Journal of Behavioral and Experimental Economics最新文献

Chen (2013) suggests a weak future time reference (FTR) language would encourage the speaker to undertake the investment through the distance effect (i.e., future appears closer with weak FTR) and the precision effect (i.e., weak FTR leads to less precise future reward timing which increases the expected future value due to the convex discounting function). This paper provides an analytic counterexample invalidating this conclusion. To be specific, Chen's argument assumes the speaker is risk neutral. We incorporate risk aversion into the consideration and show that both effects would magnify the return and the risk of the investment simultaneously. Consequently, an appropriate degree of risk aversion can overturn the Chen's conclusion. We show the waiting time to receive the return from the investment plays an important role. When the expected waiting time is short or the uncertainty of the waiting time is large, a weak FTR language is more likely to decrease the investment.

Individuals are at their most mental plasticity in their impressionable years (ages 18–25 years) forming long-term attitudes and behaviours essential to functioning in a society, such as trust. In this paper we ask how exposure to natural disasters within the impressionable years may affect the formation of trust by matching data from over 1,000 disaster occurrences with data from 88,670 individuals across 36 African nations. Exploiting the frequency of disaster exposure across the impressionable years, we show that disaster exposure has a negative and significant association with generalized trust. Additionally, we show that disasters experienced during the impressionable years have an impact on other dimensions of interpersonal and institutional trust. Our findings are robust to a battery of tests and add to the evidence base on the lasting impacts of natural disasters on individuals and societies.

Cryptocurrencies have found their way into the financial market as a serious alternative in recent years. In particular, Bitcoin is increasingly coming into focus. Currently, however, little is known why people invest in cryptocurrency or not. The present study seeks to shed light on individual difference variables potentially associated with these investment decisions. This includes personality traits, knowledge, and attitudes toward the social and political environment. The effective sample comprised 603 respondents who completed an online survey. Based on the proportion of their financial portfolio invested into Bitcoin, participants were divided into three groups: Non-Bitcoiners, Bitcoin Enthusiasts, and Bitcoin Maximalists. Group comparisons and prediction models indicated that Bitcoiners differed substantially from Non-Bitcoiners in justice-related attitudes as well as in specific knowledge about this cryptocurrency. By contrast, general political attitudes or reinforcement sensitivity did not differ much, and there was hardly a difference in basic dimensions of personality and general knowledge.

Is dishonesty more prevalent in interactions with chatbots compared to humans? Amidst the rise of artificial intelligence, this question holds significant economic implications. We conduct a novel experiment where participants report the outcome of a private, payout-relevant random draw to either a chatbot or a human counterpart, with varying degrees of signaled agency. We find that signaling agency increases honesty when interacting with humans but not with chatbots. Moreover, participants are consistently more honest with humans in the presence of agency cues. Our results suggest that social image concerns and perceived honesty norms play a more prominent role in human interactions. Surprisingly, standard online forms generate the same levels of honesty as human-to-human chat interactions. These findings offer valuable insights for designing effective communication and trust-building mechanisms in digital economies where human-chatbot interactions are increasingly prevalent.