We examine high-stakes strategic choice using more than 40 years of data from the American TV game show The Price Is Right. In every episode, contestants play the Showcase Showdown, a sequential game of perfect information for which the optimal strategy can be found through backward induction. We find that contestants systematically deviate from the subgame perfect Nash equilibrium. These departures from optimality are well explained by a modified agent quantal response model that allows for limited foresight. The results suggest that many contestants simplify the decision problem by adopting a myopic representation and optimize their chances of beating the next contestant only. In line with learning, the quality of contestants’ choices improves over the course of our sample period.

Loss aversion has been shown to be an important driver of people’s investment decisions. Encouraged by regulators, financial institutions are in search of ways to incorporate clients’ loss aversion in their risk classifications. The most critical obstacle appears to be the lack of a valid measurement method for loss aversion that can be straightforwardly incorporated into existing processes. This paper presents the results of two large-scale implementations of such a method within a risk-profiling application of an established financial institution. In total, we elicit loss aversion for 1,040 employees and 3,740 clients. We find that the observed distributions align with existing findings, and that loss aversion is largely independent of the risk-return preferences commonly used for investor classification. Furthermore, the correlations we observe between these two preferences and individuals’ background characteristics align with those observed in the literature. Loss aversion is strongly related to education—higher educated individuals being more loss averse—whereas risk aversion is strongly related to gender, age, and clients’ financial situation—women, more senior, and less wealthy participants being more risk averse. These findings support the conjecture that risk and loss aversion are complementary in capturing investor preferences.

Conditional cooperation is usually investigated in experiments where the choices of others are known. In many circumstances, however, there is uncertainty about others’ cooperativeness. Using a novel experimental protocol, we manipulate the perceived likelihood of cooperation in a Prisoner’s Dilemma, and whether such information is described unambiguously or learned through experience and thus ambiguous. We report on a ‘description-experience gap’ in which rare events appear to be more influential under experience than under description. This contrasts with earlier results from the individual choice literature. We show how stronger priors under social than individual uncertainty can account for this reversal.

We examine gender differences in willingness to compete, using data from a TV game show where the winner of an elimination competition in expectation wins hundreds of thousands of euros. At several stages of this competition, contestants face a choice between continuing to compete and opting out in exchange for a comparatively modest prize. When there is no strategic interaction, we observe the well-known pattern that women compete less than men, but this difference derives entirely from women avoiding competition against men. When there is strategic interaction and contestants should factor in the willingness to compete of their opponent, women again avoid competing against men. Men then seem to anticipate the lower competitiveness of female opponents, as evidenced by their greater propensity to compete against women. Ability differences are unlikely to explain these results. Our findings show that the gender difference in willingness to compete that is well-documented in the experimental economics literature also occurs in a quasi-experimental real-world setting with exceptionally high stakes, and underline the importance of the gender of competitors.