Prolonged Learning and Hasty Stopping: The Wald Problem with Ambiguity.

This paper studies sequential information acquisition by an ambiguity-averse decision-maker (DM), who decides how long to collect information before taking an irreversible action. The agent optimizes against the worst-case belief and updates prior by prior. We show that the consideration of ambiguit...

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Publicado en:American Economic Review Vol. 114; no. 2; pp. 426 - 462
Autores principales: Auster, Sarah, Che, Yeon-Koo, Mierendorff, Konrad
Formato: Artículo
Publicado: American Economic Association Feb2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Prolonged Learning and Hasty Stopping: The Wald Problem with Ambiguity.
      aug:
        au:
          Auster, Sarah
          Che, Yeon-Koo
          Mierendorff, Konrad
        affil:
          University of Bonn
          Columbia University
          University College London.
      su:
        Ambiguity
        Sequential learning
      sug:
        subj:
          Ambiguity
          Sequential learning
      ab: This paper studies sequential information acquisition by an ambiguity-averse decision-maker (DM), who decides how long to collect information before taking an irreversible action. The agent optimizes against the worst-case belief and updates prior by prior. We show that the consideration of ambiguity gives rise to rich dynamics: compared to the Bayesian DM, the DM here tends to experiment excessively when facing modest uncertainty and, to counteract it, may stop experimenting prematurely when facing high uncertainty. In the latter case, the DM's stopping rule is nonmonotonic in beliefs and features randomized stopping. (JEL C61, D81, D83, D91)
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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