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Bibliographic Details
Main Authors: Whitmeyer, Mark, Zhang, Kun
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2303.15723
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Table of Contents:
  • We revisit Popper's falsifiability criterion. A tester hires a potential expert to produce a theory, offering payments contingent on the observed performance of the theory. In our model, instead of knowing the true data-generating process, the expert knows the state-of-the-art belief over data-generating processes. A non-expert does not. We argue that if the expert can, moreover, acquire additional information to refine this knowledge, falsifiability does have the power to distinguish between experts and non-experts and to identify valuable theories, capitalizing on experts' ability to acquire and refine knowledge.