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Identifying the Effects of Unjustified Confidence versus Overconfidence: Lessons Learned from Two Analytic Methods
Author(s) -
Parker Andrew M.,
Stone Eric R.
Publication year - 2014
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.1787
Subject(s) - overconfidence effect , set (abstract data type) , outcome (game theory) , psychology , low confidence , range (aeronautics) , confidence interval , cognitive psychology , social psychology , computer science , statistics , economics , mathematics , mathematical economics , materials science , composite material , programming language
One of the most common findings in behavioral decision research is that people have unrealistic beliefs about how much they know. However, demonstrating that misplaced confidence exists does not necessarily mean that there are costs to it. This paper contrasts two approaches toward answering whether misplaced confidence is good or bad, which we have labeled the overconfidence and unjustified confidence approach. We first consider conceptual and analytic issues distinguishing these approaches. Then, we provide findings from a set of simulations designed to determine when the approaches produce different conclusions across a range of possible confidence–knowledge–outcome relationships. Finally, we illustrate the main findings from the simulations with three empirical examples drawn from our own data. We conclude that the unjustified confidence approach is typically the preferred approach, both because it is appropriate for testing a larger set of psychological mechanisms as well as for methodological reasons. Copyright © 2013 John Wiley & Sons, Ltd.