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on Cognitive and Behavioural Economics |
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Issue of 2025–06–23
three papers chosen by Marco Novarese, Università degli Studi del Piemonte Orientale |
| By: | Jonathan Benchimol (Bank of Israel); Lahcen Bounader (World Bank); Mario Dotta (Sao Paulo School of Business Administration, Getulio Vargas Foundation) |
| Abstract: | Bounded rationality and limited attention significantly influence expectation formation and macroeconomic dynamics, yet empirical quantification of these behavioral phenomena remains challenging. This paper provides the first cross-country estimation of both micro- and macro-level attention parameters using a structurally identified behavioral New Keynesian model. Employing Bayesian techniques on harmonized data from 22 OECD countries (1996-2019) and ensuring robust parameter identification, we document substantial heterogeneity in behavioral inattention across countries. Our cognitive discounting estimates range from 0.76 to 0.98, with higher values indicating greater attention. We establish three key empirical regularities: (1) attention parameters are positively associated with macroeconomic volatility, supporting rational inattention theory; (2) surprise movements in key macroeconomic variables and online information-seeking behavior significantly influence attention allocation; and (3) institutional quality, particularly government effectiveness, is correlated with attention levels. These findings reveal that attention is both a behavioral and a structural phenomenon, responding to institutional factors and economic conditions. Our results provide an empirical foundation for calibrating country-specific models and yield important implications for the design and transmission of monetary policy under bounded rationality, showing that policy effectiveness may systematically vary with the macroeconomic environment. |
| Keywords: | Cognitive discounting, myopia, attention, Bayesian estimation, behavioral macroeconomics |
| JEL: | E |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:inf:wpaper:2025.8 |
| By: | Fedele, Alessandro (Free University of Bozen/Bolzano); Tonin, Mirco (Free University of Bozen/Bolzano); Wiesen, Daniel (University of Cologne) |
| Abstract: | The health sector requires skilled, altruistic, and motivated individuals to perform complex tasks for which ex-post incentives may prove ineffective. Understanding the determinants of self-selection into health professions is therefore critical. We investigate this issue relying on data from surveys and incentivized dictator games. We compare applicants to medical and healthcare schools in Italy and Austria with non-applicants from the same regions and age cohorts. Drawing on a wide range of individual characteristics, we employ machine learning techniques for variable selection. Our findings show that higher cognitive ability, greater altruism, and the personality trait of conscientiousness are positively associated with the likelihood of applying to medical or nursing school, while neuroticism is negatively associated. Additionally, individuals with a strong identification with societal goals and those with parents working as doctors are more likely to pursue medical education. These results provide evidence of capable, altruistic, and motivated individuals self-selecting into the health sector, a necessary condition for building a high-quality healthcare workforce. |
| Keywords: | personality traits, cognitive ability, altruism, health professions, self-selection, machine learning |
| JEL: | I1 J24 J4 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17941 |
| By: | Holden, Stein T. (Centre for Land Tenure Studies, Norwegian University of Life Sciences); Tione, Sarah (Centre for Land Tenure Studies, Norwegian University of Life Sciences); Tilahun, Mesfin (Centre for Land Tenure Studies, Norwegian University of Life Sciences); Katengeza, Samson (Centre for Land Tenure Studies, Norwegian University of Life Sciences) |
| Abstract: | Multiple Price Lists (MPLs) or Choice Lists (CLs) are widely used to elicit risk and time preferences, yet are prone to cognitive biases, particularly among respondents with limited numeracy skills. This paper compares three elicitation approaches; row-by-row from the top, from the bottom, and a Rapid Elicitation (RE) method using random starting points; in a field experiment with 906 rural Malawian farmers. With 20 MPLs per subject, we estimate starting point and order biases in switch points using nonparametric and parametric methods. Row-by-row elicitation from the top or bottom introduces significant bias in preference elicitation, with effect sizes of up to 0.4 standard deviations. In contrast, the RE approach yields significantly lower starting point bias (Cohen’s d of 0.08 or less). Order effects were present but smaller in magnitude. RE also reduced cognitive load and shortened response time. These findings underscore the importance of the elicitation method in experimental design, particularly in low-literacy settings. The RE method offers a more reliable and scalable tool for eliciting behavioral preferences in development economics. |
| Keywords: | Multiple Price Lists; Elicitation method; Starting point bias; Order bias; Field experiment; Malawi |
| JEL: | C93 D81 D91 |
| Date: | 2025–06–12 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:nlsclt:2025_003 |