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on Cognitive and Behavioural Economics |
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Issue of 2024‒09‒09
four papers chosen by Marco Novarese, Università degli Studi del Piemonte Orientale |
| By: | Schütze, Tobias; Schmidt, Ulrich; Spitzer, Carsten; Wichardt, Philipp C. |
| Abstract: | Financial decision making requires a sound handling of chance events. However, various studies have suggested that people are prone to illusion of control, i.e., the belief that prospects of a chancy event are better if they are involved in the randomisation process. This paper reports results from an experiment (N=420) suggesting that psychological characteristics moderate risk-taking behaviour under such circumstances. For example, we find that subjects high in sensation seeking buy more tickets of a risky lottery if they determine the winning numbers themselves and the random event lies in the future. The findings suggest that “illusion of control” effects are at least partly driven by underlying (idiosyncratic) emotions/preferences rather than an actual belief in control. Regarding applications, the results emphasise the importance of individual characteristics for the behaviour of decision makers in a financial context. |
| Keywords: | illusion of control, financial decision making, investment decisions, risk |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:ifwkie:300919 |
| By: | Uri Gneezy; Yoram Halevy; Brian Hall; Theo Offerman; Jeroen van de Ven |
| Abstract: | Researchers in behavioral and experimental economics often argue that only incentive-compatible mechanisms can elicit effort and truthful responses from participants. Others argue that participants make less-biased decisions when the stakes are sufficiently high. Are these claims correct? We investigate the change in behavior as incentives are scaled up in the Allais paradox, and document an increase , not decrease, in deviations from expected utility with higher stakes. We also find that if one needs to approximate participants’ behavior in real high-stakes Allais (which are often too expensive to conduct), it is better to use hypothetically high stakes than real low stakes, as is typically the practice today. |
| Keywords: | high stakes, real and hypothetical incentives, Allais paradox, Expected Utility |
| JEL: | C91 D81 |
| Date: | 2024–08–17 |
| URL: | https://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-783 |
| By: | Soane, Emma |
| Abstract: | The capability to vary risk-taking is an important aspect of performance in organizations where behavioral adjustments are required to suit changing objectives. Incentive schemes are one way to influence risk-taking. Yet, evidence indicates incentives do not have their intended effects and may encourage excessive risk-taking. To examine this issue, we draw on compensation activation theory that proposes individual motives are activated by specific features of compensation schemes and expressed in behaviors. We extend compensation activation theory by focusing on (1) responses to a sequence of tasks designed to activate risk-taking and (2) the effects of incentive schemes on these relationships. We conducted a laboratory experiment with 173 participants who were allocated randomly to one of three bonus schemes. The linear scheme has a linear relationship between returns from risk-taking and rewards. The bonus cap scheme operates similarly up to a point where no further rewards are paid. The outcome-adjusted scheme, with a two-year hypothetical time frame, requires realized gains for the first year of investment and no losses in next year. Results support our hypotheses that these incentive schemes have differential effects on the strength and direction of relationships between risk-taking across a sequence of tasks. The linear scheme strengthens the relationships between risk-taking across sequential tasks. Conversely, the bonus cap scheme weakens the relationships between risk-taking across sequential tasks. The outcome-adjusted scheme creates variability by decreasing risk-taking when the connections between risk-taking and rewards are less salient and increasing risk-taking when connections between risk-taking and rewards are more salient. We contribute to the literature concerning compensation activation and incentives by deepening our understanding of the roles played by tasks and incentives in activation processes and by explaining the variability of risk-taking in terms of changes in connections between behavior and rewards. |
| Keywords: | risk-taking; activation; incentives; variability; Taylor & Francis deal |
| JEL: | G32 J50 |
| Date: | 2024–08–08 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:124339 |
| By: | Brian Jabarian |
| Abstract: | In this article, we explore the transformative potential of integrating generative AI, particularly Large Language Models (LLMs), into behavioral and experimental economics to enhance internal validity. By leveraging AI tools, researchers can improve adherence to key exclusion restrictions and in particular ensure the internal validity measures of mental models, which often require human intervention in the incentive mechanism. We present a case study demonstrating how LLMs can enhance experimental design, participant engagement, and the validity of measuring mental models. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.12032 |