What You See is All There is.

News reports and communication are inherently constrained by space, time, and attention. As a result, news sources often condition the decision of whether to share a piece of information on the similarity between the signal and the prior belief of the audience, which generates a sample selection pro...

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Publicado en:Quarterly Journal of Economics Vol. 135; no. 3; pp. 1363 - 1399
Autor principal: Enke, Benjamin
Formato: Artículo
Publicado: Oxford University Press / USA Aug2020
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2020
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      pub: Oxford University Press / USA
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        atl: What You See is All There is.
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        au: Enke, Benjamin
        affil: Harvard University and National Bureau of Economic Research
      su:
        Information sharing
        Signals & signaling
        Statistical errors
        Statistical decision making
        Computational complexity
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        subj:
          Information sharing
          Signals & signaling
          Statistical errors
          Statistical decision making
          Computational complexity
      ab: News reports and communication are inherently constrained by space, time, and attention. As a result, news sources often condition the decision of whether to share a piece of information on the similarity between the signal and the prior belief of the audience, which generates a sample selection problem. This article experimentally studies how people form beliefs in these contexts, in particular the mechanisms behind errors in statistical reasoning. I document that a substantial fraction of experimental participants follows a simple "what you see is all there is" heuristic, according to which participants exclusively consider information that is right in front of them, and directly use the sample mean to estimate the population mean. A series of treatments aimed at identifying mechanisms suggests that for many participants, unobserved signals do not even come to mind. I provide causal evidence that the frequency of such incorrect mental models is a function of the computational complexity of the decision problem. These results point to the context dependence of what comes to mind and the resulting errors in belief updating.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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