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on Neuroeconomics |
| By: | James J. Heckman; Haihan Tian; Zijian Zhang; Jin Zhou |
| Abstract: | This paper discusses a fundamental problem in measuring the growth of knowledge and comparing the skills of people. New skills emerge that are not just more of the previously acquired skills. Psychometric convention forces these skills into arbitrarily constructed scales, which can severely distort measurement. To formally address this problem, we measure skills using a novel measurement scheme, estimate a stochastic learning process and reject the common scale assumption across levels for language and cognitive skills. Furthermore, we estimate dynamic complementarity without imposing arbitrary scales for skills. |
| JEL: | C18 J24 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34737 |
| By: | Emily Breza; Supreet Kaur |
| Abstract: | We outline a research agenda for behavioral development economics that seeks to understand the role of psychological channels in: (i) impeding individuals' ability to climb out of poverty, and (ii) shaping the organization of production, functioning of markets, and role of informal institutions in developing countries. We apply a missing markets lens to rationalize why tools, products and services that help individuals overcome their biases will be under-supplied by the market and why behavioral biases can have large impacts in steady state, even among highly experienced agents. We argue that these biases are especially likely to matter for the field of development because core features of poverty---proximity to subsistence, high volatility, market failures, weak formal institutions, and reliance on social ties---amplify the impact of psychological constraints. We organize our review around a core set of psychological constructs: self-control, cognitive constraints, self-beliefs, mental health, and social norms. For each construct, we highlight places where there is only a proof of concept versus evidence of meaningful impacts, and the resultant implications for future research. We also highlight where social capital can be deployed to mitigate the impacts of missing markets. The field research to date has only begun to scratch the surface in document how psychological mechanisms affect behavior and decision-making, and substantial scope remains for future work to determine whether these constraints play a first-order role in shaping poverty. |
| JEL: | D03 I3 O1 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34753 |
| By: | Pietro Bini; Lin William Cong; Xing Huang; Lawrence J. Jin |
| Abstract: | Do generative AI models, particularly large language models (LLMs), exhibit systematic behavioral biases in economic and financial decisions? If so, how can these biases be mitigated? Drawing on the cognitive psychology and experimental economics literatures, we conduct the most comprehensive set of experiments to date—originally designed to document human biases—on prominent LLM families across model versions and scales. We document systematic patterns in LLM behavior. In preference-based tasks, responses become more human-like as models become more advanced or larger, while in belief-based tasks, advanced large-scale models frequently generate rational responses. Prompting LLMs to make rational decisions reduces biases. |
| JEL: | D03 G02 G11 G4 G40 G41 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34745 |