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Testing for Overconfidence Statistically: A Moment Inequality Approach

Yanchun Jin () and Ryo Okui ()
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Yanchun Jin: Graduate School of Economics, Kyoto University

No 984, KIER Working Papers from Kyoto University, Institute of Economic Research

Abstract: We propose an econometric procedure to test for the presence of overconfidence using data collected by "ranking experiments." Our approach applies the techniques from the moment inequality literature. Although a ranking experiment is a typical way to collect data for analyzing overconfidence, Benoit and Dubra (2011) show that a ranking experiment may generate data that indicate overconfidence even if participants are purely rational Bayesian updaters. Instead, they provide a set of inequalities that are consistent with purely rational Bayesian updaters. We propose to apply the tests of moment inequalities developed by Romano et al. (2014) to test such a set of inequalities. Then, we examine the data from Svenson (1981) on driving safety. Our results indicate the presence of overconfidence on safety among the US subjects tested by Svenson. However, the other cases tested do not show evidence of overconfidence.

Keywords: overconfidence; ranking experiments; moment inequality; driving safety (search for similar items in EconPapers)
JEL-codes: C12 D03 D81 R41 (search for similar items in EconPapers)
Pages: 14pages
Date: 2018-01
New Economics Papers: this item is included in nep-ecm and nep-exp
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Working Paper: Testing for Overconfidence Statistically: A Moment Inequality Approach (2019) Downloads
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