Machine Learning and Economic Policy: The Uses of Prediction.

Machine learning tools excel at producing models that work in a predictive sense. Economics and policy, however, rely heavily on causality. One fruitful approach to this tension is to marry causal inference and machine learning techniques. In this talk, I will argue for a complementary, second approach: that prediction in and of itself can be very useful for a swath of applications. Many important policy problems have embedded in them pure prediction problems. Moreover, prediction tools by themselves can help reveal fundamental social mechanisms. These kinds of applications are plentiful, but sit in a blind spot: because we have not had prediction tools in the past, we are not used to seeing them.