· In Science this week (gated), Katz and Kling add some co-authors and follow-up on their famous Econometrica paper on the Moving to Opportunity program to examine impacts 10-15 years after moving from a high-poverty to a low-poverty neighborhood. They find long-term improvements in physical and mental health and subjective well-being, with some of these impacts large, despite no impact on economic self-sufficiency. Although the paper is gated, there is a good summary and analysis here at Boston.com.
· Andrew Gelman looks at studies which show the impact of higher temperatures on worker productivity – above 26 degrees Celsius, each degree reduces productivity by 2%.
· Interesting interview with John List in the Richmond Fed’s Region Focus – he talks about how he got into field experiments, where behavioral economics matters (“If I want to take a tripfrom Chicago to Fenway Park — say I want to go watch the Red Sox play the Yankees — neoclassical theory will get me to Cambridge. But I need behavioral economics to get me from Cambridge to my seat in the 25th row of Fenway Park”….and why randomization is good even in complicated scenarios “Experimentation should be used in environments that are messy; and I think the profession has had it exactly backwards for decades. They have always thought if the test tube is not clean, then you can’t experiment. That’s exactly wrong. When the test tube is dirty, it means that it’s harder to make proper causal inference by using our typical empirical approaches that model mounds and mounds of data”. (h/t Tim Taylor).
· On the CGD blog, Bill Savedoff discusses how three NGOs do impact evaluations. “Oxfam GB randomly picks about 40 projects a year and tries to infer impact using different methods…Randomly choosing projects also increases the probability of discovering things that staff might not have expected”.
· How data and experiments are shifting voter mobilization strategies – NPR covers a new book called Victory Lab.