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Overconfidence in Business, Economics, Finance, and Psychology: How much of a Problem is it?
Krajč, Marian ; Ortmann, Andreas (vedoucí práce) ; Hoelzl, Erik (oponent) ; Fellner, Gerlinde (oponent)
Marian Krajc Abstract The first chapter offers a theoretical model that suggests an alternative explanation to the so- called unskilled-and-unaware problem - the unskilled overestimate their skills while the skilled underestimate (but less than the unskilled). The unskilled-and-unaware problem was experimentally identified about a decade ago and numerous authors have elaborated on this problem since. We propose that the alleged unskilled-and-unaware problem, rather than being one of biased judgments, is a signal extraction problem that differs for the skilled and the unskilled. The model is based on two assumptions. First, we assume that skills are distributed according to a J-distribution, which can be regarded as an approximation of the very right tail of the IQ distribution. This assumption is reasonable given the typical subject pool used in the experimental studies of overconfidence - students from prominent US universities. Second, we assume an error term in own-ability perception, which is a common assumption in psychology models. Our simple model generates, by means of analytical computations, patterns similar to those identified in the previous experimental literature. We also discuss conditions under which the unskilled-and-unaware problem should disappear. The second chapter reports the results...
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Overconfidence in Business, Economics, Finance, and Psychology: How much of a Problem is it?
Krajč, Marian ; Ortmann, Andreas (vedoucí práce) ; Hoelzl, Erik (oponent) ; Fellner, Gerlinde (oponent)
Marian Krajc Abstract The first chapter offers a theoretical model that suggests an alternative explanation to the so- called unskilled-and-unaware problem - the unskilled overestimate their skills while the skilled underestimate (but less than the unskilled). The unskilled-and-unaware problem was experimentally identified about a decade ago and numerous authors have elaborated on this problem since. We propose that the alleged unskilled-and-unaware problem, rather than being one of biased judgments, is a signal extraction problem that differs for the skilled and the unskilled. The model is based on two assumptions. First, we assume that skills are distributed according to a J-distribution, which can be regarded as an approximation of the very right tail of the IQ distribution. This assumption is reasonable given the typical subject pool used in the experimental studies of overconfidence - students from prominent US universities. Second, we assume an error term in own-ability perception, which is a common assumption in psychology models. Our simple model generates, by means of analytical computations, patterns similar to those identified in the previous experimental literature. We also discuss conditions under which the unskilled-and-unaware problem should disappear. The second chapter reports the results...
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