls, while the education effects during adolescence are largely driven by boys.