Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/149796
Authors: 
Tetenov, Aleksey
Year of Publication: 
2016
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP50/16
Abstract: 
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.
Document Type: 
Working Paper

Files in This Item:
File
Size
426.28 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.