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      <maintitle inherited="0" form="plain">Overweighting Private Information:&#13;
Three Measures, One Bias?</maintitle>
      <maintitle inherited="1" form="plain">Volume 4</maintitle>
      <maintitle inherited="2" form="plain">Jena Economic Research Papers</maintitle>
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      <keyword inherited="0" form="plain">overconﬁdence</keyword>
      <keyword inherited="0" form="plain">miscalibration</keyword>
      <keyword inherited="0" form="plain">signal perception</keyword>
      <keyword inherited="0" form="plain">cognitive bias</keyword>
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      <abstract inherited="0" form="plain">Overweighting private information is often used to explain various detrimental decisions. In behavioral economics and ﬁnance, it is usually modeled as a direct consequence of misperceiving signal reliability. This bias is typically dubbed overconﬁdence and linked to the judgment literature in psychology. Empirical tests of the models often fail to ﬁnd evidence for the predicted eﬀects of overconﬁdence. These studies assume, however, that a speciﬁc type of overconﬁdence, i.e., “miscalibration,” captures the underlying trait. We challenge this assumption and borrow the psychological methodology of single-cue probability learning to obtain a direct measure for overweighting private information. We ﬁnd that overweighting private information and measures of “miscalibration” are unrelated, indicating that diﬀerent kinds of misperceptions are at work. Thus, in order to test the theoretical predictions of the overconﬁdence literature in economics and ﬁnance, one cannot rely on the well-established “miscalibration” bias. We ﬁnd no gender diﬀerences in overconﬁdence for our measures except for one, where women are more overconﬁdent than men.</abstract>
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