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on Neuroeconomics |
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Issue of 2024‒01‒08
four papers chosen by |
| By: | Jacopo Bonan; Sergiu Burlacu; Arianna Galliera |
| Abstract: | We investigate the consistency of prosocial behaviors in response to changes in the in- stitutional setting of a lab-in-the-field experiment involving primary school students in El Salvador. Students play variants of the dictator game allowing the option to take and with relative unequal initial endowments. We exploit within-subject variation and find that children are sensitive to the enlargement of the choice-set, with a significant drop in the offers when the take option becomes available. Higher cognitive skills are systematically associated with higher levels of prosociality and lower sensitivity to changes in the choice set. However they do not correlate with responses to relative unequal initial endowments. Children, irrespective of their cognitive skills levels, care about equality and converge to a similar split of the final payoff, regardless of the initial inequality in the endowment, consistent with inequality aver- sion. The relationship between individual traits in childhood and the degree of consistency of prosocial behaviors appears to vary depending on the type of institutional change in the dictator game. |
| Keywords: | prosocial behavior, preference consistency, choice-set, cognitive skills, inequality aversion, El Salvador |
| JEL: | D91 C91 |
| Date: | 2022–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:csl:devewp:478&r=neu |
| By: | Germán Reyes |
| Abstract: | Cognitive endurance-the capacity to sustain performance on a cognitively-demanding task over time-is thought to be a crucial productivity determinant. However, a lack of data on this variable has limited researchers' ability to understand its role for success in college and the labor market. This paper uses college-admission-exam records from 15 million Brazilian high-school students to measure cognitive endurance based on changes in performance during the exam. By exploiting exogenous variation in the order of exam questions, I first show that students are significantly more likely to correctly answer a given question when it appears at the beginning of the test versus the end. Motivated by this fact, I develop a method to decompose test scores into fatigue-adjusted ability and cognitive endurance. I then link these measures to college and employment records to quantify the association between endurance and long-run outcomes. I find that cognitive endurance has a significant wage return. Controlling for fatigue-adjusted ability and other student characteristics, an increase of one standard deviation in endurance predicts a 5.4% wage increase. This wage return is equivalent to a third of the wage return to fatigue-adjusted ability. I also document positive associations between endurance and college attendance, college graduation, firm quality, and other outcomes. Finally, I show that, due to systematic differences in endurance among students, the exam design can impact income-based test-score gaps and the informational content of the exam. I discuss the implications of these findings for designing more informative cognitive assessments to select talent and more effective interventions to build human capital. |
| Keywords: | Cognitive Endurance; Returns to Education; Human Capital; Wage Level and Structure |
| JEL: | I26 J24 J31 M54 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2023_490&r=neu |
| By: | Goller, Daniel (University of Bern); Gschwendt, Christian (University of Bern); Wolter, Stefan C. (University of Bern) |
| Abstract: | In this paper, we show the causal influence of the launch of generative AI in the form of ChatGPT on the search behavior of young people for apprenticeship vacancies. There is a strong and long-lasting decline in the intensity of searches for vacancies, which suggests great uncertainty among the affected cohort. Analyses based on the classification of occupations according to tasks, type of cognitive requirements, and the expected risk of automation to date show significant differences in the extent to which specific occupations are affected. Occupations with a high proportion of cognitive tasks, with high demands on language skills, and those whose automation risk had previously been assessed by experts as lower are significantly more affected by the decline. However, no differences can be found with regard to the proportion of routine vs. non-routine tasks. |
| Keywords: | artificial intelligence, occupational choice, labor supply, technological change |
| JEL: | J24 O33 |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16638&r=neu |
| By: | Pedro H. Albuquerque (Aix Marseille Univ, CNRS, AMSE, Marseille, France and ACCELERATION & ADAPTATION, Aix-en-Provence, France); Sophie Albuquerque (Université du Québec à Trois-Rivières, Département de philosophie et des arts, Trois-Rivières, Canada and Aix Marseille Univ, SMPM, Marseille, France and ACCELERATION & ADAPTATION, Aix-en-Provence, France) |
| Abstract: | Aims: we propose a sociotechnical taxonomy for the analysis of socioeconomic disruptions caused by technological innovations. Methodology: a transdisciplinary principled approach is used to build the taxonomy through categorization and characterization of technologies using concepts and definitions originating from cybernetics, occupational science, and economics. The sociotechnical taxonomy is then used, with the help of logical propositions, to connect the characteristics of different categories of technologies to their socioeconomic effects, for example their externalities. Results: we offer concrete illustrations of concepts and uses, and an Industry 5.0 case study as an application of the taxonomy. We suggest that the taxonomy can inform the analysis of opportunities and risks related to technological disruptions, specially of those that result from the rise of cognitive machines. |
| Keywords: | sociotechnical taxonomy, technological disruptions, technological innovations, automatic, autonomous, physical technology, cognitive technology, skill-enhancing, skill-replacing, externalities, Industry 5.0, cognitive machines, artificial intelligence, occupational science |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:aim:wpaimx:2323&r=neu |