My paper “Beyond Baseline and Follow-up: the case for more T in experiments” was recently accepted at the JDE. As with most papers that go through review, the accepted version is a definite improvement on the working paper version.
As the United States prepares for its first presidential election after the Great Recession, inequality has emerged as a central political issue. This is not unremarkable: Americans have historically seemed much less troubled by income differences than, say, Europeans. You may remember a 2004 article by Alberto Alesina, Rafael di Tella and Robert MacCulloch in the Journal of Public Economics, which reported that happiness in the US was much less sensitive to inequality than in Europe.
For many years, researchers have recognized the need to correct standard error estimates for observational dependence within clusters. An earlier post contrasted the typical approach to this matter, the cluster robust standard error (CRSE), and various methods to cluster bootstrap the standard error.
Back in the tail end of last year, I did a post on using workshops with project teams to build impact evaluation design. My friend anonymous requested copies of the presentations. Since I am in the midst of doing another one of these workshops here in Ghana, I thought it would be worth posting them now.
I’ve been meaning to read for the last month this new paper by Orazio Attanasio and co-authors, which is the latest in the still small number of studies to carry out a randomized experiment to measure the impact of microfinance. David Roodman was quick to give his thoughts on it in this post, but I thought I’d also summarize it briefly for you and offer my thoughts.
· A New paper has innovative way of getting data on H1B migrants – they obtained administrative data through a Freedom of Information Act request – and use this for most comprehensive look yet at how high-skilled migrants coming through H1B compare to natives.
Update: As if on cue, the Washington Post published an article (on January 19, 2012, 3:42 PM EST) that says:
If economists view mental health as one component of human capital, as we typically view physical health, then it’s a natural step to the corollary view that good mental health leads to productivity enhancing behaviors such as increased labor supply, greater effort, enhanced concentration, and so on. Given its productive role perhaps mental health, often neglected in the policy realm, deserves more attention. Unfortunately there are precious few studies till date that actually establish such a link between psychological health and productivity.
After talking about domestic violence measurement and the need for some kind of model when you think about things like domestic violence with Toan last week, this week I look at a new paper from Jonas Hort and Espen Villanger which both asks the question carefully and definitely makes me think hard about what the ri