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on Microeconomic European Issues |
| By: | Michael Doersam; Henrika Langen |
| Abstract: | To enhance the attractiveness of vocational education and training and to secure an adequate supply of skilled labour, the German government introduced a statutory minimum apprenticeship wage. Since January 1, 2020, apprentices who start their training have been entitled to a minimum wage that increases annually. Using administrative register data on apprenticeship contracts, we estimate the causal effect of this legislation on apprentice employment. Exploiting regional and occupational variation in the share of apprenticeships paid at the minimum wage, we apply standard difference-in-differences, triple-difference, and synthetic difference-in-differences models. Our results indicate that the minimum apprenticeship wage increased the number of apprenticeship contracts while reducing the contract termination rate in low-wage occupations. We also find considerable heterogeneity across occupations, which may be best explained by differences in exposure to skilled labour shortages and changes in apprentices' educational attainment. |
| Keywords: | minimum wage, apprenticeship market, employment effects, difference-in-differences, triple difference, synthetic difference-in-differences |
| JEL: | J08 J24 J38 C23 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:iso:educat:0250 |
| By: | McGuinness, Seamus (Economic and Social Research Institute, Dublin); Kelly, Lorcan (Economic and Social Research Institute, Dublin); Devlin, Anne (Economic and Social Research Institute, Dublin); Whelan, Adele (ESRI, Dublin) |
| Abstract: | This paper examines the earnings and job satisfaction of Vocational Education and Training (VET) graduates in the European Union (EU) using two definitions of vocational education: a self-reported definition and a more specific definition that incorporates work-based learning. The incidence of third-level VET falls from 74% to 29% under the stricter definition. Across the EU, the returns to vocational and academic qualifications are comparable for upper secondary, post-secondary and tertiary qualifications. Earnings premia vary between countries, with VET generating higher returns in just under one-third of all EU-28 members. Additionally, third level VET graduates enjoy higher levels of job satisfaction. |
| Keywords: | work-based learning, european countries, job satisfaction, earnings, vocational education, on-the-job training |
| JEL: | I21 I26 J24 J30 J31 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18134 |
| By: | Salla Kalin (Labour Institute for Economic Research Labore); Tomi Kyyrä (VATT Institute for Economic Research); Tuomas Matikka (VATT Institute for Economic Research) |
| Abstract: | We use detailed, population-wide data from Finland to provide evidence of the impact of earnings disregard policies on part-time work during unemployment spells.The share of part-time workers among benefit recipients increased sharply from 10% to 18% over a few years after the implementation of earnings disregards in unemployment beneifts and housing allowances, which allowed individuals to earn up to 300 euros per month without reductions in their benefits. Using variation in the impact of the reforms on incentives between individuals eligible for different types of benefits, we estimate a 21–30% increase in participation in part-time work due to the implementation of earnings disregards. On average, we find no economically sizable effects of the earnings disregards on future full-time employment or the likelihood of leaving unemployment benefits, but find moderate positive employment effects among those unemployed individuals who are more attached to the labor market. |
| Keywords: | labor supply; social benefits; part-time work; earnings disregards |
| JEL: | H24 J21 J22 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:fit:wpaper:36 |
| By: | De Paola, Maria (University of Calabria); Nistico, Roberto (University of Naples Federico II); Scoppa, Vincenzo (University of Calabria) |
| Abstract: | This paper examines the impact of co-workers’ fertility on individual fertility decisions. Using matched employer-employee data from Italian social security records (2016–2020), we estimate how fertility among co-workers of similar age and occupation affects the individual likelihood of having a child. We exploit variation introduced by the 2015 Jobs Act, which reduced fertility among workers hired under weaker employment protection. Focusing on workers hired before the reform and using the share of colleagues hired after the reform as an instrument for peer fertility, we find that a one-percentage-point increase in peer fertility raises individual fertility by 0.4 percentage points (a 10% increase). Heterogeneity analysis suggests that while social influence and social norms are key mechanisms, information sharing and career concerns, particularly among women, tend to moderate the response. Our findings highlight how changes in employment protection may have unintended fertility spillovers through workplace social interactions. |
| Keywords: | social learning, fertility, EPL, career concerns, social norms, workplace |
| JEL: | C3 J13 J65 J41 M51 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18127 |
| By: | Erwan Gautier; Frédérique Savignac; Olivier Coibion |
| Abstract: | Using a new survey of French firms’ inflation expectations that predates the inflation spike, we document i) evidence on the anchoring of inflation expectations during the inflation surge, and ii) the relevance of inflation expectations for firms’ decisions. First, we show that inflation expectations under-responded to the initial surge but then persistently overshot actual inflation dynamics. As inflation rose, firms initially perceived inflation to be less persistent than in previous years, an effect that dissipated over time. Second, we find that inflation expectations correlate with firms’ wage and price decisions. One-year expectations matter more than long-term expectations. During the inflation surge, wage and price decisions became increasingly disconnected from inflation expectations. This suggests that the scope for wage-price spirals is likely more limited than one might have expected from the surge in inflation and inflation expectations. |
| Keywords: | Lifetime Earnings, Inequality, Gender Earnings Gaps |
| JEL: | E2 E3 E4 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:bfr:banfra:995 |
| By: | Carnicelli, Lauro (LABORE Labour Institute for Economic Research); Morando, Greta (University of Sheffield) |
| Abstract: | We study how maternal preferences interact with education to shape the motherhood penalty. Using rich Finnish registry data and the quasi-random gender of the firstborn child, we show that mothers across education groups display a mild preference for daughters, reflected in their fertility and parental leave choices. Yet this shared preference translates into divergent long-run outcomes. Ten years after birth, highly educated mothers face a 10\% larger earnings penalty if their firstborn is a son, whereas less educated mothers experience slightly higher penalties with daughters. These differences stem from distinct labor market adjustments: less educated mothers are marginally more likely to exit employment after having a daughter, while highly educated mothers with daughters disproportionately move into public-sector jobs, which offer a relative wage premium. Our findings demonstrate that similar parental preferences can generate contrasting long-term earnings dynamics across education groups, highlighting the role of maternal preferences and labor market sorting in shaping the motherhood penalty. |
| Keywords: | parental preferences, gender wage gap, child penalty, occupational sorting |
| JEL: | J13 J16 J24 J42 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18140 |
| By: | Fernández Guerrico, Sofía (University of Konstanz); Tojerow, Ilan (Université Libre de Bruxelles) |
| Abstract: | We examine the causal impact of high-speed internet on adult mental health using administrative data from Belgium. We exploit predetermined telecommunications infrastructure and broadband technology's distance-sensitive nature for identification. Our difference-in-differences estimates show internet increased mental health-related disability insurance claims by 0.054 percentage points—a 31% increase relative to the control group. These findings are supported by increased antidepressant use at the municipality level. Results point to a work-related mechanism: effects are concentrated among knowledge workers and those in high work-from-home potential jobs. Time-use data show a substitution from leisure to work and less social interaction on weekends. |
| Keywords: | disability insurance, internet, mental health, employment |
| JEL: | H55 I1 J2 L86 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18130 |
| By: | Meekes, Jordy (Leiden University); van Lent, Max (Leiden University) |
| Abstract: | Child penalties in paid working hours are persistent and widen the gender earnings gap. This paper studies an important mechanism through which working hours are affected: peer effects. Using three unique layers of peer networks: neighbours, colleagues, and family, we analyse peer effects on individuals’ paid working hours. We analyse peer effects up to six years after childbirth on individuals who become first-time parents in the period 2014-2018, using Dutch full-population administrative monthly microdata up to September 2024. The identification strategy exploits exogenous variation in peers’ working hours through peers-of-peers. Our research is the first to establish long-term statistically significant peer effects on fathers’ working hours. The results indicate positive peer effects on fathers and mothers, where colleague peers are more important than neighbour peers and family peers. |
| Keywords: | peers-of-peers, paid working hours, colleague peers, neighbour peers, family peers |
| JEL: | J22 D85 C26 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18148 |
| By: | Michele Cantarella; Maria Cristina Maurizio; Francesco Serti |
| Abstract: | This paper evaluates the short and medium-term effectiveness of hiring incentives aimed at promoting the permanent conversion of temporary contracts through social contribution exemptions. Using rich administrative data from Tuscany, providing detailed employment histories, we use difference in differences and regression discontinuity designs to exploit a unique change in eligibility criteria in 2018. We find that the incentives immediately increased the probability of conversion, with no evidence of substitution against non-eligible cohorts. However, these positive effects were short-lived and appear to reflect anticipated conversions, as we find null longer-term effects on permanent hirings. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.10193 |
| By: | Marion Mauchaussée (LITL - Laboratoire Interdisciplinaire des transitions de Lille - UCL FGES - Université Catholique de Lille - Faculté de gestion, économie et sciences - ICL - Institut Catholique de Lille - UCL - Université catholique de Lille - JUNIA - JUNIA - UCL - Université catholique de Lille, CEET - Centre d'études de l'emploi et du travail - Cnam - Conservatoire National des Arts et Métiers [Cnam] - M.E.N.E.S.R. - Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche - Ministère du Travail, de l'Emploi et de la Santé) |
| Abstract: | This article proposes to analyze the profiles of civil servants and temporary contract workers in the public service through the prism of labour market segmentation. Based on the 2007 to 2018 employment surveys, we show that the three public service sectors (State, Hospital, Local government) can be considered as internal labour markets and are differentiated by their socio-demographic characteristics. We then show that the profiles of temporary employees in the three public service sectors have points in common (individual characteristics that are less favorable than those of civil servants), but also differentiating factors that may or not may enable them to access their internal labour market (in terms of gender or qualifications). |
| Abstract: | Cet article se propose d'analyser les profils de fonctionnaires et d'agents en contrat temporaire de la fonction publique au prisme de la segmentation du marché du travail. À partir des enquêtes Emploi de 2007 à 2018, nous montrons que les trois fonctions publiques peuvent être considérées comme des marchés internes et se différencient par leurs caractéristiques sociodémographiques. Nous montrons ensuite que les profils des agents en emploi temporaire des trois fonctions publiques ont des points communs (des caractéristiques individuelles moins favorables que celles des fonctionnaires), mais également des éléments de différenciation leur permettant ou non d'accéder à leur marché interne de rattachement (en termes de genre ou de diplôme). |
| Keywords: | Fonctionnaires, Fonctions publiques, Segmentation du marché du travail, Écart expérimental, Temporary employees, Civil servants, Public services, Labour market segmentation, Experimental gap, Emplois temporaires |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05214387 |
| By: | McGuinness, Seamus (Economic and Social Research Institute, Dublin); Staffa, Elisa (Economic and Social Research Institute, Dublin); Lee, Sangwoo (University of Warwick); Kelly, Lorcan (Economic and Social Research Institute, Dublin); Redmond, Paul (ESRI, Dublin) |
| Abstract: | Skill shortages are a type of skill mismatch whereby employers are unable to fill existing vacancies due to a lack of suitably qualified and/or skilled candidates. Despite representing a significant concern for policy makers, both at national and EU level, the literature on skill shortages is hugely underdeveloped. There is a lack of clarity and consistency on how skill shortages are defined and measured. In this study, using data from the 2021 European Skills and Jobs Survey combined with Lightcast job vacancy data, we attempt to bridge the methodological gap by developing a measure of potential skill shortages that can be readily replicated across countries over time. We estimate that approximately 2% of job vacancies in the European Union are likely to experience skill shortages. However, there is substantial variation across occupations, ranging from 5.1% for ICT professionals to approximately zero in more elementary occupations. There is also substantial variation in the estimated incidences of potential skill shortages at member state level. Our analysis also shows that occupations that are most likely to experience skill shortages also tend to experience relatively high rates of changes in skill requirements over time. |
| Keywords: | measurement, skill shortages, policy |
| JEL: | J6 J20 J22 J23 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18133 |
| By: | Domenech Palacios, Mar |
| Abstract: | This paper examines whether firm-specific cyclical and idiosyncratic risk profiles influence corporate bond spreads and the transmission of monetary policy. I extend the standard excess bond premium (EBP) framework of Gilchrist & Zakrajšek (2012) to allow investors’ required compensation for default risk to vary with firm-level risks. Incorporating these effects reveals that a significantly larger share of a monetary policy shock’s impact on credit spreads is driven by changes in default risk compensation (as opposed to the EBP). In particular, for firms with more cyclical risk, up to one-fourth of the additional spread widening following a contractionary monetary policy shock reflects higher expected default compensation, substantially more than implied by the traditional EBP. By contrast, firms with high idiosyncratic risk show no strong differential response to monetary policy shocks relative to other firms. JEL Classification: D22, E43, E44, E52, G12 |
| Keywords: | cyclicality, excess bond premium, monetary policy, risk, sentiment |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:ecb:ecbwps:20253118 |
| By: | Dimitra Spyropoulou (Charles University Environment Centre, Charles University, Prague, Czech Republic); Milan Scasny (Charles University Environment Centre, Charles University, Prague, Czech Republic) |
| Abstract: | This study investigates consumer preferences for passenger battery electric vehicles and their joint adoption with a residential solar photovoltaic system in Greece, where electric vehicle uptake remains low. Using discrete choice experiments, we analyse the preferences of 891 potential car buyers for conventional, hybrid, plug-in hybrid, and battery electric vehicles, comparing scenarios where a battery electric vehicle is offered alone or as a bundle with subsidised home solar photovoltaics. Results indicate that offering a technology bundle shifts consumer preferences, with the most notable effect being a decrease in the likelihood of choosing conventional vehicles. The willingness to pay for the bundle also exceeds that for battery electric vehicles, suggesting that installing PV systems adds value to BEVs. Key factors influencing adoption include purchase price, operating costs, wallbox subsidies, and normal charging time, while driving range and fast-mode charging do not seem to significantly affect consumer preferences. However, the analysis reveals substantial unobserved preference heterogeneity across all attributes. Robustness checks support the validity of our results. These findings suggest that integrated green technology bundles can accelerate low-carbon transport adoption, supporting the EU decarbonisation targets through complementary renewable energy and electromobility solutions. |
| Keywords: | Battery Electric Vehicles; Photovoltaics; Technology bundle; Consumer choices; Discrete Choice Experiments; Willingness to Pay |
| JEL: | C15 D12 D90 Q42 Q55 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:fau:wpaper:wp2025_16 |
| By: | Francesca Barigozzi; Natalia Montinari; Giovanni Righetto; Alessandro Tampieri |
| Abstract: | In most countries, women systematically outperform men in academic achievement across fields of study. Yet within a year of graduation, they earn less, face lower employment rates, and are more likely to work part-time. If human capital were the sole determinant of pay, this pattern would be difficult to reconcile. We address this puzzle by extending the statistical discrimination framework ‘a la Phelps (1972) to include not only human capital but also additional components of productivity, such as IT skills and mobility intentions -the willingness to travel or relocate for work -which might capture candidates’ technological proficiency and adaptability. Using rich microdata from the AlmaLaurea survey of master’s graduates from the University of Bologna (2015–2022), we show that while human capital alone predicts no gender wage gap in favor of men, combining it with mobility intentions reproduces the early wage disadvantage observed for women in Economics and Engineering. We further show that IT skills -an observable CV trait constructed from multiple IT-skill items- reduce the residual gender wage gap, especially in Engineering. Our findings highlight the importance of complementing human capital with field-specific preference and skill traits to explain-and potentially address-early gender wage gaps. |
| JEL: | J16 J31 J71 J24 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:bol:bodewp:wp1212 |
| By: | Faella, Francesca; Scheins, Christopher; Schwarz, Claudia; van Breemen, Vivian |
| Abstract: | In this paper, we empirically investigate how suitability concerns detected by the SSM in the fitness and propriety of management body appointees impact the performance of European banks in the period 2014-2023. We provide evidence that management body appointees where the assessment of the supervisory authorities raised concerns, had a negative impact on the bank’s future performance. The negative effect can be attributed to appointees where the supervisory assessment revealed such severe concerns that ancillary measures were imposed. These results outline the importance of the SSM’s work for safeguarding the quality of bank’s corporate governance and suggest that the Supervisors seem to be effective in pointing out those appointees that exhibit severe concerns. In addition, we find that the designation of female appointees by supervised entities increased the bank’s performance sustainably. This result indicates that stimulating diversity, in terms of gender, in the management bodies of banks positively contributed to bank performance. JEL Classification: G21, G28, G30, M14 |
| Keywords: | ancillary measures, banking supervision, management body appointees |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:ecb:ecbwps:20253115 |
| By: | Drydakis, Nick (Anglia Ruskin University) |
| Abstract: | The study evaluates the effectiveness of a 12-week AI module delivered to non-STEM university students in England, aimed at building students’ AI Capital. An integral part of the process involved the development and validation of the AI Capital of Students scale, used to measure AI Capital before and after the educational intervention. The module was delivered on four occasions to final-year students between 2023 and 2024, with follow-up data collected on students’ employment status. Moreover, AI Capital is positively associated with academic performance in AI-related coursework. However, disparities persist.students, White students, and those with stronger backgrounds in mathematics and empirical methods achieved higher levels of AI Capital and academic success. Furthermore, enhanced AI Capital is associated with higher employment rates six months after graduation. To provide a theoretical foundation for this pedagogical intervention, the study introduces and validates the AI Learning–Capital–Employment Transition model, which conceptualises the pathway from structured AI education to the development of AI Capital and, in turn, to improved employment outcomes. |
| Keywords: | university students, AI Capital, AI literacy, Artificial Intelligence, grades, academic performance, employment rates |
| JEL: | I23 I21 J24 J21 O33 O15 I24 J15 J16 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18138 |
| By: | Tigist Woldetsadik Sommeno; Roy Mersland (UIA - University of Agder); Trond Randøy |
| Abstract: | This study extends the concept of liability of foreignness from for-profit firms to "hybrid" organizations that combine financial and social goals. By using a global dataset of 655 microfinance institutions (MFIs) observed in 77 countries between 1998 and 2015, we investigate the effect of foreignness on the financial and social performance of MFIs. The results suggest a negative effect of foreignness on the financial and social performance of hybrid organizations. Our results also suggest that the negative financial performance effect of foreignness is stronger in organizations with high social performance and in MFIs hosted in institutionally weaker countries. Furthermore, our results emphasize the moderating influence of scaling and longer tenure of MFIs in their host countries. Interestingly, our findings also shed light on the dual nature of scaling, demonstrating both its positive and negative moderating effects. By applying the concept of liability of foreignness this study enriches the understanding of performance in international hybrid organizations. |
| Keywords: | Liability of foreignness Hybrid organization Social enterprise Microfinance Social performance Financial performance |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05221048 |
| By: | Vojtech Sikl (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague); Zuzana Irsova (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague); Peter Kudela (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague); Anna Kudelova (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague) |
| Abstract: | This meta-analysis synthesizes 4, 521 elasticity estimates drawn from 413 studies to examine the presence of publication and endogeneity bias in the literature. We coded over 100 study-level variables to assess how electricity consumers respond to price changes. Our results show that electricity demand is price inelastic, with an average short-run elasticity of -0.231 and average long-run elasticity of -0.532. However, after correcting for publication bias, the short-run elasticity declines in magnitude to -0.116, while the long-run elasticity adjusts to -0.303. Using Bayesian model averaging, we explore substantial heterogeneity in elasticity estimates. Factors such as declining tariff structures, demographic characteristics, fuel usage controls, daylight hours, and citation frequency significantly affect reported elasticities. In contrast, variables related to average and marginal electricity prices and time-of-use tariffs contribute minimally to the observed variation. |
| Keywords: | meta-analysis, elasticity, price elasticity, electricity, heterogeneity, publication bias, consumer sensitivity |
| JEL: | D01 Q40 Q49 C11 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:fau:wpaper:wp2025_17 |
| By: | Rudzitis, Ralfs; Weißmüller, Kristina Sabrina (Vrije Universiteit Amsterdam) |
| Abstract: | This study introduces the Public-sector Chatbot Performance (PCP) framework, a novel and comprehensive approach to systematically assess AI chatbot performance in public administration. The framework evaluates both technical competence—factual accuracy, completeness, and source reliability—and normative integrity, including lawfulness, transparency, equality, and privacy. To demonstrate applicability of the PCP framework, we benchmark the full set of municipal chatbot systems currently deployed in Dutch local governments, alongside two leading proprietary large language models (LLMs): ChatGPT-4o and Gemini 2.5 Pro. Using a pragmatic mixed methods approach, we developed 26 prompts with systematic user-based variation to explore algorithmic bias, resulting in a dataset of n=326 user-chatbot interactions. Quantitative analysis revealed that ChatGPT-4o achieved a composite performance score of 95.7%, significantly outperforming all municipal systems. Municipal chatbots exhibited notable shortcomings in competence and integrity, with some failing to meet basic standards of lawful and equal service provision. Exploratory qualitative analysis further uncovered algorithmic opacity, discretionary advice in violation of Dutch good governance regulations, and discriminatory responses based on “ethnic” usernames. These insights challenge assumptions about neutrality in public sector AI and underscore the need for ethical benchmarks in chatbot evaluation. The PCP framework offers actionable guidance for policymakers, technologists, and scholars committed to responsible digital governance. |
| Date: | 2025–09–16 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:me7pf_v1 |
| By: | Jean-Francois Dewals (AMURE - Aménagement des Usages des Ressources et des Espaces marins et littoraux - Centre de droit et d'économie de la mer - IRD - Institut de Recherche pour le Développement - IFREMER - Institut Français de Recherche pour l'Exploitation de la Mer - UBO - Université de Brest - CNRS - Centre National de la Recherche Scientifique); Sterenn Lucas (SMART - Structures et Marché Agricoles, Ressources et Territoires - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement, Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement); Fabienne Daures (AMURE - Aménagement des Usages des Ressources et des Espaces marins et littoraux - Centre de droit et d'économie de la mer - IRD - Institut de Recherche pour le Développement - IFREMER - Institut Français de Recherche pour l'Exploitation de la Mer - UBO - Université de Brest - CNRS - Centre National de la Recherche Scientifique); Pascal Le Floc’h (AMURE - Aménagement des Usages des Ressources et des Espaces marins et littoraux - Centre de droit et d'économie de la mer - IRD - Institut de Recherche pour le Développement - IFREMER - Institut Français de Recherche pour l'Exploitation de la Mer - UBO - Université de Brest - CNRS - Centre National de la Recherche Scientifique); Kilian Heutte (AMURE - Aménagement des Usages des Ressources et des Espaces marins et littoraux - Centre de droit et d'économie de la mer - IRD - Institut de Recherche pour le Développement - IFREMER - Institut Français de Recherche pour l'Exploitation de la Mer - UBO - Université de Brest - CNRS - Centre National de la Recherche Scientifique, SMART - Structures et Marché Agricoles, Ressources et Territoires - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement) |
| Abstract: | Labels are currently numerous and diverse in the fishery and aquaculture products (FAPs) market, providing consumers with information about the different attributes of FAPs. This extensive development implies that consumers have to face trade-off situations. This paper aims (1) to identify which labels are most valued by consumers when they face a trade-off situation, (2) to study the consumption profiles behind these preferences and (3) to suggest ways of improving the efficiency of labelling policies. Based on a survey conducted in 2021 (n = 1 427), this article describes FAPs consumers' preferences for labelled FAPs. To do so, each consumer was asked to rank their favourite scheme from a pool of nine hypothetical labels related to specific FAPs characteristics. Then, we used a mixed multinomial logit model (MMLM) with marginal effects to analyse consumption profiles. Our results show heterogeneity among consumers regarding labelled FAPs. Overall, labels that ensure intrinsic qualities remain preferred to labels linked to ethical considerations. Moreover, while preferences for domestic productions are prominent, there is a very wide gap with real purchasing behaviour. Furthermore, this study shows that personal motivation, age, gender, knowledge or place of residence influence the preferences expressed. Labels are a policy tool used to reform the FAPs value chain. Nevertheless, they are struggling to achieve their objectives. Our results can be useful for better targeting the messages to be implemented, improving the efficiency of labelling policies and helping consumers to make informed and sustainable choices |
| Keywords: | Multinomial mixed logit model, France, Seafood, Consumers’ preferences, Labelling schemes, Multiple choices |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04678630 |
| By: | Hendriks, Patrick |
| Abstract: | Humans are not born with all the knowledge or skills needed to navigate the countless decisions, challenges, and uncertainties they face every day in their personal and professional lives. Instead, we rely on our ability to learn, developing strategies and acquiring competencies that allow us to adapt to our environment and grow over time. While some knowledge can be acquired through personal experimentation, many of the abilities we depend on have become too complex to be rediscovered through trial and error alone. As a result, humans have long recognized that progress, whether scientific, artistic, or otherwise, is only possible because we build on the insights and experiences of others. Put differently, we often learn far more effectively when we draw on existing knowledge rather than by “reinventing the wheel.” Through direct observation, imitation, collaboration, and instruction, people can acquire knowledge more quickly and with fewer risks than they could through solitary exploration. The same is true for indirect forms of social learning, such as reading books or searching the internet, which provide access to the cumulative experience of others across both space and time. As knowledge accumulates faster than any person can master it, technologies that help us acquire, store, and share information have become indispensable to organizational and societal progress. Artificial intelligence (AI) represents one of the latest milestones in a long line of technologies that have transformed the way people learn. However, unlike earlier breakthroughs such as the printing press or the internet, AI’s impact goes beyond reshaping how we store and share existing knowledge. With its ability to discover complex relationships in large amounts of data, AI can provide advice, make recommendations, and even contribute its own knowledge to organizational and societal learning processes. For example, AI can help discover promising cancer treatments by predicting patient responses to different immunotherapy drugs. This transformative potential has further grown with the emergence of generative AI, which can create entirely new content such as text, images, music, and videos by recombining and building on the human knowledge embedded in its training data. Rather than passively augmenting human learning, AI is actively collaborating with humans in the process of knowledge creation. As a result, few doubt that AI will continue to influence what we learn, how we learn it, and even who we learn from. However, this impact is unlikely to be uniform across all contexts. While AI has the potential to accelerate discovery and democratize information access, it may also obscure human expertise or reinforce existing biases. To guide researchers and practitioners in integrating AI in ways that augment, rather than displace, human learning, this dissertation examines the impact of AI at three levels of analysis, progressing from teams to organizations to society at large. At the team level, this dissertation explores how organizations can effectively manage human-AI teams to promote team collaboration. Based on interviews with potential end users, a prototype team-AI collaboration system was developed that allows human team members to individually configure AI agents by assigning them different roles and personalities. This system was then evaluated through a laboratory experiment in which human-AI teams collaborated on a decision-making task. The results suggest that integrating configurable AI team members into human teams can improve performance by introducing complementary perspectives. However, human participants consistently favored their own expertise for final team decisions, often disregarding superior solutions provided by AI agents. Shifting the focus from collaboration partners to environments, two studies investigate how the virtual reality (VR)-based metaverse can facilitate team collaboration. In a laboratory experiment, five teams performed a collaborative decision-making task using either a VR-based metaverse platform (i.e., Meta Horizon Workrooms) or a traditional videoconferencing tool (i.e., Zoom). The results indicate that team collaboration in the metaverse can be a viable alternative to videoconferencing tools, offering comparable (and in some areas superior) levels of effectiveness, even in teams with minimal prior VR experience. At the organizational level, this dissertation examines how organizations can coordinate the learning activities of their human members and AI to enhance overall organizational learning effectiveness. One study investigates the mutual learning dynamics between humans and AI by introducing artificial assistants (i.e., AI systems designed for recurring one-to-one collaboration) that learn alongside humans. These artificial assistants can affirm or challenge human knowledge while also contributing entirely new insights from domains beyond their human partners’ expertise. Through a series of agent-based simulations, the results show that artificial assistants can reduce learning myopia, the human tendency to favor familiar strategies over new and potentially better alternatives. Optimal outcomes occur when organizations ensure that humans and AI are equally receptive to each other’s insights, thus preventing an unbalanced learning process. A second study examines how AI not only learns but also shapes organizational processes by enacting its own beliefs. For example, AI can select job candidates based on self-learned practices, gradually reshaping the organization’s view of what makes a “good” candidate. Extending an established simulation model, the results suggest that extensive coordination of enactment activities may be unnecessary if humans and AI collaborate periodically to keep their beliefs aligned. Together, these studies highlight that effective human-AI collaboration depends on strategic managerial coordination to maximize organizational learning and adaptability. At the societal level, this dissertation explores strategies for integrating AI into society without compromising cultural diversity. One study examines how different AI integration strategies affect the evolution of cultural beliefs, using agent-based simulations to model interactions between humans and AI. The simulation results show that localized AI, designed to reflect regional or national values, may inadvertently reduce cultural diversity by blending the beliefs of neighboring social groups, challenging the assumption that localization inherently preserves unique cultural identities. In contrast, globalized AI, trained on data biased toward a dominant culture, may initially support diversity but risks long-term polarization by pushing groups with divergent beliefs toward (extreme) views that differ significantly from those of the surrounding majority. These findings underscore that AI affects culture in complex and sometimes unexpected ways, spreading beliefs while also creating personalized echo chambers. To mitigate these risks, the simulation results highlight the need for carefully designed policies that ensure AI leaves space for different perspectives and does not unintentionally reinforce social divides. The studies presented in this dissertation highlight that AI is no longer merely a passive tool but an active participant in human learning processes at the team, organizational, and societal levels. They demonstrate that AI’s ability to both complement and challenge human expertise can enhance collaboration, promote broader knowledge sharing, and mitigate human biases, but only if its integration is carefully managed. Without deliberate coordination, AI can instead reinforce inequalities, entrench dominant narratives, and undermine diversity. This dissertation contributes to the growing understanding of AI’s influence on human learning by offering practical strategies for designing, integrating, and governing AI systems that augment human capabilities. In doing so, it lays critical groundwork for future research aimed at fostering human-AI collaborations that enhance human learning and support the co-creation of knowledge without sacrificing unique human knowledge and agency in the learning process. |
| Date: | 2025–09–17 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:157166 |
| By: | Giner, Céline; Nauges, Céline; Hassett, Katherine |
| Abstract: | This analysis uses OECD survey data from over 8, 000 households in nine countries. The paper analyses household profiles via latent class analysis on the basis of both diet composition, as well as purchasing habits for products that are generally perceived to be environmentally sustainable. Results reveal four main household profiles that are distinguished by different broad patterns in these two behaviours. Household profiles are found to differ in terms of their socio-demographic characteristics and attitudes towards the environment, as well as with respect to their level of support for various food policies. Interestingly, results regarding the relationship between environmental attitudes and red meat consumption may suggest the existence of another “meat paradox” in the sense that one group of respondents reports high levels of environmental concern but also a high frequency of meat consumption |
| Keywords: | food choices; meat consumption; environment-friendly products; public policies; ; cognitive dissonance; latent-class analysis |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130907 |