· “We are all climate economists now” – Lydia dePillis in the New York Times notes the surge in climate-related research as seen at the recent AEA conference, and some of the variety in topics, with more focus on adaption and less on carbon pricing – but there is not much summary of what we are learning from this new research.
· Solutions for Youth Employment has a nice knowledge repository of toolkits, case study notes, and more resources for designing different types of youth employment projects.
· Paul Goldsmith-Pinkham is sharing written lecture notes for his PhD course on applied empirical methods. Also slides, exam questions, and more.
· Jason Kerwin offers his writing advice on how to get your paper written up in 10 weeks while still having time for other stuff. Also on writing, Tim Taylor covers a study in JEBO that found 6 hours of professional editing of PhD student papers improved ratings from both economists (who were asked to assess whether the paper would be accepted for a conference or journal) and by writing experts. He covers some of the key areas where editors offered help, especially around the title, abstract, and introduction.
· On the IGL, Rob Fuller summarizes survey evidence from six EU countries that survey respondents are reasonably in favor of governments doing experiments and don’t mind the word “experiment” as much as often thought.
· On the 100% CI blog, Julia Rohrer has an interesting post on cross-sectional mediation analysis and its problems, the need to be explicit in assumptions, and on the notion of test severity “Roughly speaking, an empirical observation provides a severe test of a hypothesis if it is (1) very likely to occur if your hypothesis is true and (2) very unlikely to occur otherwise. Test severity can be formalized as p(observation|hypothesis, background knowledge about the world) divided by p(observation|background knowledge about the world)…. When people criticize cross-sectional observational mediation analysis, it is often because at least one of the paths is trivially explained without the causal effect of interest. For example, a common pattern involves a psychological mediator and then some vaguely related psychological outcome, both assessed via self-report. Those variables are almost guaranteed to be correlated to some degree, because they may be affected by shared response biases, or by underlying personality traits. So usually, that part of the mediation chain is not subjected to a severe test, and without it, the whole mediation thing turns moot. Of course, often the first path (“independent” variable to mediator) suffers from the same issue, which doesn’t improve the situation. The severity of your mediation test ends up twice as much as nothing at all, which is still nothing at all.”
· Andrew Gelman on the research incumbency rule, and Tim Guinnane on why not to believe a lot of those historical data you see, with the great titled paper “we do not know the population of every country in the world for the past two thousand years”. In particular, measurement error is non-classical, and data points are not independent, but instead some are clones of each other, where one data from one country is used as a proxy for another with missing data.
· On the Econ that matters blog, Shadi Farahzadi summarizes her job market paper on muslim migration for marriage in the U.K. “the main reason behind substantial Muslim marriage migration isn’t economic gains, but rather the strong preference for shared cultural . This results don’t vary by gender.”
· On the World Bank Data blog, Susmita Dasgupta, Brian Blankespoor and Karolina Ordon describe new global databases of carbon dioxide and methane emissions based on satellite data.
· Conference deadline: 2024 NOVAFRICA conference, to be held in Lisbon June 27-28, submission deadline Feb 15.
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