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on Neuroeconomics |
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Issue of 2024‒07‒15
six papers chosen by |
| By: | Phil Schumm (University of Chicago) |
| Date: | 2023–02–23 |
| URL: | https://d.repec.org/n?u=RePEc:boc:biep23:06&r= |
| By: | Lin, Zhuoer; Ye, Justin; Allore, Heather; Gill, Thomas M.; Chen, Xi |
| Abstract: | Given the critical role of neurocognitive development in early life, this study assesses how racial differences in early-life circumstances are collectively and individually associated with racial disparities in late-life cognition. Leveraging uniquely rich information on life history from the U.S. Health and Retirement Study for non-Hispanic White (White) and non-Hispanic Black (Black) Americans 50 years or older, we employ the Blinder-Oaxaca method to decompose racial gaps in cognitive outcomes into early-life educational experiences, cohort, regional, financial, health, trauma, family relationship, demographic and genetic factors. Overall, differences in early-life circumstances are associated with 61.5% and 82.3% of the racial disparities in cognitive score and impairment, respectively. Early-life educational experience is associated with 35.2% of the disparities in cognitive score and 48.6% in cognitive impairment. Notably, school racial segregation (all segregated schooling before college) is associated with 28.8%-39.7% of the racial disparities in cognition. Policies that improve educational equity have the potential to reduce racial disparities in cognition into older ages. Clinicians may leverage early-life circumstances to promote the screening, prevention, and interventions of cognitive impairment more efficiently, thereby promoting health equity. |
| Keywords: | Early Life Circumstances, Life Course, School Segregation, Quality of Education, Racial Disparity, Cognition |
| JEL: | J15 I14 J13 J14 I20 H75 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1442&r= |
| By: | Adamecz, Anna (University College London); Shure, Nikki (University College London) |
| Abstract: | Recent evidence on the gender wage gap shows that it has remained stagnant for those with a university degree and is the largest at the top of the earnings distribution. Many studies have explored institutional factors that contribute to the gender wage gap, but there is little evidence on the role of non-cognitive traits, including overconfidence. This is surprising given its prominence in academic and popular literature. We use a measure of overconfidence captured in adolescence to explain the gender wage gap at age 42. Our results show that overconfidence explains approximately 5.5% of the unconditional gender wage gap. This is driven by women being more underconfident, not men being more overconfident. Furthermore, we find negative wage returns on being underconfident for both men and women. Most of this penalty works via occupational sorting, having lower pre-university educational outcomes, and being less likely to study high-return subjects at university. This has implications for the limitations of workplace-based interventions aimed at boosting women's confidence. |
| Keywords: | gender gaps, gender wage gap, overconfidence, underconfidence |
| JEL: | I24 I26 J24 |
| Date: | 2024–05 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17033&r= |
| By: | Joel P. Flynn; Karthik Sastry |
| Abstract: | We study how bounded rationality coevolves with the business cycle. We introduce a business-cycle model in which firms face a cognitive cost of making precise decisions. Theoretically, we characterize equilibrium with non-parametric, state-dependent stochastic choice. Firms have greater incentives to pay attention in downturns because they are owned by risk-averse households. Correspondingly, the model generates counter-cyclical attention, pro-cyclical mistakes, and an endogenous attention wedge that depresses aggregate productivity when attention is low. Empirically, we test the model's predictions using novel measures of firms' mistakes and attention. Quantitatively, attention cycles generate significant stochastic volatility of output growth and shock propagation asymmetries. |
| JEL: | E32 E44 E71 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:32553&r= |
| By: | Bernhard Kasberger; Simon Martin; Hans-Theo Normann; Tobias Werner |
| Abstract: | Algorithms play an increasingly important role in economic situations. These situations are often strategic, where the artificial intelligence may or may not be cooperative. We study the deter-minants and forms of algorithmic cooperation in the infinitely repeated prisoner’s dilemma. We run a sequence of computational experiments, accompanied by additional repeated prisoner’s dilemma games played by humans in the lab. We find that the same factors that increase human cooperation largely also determine the cooperation rates of algorithms. However, algorithms tend to play different strategies than humans. Algorithms cooperate less than humans when cooperation is very risky or not incentive-compatible. |
| Keywords: | artificial intelligence, cooperation, large language models, Q-learning, repeated prisoner’s dilemma |
| JEL: | C72 C73 C92 D83 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11124&r= |
| By: | Yeji Sung |
| Abstract: | This paper examines forecast biases through cognitive noise, moving beyond the conventional view that frictions emerge solely from using external data. By extending Sims’s (2003) imperfect attention model to include imperfect memory, I propose a framework where cognitive constraints impact both external and internal information use. This innovation reveals horizon-dependent forecast sensitivity: short-term forecasts adjust sluggishly while long-term forecasts may overreact. I explore the macroeconomic impact of this behavior, showing how long-term expectations, heavily influenced by current economic conditions, heighten inflation volatility. Moreover, structural estimation indicates that neglecting imperfect memory critically underestimates the informational challenges forecasters encounter. |
| Keywords: | information frictions; rational inattention; business cycle fluctuations |
| JEL: | D84 E32 E71 G41 |
| Date: | 2024–06–14 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedfwp:98433&r= |