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on Cognitive and Behavioural Economics |
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Issue of 2026–05–18
four papers chosen by Marco Novarese, Università degli Studi del Piemonte Orientale |
| By: | Cobb-Clark, Deborah (University of Sydney); Silva Goncalves, Juliana (University of Sydney); Tymula, Agnieszka (University of Sydney); Wang, Xueting (RMIT) |
| Abstract: | Self-control, attention, and impulsivity jointly support goal-directed behavior yet are often examined in isolation with heterogeneous measures. We integrate validated self-reported scales with a hybrid, incentivized behavioral task that synthesizes two canonical experimental designs and adds novel extensions to measure these constructs in a typical work context. Using data from a preregistered four-session online study (N = 443 adults), we characterize the cross-relationships and the relationships between different measures of self-control, attention, and impulsivity and evaluate their contributions to effort allocation over time. More broadly, the study advances an emerging research program that leverages laboratory settings with well-structured economic incentives to examine the role of personality traits and cognitive limitations in economic decision making. |
| Keywords: | self-control, impulsivity, attention, measurement |
| JEL: | D81 D83 D91 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18646 |
| By: | yoshida, ken |
| Abstract: | This study examines whether impatience measured by hypothetical monetary intertemporal choices is reflected in an observable consumption behavior, namely candy consumption. Participants first answered a series of hypothetical intertemporal-choice questions involving both monetary gains and monetary payments and then completed a candy-consumption task. Realized behavior was classified from the reported completion status at the end of the task as licking the candy to the end, biting it before finishing, or being censored after 20 minutes, while completion time was recorded from QR-code scans at the beginning and end of the task. Using a strict sample restricted to respondents who passed consistency and attention checks, we find suggestive but meaningful evidence that participants who bit the candy displayed greater impatience in monetary choices than those who licked it to the end. The average difference across all questions is modest, and the sharper contrast in some payment questions should be interpreted as exploratory. Participants who bit the candy also completed the task significantly faster. In addition, self-reported usual eating style is moderately consistent with realized behavior in the task. These findings suggest that candy-consumption behavior may serve as a behavioral indicator broadly consistent with impatience, while also indicating that it should not be interpreted as a structural estimate of an individual's discount rate. |
| Keywords: | Time preference; intertemporal choice; impatience; candy consumption; experimental economics |
| JEL: | C91 D91 |
| Date: | 2026–03–31 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:128522 |
| By: | De Grauwe, Paul; Ji, Yuemei |
| Abstract: | We argue that the mainstream macroeconomic models (DSGE-models) are models that operate like “watches”, while behavioural macroeconomic models operate like “clouds”. We define what this means. We contrast the predic ons these two simple canonical macroeconomic models make about the transmission of supply shocks. We find that in the cloud model the fog surrounding the transmission of these shocks is much denser than in the watch model, making it difficult to make condi onal forecasts. |
| Keywords: | behavioural macroeconomics; supply shock; cloud model; watch model; heuristics |
| JEL: | D84 D91 E17 E32 |
| Date: | 2026–04–25 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:137712 |
| By: | Abdel Haq, Omar (Harvard Business School); Chandra, Amitabh (Harvard Business School and Harvard Kennedy School); Jagelka, Tomáš (University of Bonn); Luttmer, Erzo (Dartmouth College); Schwartzstein, Joshua (Harvard Business School) |
| Abstract: | Large Language Models (LLMs) are trained on a prodigious corpus of human writing and may reveal human preferences over characteristics of life courses, such as income, longevity, and working conditions. We present OpenAI's GPT-5.4 and a broadly representative sample of Americans with pairs of life stories and ask them to choose the life they would prefer for themselves. A person's choice is better predicted by the LLM's choice than by another person’s choice over the same stories, and LLM valuations of several life attributes are similar to those derived from human responses. Our results suggest that LLM responses offer a scalable and cost-effective complement to existing methods for studying human preferences. |
| Keywords: | generative AI, preference estimation methods, choice experiments, survey validation |
| JEL: | D0 H0 I0 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18634 |