I gave a talk on Wed, Feb 8 at the IQSS methods workshop where I described my efforts to estimate the effects of UN intervention and UN peacekeeping on peacebuilding success following civil war. One of my goals was to demonstrate how matching-based methods and the Rubin model of causal inference can be helpful for answering questions in political science, particularly in fields like comparative politics and international relations. Read more about Thoughts on SUTVA (Part I)
As I remarked in an earlier entry, some researchers are troubled by the potential outcomes framework of causality because it makes explicit reference to unobservable quantities. The implication, of course, is that science should stick to what’s observable.
First, apologies for my delay in posting to the blog. I've spent most of the last two months involved in the Canadian federal election as a candidate in my home riding. That I lost wasn't unexpected, nor was winning necessarily my goal. I wanted to talk about ideas that weren't being brought up by other candidates. First and foremost on the list was how an election shapes the debate - and why electoral reform is necessary to allow more ideas into the public forum. Read more about Making Votes Honest: Part I
A recent study by Shane Frederick at MIT, published in the Journal of Economic Perspectives [pdf], has gotten press attention in the last few weeks for its claim that performance on a simple math test predicted risk-taking behavior. I'm a bit skeptical about the conclusions Frederick's draws (and I'll explain why), but regardless, the study itself is quite interesting. Read more about IQ and Risk-taking
This week, the Applied Statistics Workshop will present a talk by Rustam Ibragimov of the Harvard Department of Economics. Professor Ibragimov received a Ph.D. in mathematics from the Institute of Mathematics of Uzbek Academy of Sciences in 1996 and a Ph.D. in economics from Yale University in 2005 before joining the Harvard faculty at the beginning of this academic year. Read more about Applied Statistics - Rustam Ibragimov
Agreement with the Potential Outcomes Framework of Causality (counterfactual approach, Rubin model) is spreading like wildfire, but is still far from unanimous. Over the past few years I’ve had several conversations with friends in sociology, economics, statistics, and epidemiology who expressed considerable unease with the notion of potential outcomes, or even causality itself.