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An economic theory of statistical testing

Authors: Aleksey Tetenov
Date: 27 September 2016
Type: cemmap Working Paper, CWP50/16
DOI: 10.1920/wp.cem.2016.5016

Abstract

This paper models the use of statistical hypothesis testing in regulatory approval. A privately informed agent proposes an innovation. Its approval is benefi cial 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 bene fit from approval. In application to new drug approval, this level is around 15% for an average Phase III clinical trial.

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