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on Cognitive and Behavioural Economics |
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Issue of 2022‒09‒26
four papers chosen by Marco Novarese Università degli Studi del Piemonte Orientale |
| By: | Thomas Buser (University of Amsterdam); Rafael Ahlskog (Uppsala University); Magnus Johannesson (tockholm School of Economics); Sven Oskarsson (Uppsala University) |
| Abstract: | We use a novel approach to explore how people sort into different careers based on their personality skills. We link genetic data from individuals in the Swedish Twin Registry to government register data, making use of new polygenic indices that capture the genetic predispositions of individuals towards a range of relevant cognitive skills, personality traits, and economic preferences. We first present a detailed mapping of these genetic tendencies by occupation and study major. We show that – conditional on their socio-economic background – people who sort into different study majors and occupations differ significantly in their genetic predispositions. We then take advantage of random genetic variation between siblings to show that this sorting is at least partially due to a causal effect of genetic tendencies on career choices. Our results shed new light on the determinants of some of the most impactful decisions people must make in their lives. |
| Keywords: | personality traits, cognitive skills, behavioral genetics, labor markets, education |
| JEL: | D91 J24 |
| Date: | 2022–09–07 |
| URL: | http://d.repec.org/n?u=RePEc:tin:wpaper:20220062&r= |
| By: | John J. Conlon; Malavika Mani; Gautam Rao; Matthew W. Ridley; Frank Schilbach |
| Abstract: | We provide evidence of a powerful barrier to social learning: people are much less sensitive to information others discover compared to equally-relevant information they discover themselves. In a series of incentivized lab experiments, we ask participants to guess the color composition of balls in an urn after drawing balls with replacement. Participants' guesses are substantially less sensitive to draws made by another player compared to draws made themselves. This result holds when others' signals must be learned through discussion, when they are perfectly communicated by the experimenter, and even when participants see their teammate drawing balls from the urn with their own eyes. We find a crucial role for taking some action to generate one's `own' information, and rule out distrust, confusion, errors in probabilistic thinking, up-front inattention and imperfect recall as channels. |
| JEL: | D03 D83 D9 D91 |
| Date: | 2022–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:30378&r= |
| By: | Richard Freund (University of Oxford); Marta Favara (University of Oxford); Catherine Porter (Lancaster University, University of Oxford); Jere Behrman (University of Pennsylvania) |
| Abstract: | Many low- and middle-income countries have introduced Public Works Programmes (PWPs) to fight poverty. PWPs provide temporary cash-for-work opportunities to boost poor households’ incomes and to provide better infrastructure to local communities. While PWPs do not target children directly, the increased demand for adult labour may affect children’s development through increasing households’ incomes and changing household members’ time uses. This paper expands on a multidimensional literature showing the relationship between early life circumstances and learning outcomes and provides the first evidence that children from families who benefit from PWPs show increased foundational cognitive skills (FCS). We focus on four child FCS: inhibitory control, working memory, long-term memory, and implicit learning. Our results, based on unique tablet-based data collected as part of a 20-year longitudinal survey, show positive associations of family participation in the Productive Safety Net Programme (PSNP) in Ethiopia during childhood on long-term memory and implicit learning, with weaker evidence for working memory. These associations appear to be strongest for children whose households were still PSNP participants in the year of data collection. We find suggestive evidence that, the association with implicit learning may be operating through children’s time reallocation away from unpaid labour responsibilities, while the association with long-term memory may be due to the programme’s success in remediating nutritional deficits caused by early life rainfall shocks. Our results suggest that policy interventions such as PWPs may be able to mitigate the effects of early poverty on cognitive skills formation and thereby improve children’s potential future outcomes. |
| Keywords: | foundational cognitive skills; Ethiopia; public works programmes; PSNP; skills development |
| JEL: | J24 I2 I1 |
| Date: | 2022–09–09 |
| URL: | http://d.repec.org/n?u=RePEc:pen:papers:22-022&r= |
| By: | Wolfram Barfuss; Janusz Meylahn |
| Abstract: | In this work, we ask for and answer what makes classical reinforcement learning cooperative. Cooperating in social dilemma situations is vital for animals, humans, and machines. While evolutionary theory revealed a range of mechanisms promoting cooperation, the conditions under which agents learn to cooperate are contested. Here, we demonstrate which and how individual elements of the multi-agent learning setting lead to cooperation. Specifically, we consider the widely used temporal-difference reinforcement learning algorithm with epsilon-greedy exploration in the classic environment of an iterated Prisoner's dilemma with one-period memory. Each of the two learning agents learns a strategy that conditions the following action choices on both agents' action choices of the last round. We find that next to a high caring for future rewards, a low exploration rate, and a small learning rate, it is primarily intrinsic stochastic fluctuations of the reinforcement learning process which double the final rate of cooperation to up to 80\%. Thus, inherent noise is not a necessary evil of the iterative learning process. It is a critical asset for the learning of cooperation. However, we also point out the trade-off between a high likelihood of cooperative behavior and achieving this in a reasonable amount of time. Our findings are relevant for purposefully designing cooperative algorithms and regulating undesired collusive effects. |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2209.01013&r= |