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UID:bc6ee4a90f879709eb17cc11d44a05ac
CATEGORIES:Seminars
CREATED:20170421T181510
SUMMARY:Lunch Seminar: Emanuele Tarantino - University of Mannheim
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:Learning When to Quit\nAbstract:\n We propose a model of research and devel
 opment as a process of experimentation in which researchers repeatedly revi
 se specifications of a project and update their beliefs about the project’s
  type. Only a good project whose type is learned by researchers can generat
 e value. Researchers abandon a project when the opportunity costs of contin
 uing exceed the expected benefits. We estimate the structural parameters of
  this dynamic optimization problem using a novel data set with information 
 on both successful and abandoned projects from the Internet Engineering Tas
 k Force (IETF), an organization that creates and maintains standards necess
 ary for the functioning of the internet. The structural approach allows us 
 to recover researchers’ unobserved beliefs and opportunity costs, and answe
 r questions about whether specific rules and institutions encourage “effici
 ent abandonment” of ongoing projects. We find that opportunity costs are de
 creasing over time and feedback and comments from the IETF community at lar
 ge increase the speed at which developers learn whether a project is worth 
 pursuing.\n
DTSTAMP:20260406T115012Z
DTSTART:20161116T130000Z
DTEND:20161116T140000Z
SEQUENCE:0
TRANSP:OPAQUE
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