cemmap working paper, Centre for Microdata Methods and Practice CWP50/16
This paper models the use of statistical hypothesis testing in regulatory approval. A privately informed agent proposes an innovation. Its approval is beneficial to the proponent, but potentially detrimental to the regulator. The proponent can conduct a costly clinical trial to persuade the regulator. I show that the regulator can screen out all ex-ante undesirable proponents by committing to use a simple statistical test. Its level is the ratio of the trial cost to the proponent's benefit from approval. In application to new drug approval, this level is around 15% for an average Phase III clinical trial.