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Seeing Through the Algorithm: How Explainability Shapes Decision-Making on Robo-Advisor Platforms

Date : Jeudi | 2025-05-22 Ă  12h30
Lieu : Salle des thĂšses

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Mehdi LOUAFI (LEO, UniversitĂ© d’OrlĂ©ans)

This paper examines how algorithmic explainability shapes user decision-making and engagement on a leading French robo-advisor platform. In a large-scale field experiment, we randomly assigned 4,646 prospective clients to one of two conditions: a treatment group that viewed a graphical breakdown of the factors driving their personalized risk-profile recommendation, or a control group that received no additional information. Our primary analyses show that, on average, providing an explanation neither changes the probability of accepting the recommended risk score nor affects deviations from it. However, we uncover significant heterogeneity in treatment effects. First, among mobile users, explanations reduce the number of profile-adjustment attempts before contract signing. Second, for users who initially deviate conservatively from the algorithm’s suggestion, explanations prompt even more conservative portfolio choices. Finally, leveraging machine-learning methods, we estimate conditional average treatment effects across socio-demographic and economic subgroups, identifying additional segments for which explainability meaningfully alters behavior.

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Willingness to pay for the environment : the role of social status and of proactive attitude

Date : Jeudi | 2025-03-20 Ă  12h30
Lieu : Salle des thĂšses

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Martin CIMETIERE (LEO, UniversitĂ© d’OrlĂ©ans)

Based on the 2020 International Social Survey Program (ISSP) IV Environment Module, this paper examines how individual characteristics influence the willingness to pay to protect the environment. We confirm the main findings of the literature: the more respondents perceive the environment as an issue for their country and the more personally concerned they feel, the more they are willing to pay. However, we contribute to the literature by highlighting the role of social status: the higher respondents place themselves on the social scale, the more they are willing to pay; and of proactive attitudes: the more willing respondents are to take action for the environment independently of others, the more they are willing to pay. We underline that the impact of social status, i.e., respondents' subjective perception of their position on the social scale, remains significant even after controlling for income level. Our results suggest that, in order to strengthen individuals' willingness to pay for the environment, two types of policies can be effective: (1) reducing perceived inequality, not just income inequality, and (2) convincing individuals that personal actions are meaningful, even if they do not seem widely adopted by others.

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Impact of Environmental Stringency on Developing Countries’ Participation in Global Value Chains

Date : Jeudi | 2025-02-27 Ă  12h30
Lieu : Salle B.103

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Nada HAZEM (Cairo University and Paris 1 Panthéon-Sorbonne University)

This paper examines the impact of increasing environmental stringency on countries' participation in global value chains (GVCs), with a particular focus on developing economies. Using data from the UNCTAD-Eora Global Value Chain database and the ECOLEX database, this study analyzes the effect of domestic environmental regulations on both forward and backward GVC linkages across 145 countries from 1990 to 2021. The study contributes to the literature in three ways. First, it shifts the focus from gross trade to the distinct forward and backward linkages in GVC participation. Second, it is the first to explore this relationship in a large panel of 145 countries, with an emphasis on developing economies. Third, it combines both country-level and sector-level analyses, providing a more nuanced perspective. The results indicate that environmental regulations enhance forward GVC participation but reduce backward participation. The positive effect on forward linkages is driven by developed economies, whereas the negative impact on backward linkages primarily affects developing countries. Sectoral analysis shows that forward participation increases across all sectors except mining, while backward participation declines in all sectors except fishing. These findings remain robust after addressing endogeneity using an instrumental variable (IV) approach.

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Rise of China’s National Sword: Evaluating its impact on Chinese waste imports

Date : Jeudi | 2025-01-23 Ă  12h30
Lieu : Salle des thĂšses

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Saniya ALI ZAHED (LEO, UniversitĂ© d’OrlĂ©ans)

This paper analyzes the impact of China's National Sword policy introduced in 2018 on its import flows, particularly on waste imports. Our analysis scrutinizes the heterogeneity of the policy's impact across products, time, and exporters. We also explore other moderating factors including income levels, relative environmental stringency, and geopolitics that could have influenced the effectiveness of this policy. To conduct our analysis, we use HS6 product-level trade data from CEPII BACI from 1996 to 2022 for 213 exporting partners to China. We estimate a gravity model using Poisson Pseudo Maximum Likelihood (PPML) with high-dimensioned fixed effects. Our findings indicate that the National Sword policy declined China's imports in quantities by 115.0%, with banned products reduced by 219.6% and products subject to quality controls by 102.9%. The results also indicate a high level of heterogeneity in the impact across the income levels, exporters, and waste products addressed in the National Sword.

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Compliance in fishing regulations: a Social Norms perspective in Ghana

Date : Jeudi | 2025-01-09 Ă  12h30
Lieu : Salle des thĂšses

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Zélie GANKON SIEYADJEU (Université Paris Dauphine-PSL/Chaire Economie du Climat/Université Mohammed VI Polytechnique)

Compliance with environmental regulations relies on a nuanced understanding of both formal incentives and informal social motivations. This paper explores the effect of social and moral norms on individuals’ decisions to engage in illegal fishing activities. We develop a theoretical model that incorporates social norms and peer effects to assess the utility derived from these choices, revealing an equilibrium where only half of the individuals adhere to regulations. We then present a discrete choice model to empirically investigate the effect of these drivers on illegal fishing behaviour. A Hybrid Choice Model is specified, featuring a latent variable that captures fishing-related social norms. Using data collected in 2020 from a fishing community in Ghana, encompassing 410 fishermen, their households, and various fishing practices—including the illegal activity of Saiko fishing—we uncover key findings. Observable indicators, particularly fishermen’s perceptions of peer attitudes toward fishing bans, effectively capture the social norm. Furthermore, the fishing social norm significantly influences both fishermen's satisfaction and their decision to participate in illegal activities. Finally, we extend the analysis to the intensive margin, examining hours spent on Saiko retail and the productivity of participants. The latent score is found to be negatively associated with the intensity of Saiko retail, indicating that social norms impose a constraining effect even after the decision to engage in the activity has been made.

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