EDUCATION

The members and president of the jury warmly congratulate Hugo ORIOLA for his brilliant thesis defense which focuses on the direct or indirect impact of the actions of the central bank on the outcome of the elections.

RESEARCH

Why is it so difficult to reform pensions in France? A reflection by Anne Lavigne, Professor of Economics at the LÉO and Advisor to the COR from 2016 to 2022

RESEARCH

Economy in Orléans: the LEO and the future university campus will open on the Porte-Madeleine site in September 2025

leo

The Orléans Economics Laboratory is a host team at the University of Orléans.

It has about a hundred members, whose research covers three main areas of expertise:

Lab news

Latest publications

> All publications

Does sustainable fishing eco-label increase ex-vessel fish prices? Evidence from a French tuna fishery

François-Charles Wolff, Yohan Renard


Ecological Economics - 2026-08

Eco-certification initiatives are market-based solutions that create incentives for producers to adopt sustainable practices and preserve ecosystems. These initiatives rely on the assumption that producers will receive a price premium sufficient to encourage engagement with and commitment to eco-labels. This paper explores the price differential associated with the eco-certification of a bluefin tuna fishery in Les Sables d'Olonne, on the French Atlantic coast, on prices obtained by certified vessels at auction. Using unique transaction data from 2015 to 2024 and a difference-in-differences strategy, we find that eco-certified vessels experience a 10% price premium after certification compared to non-certified vessels. However, the daily premiums associated with ecocertification vary considerably.

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Financements intermédiés et informalité en Afrique

Gregory Mvogo, Mohamed Coulibaly, Modeste Abate, Novice Bakehe


2026-05-03

Cet article analyse l'impact des financements intermédiés des institutions financières internationales sur le niveau d'informalité des économies africaines. En s'appuyant sur un panel de 39 pays africains couvrant la période 2000-2018, l'étude évalue dans quelle mesure ces financements, canalisés via des intermédiaires financiers locaux, constituent un levier de formalisation des activités économiques, en particulier des petites et moyennes entreprises. L'analyse mobilise une approche quasi-expérimentale combinant l'équilibrage entropique comme méthode principale et l'appariement par score de propension pour les tests de robustesse. Les résultats empiriques montrent que les financements intermédiés exercent un effet négatif et statistiquement significatif sur l'informalité, avec une réduction comprise entre 8 % et 13 % selon les spécifications. Ces résultats suggèrent que l'accès à des ressources longues et formalisées renforce l'inclusion financière, améliore la transparence et incite les entreprises à se conformer aux exigences institutionnelles. L'étude comble ainsi un vide dans la littérature en mettant en évidence le rôle spécifique des financements intermédiés comme instrument de soutien à la formalisation et au développement économique en Afrique.

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Measuring the Driving Forces of Predictive Performance: Application to Credit Scoring

Sullivan Hué, Christophe Hurlin, Christophe Pérignon, Sébastien Saurin


Management Science - 2026-04-08

Because they play an increasingly important role in determining access to credit, credit scoring models are under growing scrutiny from banking supervisors and internal model validators. These authorities need to monitor the model performance and identify its key drivers. To facilitate this, we introduce the explainable performance (XPER) methodology to decompose a performance metric (e.g., area under the curve (AUC), [Formula: see text]) into specific contributions associated with the various features of a forecasting model. XPER is theoretically grounded on Shapley values and is both model-agnostic and performance metric-agnostic. Furthermore, it can be implemented either at the model level or at the individual level. Using a novel data set of car loans, we decompose the AUC of a machine-learning model trained to forecast the default probability of loan applicants. We show that a small number of features can explain a surprisingly large part of the model performance. Notably, the features that contribute the most to the predictive performance of the model may not be the ones that contribute the most to individual forecasts (Shapley additive explanation). Finally, we show how XPER can be used to deal with heterogeneity issues and improve performance. This paper was accepted by Kay Giesecke, finance. Funding: The authors thank the Institut Universitaire de France, the Autorité de contrôle prudentiel et de résolution Chair in Regulation and Systemic Risk, the HEC-Deloitte Chair on Artificial Intelligence for Business Innovation, the Excellence Initiative of Aix-Marseille University [A*MIDEX], and the French National Research Agency [Grants AMSE ANR-17-EURE-0020, Ecodec ANR-11-LABX-0047, and MLEforRisk ANR-21-CE26-0007] for supporting our research. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.02025 .
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Prediction of bubbles in presence of α-stable aggregates moving averages

Gilles de Truchis, Sébastien Fries, Arthur Thomas


2026-03-25

Financial markets frequently exhibit dramatic episodes where asset prices undergo rapid growth followed by abrupt collapses, that are incompatible with standard linear time series models. While anticipative heavytailed linear processes offer a promising alternative for modeling such phenomena, they impose uniform bubble patterns across different episodes, contradicting empirical evidence. This paper introduces a new model, based on α-stable moving average aggregates, that accommodates heterogeneous bubble dynamics.

We establish the theoretical properties of this model, demonstrating that it admits a semi-norm representation on a unit cylinder, thereby enabling the prediction of extreme trajectories with varying growth dynamics. We develop a minimum distance estimation procedure based on the joint characteristic function and establish its asymptotic properties. Monte Carlo simulations confirm the estimator's good finite-sample performance across various specifications, and we implement a subsampling methodology to empirically verify the convergence to asymptotic normality. Our empirical application to the CBOE Crude Oil ETF Volatility Index successfully decomposes observed volatility dynamics into distinct components with different persistence properties, revealing that what appears as a single bubble episode actually consists of multiple superimposed processes with heterogeneous growth rates and crash probabilities.

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Carbon Tax and Emissions Transfer: A Spatial Analysis

Sahar Amidi, Rezgar Feizi, Thaís Núñez Rocha, Isabelle Rabaud


Environmental Modeling & Assessment - 2026-02-27

With the rising role of globalization, assessing the impact of carbon taxation on emissions embodied in trade has become a key issue. Our contribution consists of examining the effect of the carbon tax on emissions embodied in trade, in the framework of the input–output tables. We use variations in the economic sectors of each country to first identify the most and least polluting sectors and, second, investigate the spatial correlation resulting from carbon taxes in the emissions embodied in trade using SDA (structural decomposition analysis), MRIO (multiregional input–output model), and spatial econometric models, covering 56 sectors and 43 countries (32 OECD and 11 non-OECD) from 2000 to 2014. We identify the “electricity, gas, steam and air conditioning supply” sector as the highest emitter. When the carbon tax is imposed on OECD countries, emissions embodied in exports (EEE) and in imports (EEI) from neighboring countries increase by 7.4% and 83.2%, respectively. For non-OECD countries, the results show a 20.7% increase in EEE and a 79% increase in EEI. Our policy recommendation is to coordinate the tax levels, at least regionally, in order to avoid an increase in EEE.
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Heat and Hurdles: Unpacking the Impact of Climate Risks on Women's Empowerment

City Eldeep, Fida Karam, Chahir Zaki


2026

Climate change poses complex risks that extend beyond environmental impacts, shaping social and economic inequalities. This paper examines how physical risks, such as extreme weather, and transition risks, linked to decarbonization and green policies, affect women's empowerment in firms across developing and developed contexts. Using firm-level data from the World Bank Enterprise Surveys and World Development Indicators, we measure empowerment through female employment, management, and ownership. Our results reveal contrasting effects: physical risks reduce female ownership, while transition risks boost female management, particularly in smaller, younger, non-exporting, and non-privately owned firms. The negative impact of physical risks is largely uniform, except in foreign-owned firms, and operates mainly through constraints on finance and land. These findings highlight the need for integrated climate and gender policies that recognize women not only as vulnerable to climate change but also as key agents of sustainable economic transformation.
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Research Documents

> All documents

Financements intermédiés et informalité en Afrique

Gregory Mvogo, Mohamed Coulibaly, Modeste Abate, Novice Bakehe


2026-05-03

Prediction of bubbles in presence of α-stable aggregates moving averages

Gilles de Truchis, Sébastien Fries, Arthur Thomas


2026-03-25

Heat and Hurdles: Unpacking the Impact of Climate Risks on Women's Empowerment

City Eldeep, Fida Karam, Chahir Zaki


2026

Tight belts, different cuts: How political preferences shape the effects of fiscal rules

Dorian Balvir


2026

Advancing clean energy transition in MENA enterprises through awareness, feasibility, and perceived efficiency

Giorgia Giovannetti, Enrico Marvasi, Chahir Zaki


2026

Tail Risk from Extreme Temperature in an Integrated Northeastern American Low- Carbon Electricity System

Anson T. Y. Ho, Adrien Desroziers, Kim P Huynh, Marcel-Cristian Voia


2026

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