We thank David Cutler, Tim Deering, James Fearon, Sven Feldmann, John Ferejohn, Tom Hammond, Lewis Kornhauser, Keith Krehbiel, Alison Lawton, Albert Ma, Caroline McGregor, David Meltzer, Ariel Pakes, Allison Sovey, Sonja Tong, Andrea Venneri, Natasha Zharinova, seminar participants at the University of Michigan, Stanford University, NYU Law School, Boston University, Harvard University, the University of Chicago, and Northwestern University, and panel participants at the 2001 annual meeting of the American Political Science Association and 2002 annual meeting of the Midwest Political Science Association for useful comments and discussions. Carpenter acknowledges the National Science Foundation (SES-0076452), the Robert Wood Johnson Foundation Scholars in Health Policy Program, and the RWJ Investigator Awards in Health Policy Research Program. Ting acknowledges the National Science Foundation (SES-0519082) for financial support. All errors, arguments, and interpretations are ours.
Regulatory Errors with Endogenous Agendas
Article first published online: 2 OCT 2007
American Journal of Political Science
Volume 51, Issue 4, pages 835–852, October 2007
How to Cite
Carpenter, D. and Ting, M. M. (2007), Regulatory Errors with Endogenous Agendas. American Journal of Political Science, 51: 835–852. doi: 10.1111/j.1540-5907.2007.00284.x
- Issue published online: 2 OCT 2007
- Article first published online: 2 OCT 2007
How do a regulator's decisions depend on the characteristics and strategies of its external clients? We develop a theory of approval regulation in which an uninformed regulator may veto the submission of a better-informed firm. The firm can perform publicly observable experiments to generate product information prior to submission. We find that when experimentation is short, Type I errors (approving bad products) are more likely for products submitted by firms with lower experimentation costs (larger firms), while Type II errors (rejecting good products) should be concentrated among smaller firms. These comparative statics are reversed when experimentation is long. We perform a statistical analysis on FDA approvals of new pharmaceutical products using two different measures of Type I error. We find consistent support for the counterintuitive hypothesis that, under particular conditions, errors are decreasing in the size of the firm submitting the product.