App Stats: Carpenter on "R&D Abandonment in Regulatory Equilibrium: Evidence from Asset Price Shocks Induced by FDA Decisions" 

 We hope you can join us this Wednesday, February 13, 2013 for the  Applied Statistics Workshop .  Dan Carpenter , the  Allie S. Freed Professor of Government from the  Department of Government  at Harvard University, will give a presentation entitled "R&D Abandonment in Regulatory Equilibrium: Evidence from Asset Price Shocks Induced by FDA Decisions". A light lunch will be served at 12 pm and the talk will begin at 12.15. 

 "R&D Abandonment in Regulatory Equilibrium: Evidence from Asset Price Shocks Induced by FDA Decisions" 
Dan Carpenter 
Government Department, Harvard University 
CGIS K354 (1737 Cambridge St.)  
Wednesday, February 13th, 2013 12.00 pm 

 This is joint work with Jessica Blankshain (Harvard University) and Susan Moffitt (Brown University). 

 Abstract: 
 Observers of approval regulation regimes such as FDA drug review have long proposed that they cause private companies to avoid developing new products that would otherwise have been marketed. The welfare conclusions and policy recommendations vary, but the causal claim is common. Yet most such claims suffer from the problem of endogeneity and non-random assignment, such that the necessary counterfactual cannot be sustained. If a regulatory decision occurs and drug projects are discontinued or delayed, the analyst cannot usually infer whether it was a change in regulation or something else that caused the project abandonment. Using a rich dataset on the development of over 15,000 pharmaceutical investment projects from 1989 to 2003, we examine responses in development projects to "bad news" regulatory announcements weighted by the asset price shocks in a general equilibrium financial market. Using a Lévy process model of asset price evolution, we demonstrate that the abrupt changes in sponsor asset prices upon the announcement of adverse regulatory news are plausibly non-anticipable for all participants but the regulator. Specifically, for the development projects of companies other than the sponsor affected, they are quasi-random, conditional on all information known on the day before the announcement. This assumption is supported by analysis of data, and then used to identify a model of regulatory effects upon drug development. The results suggest robust effects of induced project abandonment by regulatory decisions; a ten percent (negative) shock to the sponsor's asset price in response to adverse FDA news is sufficient to induce a three to four percent increase in the hazard rate of drug project discontinuation for all other firms' projects in the months following the news. While some immediate responses to adverse regulatory news are witnessed, most response takes place in a six month period following the event. Effects are larger for bad news from advisory committee decisions and FDA requests for additional data, and are negative (development-facilitating) for surprise other-company abandonments where FDA factors are implicit. The results are generally supportive of dominant theoretical models of endogenous approval regulation (Carpenter and Ting 2007), but policy implications are unclear and depend upon the potential health and welfare effects of the therapies foregone.