Over at Let’s Talk Development, I write about an experiment that showed an inspirational movie to Ugandan high school students and led many of them to pass their math exams:
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.
- 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.
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.)
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.
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.)
5. I then highlighted geographical concentrations of poverty.
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.
8. I then invited the students to suggest what makes countries grow. We talked about a few possibilities.
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).
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).
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.
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.
How do cash transfers conditioned on health clinic visits and school attendance impact health-related outcomes? Examining the 2010 randomized introduction of a program in Tanzania, this paper finds nuanced impacts. An initial surge in clinic visits after 1.5 years—due to more visits by those already complying with program health conditions and by non-compliers—disappeared after 2.5 years, largely due to compliers reducing above-minimal visits. The study finds significant increases in take-up of health insurance and the likelihood of seeking treatment when ill. Health improvements were concentrated among children ages 0–5 years rather than the elderly, and took time to materialize; the study finds no improvements after 1.5 years, but 0.76 fewer sick days per month after 2.5 years, suggesting the importance of looking beyond short-term impacts. Reductions in sick days were largest in villages with more baseline health workers per capita, consistent with improvements being sensitive to capacity constraints. These results are robust to adjustments for multiple hypothesis testing.
This is a deep analysis of the health investments and impacts stemming from cash transfers in Tanzania. Here are some other resources from the same experiment:
- An open access working paper version of the attached paper is available here (which is substantively the same as the published version), and a summary blog post is here.
- A broader analysis of program impacts (beyond health) is available here. A quick summary of those results is available here.
- All of the data from the Tanzania community-based conditional cash transfer evaluation are available here.
In a recent EconTalk episode, Russ Roberts interviews Chris Blattman about his experiment with Stefan Dercon on sweatshops in Ethiopia.
This exchange amused me.
BLATTMAN: Getting a bad shock when you’re poor means–
BLATTMAN: –can mean really terrible things. For these guys, not death. If you have a Grade 8 education in Ethiopia and you have a family that can support you, they’re outside option in the end is living at home and not having anything to do and not being able to contribute to the family, not having any spending money, and maybe having a harder time finding a husband or a wife. Maybe also bad things happen in the household. Maybe you’re contributing to your younger brother going to private school. But these people are not on the margins of death. This isn’t who sweatshops are hiring, at least in this case.
This is NOT to critique the great work that Russ Roberts does on the EconTalk podcast.
But it’s a reminder that many choices in developing countries are not about life or death, but that doesn’t mean they don’t have major implications for human well-being.
Is a factory job better than a cash grant and some training? Chris Blattman and Stefan Dercon have a recent study in Ethiopia where they test these two options with a randomized-controlled trial. Back in December, Chris Blattman discussed with study with Russ Roberts on the EconTalk podcast.
In one interesting bit, Blattman highlights how holding onto an idea and repeatedly seeking an opportunity to implement it can ultimately bear fruit. I transcribed it (abridging a little for readability).
Since you have 300 people lining up for these jobs, instead of taking the first 50 in line who are qualified for the job and hiring them, why not see if we can find a factory owner who will find 150 who are qualified and instead of taking the first 50, we’ll flip a coin and we’ll take 50 out of those 150 qualified applicants as random and we’ll follow them over time and we’ll look at what happens to their incomes and their health and their career trajectories.
I had this idea as a graduate student 10 or 12 years ago, and I always thought, “Every time I meet a factory owner I’m going to feel him out. And I did. Once in a while I’d be on a plane to Uganda to work on one of my projects, usually related to poverty or conflict, and maybe I’d sit by a factory owner, and I’d say here’s this idea that I have, and they’d usually look at me kind of funny. They wouldn’t leap at the possibility. I was just this person they met on a plane, and I was a graduate student. I probably didn’t approach it well, and so it never really materialized.
So I was at a conference in London and there was an Ethiopian businessman who was sort of a real estate mogul. He was giving a talk to a group of development economics at the International Growth Centre, and I approached him afterwards and said, “That was terrific,” and I really enjoyed talking to him and we kept chatting and I said, “I had this idea. I think that your firms not only help achieve growth, but I think they might actually be tools of poverty alleviation. Here’s an easy way to answer that question.” And he said, “That sounds great. Let’s do it.” And so literally five or six weeks later we were on the ground in Ethiopia doing the first randomization.
I recommend the whole conversation.
Two years ago, Anna Popova and I put out a working paper examining whether beneficiaries of cash transfer programs are more likely than others to spend money on alcohol and cigarettes (“temptation goods”). That paper has just been published, in the journal Economic Development and Cultural Change.
The findings of the published version do not vary from the working paper: Across continents, whether the programs have conditions or don’t, the result is the same. The poor don’t spend more on temptation goods. But for the published version, we complemented our vote count (where you sum up how many programs find a positive effect and how many find a negative effect) with a formal meta-analysis. You can see the forest plot below. (The results are not substantively different from the “vote count” review that we did in the working paper and maintain in the published version as a complement to the meta-analysis.)
As you can see, while there are only two big negative effects, both from Nicaragua, most of the effects are slightly negative, and none of them are strongly positive. We do various checks to make sure that we’re not just picking up people telling surveyors what they want to hear, and we’re confident that cannot explain the consistent lack of impact across venues.
Why might there be a negative effect? After all, if people like alcohol, we might expect them to spend more on it when they have more money. We can’t say definitively, but even unconditional transfer programs almost always come with strong messaging: Recipients hear, again and again, that this money is for their family, that this money is to make their lives better, and so on and so on. We know from others areas of economics that labeling money has an effect (called the flypaper effect).
So you can be for cash transfers or against cash transfers, but don’t be against them because you think the poor will use the money on temptation goods. They won’t. To quote the last line of our paper, “We do have estimates from Peru that beneficiaries are more likely to purchase a roasted chicken at a restaurant or some chocolates soon after receiving their transfer (Dasso and Fernandez 2013), but hopefully even the most puritanical policy maker would not begrudge the poor a piece of chocolate.”
Yes and no. Better income and better social conditions, but also a black-white pay gap that changed little over time. Why?
Leah Platt Boustan, UCLA economist (and my friend), just wrote a book on it, Competition in the Promised Land: Black Migrants in Northern Cities and Labor Markets.
This is from James Ryerson’s New York Times review:
In her rich and technical account, the economist Leah Platt Boustan employs the tools of her trade — resourceful matching of data sets, rigorous modeling of labor phenomena, sweeping use of census figures — to analyze the demographics and economics of the Great Migration as a whole… Her investigation both deepens our understanding of what we think we know and adds new complexities and wrinkles.
I expect it’s excellent.