Arbeitspapier

Herd behavior in FDA committees: A structural approach

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.

Language
Englisch

Bibliographic citation
Series: DIW Discussion Papers ; No. 1744

Classification
Wirtschaft
Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
Asymmetric and Private Information; Mechanism Design
Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making‡
Health: General
Health: Government Policy; Regulation; Public Health
Subject
herd behavior
expert committees
structural estimation
FDA
pharmaceuticals

Event
Geistige Schöpfung
(who)
Newham, Melissa
Midjord, Rune
Event
Veröffentlichung
(who)
Deutsches Institut für Wirtschaftsforschung (DIW)
(where)
Berlin
(when)
2018

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Newham, Melissa
  • Midjord, Rune
  • Deutsches Institut für Wirtschaftsforschung (DIW)

Time of origin

  • 2018

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