Here is a great introductory lecture into causal inference and the power of directed acyclic graphs / bayesian networks. It repeats a point I made earlier on this blog that big data alone, without a causal model (i.e., theory) to support it, is simply not sufficient for making causal claims. Continue reading Causality for Policy Assessment and Impact Analysis
Two weeks ago I’ve been at the Annual Meeting of the Academy of Management (see this post). And you might have guessed, big data was a huge topic. There is tremendous potential for the use of data science in the business world. Continue reading This isn’t a scientific revolution
John Cochrane recently released a blog post about the discrepancy between academic work and policy advice in macroeconomics. He criticizes that consulting for the policy world is most often based on economic methodology such as static IS-LM/AS-AD models. These date back 40 years and have largely disappeared from the academic landscape.
This current state is puzzling. At least one of the reasons why we do economic research is to better guide policy makers to more sensible interventions to the economy. So either “academic research ran off the rails for 40 years producing nothing of value” or we hold back the diamonds for our little elite circle in the ivory tower. I have seen quite some policy related work myself. Thus, I want report from my own field – innovation economics. Continue reading What’s wrong with policy advice?