This paper analyzes the joint association of emotions and knowledge in decision-making under uncertainty on a TV game show setting. The objective of this research is to understand the impact of emotions and knowledge on the preference for uncertainty (PU), which have mostly been investigated separately in Economics and Psychology until now. We examine the preference for uncertainty, proxied by a preference for gambling against a sure payoff, in 59 contestants in the TV game show “JOKER”. The data used contain individuals’ characteristics, as well as the decisions regarding the game, including the choice to carry on playing or accept a sure payoff, the level of knowledge of the topic, and the emotions experienced by the contestant. The methodology adopted includes a bivariate association between PU and knowledge and emotions, respectively. Additionally, we test a multivariate association using a Classification and Regression Tree (CART) method, which is suited for a complex nonlinear decision process that robustly mimics human decision-making. We find that preference for uncertainty increases when the contestants have a full domain or total absence of knowledge. Our results suggest, also, that emotions are the factor that only determines the preference for uncertainty when contestants have a restricted level of knowledge. Our results are robust across different proxies for knowledge and emotions and for different methodological thresholds. Results matter for investors, regulators, and policymakers, since it provides novel insights about the relative impact of knowledge and emotional status on risk behavior in general.
Link para artigo completo: https://www.mdpi.com/2227-9091/11/1/2
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