I found this job ad by accident on Twitter and was surprised to see that Facebook has a causal inference group. Continue reading Facebook’s Causal Inference Group
In my class we recently discussed a paper by Higgins and Rodriguez (2006)—published in the Journal of Financial Economics—that contains an important lesson for researchers who want to apply the difference-in-differences (DiD) method in competition analysis and merger control. Continue reading Becoming More Different Over Time
[This is the second part of a fair copy of a recent Twitter thread of mine. I suggest you have a look at part 1 about nonlinear mediation analysis first. Otherwise, it might be hard to follow this post.]
Understanding causal effects is tough, but understanding causal mechanisms is even tougher. When we try to understand mechanisms we move beyond the question whether a certain causal effect exists, and ask how an effect comes about instead. Continue reading A plea for simple theories
This is a fair copy of a recent Twitter thread of mine. I thought it might be interesting to develop my arguments in a bit more detail and preserve them for later use.
Here’s a quote from John K. Galbraith’s 1952 book American Capitalism: The Concept of Countervailing Power Continue reading Do we really run out of good ideas?
There are not many better things (personal things aside) that can happen to a job market candidate than getting mentioned by Tyler Cowen on Marginal Revolution, one of the most widely read economics blogs on the internet. This happened to Nicholas Kozeniauskas from NYU. His paper got judged to be “one of the more important papers of this job market season” by Tyler. And it has indeed many interesting results to offer. Continue reading Why do less and less people start their own business?
[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