New York Times published an article last week, titled “The Future of Not Working.” In it, Annie Lowrie discusses the universal basic income experiments in Kenya by GiveDirectly: no surprise there: you can look forward to more pieces in other popular outlets very soon, as soon as they return from the same villages visited by the Times.
- On the 74 million blog, interview with Kirabo Jackson about the importance of school spending and other education-related discussion: “In casual conversation with most economists, they would say, “Yeah, yeah, we know that school spending doesn’t matter.” I sort of started from that standpoint and thought, Let me look at the literature and see what the evidence base is for that statement. As I kept on looking through, it became pretty clear that the evidence supporting that idea was pretty weak.” Also discussion on the need to measure things beyond test scores.
- IPA has a nice little booklet on nudges for financial health – a quick summary of the evidence for commitment devices, opt-out defaults, and reminders.
I recently became a co-editor at the World Bank Economic Review, and was surprised to learn how low the acceptance rate is for submitted papers. The American Economic Review and other AEA journals such as the AEJ Applied publish annual editor reports in which key information on acceptance rates and review times are made publicly available, but this information is not there for development economics journals.
- Chris Blattman provides an incentive to delay giving up on that great research idea you’ve been peddling for years in this story from the EconTalk podcast: For years, he pitched random African factory owners the idea of an RCT of factory employment. “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.” One day it worked, and six weeks later he was randomizing applicants.
Some years ago, a government I was working with really wanted to increase the data they had on their own education system. They didn’t have great data on student attendance or teacher attendance, much less on tardiness or instruction time. They designed an information management system with swipe cards for every student and teacher to use going in and out of classrooms, all of which would feed wirelessly into the district office, allowing real-time interventions to improve education. It sounded amazing! And it fell apart before it ever began.
- Andrew Gelman on the “what does not kill my statistical significance makes it stronger” fallacy, and why even Heckman has fallen victim to it. “conditional on statistical significance at some specified level, the noisier the estimate, the higher the Type M and Type S errors. Type M (magnitude) error says that a statistically significant estimate will overestimate the magnitude of the underlying effect, and Type S error says that a statistically significant estimate can have a high probability of getting the sign wrong”
- Let the data talk, but what language should it speak? 25 ways of visualizing the same dataset on life expectancies around the world.
Do skills matter for agricultural productivity? Rachid Laajaj and Karen Macours have a fascinating new paper out which looks at this question. The paper is fundamentally about how to measure skills better, and they put a serious amount of work into that. But for those of you dying to know the answer – skills do matter, with cognitive, noncognitive, and technical skills explaining about 12.1 to 16.6 of the variation in yields. Before we delve into that
I have worked for a while with different attempts to get informal firms to register their businesses and become formal. We have tried giving them information and actually paying them to formalize, lowering the cost of registering to zero, offering them accountants and increasing enforcement.
- In the latest JEP, how to write an effective referee report: With three specific recommendations: I) Make clear the contribution, and give appropriate value to innovative work: “The importance of a contribution can be undervalued in some cases by referees and editors. After all, papers that are more ambitious are often more likely to have loose ends, which gives referees and editors a reason to avoid taking a chance on them” II) divide comments into two clearly demarcated sections: 1) problems that make the paper unpublishable, which (if revision is invited) must be addressed before the paper is publishable; and 2) problems that are not essential for the publishability of the paper, which should labeled as “suggestions.”; and III) In making requests of authors, weigh the costs of the request. It is not enough that a particular request will improve the paper. The benefits must exceed the costs, so that the improvement has positive net present value. Since the author bears the costs, it is easy for a referee to make absurd demands thoughtlessly. Don’t.” – and finally, after receiving multiple 5+ page referee reports recently, I agree with “Unless a referee needs to make extremely technical points, 2–3 pages should be sufficient.”