Last week I was teaching about graphical models of causation at a summer school in Montenegro. You can find my slides and accompanying R code in the teaching section of this page. It was lots of fun and I got great feedback from students. After the workshop we had stimulating discussions about the usefulness of this new approach to causal inference in economics and business. I’d like to pick up one of those points here, as this is an argument I frequently hear when talking to people with a classical econometrics training. Continue reading No Free Lunch in Causal Inference
Tag: Treatment Effect
Econometrics and the “not invented here” syndrome: suggestive evidence from the causal graph literature
[This post requires some knowledge of directed acyclic graphs (DAG) and causal inference. Providing an introduction to the topic goes beyond the scope of this blog though. But you can have a look at a recent paper of mine in which I describe this method in more detail.]
Graphical models of causation, most notably associated with the name of computer scientist Judea Pearl, received a lot of pushback from the grandees of econometrics. Heckman had his famous debate with Pearl, arguing that economics looks back on its own tradition of causal inference, going back to Haavelmo, and that we don’t need DAGs. Continue reading Econometrics and the “not invented here” syndrome: suggestive evidence from the causal graph literature
Dear European Research Council, evaluating grant programs is harder than you think
Today the European Research Council tweeted about a study that supposedly shows how succesful their research grants are.
ERC grants provide a lot of money to upcoming and established researchers who are based in Europe to carry out larger research projects and agendas. Of course we would like to know whether the money is well spent. Continue reading Dear European Research Council, evaluating grant programs is harder than you think
Paul Hünermund, Ph.D. 