Over at Development Impact, I’ve recently published two blog posts:
- Growing or fading? The long-run impacts of educational interventions
- Human Capital Round-up – May 2018 Edition
Over at Development Impact, I’ve recently published two blog posts:
One method for evaluating the impact of a program is regression discontinuity design (RDD). This works when an intervention (to be evaluated) is assigned based on a score of some sort. For example, a welfare program that is assigned for all households below a certain level of income, or an education program that is assigned to all students above a certain test score (or below a certain test score). In short, this method compares individuals who are just above and below the cut-off for assignment to the program, since they are very similar (except for 1 or 2 points on a test or a small amount of income). You then adjust for those small differences statistically, but the intuition is that you’re comparing people who are very similar, except that one group gets the intervention.
When I teach impact evaluation, an activity where students get up and move around can be helpful for more at least two reasons: It can make a point visually, and it can keep people from falling asleep. Here’s an activity I came up with for demonstrating the concept behind RDD, and it has worked pretty well.
Tell the students that we are evaluating the impact of an injection that is supposed to increase the height of recipients. Every participant under a certain height will receive the injection. How can we evaluate it?
Have all the students line up in a row by height. (With a big class, use a subset of students.) Pick a couple of students of similar (but not identical) height in the middle and explain that this is the height cut-off. The shorter student on the left will receive the injection, and the taller student on the right will not.
Now, if we were to compare the height of the tallest student (to the right of the group) and the shortest student (to the left of the group), we wouldn’t have a good sense of the impact of the injection, since their heights are already so different. But if we compare those who are just below the qualifying height (getting the injection) to those just above (not getting the injection), then differences we observe are likely to be due to the injection.
I’ve done this activity with adults in more than one country, and it’s been effective and fun.
Any ideas for how you’d make this activity better? What activities do you use to teach impact evaluation methods?
The image at the top of this post is from Impact Evaluation in Practice (Second Edition).
I read and listen to a fair number of books. Yesterday I received this query.
I tend to remember little of what I read. That’s why I write it all down. In the words of Henry Jones, Sr., “I wrote them down…so that I wouldn’t *have* to remember.”
I have two strategies for remembering. First, I take notes. I use the note-taking and note-managing app Evernote. For each new book I read, I create a new note. As I listen to an audiobook or read a print book, I pause and make a note of a line or passage that I find particularly insightful. If it’s an audiobook, I’ll use the Amazon “Look Inside” feature to search for the exact wording. At the end of reading the book, I have a list of the lines and insights I learned from. I’ll often label them with a topic. Evernote has a good search function, so it’s relatively easy for me to find those lines later, even if I don’t remember what book it was from.
Second, I try to write a short review of each book. Nowadays I post those here on this blog. The micro-review allows me to crystallize my main takeaways and whether I’d recommend the book to others.
What do you do to remember what you’ve learned from books?
You submit your paper to a conference. You’re all fired up to share your work and to get feedback. Then no one shows up to your session! Is it because everyone hates your work? or because it’s 8am? or both? Günther, Grosse, and Klasen (published version; working paper) identify some correlates of session attendance.
We analyze the drivers of audience size and the number of questions asked in parallel sessions at the annual conference of the German Economics Association. We ﬁnd that the location of the presentation is at least as important for the number of academics attending a talk as the combined effect of the person presenting and the paper presented. Being a presenter in a late morning session on the second day of a conference, close to the place where coffee is served, signiﬁcantly increases the size of the audience. When it comes to asking questions, location becomes less important, but smaller rooms lead to more questions being asked. Younger researchers and very senior researchers attract more questions and comments. There are also interesting gender effects. Women attend research sessions more diligently than men, but seem to ask fewer questions than men. Men are less likely to attend presentations on health, education, welfare and development economics than women. Our ﬁndings suggest that strategic scheduling of sessions could ensure better participation at conferences. Moreover, different behaviors of men and women at conferences might also contribute to the lack of women in senior scientist positions. [Emphasis added by me]
So, do whatever you can to angle for that second-day, late-morning slot.
“School Costs, Short-Run Participation, and Long-Run Outcomes: Evidence from Kenya”: My paper with Mũthoni Ngatia is out as a World Bank Policy Research Working Paper. Here’s what we learned.
Even though primary education is “free” in many countries, families face many incidental expenses: uniforms, transport, and materials, among others.
In Kenya, we worked with an NGO that provided free school uniforms to children to reduce the cost of schooling.
I know that you’re going to say: Do we need another study of “giving stuff” for education and how it affects attendance? Aren’t we supposed to be focused on learning and pedagogy?
First, while attending school is no guarantee of learning, it’s a really important part of the process.
Second, we follow these students over 8 years. Few international education studies trace the time path of impact.
A school uniform can increase school participation by multiple means. Families don’t have to pay for the uniforms. AND students don’t feel stigmatized by being the only kid without a uniform.
What do we find? In the short run, providing a school uniform does increase school participation.
The impacts are particularly large for the poorest kids. Absenteeism drops by 15 percentage points for them, eliminating 55 percent of absenteeism for them.
But 8 years later, the children who participated in the program had no better educational outcomes than those who did not.
Some educational interventions have long-lasting impacts: Smaller early-grade classes in the USA have translated into better college performance.
But we can’t assume it. In this case, initial gains in school participation do not translate into more school completion.
And a few last words from the paper: “Take care when interpreting short-term results, taking into account these results and others which demonstrate that long-term impacts may vary – sometimes dramatically – from initial effects.”
“Gathering long-term data is costly, but without it, the trajectory of impacts resulting from the wide range of interventions currently being implemented remains a mystery.”
That’s it! Big short-term impacts for poor kids but disappointing long-term impacts. Check out the paper!
A new study by Burke, Bergquist, and Miguel suggests that it can. Not only that: it delivers positive spillovers. I write about it over at Let’s Talk Development.
Microcredit that helps more than just the borrower
Prices in African agricultural markets fluctuate a lot: “Grain prices in major markets regularly” rise “by 25-40% between the harvest and lean seasons, and often more than 50% in more isolated markets.” To an economist, this looks like a massive missed opportunity: Why don’t farmers just hold onto their harvested grain and sell at a much higher price during the lean season?
According to new work by researchers Burke, Bergquist, and Miguel, farmers in Kenya lack access to credit or savings opportunities, and so they “report selling their grain at low post-harvest prices to meet urgent cash needs (e.g., to pay school fees). To meet consumption needs later in the year, many then end up buying back grain from the market a few months after selling it.” It’s like the grain market is a very expensive source of short-term loans.
Can microcredit help? Offering farmers a loan at harvest led them to sell less at harvest time and to sell more grain later, when prices were higher. “The loan produces a return on investment of 28% over a roughly nine month period.”