Herd Behavior in FDA Committees: A Structural Approach

47 Pages Posted: 26 Jul 2018

See all articles by Melissa Newham

Melissa Newham

ETH Zürich - CER-ETH - Center of Economic Research at ETH Zurich; KU Leuven

Rune Midjord

Copenhagen Business School

Date Written: June 2018

Abstract

Many important decisions within public and private organizations are based on recommendations from expert committees and advisory boards. A notable example is the U.S. Food and Drug Administration's advisory committees, which make recommendations on new drug applications. Previously the voting procedure for these committees was sequential, however, due to concerns of herding and momentum effects the procedure was changed to simultaneous voting. Exploiting a novel dataset of more than ten thousand votes cast by experts in the FDA committees under both sequential and simultaneous voting, we estimate a structural model that allows us to measure the magnitude and importance of informational herding. We show that experts, voting on important scientific questions, are susceptible to herd behavior; on average 46% of the members take into consideration the sequence of previous votes when casting their vote, 17% of these voters actually herd i.e. change their vote from what they would have voted if ignoring the preceding votes.

Keywords: Herd Behavior, Expert Committees, Structural Estimation, FDA, Pharmaceuticals

JEL Classification: D72, D82, D83, D91, I10, I18

Suggested Citation

Newham, Melissa and Midjord, Rune, Herd Behavior in FDA Committees: A Structural Approach (June 2018). DIW Berlin Discussion Paper No. 1744, Available at SSRN: https://ssrn.com/abstract=3208645 or http://dx.doi.org/10.2139/ssrn.3208645

Melissa Newham (Contact Author)

ETH Zürich - CER-ETH - Center of Economic Research at ETH Zurich

Zürichbergstrasse 18
Zurich, 8092
Switzerland

KU Leuven ( email )

Oude Markt 13
Leuven, Vlaams-Brabant 3000
Belgium
3000 (Fax)

Rune Midjord

Copenhagen Business School ( email )

Solbjerg Plads 3
Frederiksberg C, DK - 2000
Denmark

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