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236 results on '"Tse R"'

1. Modulation of caseinate-stabilized model oil-in-water emulsions with soy lecithin

Author: Charmaine K.W. Koo, David Julian McClements, Alexander A. Sher, Cheryl Chung, Jun-Tse R. Fu, and Philippe Rousset
Subjects: SOY LECITHIN, food.ingredient, Food Handling, Chemistry, Sodium Caseinate, Caseins, Coffee, Lecithin, Oil in water, chemistry.chemical_compound, food, Models, Chemical, Emulsifying Agents, Lecithins, Emulsion, Emulsions, Food science, Medium-chain triglyceride, Particle Size, Food Science
Abstract: Demands for plant-based food and beverage products have escalated in recent years. However, many commercial coffee creamers are still being made using dairy derivatives such as sodium caseinate. Therefore, there is a need to investigate the replacement of dairy based proteins with plant-based alternatives. This study was carried out to systematically investigate the properties of model O/W emulsions stabilized by either sodium caseinate (0.25 to 1.5%) or soy lecithin (0.5 to 1.5%). The model emulsions were made of 10% medium chain triglyceride (MCT) oil-in-water emulsions at pH 7. All model O/W emulsions exhibited whitish appearances similar to that of commercial creamers and were effective at lightening black coffee, except those containing the lowest emulsifier concentrations i.e., 0.25% caseinate or 0.5% lecithin. The lightness of the model emulsions depended on the type and level of emulsifier used, with soy lecithin-stabilized emulsions having similar lightening power compare to that stabilized by sodium caseinate. No feathering or free oil were observed in the whitened coffees at the highest emulsifier level used. Mixtures of caseinate and lecithin emulsifiers were also used and model O/W emulsions with similar physical properties to that stabilized by sodium caseinate alone were produced. The mixed emulsifier-stabilized model emulsions had similar lightness when added to coffee than those stabilized by the individual emulsifiers, suggesting similar stabilization mechanisms using these emulsifiers alone or in combination.
Published: 2019

2. Analysis of mitochondrial genome methylation using Nanopore single-molecule sequencing

Author: Susen Schaake, Lasse Sinkkonen, Tse R, Sandro L. Pereira, Lass J, Christine Klein, Lueth T, Joanne Trinh, and Gruenewald A
Subjects: Bisulfite, Nanopore, chemistry.chemical_compound, Mitochondrial DNA, chemistry, CpG site, DNA methylation, Computational biology, Methylation, Nanopore sequencing, Biology, DNA
Abstract: The level and the biological significance of mitochondrial DNA (mtDNA) methylation in human cells is a controversial topic. Using long-read third-generation sequencing technology, mtDNA methylation can be detected directly from the sequencing data, which overcomes previously suggested biases, introduced by bisulfite treatment-dependent methods. We investigated mtDNA from whole blood-derived DNA and established a workflow to detect CpG methylation with Nanopolish. In order to obtain native mtDNA, we adjusted a whole-genome sequencing protocol and performed ligation library preparation and Nanopore sequencing. To validate the workflow, 897bp of methylated and unmethylated synthetic DNA samples at different dilution ratios were sequenced and CpG methylation was detected. Interestingly, we observed that reads with higher methylation in the synthetic DNA did not pass Guppy calling, possibly affecting conclusions about DNA methylation in Nanopore sequencing. We detected in all blood-derived samples overall low-level methylation across the mitochondrial genome, with exceptions at certain CpG sites. Our results suggest that Nanopore sequencing is capable of detecting low-level mtDNA methylation. However, further refinement of the bioinformatical pipelines including Guppy failed reads are recommended.
Published: 2021

3. Self-adaptive sensing iot platform for conserving historic buildings and collections in museums

Author: Tse, R., SIO KEI IM, Tang, S. -K, Menezes, L. F., Dias, A. M. P. G., and Pau, G.

4. Tailoring a rapid autopsy protocol to explore cancer evolution: a patient collaboration

Author: Cherie Blenkiron, Robb, T., Parker, K., Kramer, N., Stables, S., Tse, R., Modahl, L., Coats, E., Print, C., and Lawrence, B.

5. Machine learning-driven credit risk: a systemic review

Author: Si Shi, Rita Tse, Wuman Luo, Stefano D’Addona, Giovanni Pau, Shi S., Tse R., Luo W., D'Addona S., Pau G., Shi, S., Tse, R., Luo, W., D'Addona, S., and Pau, G.
Subjects: Artificial Intelligence, Machine learning, Deep learning, Credit risk, Statistical learning, Software
Abstract: Credit risk assessment is at the core of modern economies. Traditionally, it is measured by statistical methods and manual auditing. Recent advances in financial artificial intelligence stemmed from a new wave of machine learning (ML)-driven credit risk models that gained tremendous attention from both industry and academia. In this paper, we systematically review a series of major research contributions (76 papers) over the past eight years using statistical, machine learning and deep learning techniques to address the problems of credit risk. Specifically, we propose a novel classification methodology for ML-driven credit risk algorithms and their performance ranking using public datasets. We further discuss the challenges including data imbalance, dataset inconsistency, model transparency, and inadequate utilization of deep learning models. The results of our review show that: 1) most deep learning models outperform classic machine learning and statistical algorithms in credit risk estimation, and 2) ensemble methods provide higher accuracy compared with single models. Finally, we present summary tables in terms of datasets and proposed models.
Published: 2022

6. Mobility costs and income distribution

Author: Colletis, Gabriel, Piluso, Nicolas, Blanchet, Adrien, Badra, Mehdi, Laboratoire d'Etude et de Recherche sur l'Economie, les Politiques et les Systèmes Sociaux (LEREPS), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Institut d'Études Politiques [IEP] - Toulouse-École Nationale Supérieure de Formation de l'Enseignement Agricole de Toulouse-Auzeville (ENSFEA), Université de Toulouse (UT), Centre d'Etude et de Recherche Travail Organisation Pouvoir (CERTOP), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Université Toulouse III - Paul Sabatier (UT3), Toulouse School of Economics (TSE-R), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Recherche Agronomique (INRA)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS), Institut de Mathématiques de Toulouse UMR5219 (IMT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), and Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3)
Subjects: Factors of production, Income, Mobility costs, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Regulation
Abstract: International audience; This article presents a model for income distribution among factors of production in the context of a globalised economy. Previous models are most often static and do not take into account the geographical location of the factors of production nor the mobility costs that result. We have created a dynamic Nash bargaining model that integratesthe geographical distance between companies and the mobility costs for each production factor. The main result of this model is that income distribution closely depends on mobility costs: production factors with low mobility costs are those whose incomes increase most rapidly.
Published: 2023

7. Who gets injured at home? Evidence from older people in France

Author: Liliane Bonnal, Greivis Buitrago Gámez, Pascal Favard, Cornel Oros, Centre de recherche sur l'intégration économique et financière (CRIEF), Université de Poitiers, Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de recherche juridique interdisciplinaire (IRJI), Université de Tours (UT), Laboratoire d'Économie d'Orleans [2022-...] (LEO), and Université d'Orléans (UO)-Université de Tours (UT)-Université Clermont Auvergne (UCA)
Subjects: JEL: C - Mathematical and Quantitative Methods, Health problems, Economics and Econometrics, Home and leisure injuries, JEL: I - Health, Education, and Welfare/I.I2 - Education and Research Institutions, Olderpeople, Logit models, JEL: I - Health, Education, and Welfare/I.I0 - General, [SHS.ECO]Humanities and Social Sciences/Economics and Finance
Abstract: International audience; The study analyses unintentional home and leisure injuries (HLIs) for the French senior population using data from the 2012 wave of the French health, health care and insurance survey. The results of our logit models reveal that health status, age, and risky attitudes are the main characteristics associated with HLIs for older people. When the severity of injuries is taken into consideration, the highest exposure to HLIs concerns the oldest seniors, aged 85 years old or older, with deteriorated health. This result is confirmed in the case of severe indoor HLIs, whereas for severe outdoor injuries, the most vulnerable individuals seem to be younger seniors, that is, 75–79 years old. Moreover, our findings suggest that HLIs, and mainly severe home HLIs, generate a short-term influence on a person's health.
Published: 2022

8. On the convergence of global-optimization fraudulent stochastic algorithms

Author: Miclo, Laurent, Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), AFOSR-22IOE016, and ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017)
Subjects: Stochastic algorithms, Morse functions, Diffusion processes on Riemannian manifolds, Global optimization, [MATH]Mathematics [math], Almost sure convergence, Bessel processes, MSC2020: primary: 60J60, secondary: 58J65, 90C26, 65C05, 60F15, 60J35, 35K10
Abstract: We introduce and analyse the almost sure convergence of a new stochastic algorithm for the global minimization of Morse functions on compact Riemannian manifolds. This diffusion process is called fraudulent because it requires the knowledge of minimal value of the function. Its investigation is nevertheless important, since in particular it appears as the limit behavior of non-fraudulent and time-inhomogeneous swarm mean-field algorithms used in global optimization.
Published: 2023

9. On damped second-order gradient systems

Author: Jendoubi, Mohamed Ali, Bégout, Pascal, Bolte, Jérôme, Jendoubi, Mohamed, Institut de Mathématiques de Toulouse UMR5219 (IMT), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), TSE-R, Groupe de recherche en économie mathématique et quantitative (GREMAQ), Centre National de la Recherche Scientifique (CNRS)-École des hautes études en sciences sociales (EHESS)-Institut National de la Recherche Agronomique (INRA)-Université Toulouse 1 Capitole (UT1)-Centre National de la Recherche Scientifique (CNRS)-École des hautes études en sciences sociales (EHESS)-Institut National de la Recherche Agronomique (INRA)-Université Toulouse 1 Capitole (UT1), Faculté des sciences de Bizerte (Département de Mathématiques), Faculté des Sciences de Bizerte, Bégout, Pascal, Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Faculté des Sciences de Bizerte [Université de Carthage], Université de Carthage - University of Carthage, Air Force Office of Scientific Research, Air Force Material Command, USAF (FA9550-14-1-0056), FMJH Program Gaspard Monge in optimization and operations research, Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Mathématiques de Toulouse UMR5219 ( IMT ), Université Toulouse 1 Capitole ( UT1 ) -Université Toulouse - Jean Jaurès ( UT2J ) -Université Toulouse III - Paul Sabatier ( UPS ), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-PRES Université de Toulouse-Institut National des Sciences Appliquées - Toulouse ( INSA Toulouse ), Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Centre National de la Recherche Scientifique ( CNRS ), GREMAQ, Groupe de recherche en économie mathématique et quantitative ( GREMAQ ), Université Toulouse 1 Capitole ( UT1 ) -Institut National de la Recherche Agronomique ( INRA ) -École des hautes études en sciences sociales ( EHESS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Toulouse 1 Capitole ( UT1 ) -Institut National de la Recherche Agronomique ( INRA ) -École des hautes études en sciences sociales ( EHESS ) -Centre National de la Recherche Scientifique ( CNRS ), and Faculté des sciences de Bizerte ( Département de Mathématiques )
Subjects: [ MATH ] Mathematics [math], Pure mathematics, gradient systems, inertial systems, Kurdyka-{\L}ojasiewicz inequality, dissipative dynamical systems, global convergence, Second order systems, [ MATH.MATH-AP ] Mathematics [math]/Analysis of PDEs [math.AP], Mathematics - Analysis of PDEs, Gradient system, FOS: Mathematics, [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP], Equations aux dérivées partielles, Nabla symbol, Total energy, B- ECONOMIE ET FINANCE, Mathematics, Applied Mathematics, Mathematical analysis, Analysis of PDEs, G- MATHEMATIQUES, 35B40, 34D05, 37N40, Mathématiques, Norm (mathematics), Dissipative dynamical systems, Convex function, Analysis, Inertial systems, Analysis of PDEs (math.AP)
Abstract: Using small deformations of the total energy, as introduced in \cite{MR1616968}, we establish that damped second order gradient systems \begin{gather*} u^\pp(t)+\gamma u^\p(t)+\nabla G(u(t))=0, \end{gather*} may be viewed as quasi-gradient systems. In order to study the asymptotic behavior of these systems, we prove that any (nontrivial) desingularizing function appearing in KL inequality satisfies $\vphi(s)\ge c\sqrt s$ whenever the original function is definable and $C^2.$ Variants to this result are given. These facts are used in turn to prove that a desingularizing function of the potential $G$ also desingularizes the total energy and its deformed versions. Our approach brings forward several results interesting for their own sake: we provide an asymptotic alternative for quasi-gradient systems, either a trajectory converges, or its norm tends to infinity. The convergence rates are also analyzed by an original method based on a one-dimensional worst-case gradient system. We conclude by establishing the convergence of solutions of damped second order systems in various cases including the definable case. The real-analytic case is recovered and some results concerning convex functions are also derived.
Published: 2015

10. Using Data from job seekers, job offers and past hirings to learn a Job Recommender System: the VADORE Project

Author: Bied, Guillaume, Nathan, Solal, Perennes, Elia, Gaillac, Christophe, Caillou, Philippe, Crépon, Bruno, Sebag, Michèle, Centre de Recherche en Économie et Statistique (CREST), Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] (ENSAI)-École polytechnique (X)-École Nationale de la Statistique et de l'Administration Économique (ENSAE Paris)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), TAckling the Underspecified (TAU), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Pôle emploi (France), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de mécanique des solides (LMS), École polytechnique (X)-Mines Paris - PSL (École nationale supérieure des mines de Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)
Subjects: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract: International audience; The Vador Project started in 2018 between the French Public Employment Service Pole Emploi, computer scientists from Paris Saclay and economist from CREST. The project aims to learn a new recommender system from past hirings and job seekers and offers data. We will present both the past, current and futur research and technical challenges faced by the projects and its contributions.
Published: 2023

11. Gender fairness in job recommendation: a case study

Author: Bied, Guillaume, Gaillac, Christophe, Hoffmann, Morgane, Nathan, Solal, Caillou, Philippe, Crépon, Bruno, Sebag, Michèle, Centre de Recherche en Économie et Statistique (CREST), Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] (ENSAI)-École polytechnique (X)-École Nationale de la Statistique et de l'Administration Économique (ENSAE Paris)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), TAckling the Underspecified (TAU), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de mécanique des solides (LMS), École polytechnique (X)-Mines Paris - PSL (École nationale supérieure des mines de Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)
Subjects: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract: International audience; Algorithmic recommendations of job ads to job seekers promise to alleviate frictional unemployment, but raise fairness considerations due to biases in training data. This paper strives to discuss the issue of algorithmic fairness, with a focus on gender, in a hybrid job recommender system trained on past hires developed in partnership with the French Public Employment Service.
Published: 2023

12. When Nudges backfire : Evidence from a Randomized Field Experiment to Boost Biological Pest Control

Author: Chabé-Ferret, Sylvain, Le Coent, Philippe, Lefebvre, Caroline, Préget, Raphaële, Salanié, François, Julie, Subervie, Thoyer, Sophie, Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institute for Advanced Studies, Gestion de l'Eau, Acteurs, Usages (UMR G-EAU), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Laboratoire Virologie [CHU Toulouse], Institut Fédératif de Biologie (IFB), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Pôle Biologie [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Centre d'Economie de l'Environnement - Montpellier (CEE-M), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM)
Subjects: Nudges, Behavioral Economics, [QFIN]Quantitative Finance [q-fin], JEL: D - Microeconomics/D.D9 - Intertemporal Choice/D.D9.D90 - General, Pesticides, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q5 - Environmental Economics/Q.Q5.Q58 - Government Policy, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q2 - Renewable Resources and Conservation/Q.Q2.Q25 - Water, Government Policy, [SHS]Humanities and Social Sciences
Abstract: Nudges are increasingly used to alter the behavior of economic agents as an alternative to monetary incentives. However, little is known as to whether nudges can backfire, that is, how and when they may generate effects opposite to those they intend to achieve. We provide the first field evidence of a nudge that is designed to encourage pro-environmental behavior, which instead backfires. We randomly allocate a social comparison nudge inviting winegrowers to adopt biological pest control as an alternative to chemical pesticide use. We find that our nudge decreases by half the adoption of biological pest control among the largest vineyards, where the bulk of adoption occurs. We show that this result can be rationalized in an economic model where winegrowers and winegrower-cooperative managers bargain over future rents generated by the adoption of biological pest control. This study highlights the importance of experimenting on a small scale with nudges aimed at encouraging adoption of virtuous behaviors in order to detect unexpected adverse effects, particularly in contexts where negotiations on the sharing of the costs of adoption are likely to occur.
Published: 2023

13. Risk-sharing and optimal contracts with large exogenous risks

Author: Villeneuve, Stéphane, Martin, Jessica, Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), and Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Shutdown risk, JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C61 - Optimization Techniques • Programming Models • Dynamic Analysis, JEL: D - Microeconomics/D.D8 - Information, Knowledge, and Uncertainty/D.D8.D86 - Economics of Contract: Theory, Principal-Agent problems, JEL: D - Microeconomics/D.D8 - Information, Knowledge, and Uncertainty/D.D8.D81 - Criteria for Decision-Making under Risk and Uncertainty, Hamilton-Jacobi Bellman equations, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, General Economics, Econometrics and Finance, B- ECONOMIE ET FINANCE, Finance
Abstract: National audience; What type of delegation contract should be offered when facing a risk of the magnitude of the pandemic we are currently experiencing and how does the likelihood of an exogenous early termination of the relationship modify the terms of a full-commitment contract? We study these questions by considering a dynamic principal-agent model that naturally extends the classical Holmström-Milgrom setting to include a risk of shutdown before the maturity of the contract. We obtain an explicit characterization of the optimal wage along with the optimal action provided by the agent when the shutdown risk is independent of the inherent agency problem. The optimal contract is linear by offering both a fixed share of the output which is similar to the standard shutdown-free Holmström Milgrom model and a linear prevention mechanism that is proportional to the random lifetime of the contract. We then extend the model in two directions. We first allow the agent to control the intensity of the shutdown risk. We also consider a structural agency model where the shutdown risk materializes when the state process hits zero.
Published: 2023

14. On a Markov construction of couplings

Author: Diaconis, Persi, Miclo, Laurent, Department of Mathematics [Stanford], Stanford University, Department of Statistics [Stanford], Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), AFOSR-22IOE016, and NSF grant 1954042
Subjects: [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], Coupling, Markov approach, Uniform random permutation, Number of fixed point(s), MSC2020: primary: 60J10, secondary: 05A05, 60E15, 60J22, 60J80, 37A25, Probability (math.PR), FOS: Mathematics, Poisson approximation, Intertwining, Mathematics - Probability
Abstract: For $N\in\mathbb{N}$, let $\pi_N$ be the law of the number of fixed points of a random permutation of $\{1, 2, ..., N\}$. Let $\mathcal{P}$ be a Poisson law of parameter 1.A classical result shows that $\pi_N$ converges to $\mathcal{P}$ for large $N$ and indeed in total variation $$\left\Vert \pi_N-\mathcal{P}\right\Vert_{\mathrm{tv}} \leq \frac{2^N}{(N+1)!}$$ This implies that $\pi_N$ and $\mathcal{P}$ can be coupled to at least this accuracy. This paper constructs such a coupling (a long open problem) using the machinery of intertwining of two Markov chains. This method shows promise for related problems of random matrix theory.
Published: 2023
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15. Long term dynamics of the subgradient method for Lipschitz path differentiable functions

Author: Bolte, Jerome, Pauwels, Edouard, Rios-Zertuche, Rodolfo, Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Argumentation, Décision, Raisonnement, Incertitude et Apprentissage (IRIT-ADRIA), Institut de recherche en informatique de Toulouse (IRIT), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Équipe Méthodes et Algorithmes en Commande (LAAS-MAC), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), ANR-19-P3IA-0004,ANITI,Artificial and Natural Intelligence Toulouse Institute(2019), ANR-19-CE23-0017,MaSDOL,Mathématiques de l'optimisation déterministe et stochastique liées à l'apprentissage profond(2019), and ANR-11-LABX-0040,CIMI,Centre International de Mathématiques et d'Informatique (de Toulouse)(2011)
Subjects: I.2.6, G.1.6, Applied Mathematics, General Mathematics, [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO], Numerical Analysis (math.NA), Dynamical Systems (math.DS), Optimization and Control (math.OC), FOS: Mathematics, Mathematics - Numerical Analysis, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Mathematics - Dynamical Systems, Mathematics - Optimization and Control, 65K10 (Primary), 37A50, 37B35, 62M45 (Secondary)
Abstract: We consider the long-term dynamics of the vanishing stepsize subgradient method in the case when the objective function is neither smooth nor convex. We assume that this function is locally Lipschitz and path differentiable, i.e., admits a chain rule. Our study departs from other works in the sense that we focus on the behavoir of the oscillations, and to do this we use closed measures. We recover known convergence results, establish new ones, and show a local principle of oscillation compensation for the velocities. Roughly speaking, the time average of gradients around one limit point vanishes. This allows us to further analyze the structure of oscillations, and establish their perpendicularity to the general drift., Comment: 28 pages, 2 figures
Published: 2022

16. Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems

Author: Bolte, Jérôme, Pauwels, Edouard, Silveti-Falls, Antonio, Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Argumentation, Décision, Raisonnement, Incertitude et Apprentissage (IRIT-ADRIA), Institut de recherche en informatique de Toulouse (IRIT), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Centre de vision numérique (CVN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay, OPtimisation Imagerie et Santé (OPIS), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de vision numérique (CVN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-CentraleSupélec-Université Paris-Saclay, Air Force Office of Scientific Research, Air Force Material Command, USAF, under grant numbers FA9550-19-1-7026, ANR-19-P3IA-0004,ANITI,Artificial and Natural Intelligence Toulouse Institute(2019), ANR-19-CE23-0017,MaSDOL,Mathématiques de l'optimisation déterministe et stochastique liées à l'apprentissage profond(2019), and ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017)
Subjects: conservative field, FOS: Computer and information sciences, Computer Science - Machine Learning, generalized gradient, generalized equation, Clarke subdifferential, Machine Learning (cs.LG), monotone inclusion, Maximal monotone operator, dif- ferentiating solutions, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Optimization and Control (math.OC), implicit differentiation, FOS: Mathematics, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Mathematics - Optimization and Control
Abstract: We leverage path differentiability and a recent result on nonsmooth implicit differentiation calculus to give sufficient conditions ensuring that the solution to a monotone inclusion problem will be path differentiable, with formulas for computing its generalized gradient. A direct consequence of our result is that these solutions happen to be differentiable almost everywhere. Our approach is fully compatible with automatic differentiation and comes with assumptions which are easy to check, roughly speaking: semialgebraicity and strong monotonicity. We illustrate the scope of our results by considering three fundamental composite problem settings: strongly convex problems, dual solutions to convex minimization problems and primal-dual solutions to min-max problems.
Published: 2022

17. On the elementary Hodge decomposition for finite Markov processes

Author: Miclo, Laurent, Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), AFOSR-22IOE016, and ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017)
Subjects: Elementary Hodge decompositions, Finite weighted graphs, Optimal transport, MSC2020: primary: 60J27, secondary: 60J60, 58J65, 46E27, 37C10, 58B20, Compact Riemannian manifolds, Finite Markov processes, [MATH]Mathematics [math], Gradient fields, Poisson equation, Vector fields
Abstract: Elementary Hodge decompositions break down any vector field into a sum of a gradient field and a divergence-free vector field. Such a result is extended to finite irreducible and reversible Markov processes, where vector fields correspond to anti-symmetric functions on the oriented edges of the underlying graph.
Published: 2022

18. Economic analysis of choices among differing measures to manage coastal erosion in Hoi An (a UNESCO World Heritage Site)

Author: Tuan Nguyen, Thi Lan Anh Nguyen, Manh-Hung Nguyen, Viet-Ngu Hoang, Michel Simioni, Arnaud Reynaud, Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), HoChiMinh City National University, Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) (UMR MoISA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Banking Academy of Vietnam, Institute of Research in Economics, Environment and Data Science (IREEDS), Queensland University of Technology [Brisbane] (QUT), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Subjects: Economics and Econometrics, Economics, Econometrics and Finance (miscellaneous), 0211 other engineering and technologies, Developing country, 02 engineering and technology, Coastal erosion, Residents’ valuation, Revetment, Willingness to pay, 0502 economics and business, 11. Sustainability, 021108 energy, 14. Life underwater, 050207 economics, B- ECONOMIE ET FINANCE, Valuation (finance), Multinomial logistic regression, business.industry, 05 social sciences, Environmental resource management, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q5 - Environmental Economics/Q.Q5.Q54 - Climate • Natural Disasters and Their Management • Global Warming, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Livelihood, Geography, Discrete choice experiment, Vietnam, [SHS.ENVIR]Humanities and Social Sciences/Environmental studies, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q5 - Environmental Economics/Q.Q5.Q51 - Valuation of Environmental Effects, business, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q2 - Renewable Resources and Conservation/Q.Q2.Q26 - Recreational Aspects of Natural Resources, Tourism
Abstract: International audience; The paper presents one of the first economic analyses of residents’ choice of different coastal erosion control measures in a developing country - Vietnam. Hoi An, a UNESCO World Heritage Site, was selected given the frequency of coastal erosion events which have caused increasing damages to property, tourism activities and the livelihood of local people in an iconic tourist destination. We designed a discrete choice experiment based on responses from 399 households in order to estimate the willingness to pay (WTP) for differing coastal erosion control measures. Using the generalized multinomial logit model, empirical results yield five important findings. First, residents prefer wider, more public beaches having both trees and restaurants and are willing to accept visible structures such as groynes and stair revetment to prevent further erosion. Second, residents place a higher value on a beach that is protected by robust permanent structures. In particular, residents have the highest WTP for groynes. Third, there exists preference and scale heterogeneity across respondents which are driven by level of education, knowledge of the problem, and the stated level of choice certainty. Fourth, knowledge and experience of coastal erosion are shown to have a strong influence on the valuation residents place on the choice of protective structures. Finally, on average, a resident is willing to pay USD 1.7 per year for a coastal erosion management program that increases beach width by additional 50 meters, beach access by additional 25%, restaurants and trees on the beach and groynes as the erosion protection structure.
Published: 2021

19. Asymptotic study of stochastic adaptive algorithm in non-convex landscape

Author: Gadat, Sébastien, Gavra, Ioana, Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut Agro Rennes Angers, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Subjects: FOS: Computer and information sciences, Computer Science - Machine Learning, Probability (math.PR), Stochastic optimization, Convergence of random variables, Machine Learning (stat.ML), Mathematics - Statistics Theory, Statistics Theory (math.ST), [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Machine Learning (cs.LG), Statistics - Machine Learning, Stochastic adaptive algorithm, FOS: Mathematics, B- ECONOMIE ET FINANCE, Mathematics - Probability
Abstract: This paper studies some asymptotic properties of adaptive algorithms widely used in optimization and machine learning, and among them Adagrad and Rmsprop, which are involved in most of the blackbox deep learning algorithms. Our setup is the non-convex landscape optimization point of view, we consider a one time scale parametrization and we consider the situation where these algorithms may be used or not with mini-batches. We adopt the point of view of stochastic algorithms and establish the almost sure convergence of these methods when using a decreasing step-size point of view towards the set of critical points of the target function. With a mild extra assumption on the noise, we also obtain the convergence towards the set of minimizer of the function. Along our study, we also obtain a "convergence rate" of the methods, in the vein of the works of \cite{GhadimiLan}., 36 pages
Published: 2022

20. Couplings of brownian motions with set-valued dual processes on riemannian manifolds

Author: Arnaudon, Marc, Coulibaly-Pasquier, Koléhè, Miclo, Laurent, Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Institut Élie Cartan de Lorraine (IECL), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Mathématiques de Toulouse UMR5219 (IMT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), and ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017)
Subjects: Brownian motions on Riemannian manifolds, Generalized Pitman theorem, [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], Boundary and skeleton local times, MSC 2010 primary : 60J60, secondary: 60J65, 60H10, 58J65, 53C44, 60J55, 35K93, Couplings of primal and dual processes, Stochastic mean curvature evolutions, Intertwining relations, Set-valued dual processes
Abstract: The purpose of this paper is to construct a Brownian motion X_t taking values in a Riemannian manifold M , together with a compact valued process D_t such that, at least for small enough D-stopping time T and conditioned to the filtration of D_t up to time T , the law of X_T is the normalized Lebesgue measure on D_T. This intertwining result is a generalization of Pitman theorem. We first construct regular intertwined processes related to Stokes' theorem. Then using several limiting procedures we construct synchronous intertwined, free intertwined, mirror intertwined processes. The local times of the Brownian motion on the (morphological) skeleton or the boundary of D plays an important role. Several example with moving intervals, discs, annulus, symmetric convex sets are investigated.
Published: 2022

21. Portfolio optimization under CV@R constraint with stochastic mirror descent

Author: Costa, Manon, Gadat, Sébastien, Huang, Lorick, Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut Universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT), and ANR-19-CE23-0017,MaSDOL,Mathématiques de l'optimisation déterministe et stochastique liées à l'apprentissage profond(2019)
Subjects: [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], Stochastic Mirror Descent, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Portfolio selection, Biased observations, Risk management constraint, Discretization
Abstract: This article studies and solves the problem of optimal portfolio allocation with CV@R constraints when dealing with imperfectly simulated financial assets. We use a Stochastic biased Mirror Descent to find optimal resource allocation for a portfolio whose underlying assets cannot be generated exactly and may only be approximated with a numerical scheme that satisfies suitable error bounds, under a risk management constraint. We establish almost sure asymptotic properties as well as the rate of convergence for the averaged algorithm. We then focus on the optimal tuning of the overall procedure to obtain an optimized numerical cost. Our results are then illustrated numerically on simulated as well as real data sets.
Published: 2022

22. Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a crosssectionally dependent panel framework

Author: Musolesi, Antonio, Prete, Giada Andrea, Simioni, Michel, Università degli Studi di Ferrara = University of Ferrara (UniFE), Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) (UMR MoISA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Perez, Isabelle
Subjects: Cross-sectional dependence, Non-parametric regression, JEL: C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C23 - Panel Data Models • Spatio-temporal Models, JEL: C - Mathematical and Quantitative Methods/C.C5 - Econometric Modeling, JEL: O - Economic Development, Innovation, Technological Change, and Growth/O.O4 - Economic Growth and Aggregate Productivity, [SHS.ECO] Humanities and Social Sciences/Economics and Finance, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, B- ECONOMIE ET FINANCE, Factor models, Moving block bootstrap, Spline functions, Public capital hypothesis
Abstract: This paper provides a broad replication of Calderón et al. (2015). We address some complex and relevant issues, namely functional form, non-stationary variables and cross-sectional depen- dence. In particular, by adopting the CCE framework, we consider both parametric - static and dynamic - and non-parametric specifications, thus allowing for different degrees of flexibility. Contrary to Calderón et al. (2015), we find a lack of significance of the infrastructure index, with an estimated elasticity very close to zero for all estimates. Moreover, by employing the data-driven model selection procedure proposed by Gioldasis et al. (2021), it is found that non-parametric specifications provide the best predictive performance and that CCE models always overperform with respect to traditional panel data methods that employ cross-sectional demeaning to account for cross-sectional dependence.
Published: 2022

23. Edge-Based Transfer Learning for Classroom Occupancy Detection in a Smart Campus Context

Author: Lorenzo Monti, Rita Tse, Su-Kit Tang, Silvia Mirri, Giovanni Delnevo, Vittorio Maniezzo, Paola Salomoni, Monti L., Tse R., Tang S.-K., Mirri S., Delnevo G., Maniezzo V., and Salomoni P.
Subjects: smart sensing, smart environment, smart building, COVID-19, deep learning, transfer learning, Biochemistry, Atomic and Molecular Physics, and Optics, Analytical Chemistry, Machine Learning, Internet of Things, smart buildings, smart environments, occupancy detection, ambient intelligence, Image Processing, Computer-Assisted, Humans, Electrical and Electronic Engineering, Internet of Thing, Instrumentation, Pandemics
Abstract: Studies and systems that are aimed at the identification of the presence of people within an indoor environment and the monitoring of their activities and flows have been receiving more attention in recent years, specifically since the beginning of the COVID-19 pandemic. This paper proposes an approach for people counting that is based on the use of cameras and Raspberry Pi platforms, together with an edge-based transfer learning framework that is enriched with specific image processing strategies, with the aim of this approach being adopted in different indoor environments without the need for tailored training phases. The system was deployed on a university campus, which was chosen as the case study. The proposed system was able to work in classrooms with different characteristics. This paper reports a proposed architecture that could make the system scalable and privacy compliant and the evaluation tests that were conducted in different types of classrooms, which demonstrate the feasibility of this approach. Overall, the system was able to count the number of people in classrooms with a maximum mean absolute error of 1.23.
Published: 2022
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24. Séminaire de Probabilités LI

Author: Karandikar, R. L., Rao, B. V., Leuridan, Christophe, Vidmar, Matija, Miclo, Laurent, Patie, Pierre, Bernou, Armand, Caballero, Maria-Emilia, Rouault, Alain, Dedecker, Jérôme, Merlevède, Florence, Rio, Emmanuel, Brosset, Fabien, Klein, Thierry, Lagnoux, Agnès, Petit, Pierre, Marinelli, Carlo, Scarpa, Luca, Castaing, Charles, Marie, Nicolas, Fitte, Paul Raynaud De, Attal, Stéphane, Deschamps, Julien, Pellegrini, Clément, Eisenbaum, Nathalie, Chennai Mathematical Institute [Inde], Institut Fourier (IF), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Department of Mathematics (University of Ljubljana), University of Ljubljana, Toulouse School of Economics (TSE-R), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), School of Operations Research and Information Engineering (ORIE), Cornell University [New York], Laboratoire Jacques-Louis Lions (LJLL (UMR_7598)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Instituto de Matematicas (UNAM), Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), Laboratoire de Mathématiques de Versailles (LMV), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Mathématiques Appliquées Paris 5 (MAP5 - UMR 8145), Université Paris Descartes - Paris 5 (UPD5)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Analyse et Mathématiques Appliquées (LAMA), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université Gustave Eiffel, Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Ecole Nationale de l'Aviation Civile (ENAC), University College of London [London] (UCL), Faculty of Mathematics [Vienna], University of Vienna [Vienna], Université de Montpellier (UM), Modélisation aléatoire de Paris X (MODAL'X), Université Paris Nanterre (UPN), Laboratoire de Mathématiques Raphaël Salem (LMRS), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS), Institut Camille Jordan [Villeurbanne] (ICJ), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet [Saint-Étienne] (UJM)-Centre National de la Recherche Scientifique (CNRS), Università degli studi di Genova = University of Genoa (UniGe), Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Donati-Martin, Catherine, Lejay, Antoine, Rouault, Alain, Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Institut Camille Jordan (ICJ), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS), Équations aux dérivées partielles, analyse (EDPA), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL)
Subjects: [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2022

25. Few-shot learning approach with multi-scale feature fusion and attention for plant disease recognition

Author: Hong Lin, Rita Tse, Su-Kit Tang, Zhen-ping Qiang, Giovanni Pau, Lin H., Tse R., Tang S.-K., Qiang Z.-P., and Pau G.
Subjects: training strategy, meta-learning, plant disease recognition, sub-class classification, few-shot learning, Plant Science, cross-domain, multi-scale feature fusion, attention
Abstract: Image-based deep learning method for plant disease diagnosing is promising but relies on large-scale dataset. Currently, the shortage of data has become an obstacle to leverage deep learning methods. Few-shot learning can generalize to new categories with the supports of few samples, which is very helpful for those plant disease categories where only few samples are available. However, two challenging problems are existing in few-shot learning: (1) the feature extracted from few shots is very limited; (2) generalizing to new categories, especially to another domain is very tough. In response to the two issues, we propose a network based on the Meta-Baseline few-shot learning method, and combine cascaded multi-scale features and channel attention. The network takes advantage of multi-scale features to rich the feature representation, uses channel attention as a compensation module efficiently to learn more from the significant channels of the fused features. Meanwhile, we propose a group of training strategies from data configuration perspective to match various generalization requirements. Through extensive experiments, it is verified that the combination of multi-scale feature fusion and channel attention can alleviate the problem of limited features caused by few shots. To imitate different generalization scenarios, we set different data settings and suggest the optimal training strategies for intra-domain case and cross-domain case, respectively. The effects of important factors in few-shot learning paradigm are analyzed. With the optimal configuration, the accuracy of 1-shot task and 5-shot task achieve at 61.24% and 77.43% respectively in the task targeting to single-plant, and achieve at 82.52% and 92.83% in the task targeting to multi-plants. Our results outperform the existing related works. It demonstrates that the few-shot learning is a feasible potential solution for plant disease recognition in the future application.
Published: 2022

26. Introduction to the thematic issue on government‐provided services

Author: Rabah Amir, Rim Lahmandi-Ayed, Helmuth Cremer, University of Iowa [Iowa City], Institut d'Etudes Avancées [AMU] (IMéRA), Aix Marseille Université (AMU), Aix-Marseille Sciences Economiques (AMSE), École des hautes études en sciences sociales (EHESS)-Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Modélisation et Analyse Statistique et Economique (UR MASE), Ecole Supérieure de la Statistique et de l'Analyse de l'Information (ESSAIT), Université de Carthage - University of Carthage-Université de Carthage - University of Carthage, Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Economics and Econometrics, Government, Thematic map, Sociology and Political Science, InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, ACL-2, Economics, ComputingMilieux_LEGALASPECTSOFCOMPUTING, Public administration, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, ComputingMilieux_MISCELLANEOUS, Finance
Abstract: International audience; Introduction to the thematic issue on government‐provided services
Published: 2020

27. Uncertainty, Learning, and Technology Adoption in Agriculture

Author: Céline Nauges, Jean-Paul Chavas, Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Economie des Ressources Naturelles (LERNA), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Recherche Agronomique (INRA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), University of Missouri [Columbia] (Mizzou), University of Missouri System, Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)
Subjects: Economics and Econometrics, media_common.quotation_subject, Development, JEL: O - Economic Development, Innovation, Technological Change, and Growth/O.O3 - Innovation • Research and Development • Technological Change • Intellectual Property Rights/O.O3.O33 - Technological Change: Choices and Consequences • Diffusion Processes, Adoption, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q1 - Agriculture/Q.Q1.Q16 - R&D • Agricultural Technology • Biofuels • Agricultural Extension Services, 0502 economics and business, Agricultural technology, Learning, 050207 economics, Productivity, media_common, 2. Zero hunger, Public economics, Agricultural machinery, business.industry, 05 social sciences, Uncertainty, Innovation process, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q1 - Agriculture/Q.Q1.Q11 - Aggregate Supply and Demand Analysis • Prices, Food sector, Agriculture, 050202 agricultural economics & policy, Business, Welfare
Abstract: National audience; Adoption of agricultural innovations has been an important factor affecting the welfare of farmers, the productivity of agriculture and the economics of the food sector. This paper reviews the literature on technology adoption in agriculture with a focus on the role of uncertainty and learning. It examines the factors affecting adoption benefits for farmers and their linkages with the innovation process. It also discusses the welfare implications of innovation and adoption for farmers and consumers.
Published: 2020

28. National identity predicts public health support during a global pandemic

Author: Van Bavel, Jay J., Cichocka, Aleksandra, Capraro, Valerio, Sjåstad, Hallgeir, Nezlek, John B., Pavlović, Tomislav, Alfano, Mark, Gelfand, Michele J., Azevedo, Flavio, Birtel, Michèle D., Cislak, Aleksandra, Lockwood, Patricia L., Ross, Robert Malcolm, Abts, Koen, Agadullina, Elena, Aruta, John Jamir Benzon, Besharati, Sahba Nomvula, Bor, Alexander, Choma, Becky L., Crabtree, Charles David, Cunningham, William A., De, Koustav, Ejaz, Waqas, Elbaek, Christian T., Findor, Andrej, Flichtentrei, Daniel, Franc, Renata, Gjoneska, Biljana, Gruber, June, Gualda, Estrella, Horiuchi, Yusaku, Huynh, Toan Luu Duc, Ibanez, Agustin, Imran, Mostak Ahamed, Israelashvili, Jacob, Jasko, Katarzyna, Kantorowicz, Jaroslaw, Kantorowicz-Reznichenko, Elena, Krouwel, André, Laakasuo, Michael, Lamm, Claus, Leygue, Caroline, Lin, Ming-Jen, Mansoor, Mohammad Sabbir, Marie, Antoine, Mayiwar, Lewend, Mazepus, Honorata, McHugh, Cillian, Minda, John Paul, Mitkidis, Panagiotis, Olsson, Andreas, Otterbring, Tobias, Packer, Dominic J., Perry, Anat, Petersen, Michael Bang, Puthillam, Arathy, Riaño-Moreno, Julián C., Rothmund, Tobias, Santamaría-García, Hernando, Schmid, Petra C., Stoyanov, Drozdstoy, Tewari, Shruti, Todosijević, Bojan, Tsakiris, Manos, Tung, Hans H., Umbreș, Radu G., Vanags, Edmunds, Vlasceanu, Madalina, Vonasch, Andrew, Yucel, Meltem, Zhang, Yucheng, Abad, Mohcine, Adler, Eli, Akrawi, Narin, Mdarhri, Hamza Alaoui, Amara, Hanane, Amodio, David M., Antazo, Benedict G., Apps, Matthew, Ay, F. Ceren, Ba, Mouhamadou Hady, Barbosa, Sergio, Bastian, Brock, Berg, Anton, Bernal-Zárate, Maria P., Bernstein, Michael, Białek, Michał, Bilancini, Ennio, Bogatyreva, Natalia, Boncinelli, Leonardo, Booth, Jonathan E., Borau, Sylvie, Buchel, Ondrej, Cameron, C. Daryl, Carvalho, Chrissie F., Celadin, Tatiana, Cerami, Chiara, Chalise, Hom Nath, Cheng, Xiaojun, Cian, Luca, Cockcroft, Kate, Conway, Jane, Córdoba-Delgado, Mateo Andres, Crespi, Chiara, Crouzevialle, Marie, Cutler, Jo, Cypryańska, Marzena, Dabrowska, Justyna, Daniels, Michael A., Davis, Victoria H., Dayley, Pamala N., Delouvee, Sylvain, Denkovski, Ognjan, Dezecache, Guillaume, Dhaliwal, Nathan A., Diato, Alelie B., Di Paolo, Roberto, Drosinou, Marianna, Dulleck, Uwe, Ekmanis, Jānis, Ertan, Arhan S., Etienne, Tom W., Farhana, Hapsa Hossain, Farkhari, Fahima, Farmer, Harry, Fenwick, Ali, Fidanovski, Kristijan, Flew, Terry, Fraser, Shona, Frempong, Raymond Boadi, Fugelsang, Jonathan A., Gale, Jessica, Garcia-Navarro, E. Begoña, Garladinne, Prasad, Ghajjou, Oussama, Gkinopoulos, Theofilos, Gray, Kurt, Griffin, Siobhán M., Gronfeldt, Bjarki, Gümren, Mert, Gurung, Ranju Lama, Halperin, Eran, Harris, Elizabeth, Herzon, Volo, Hruška, Matej, Huang, Guanxiong, Hudecek, Matthias F. C., Isler, Ozan, Jangard, Simon, Jørgensen, Frederik J., Kachanoff, Frank, Kahn, John, Dangol, Apsara Katuwal, Keudel, Oleksandra, Koppel, Lina, Koverola, Mika, Kubin, Emily, Kunnari, Anton, Kutiyski, Yordan, Laguna, Oscar, Leota, Josh, Lermer, Eva, Levy, Jonathan, Levy, Neil, Li, Chunyun, Long, Elizabeth U., Longoni, Chiara, Maglić, Marina, McCashin, Darragh, Metcalf, Alexander L., Mikloušić, Igor, El Mimouni, Soulaimane, Miura, Asako, Molina-Paredes, Juliana, Monroy-Fonseca, César, Morales-Marente, Elena, Moreau, David, Muda, Rafał, Myer, Annalisa, Nash, Kyle, Nesh-Nash, Tarik, Nitschke, Jonas P., Nurse, Matthew S., Ohtsubo, Yohsuke, Oldemburgo De Mello, Victoria, O’Madagain, Cathal, Onderco, Michal, Palacios-Galvez, M. Soledad, Palomäki, Jussi, Pan, Yafeng, Papp, Zsófia, Pärnamets, Philip, Paruzel-Czachura, Mariola, Pavlović, Zoran, Payán-Gómez, César, Perander, Silva, Pitman, Michael Mark, Prasad, Rajib, Pyrkosz-Pacyna, Joanna, Rathje, Steve, Raza, Ali, Rêgo, Gabriel G., Rhee, Kasey, Robertson, Claire E., Rodríguez-Pascual, Iván, Saikkonen, Teemu, Salvador-Ginez, Octavio, Sampaio, Waldir M., Santi, Gaia C., Santiago-Tovar, Natalia, Savage, David, Scheffer, Julian A., Schönegger, Philipp, Schultner, David T., Schutte, Enid M., Scott, Andy, Sharma, Madhavi, Sharma, Pujan, Skali, Ahmed, Stadelmann, David, Stafford, Clara Alexandra, Stanojević, Dragan, Stefaniak, Anna, Sternisko, Anni, Stoica, Agustin, Stoyanova, Kristina K., Strickland, Brent, Sundvall, Jukka, Thomas, Jeffrey P., Tinghög, Gustav, Torgler, Benno, Traast, Iris J., Tucciarelli, Raffaele, Tyrala, Michael, Ungson, Nick D., Uysal, Mete S., Van Lange, Paul A. M., Van Prooijen, Jan-Willem, Van Rooy, Dirk, Västfjäll, Daniel, Verkoeijen, Peter, Vieira, Joana B., Von Sikorski, Christian, Walker, Alexander Cameron, Watermeyer, Jennifer, Wetter, Erik, Whillans, Ashley, Willardt, Robin, Wohl, Michael J. A., Wójcik, Adrian Dominik, Wu, Kaidi, Yamada, Yuki, Yilmaz, Onurcan, Yogeeswaran, Kumar, Ziemer, Carolin-Theresa, Zwaan, Rolf A., Boggio, Paulo S., Van Bavel, Jay J., Cichocka, Aleksandra, Capraro, Valerio, Sjåstad, Hallgeir, Nezlek, John B., Pavlović, Tomislav, Alfano, Mark, Gelfand, Michele J., Azevedo, Flavio, Birtel, Michèle D., Cislak, Aleksandra, Lockwood, Patricia L., Ross, Robert Malcolm, Abts, Koen, Agadullina, Elena, Aruta, John Jamir Benzon, Besharati, Sahba Nomvula, Bor, Alexander, Choma, Becky L., Crabtree, Charles David, Cunningham, William A., De, Koustav, Ejaz, Waqa, Elbaek, Christian T., Findor, Andrej, Flichtentrei, Daniel, Franc, Renata, Gjoneska, Biljana, Gruber, June, Gualda, Estrella, Horiuchi, Yusaku, Huynh, Toan Luu Duc, Ibanez, Augustin, Imran, Mostak Ahamed, Israelashvili, Jacob, Jasko, Katarzyna, Kantorowicz, Jaroslaw, Kantorowicz-Reznichenko, Elena, Krouwel, André, Laakasuo, Michael, Lamm, Clau, Leygue, Caroline, Lin, Ming-Jen, Mansoor, Mohammad Sabbir, Marie, Antoine, Mayiwar, Lewend, Mazepus, Honorata, McHugh, Cillian, Minda, John Paul, Mitkidis, Panagioti, Olsson, Andrea, Otterbring, Tobia, Packer, Dominic J., Perry, Anat, Petersen, Michael Bang, Puthillam, Arathy, Riaño-Moreno, Julián C., Rothmund, Tobia, Santamaría-García, Hernando, Schmid, Petra C., Stoyanov, Drozdstoy, Tewari, Shruti, Todosijević, Bojan, Tsakiris, Mano, Tung, Hans H., Umbreș, Radu G., Vanags, Edmund, Vlasceanu, Madalina, Vonasch, Andrew, Yucel, Meltem, Zhang, Yucheng, Abad, Mohcine, Adler, Eli, Akrawi, Narin, Mdarhri, Hamza Alaoui, Amara, Hanane, Amodio, David M., Antazo, Benedict G., Apps, Matthew, Ay, F. Ceren, Ba, Mouhamadou Hady, Barbosa, Sergio, Bastian, Brock, Berg, Anton, Bernal-Zárate, Maria P., Bernstein, Michael, Białek, Michał, Bilancini, Ennio, Bogatyreva, Natalia, Boncinelli, Leonardo, Booth, Jonathan E., Borau, Sylvie, Buchel, Ondrej, Cameron, C. Daryl, Carvalho, Chrissie F., Celadin, Tatiana, Cerami, Chiara, Chalise, Hom Nath, Cheng, Xiaojun, Cian, Luca, Cockcroft, Kate, Conway, Jane, Córdoba-Delgado, Mateo Andre, Crespi, Chiara, Crouzevialle, Marie, Cutler, Jo, Cypryańska, Marzena, Dabrowska, Justyna, Daniels, Michael A., Davis, Victoria H., Dayley, Pamala N., Delouvee, Sylvain, Denkovski, Ognjan, Dezecache, Guillaume, Dhaliwal, Nathan A., Diato, Alelie B., Di Paolo, Roberto, Drosinou, Marianna, Dulleck, Uwe, Ekmanis, Jāni, Ertan, Arhan S., Etienne, Tom W., Farhana, Hapsa Hossain, Farkhari, Fahima, Farmer, Harry, Fenwick, Ali, Fidanovski, Kristijan, Flew, Terry, Fraser, Shona, Frempong, Raymond Boadi, Fugelsang, Jonathan A., Gale, Jessica, Garcia-Navarro, E. Begoña, Garladinne, Prasad, Ghajjou, Oussama, Gkinopoulos, Theofilo, Gray, Kurt, Griffin, Siobhán M., Gronfeldt, Bjarki, Gümren, Mert, Gurung, Ranju Lama, Halperin, Eran, Harris, Elizabeth, Herzon, Volo, Hruška, Matej, Huang, Guanxiong, Hudecek, Matthias F. C., Isler, Ozan, Jangard, Simon, Jørgensen, Frederik J., Kachanoff, Frank, Kahn, John, Dangol, Apsara Katuwal, Keudel, Oleksandra, Koppel, Lina, Koverola, Mika, Kubin, Emily, Kunnari, Anton, Kutiyski, Yordan, Laguna, Oscar, Leota, Josh, Lermer, Eva, Levy, Jonathan, Levy, Neil, Li, Chunyun, Long, Elizabeth U., Longoni, Chiara, Maglić, Marina, McCashin, Darragh, Metcalf, Alexander L., Mikloušić, Igor, El Mimouni, Soulaimane, Miura, Asako, Molina-Paredes, Juliana, Monroy-Fonseca, César, Morales-Marente, Elena, Moreau, David, Muda, Rafał, Myer, Annalisa, Nash, Kyle, Nesh-Nash, Tarik, Nitschke, Jonas P., Nurse, Matthew S., Ohtsubo, Yohsuke, Oldemburgo de Mello, Victoria, O’Madagain, Cathal, Onderco, Michal, Palacios-Galvez, M. Soledad, Palomäki, Jussi, Pan, Yafeng, Papp, Zsófia, Pärnamets, Philip, Paruzel-Czachura, Mariola, Pavlović, Zoran, Payán-Gómez, César, Perander, Silva, Pitman, Michael Mark, Prasad, Rajib, Pyrkosz-Pacyna, Joanna, Rathje, Steve, Raza, Ali, Rêgo, Gabriel G., Rhee, Kasey, Robertson, Claire E., Rodríguez-Pascual, Iván, Saikkonen, Teemu, Salvador-Ginez, Octavio, Sampaio, Waldir M., Santi, Gaia C., Santiago-Tovar, Natalia, Savage, David, Scheffer, Julian A., Schönegger, Philipp, Schultner, David T., Schutte, Enid M., Scott, Andy, Sharma, Madhavi, Sharma, Pujan, Skali, Ahmed, Stadelmann, David, Stafford, Clara Alexandra, Stanojević, Dragan, Stefaniak, Anna, Sternisko, Anni, Stoica, Augustin, Stoyanova, Kristina K., Strickland, Brent, Sundvall, Jukka, Thomas, Jeffrey P., Tinghög, Gustav, Torgler, Benno, Traast, Iris J., Tucciarelli, Raffaele, Tyrala, Michael, Ungson, Nick D., Uysal, Mete S., Van Lange, Paul A. M., van Prooijen, Jan-Willem, van Rooy, Dirk, Västfjäll, Daniel, Verkoeijen, Peter, Vieira, Joana B., von Sikorski, Christian, Walker, Alexander Cameron, Watermeyer, Jennifer, Wetter, Erik, Whillans, Ashley, Willardt, Robin, Wohl, Michael J. A., Wójcik, Adrian Dominik, Wu, Kaidi, Yamada, Yuki, Yilmaz, Onurcan, Yogeeswaran, Kumar, Ziemer, Carolin-Theresa, Zwaan, Rolf A., Boggio, Paulo S., Department of Digital Humanities, Faculty Common Matters (Faculty of Arts), Cognitive Science, Helsinki Research Hub on Religion, Media and Social Change, Helsinki Social Computing Group, Doctoral Programme in Cognition, Learning, Instruction and Communication, Mind and Matter, High Performance Cognition group, Medicum, Digital Humanities, Law and Economics, Pharmacy, Public Administration, Molecular Genetics, Research Methods and Techniques, Brain and Cognition, Van Bavel, Jay J [0000-0002-2520-0442], Cichocka, Aleksandra [0000-0003-1703-1586], Sjåstad, Hallgeir [0000-0002-8730-1038], Nezlek, John B [0000-0003-4963-3637], Pavlović, Tomislav [0000-0002-4470-3715], Alfano, Mark [0000-0001-5879-8033], Azevedo, Flavio [0000-0001-9000-8513], Cislak, Aleksandra [0000-0002-9880-6947], Lockwood, Patricia L [0000-0001-7195-9559], Ross, Robert Malcolm [0000-0001-8711-1675], Abts, Koen [0000-0001-8546-8347], Agadullina, Elena [0000-0002-1505-1412], Aruta, John Jamir Benzon [0000-0003-4155-1063], Besharati, Sahba Nomvula [0000-0003-2836-7982], Bor, Alexander [0000-0002-2624-9221], Crabtree, Charles David [0000-0001-5144-8671], De, Koustav [0000-0001-9562-0672], Ejaz, Waqas [0000-0002-2492-4115], Elbaek, Christian T [0000-0002-7039-4565], Findor, Andrej [0000-0002-5896-6989], Franc, Renata [0000-0002-1909-2393], Gjoneska, Biljana [0000-0003-1200-6672], Huynh, Toan Luu Duc [0000-0002-1486-127X], Ibanez, Augustin [0000-0001-6758-5101], Imran, Mostak Ahamed [0000-0002-5101-3149], Kantorowicz, Jaroslaw [0000-0002-1186-5427], Krouwel, André [0000-0003-0952-6028], Laakasuo, Michael [0000-0003-2826-6073], Lamm, Claus [0000-0002-5422-0653], Leygue, Caroline [0000-0002-0355-1030], Lin, Ming-Jen [0000-0002-7174-2226], Mansoor, Mohammad Sabbir [0000-0002-6541-3506], Marie, Antoine [0000-0002-7958-0153], McHugh, Cillian [0000-0002-9701-3232], Minda, John Paul [0000-0002-4081-010X], Mitkidis, Panagiotis [0000-0002-9495-7369], Olsson, Andreas [0000-0001-5272-7744], Otterbring, Tobias [0000-0002-0283-8777], Perry, Anat [0000-0003-2329-856X], Petersen, Michael Bang [0000-0002-6782-5635], Riaño-Moreno, Julián C [0000-0003-4182-0550], Rothmund, Tobias [0000-0003-2979-5129], Schmid, Petra C [0000-0002-9990-5445], Stoyanov, Drozdstoy [0000-0002-9975-3680], Todosijević, Bojan [0000-0002-6116-993X], Tsakiris, Manos [0000-0001-7753-7576], Tung, Hans H [0000-0001-5332-7582], Vanags, Edmunds [0000-0003-1932-936X], Vlasceanu, Madalina [0000-0003-2138-1968], Yucel, Meltem [0000-0002-7274-5971], Zhang, Yucheng [0000-0001-9435-6734], Abad, Mohcine [0000-0002-4964-5411], Mdarhri, Hamza Alaoui [0000-0001-9831-6561], Amara, Hanane [0000-0003-0732-2320], Antazo, Benedict G [0000-0001-9993-8960], Apps, Matthew [0000-0001-5793-2202], Barbosa, Sergio [0000-0003-1989-158X], Bastian, Brock [0000-0003-4619-3322], Bernal-Zárate, Maria P [0000-0001-8232-6220], Białek, Michał [0000-0002-5062-5733], Boncinelli, Leonardo [0000-0003-0626-5133], Booth, Jonathan E [0000-0002-8563-4613], Borau, Sylvie [0000-0003-1564-0695], Buchel, Ondrej [0000-0002-0139-5513], Chalise, Hom Nath [0000-0002-9301-6890], Cian, Luca [0000-0002-8051-1366], Cockcroft, Kate [0000-0002-6166-8050], Conway, Jane [0000-0003-3883-349X], Córdoba-Delgado, Mateo Andres [0000-0002-2264-7388], Crouzevialle, Marie [0000-0002-5538-6030], Cutler, Jo [0000-0003-1073-764X], Dabrowska, Justyna [0000-0002-8821-7161], Davis, Victoria H [0000-0002-7207-4629], Dayley, Pamala N [0000-0001-8955-9502], Delouvee, Sylvain [0000-0002-4029-597X], Di Paolo, Roberto [0000-0002-6081-6656], Dulleck, Uwe [0000-0002-0953-5963], Ekmanis, Jānis [0000-0003-1781-1785], Etienne, Tom W [0000-0002-4299-6593], Farkhari, Fahima [0000-0002-8484-5128], Farmer, Harry [0000-0002-3684-0605], Fenwick, Ali [0000-0002-5412-9745], Flew, Terry [0000-0003-4485-9338], Frempong, Raymond Boadi [0000-0002-4603-5570], Gale, Jessica [0000-0001-5677-8629], Garcia-Navarro, E Begoña [0000-0001-6913-8882], Ghajjou, Oussama [0000-0002-2975-0265], Griffin, Siobhán M [0000-0002-3613-2844], Halperin, Eran [0000-0002-3379-2935], Herzon, Volo [0000-0001-7781-1651], Huang, Guanxiong [0000-0002-8588-1454], Hudecek, Matthias FC [0000-0002-7696-766X], Isler, Ozan [0000-0002-4638-2230], Jangard, Simon [0000-0002-7876-4161], Jørgensen, Frederik J [0000-0002-5461-912X], Kahn, John [0000-0002-0548-3123], Koppel, Lina [0000-0002-6302-0047], Koverola, Mika [0000-0001-8227-6120], Leota, Josh [0000-0002-7714-4630], Lermer, Eva [0000-0002-6600-9580], Maglić, Marina [0000-0002-6851-4601], Metcalf, Alexander L [0000-0001-9532-585X], Miura, Asako [0000-0002-7563-7503], Monroy-Fonseca, César [0000-0003-4696-8159], Morales-Marente, Elena [0000-0002-1227-9606], Moreau, David [0000-0002-1957-1941], Nesh-Nash, Tarik [0000-0002-5532-9095], Nitschke, Jonas P [0000-0002-3244-8585], Nurse, Matthew S [0000-0003-1787-5914], Palomäki, Jussi [0000-0001-6063-0926], Pan, Yafeng [0000-0002-5633-8313], Pavlović, Zoran [0000-0002-9231-5100], Payán-Gómez, César [0000-0002-0633-1332], Perander, Silva [0000-0001-6711-8079], Pitman, Michael Mark [0000-0001-5532-5388], Pyrkosz-Pacyna, Joanna [0000-0002-9112-8629], Raza, Ali [0000-0002-2438-6054], Rhee, Kasey [0000-0002-8562-0801], Rodríguez-Pascual, Iván [0000-0002-5385-3643], Saikkonen, Teemu [0000-0001-9619-3270], Sampaio, Waldir M [0000-0002-6066-4314], Schönegger, Philipp [0000-0001-9930-487X], Schultner, David T [0000-0003-2253-4065], Scott, Andy [0000-0002-3294-0078], Skali, Ahmed [0000-0002-4753-3280], Stadelmann, David [0000-0002-1211-9936], Stafford, Clara Alexandra [0000-0003-1716-7870], Stanojević, Dragan [0000-0002-3667-2461], Stefaniak, Anna [0000-0002-1706-7784], Sternisko, Anni [0000-0002-2507-3076], Stoica, Augustin [0000-0003-0585-1114], Sundvall, Jukka [0000-0003-4310-1162], Tinghög, Gustav [0000-0002-8159-1249], Torgler, Benno [0000-0002-9809-963X], Tucciarelli, Raffaele [0000-0002-0342-308X], Tyrala, Michael [0000-0001-5268-8319], Van Lange, Paul AM [0000-0001-7774-6984], van Prooijen, Jan-Willem [0000-0001-6236-0819], Västfjäll, Daniel [0000-0003-2873-4500], von Sikorski, Christian [0000-0002-3787-8277], Walker, Alexander Cameron [0000-0003-1431-6770], Watermeyer, Jennifer [0000-0001-7918-8832], Whillans, Ashley [0000-0002-1726-6978], Willardt, Robin [0000-0002-2495-3450], Wohl, Michael JA [0000-0001-6945-5562], Wójcik, Adrian Dominik [0000-0002-7073-6019], Wu, Kaidi [0000-0001-6881-7437], Yamada, Yuki [0000-0003-1431-568X], Yilmaz, Onurcan [0000-0002-6094-7162], Ziemer, Carolin-Theresa [0000-0002-0794-7702], Apollo - University of Cambridge Repository, Communication Science, Network Institute, Communication Choices, Content and Consequences (CCCC), Social Psychology, IBBA, A-LAB, New York University [New York] (NYU), NYU System (NYU), University of Kent [Canterbury], Middlesex University [London], Norwegian School of Economics and Business Administration, SWPS University of Social Sciences and Humanities (SWPS), College of William and Mary [Williamsburg] (WM), Ivo Pilar Institute of Social Sciences, Macquarie University, Stanford University, Friedrich-Schiller-Universität = Friedrich Schiller University Jena [Jena, Germany], University of Greenwich, University of Oxford, University of Birmingham [Birmingham], Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Vysšaja škola èkonomiki = National Research University Higher School of Economics [Moscow] (HSE), De La Salle University [Manila] (DLSU), University of the Witwatersrand [Johannesburg] (WITS), Aarhus University [Aarhus], University of Toronto, Dartmouth College [Hanover], University of Kentucky (UK), National University of Sciences and Technology [Islamabad] (NUST), Comenius University in Bratislava, IntraMed, Buenos Aires, DF, Argentina, Macedonian Academy of Sciences and Arts [Skopje, North Macedonia] (MASA), University of Colorado [Boulder], Universidad de Huelva, WHU-Otto Beisheim School of Management, University Adolfo Ibanez (Santiago), University of Dhaka, The Hebrew University of Jerusalem (HUJ), Uniwersytet Jagielloński w Krakowie = Jagiellonian University (UJ), Universiteit Leiden, Erasmus University Rotterdam, Vrije Universiteit Amsterdam [Amsterdam] (VU), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, University of Vienna [Vienna], Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), National Taiwan University [Taiwan] (NTU), Tribhuvan University, BI Norwegian Business School [Oslo], University of Limerick (UL), University of Western Ontario (UWO), Duke University [Durham], Karolinska Institute, University of Agder (UIA), Lehigh University [Bethlehem], Monk Prayogshala, Cooperative University of Colombia, Pontificia Universidad Javeriana (PUJ), Department of Management, Technology, and Economics [ETH Zürich] (D-MTEC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Medical University of Plovdiv, Indian Institute of Management Indore (IMM Indore), Institute of Social Sciences Belgrade, University of London [London], University of Luxembourg [Luxembourg], National School of Political and Administrative Studies (SNSPA), University of Latvia (LU), Princeton University, University of Canterbury [Christchurch], University of Virginia, Hebei University of Technology [Tianjin], Université Mohammed VI Polytechnique [Ben Guerir] (UM6P), Institute for Research and Development-Kurdistan, University of Amsterdam [Amsterdam] (UvA), Jose Rizal Memorial State University, Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD), Universidad del Rosario [Bogota], University of Melbourne, Penn State Abington, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Penn State System, University of Wrocław [Poland] (UWr), IMT Alti Studi Lucca, Università degli Studi di Firenze = University of Florence (UniFI), London School of Economics and Political Science (LSE), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Tilburg University [Tilburg], Netspar, Pennsylvania State University (Penn State), Penn State System, Universidade Federal de Santa Catarina = Federal University of Santa Catarina [Florianópolis] (UFSC), University of Bologna/Università di Bologna, Istituto Universitario di Studi Superiori (IUSS), Shenzhen University [Shenzhen], Institute for Advanced Study in Toulouse (IAST), Università degli Studi di Pavia = University of Pavia (UNIPV), Cracow University of Economics, University of British Columbia (UBC), University of California [Los Angeles] (UCLA), University of California (UC), Laboratoire de Psychologie : Cognition, Comportement, Communication (LP3C - EA1285), Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Université de Rennes 2 (UR2)-Institut Brestois des Sciences de l'Homme et de la Société (IBSHS), Université de Brest (UBO), Laboratoire de Psychologie Sociale et Cognitive (LAPSCO), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), University of British Columbia [Vancouver], Cavite State University-General Trias City Campus, School for Advanced Studies Lucca (IMT), Queensland University of Technology [Brisbane] (QUT), Australian National University (ANU), Boǧaziçi üniversitesi = Boğaziçi University [Istanbul], Kieskompas, Hult International Business School Dubai, The University of Sydney, University of Bayreuth, University of Waterloo [Waterloo], University of Bradford, University of Crete [Heraklion] (UOC), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Koç University, City University of Hong Kong [Hong Kong] (CUHK), University of Regensburg, Universität Duisburg-Essen = University of Duisburg-Essen [Essen], Free University of Berlin (FU), Linköping University (LIU), University of Koblenz-Landau, University of Alberta, Ludwig Maximilian University [Munich] (LMU), Interdisciplinary Center Herzliya (IDC), Aalto University, Macquarie University [Sydney], Boston University [Boston] (BU), Dublin City University [Dublin] (DCU), University of Montana, Osaka University [Osaka], SEELE Neuroscience, University of Auckland [Auckland], Maria Curie-Sklodowska University (UMCS), CUNY Graduate Center (The Graduate Center), City University of New York [New York] (CUNY), The University of Tokyo (UTokyo), Mohammed VI Polytechnic University, Hungarian Academy of Sciences (MTA), Medical University of Silesia (SUM), University of Belgrade [Belgrade], Vidyasagar College For Women, AGH University of Science and Technology [Krakow, PL] (AGH UST), University of Cambridge [UK] (CAM), Mackenzie Presbyterian University [São Paulo] (UPM), University of Turku, University of Newcastle [Callaghan, Australia] (UoN), University of St Andrews [Scotland], University of Groningen [Groningen], Carleton University, National University of Political Studies and Public Administration Bucharest, Romania (SNSPA), University of Plovdiv, Institut Jean-Nicod (IJN), Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École des hautes études en sciences sociales (EHESS)-Collège de France (CdF (institution))-Centre National de la Recherche Scientifique (CNRS)-Département de Philosophie - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Center for Research in Economics, Management and the Arts (CREMA), Partenaires INRAE, University College of London [London] (UCL), The Hong Kong University of Science and Technology, Susquehanna University, Dokuz Eylül Üniversitesi = Dokuz Eylül University [Izmir] (DEÜ), Stockholm School of Economics (SSE), Harvard Business School, Harvard University, Nicolaus Copernicus University [Toruń], University of California [San Diego] (UC San Diego), Kyushu University, Kadir Has University (KHAS), Van Bavel, Jay J. [0000-0002-2520-0442], Nezlek, John B. [0000-0003-4963-3637], Lockwood, Patricia L. [0000-0001-7195-9559], Elbaek, Christian T. [0000-0002-7039-4565], Ibanez, Agustin [0000-0001-6758-5101], Riaño-Moreno, Julián C. [0000-0003-4182-0550], Schmid, Petra C. [0000-0002-9990-5445], Tung, Hans H. [0000-0001-5332-7582], Antazo, Benedict G. [0000-0001-9993-8960], Bernal-Zárate, Maria P. [0000-0001-8232-6220], Booth, Jonathan E. [0000-0002-8563-4613], Davis, Victoria H. [0000-0002-7207-4629], Dayley, Pamala N. [0000-0001-8955-9502], Etienne, Tom W. [0000-0002-4299-6593], Garcia-Navarro, E. Begoña [0000-0001-6913-8882], Griffin, Siobhán M. [0000-0002-3613-2844], Hudecek, Matthias F. C. [0000-0002-7696-766X], Jørgensen, Frederik J. [0000-0002-5461-912X], Metcalf, Alexander L. [0000-0001-9532-585X], Nitschke, Jonas P. [0000-0002-3244-8585], Nurse, Matthew S. [0000-0003-1787-5914], Sampaio, Waldir M. [0000-0002-6066-4314], Schultner, David T. [0000-0003-2253-4065], Stoica, Agustin [0000-0003-0585-1114], Van Lange, Paul A. M. [0000-0001-7774-6984], Wohl, Michael J. A. [0000-0001-6945-5562], New York University, University of Kent, Middlesex University, Norwegian School of Economics, College of William and Mary, Institute of Social Sciences Ivo Pilar, Friedrich Schiller University Jena, SWPS University of Social Sciences and Humanities, KU Leuven, Higher School of Economics, De La Salle University Manila, University of the Witwatersrand, Aarhus University, X University, Dartmouth College, University of Kentucky, National University of Sciences and Technology Pakistan, IntraMed, Macedonian Academy of Sciences and Arts, University of Colorado Boulder, University of Huelva, Otto Beisheim School of Management, Universidad Adolfo Ibáñez, Hebrew University of Jerusalem, Jagiellonian University in Kraków, Leiden University, Vrije Universiteit Amsterdam, University of Helsinki, University of Vienna, Universidad Nacional Autónoma de México, National Taiwan University, BI Norwegian Business School, University of Limerick, Western University, Karolinska Institutet, University of Agder, Lehigh University, Universidad Cooperativa de Colombia, Universidad Javeriana, Swiss Federal Institute of Technology Zurich, Indian Institute of Management Indore, Institute of Social Sciences, Royal Holloway University of London, University of Latvia, University of Canterbury, Duke University, Hebei University of Technology, University of Kurdistan, Impact For Development, Jose Rizal University, University of Birmingham, Université Cheikh Anta Diop de Dakar, Universidad del Rosario, Pennsylvania State University, University of Wrocław, IMT Institute for Advanced Studies Lucca, University of Florence, Birkbeck University of London, Toulouse Business School, Tilburg University, Universidade Federal de Santa Catarina, Universita di Bologna, University of Pavia, Shenzhen University, Université Toulouse 1 Capitole, IRCCS Fondazione Istituto Neurologico Casimiro Mondino - Pavia, University of British Columbia, University of California Los Angeles, University of Rennes 2, University of Amsterdam, Université Clermont Auvergne, Cavite State University, Queensland University of Technology, Bogazici University, University of Sydney, University of Waterloo, University of North Carolina at Chapel Hill, Koc University, City University of Hong Kong, Free University of Berlin, Linköping University, Ludwig Maximilian University of Munich, Department of Neuroscience and Biomedical Engineering, Boston University, Dublin City University, Osaka University, University of Auckland, Maria Curie-Sklodowska University, Australian National University, The University of Tokyo, Hungarian Academy of Sciences, University of Silesia in Katowice, University of Belgrade, University of Calcutta, AGH University of Science and Technology, University of Cambridge, Universidade Presbiteriana Mackenzie, University of Newcastle, University of St Andrews, University of Groningen, National School of Political and Administrative Studies, University College London, Hong Kong University of Science and Technology, Dokuz Eylul University, Stockholm School of Economics, Nicolaus Copernicus University in Toruń, University of California San Diego, Kadir Has University, Aalto-yliopisto, University of St Andrews. School of International Relations, University of St Andrews. School of Psychology and Neuroscience, Van Bavel, J, Cichocka, A, Capraro, V, Sjastad, H, Nezlek, J, Pavlovic, T, Alfano, M, Gelfand, M, Azevedo, F, Birtel, M, Cislak, A, Lockwood, P, Ross, R, Abts, K, Agadullina, E, Aruta, J, Besharati, S, Bor, A, Choma, B, Crabtree, C, Cunningham, W, De, K, Ejaz, W, Elbaek, C, Findor, A, Flichtentrei, D, Franc, R, Gjoneska, B, Gruber, J, Gualda, E, Horiuchi, Y, Huynh, T, Ibanez, A, Imran, M, Israelashvili, J, Jasko, K, Kantorowicz, J, Kantorowicz-Reznichenko, E, Krouwel, A, Laakasuo, M, Lamm, C, Leygue, C, Lin, M, Mansoor, M, Marie, A, Mayiwar, L, Mazepus, H, Mchugh, C, Minda, J, Mitkidis, P, Olsson, A, Otterbring, T, Packer, D, Perry, A, Petersen, M, Puthillam, A, Riano-Moreno, J, Rothmund, T, Santamaria-Garcia, H, Schmid, P, Stoyanov, D, Tewari, S, Todosijevic, B, Tsakiris, M, Tung, H, Umbres, R, Vanags, E, Vlasceanu, M, Vonasch, A, Yucel, M, Zhang, Y, Abad, M, Adler, E, Akrawi, N, Mdarhri, H, Amara, H, Amodio, D, Antazo, B, Apps, M, Ay, F, Ba, M, Barbosa, S, Bastian, B, Berg, A, Bernal-Zarate, M, Bernstein, M, Bialek, M, Bilancini, E, Bogatyreva, N, Boncinelli, L, Booth, J, Borau, S, Buchel, O, Cameron, C, Carvalho, C, Celadin, T, Cerami, C, Chalise, H, Cheng, X, Cian, L, Cockcroft, K, Conway, J, Cordoba-Delgado, M, Crespi, C, Crouzevialle, M, Cutler, J, Cypryanska, M, Dabrowska, J, Daniels, M, Davis, V, Dayley, P, Delouvee, S, Denkovski, O, Dezecache, G, Dhaliwal, N, Diato, A, Di Paolo, R, Drosinou, M, Dulleck, U, Ekmanis, J, Ertan, A, Etienne, T, Farhana, H, Farkhari, F, Farmer, H, Fenwick, A, Fidanovski, K, Flew, T, Fraser, S, Frempong, R, Fugelsang, J, Gale, J, Garcia-Navarro, E, Garladinne, P, Ghajjou, O, Gkinopoulos, T, Gray, K, Griffin, S, Gronfeldt, B, Gumren, M, Gurung, R, Halperin, E, Harris, E, Herzon, V, Hruska, M, Huang, G, Hudecek, M, Isler, O, Jangard, S, Jorgensen, F, Kachanoff, F, Kahn, J, Dangol, A, Keudel, O, Koppel, L, Koverola, M, Kubin, E, Kunnari, A, Kutiyski, Y, Laguna, O, Leota, J, Lermer, E, Levy, J, Levy, N, Li, C, Long, E, Longoni, C, Maglic, M, Mccashin, D, Metcalf, A, Miklousic, I, El Mimouni, S, Miura, A, Molina-Paredes, J, Monroy-Fonseca, C, Morales-Marente, E, Moreau, D, Muda, R, Myer, A, Nash, K, Nesh-Nash, T, Nitschke, J, Nurse, M, Ohtsubo, Y, Oldemburgo de Mello, V, O'Madagain, C, Onderco, M, Palacios-Galvez, M, Palomaki, J, Pan, Y, Papp, Z, Parnamets, P, Paruzel-Czachura, M, Pavlovic, Z, Payan-Gomez, C, Perander, S, Pitman, M, Prasad, R, Pyrkosz-Pacyna, J, Rathje, S, Raza, A, Rego, G, Rhee, K, Robertson, C, Rodriguez-Pascual, I, Saikkonen, T, Salvador-Ginez, O, Sampaio, W, Santi, G, Santiago-Tovar, N, Savage, D, Scheffer, J, Schonegger, P, Schultner, D, Schutte, E, Scott, A, Sharma, M, Sharma, P, Skali, A, Stadelmann, D, Stafford, C, Stanojevic, D, Stefaniak, A, Sternisko, A, Stoica, A, Stoyanova, K, Strickland, B, Sundvall, J, Thomas, J, Tinghog, G, Torgler, B, Traast, I, Tucciarelli, R, Tyrala, M, Ungson, N, Uysal, M, Van Lange, P, van Prooijen, J, van Rooy, D, Vastfjall, D, Verkoeijen, P, Vieira, J, von Sikorski, C, Walker, A, Watermeyer, J, Wetter, E, Whillans, A, Willardt, R, Wohl, M, Wojcik, A, Wu, K, Yamada, Y, Yilmaz, O, Yogeeswaran, K, Ziemer, C, Zwaan, R, and Boggio, P
Subjects: IMAGE, Health Behavior, COVID-19, national identity, public health, pandemic, cross-cultural, Collective narcissism, Settore SECS-P/02 - Politica Economica, health behavior, Sociology, RA0421 Public health. Hygiene. Preventive Medicine, Settore SECS-P/01 - Economia Politica, public health behaviours, COVID-19, collective behaviour, Public health, [SHS.SOCIO]Humanities and Social Sciences/Sociology, Social Identification, 706/689/477/2811, article, Social identity, Public Health, Global Health, Social Medicine and Epidemiology, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, 3142 Public health care science, environmental and occupational health, VDP::Medisinske Fag: 700::Helsefag: 800, 5141 Sociology, Settore SECS-P/03 - Scienza delle Finanze, National identity, Human, Cross-Cultural Comparison, BF Psychology, Science, COVID-19 pandemic, BF, national narcissism, HV Social pathology. Social and public welfare. Criminology, Humans, Leadership, Pandemics, Public Health, SARS-CoV-2, Self Report, Social Conformity, Human development, 692/699/255/2514, SDG 3 - Good Health and Well-being, Human behaviour, political ideology, COLLECTIVE NARCISSISM, SOCIAL IDENTITY, MCC, Pandemic, IDENTIFICATION, DAS, [SHS.SCIPO]Humanities and Social Sciences/Political science, Coronavirus, MODEL, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Viral infection, Idenfication, Image, RA Public aspects of medicine, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Human medicine, RA, Model
Abstract: Funder: Research Council of Norway through its Centres of Excellence Scheme, FAIR project No 262675, Funder: J. William Fulbright Program, Funder: Institute for Lifecourse Development, University of Greenwich, Funder: Economic Social Research Council Impact Acceleration Award, University of Oxford, Funder: Institute of Social Sciences Ivo Pilar, Funder: Academy of Finland (Suomen Akatemia); doi: https://doi.org/10.13039/501100002341, Funder: Universität Wien (University of Vienna); doi: https://doi.org/10.13039/501100003065, Funder: Ministry of Science and Technology, Taiwan (Ministry of Science and Technology of Taiwan); doi: https://doi.org/10.13039/501100004663, Funder: NOMIS Stiftung (NOMIS Foundation); doi: https://doi.org/10.13039/501100008483, Funder: Princeton Graduate Student Research Funding (Program in Cognitive Science), Funder: Corruption Laboratory on Ethics, Accountability, and the Rule of Law (CLEAR), University of Virginia, Funder: Project Pro.Co.P.E., IMT School (PAI2019), Funder: Italian Ministry of University and Research - PRIN 2017 (20178293XT), Funder: Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada); doi: https://doi.org/10.13039/501100000038, Funder: Australian Research Council (DP180102384), Funder: Ernst and Young (EY); doi: https://doi.org/10.13039/501100003064, Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.
Published: 2022

29. Optimal epidemic suppression under an ICU constraint: an analytical solution

Author: Laurent Miclo, Daniel Spiro, Jörgen Weibull, Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Uppsala University, Département d'Économie de l'École Polytechnique (X-DEP-ECO), École polytechnique (X), Department of Economics, Stockholm School of Economics (SSE/ECON), and Stockholm School of Economics (SSE)
Subjects: Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi, Economics and Econometrics, Suppression, Applied Mathematics, Epidemic, Health Care Service and Management, Health Policy and Services and Health Economy, JEL: D - Microeconomics/D.D6 - Welfare Economics, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Optimal control, JEL: I - Health, Education, and Welfare/I.I1 - Health/I.I1.I18 - Government Policy • Regulation • Public Health, JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C61 - Optimization Techniques • Programming Models • Dynamic Analysis, Health, Corona, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Infection
Abstract: How much and when should we limit economic and social activity to ensure that the healthcare system is not overwhelmed during an epidemic? We study a setting where ICU resources are constrained and suppression is costly. Providing a fully analytical solution we show that the common wisdom of "flattening the curve", where suppression measures are continuously taken to hold down the spread throughout the epidemic, is suboptimal. Instead, the optimal suppression is discontinuous. The epidemic should be left unregulated in a first phase and when the ICU constraint is approaching society should quickly lock down (a discontinuity). After the lockdown, regulation should gradually be lifted, holding the rate of infected constant, thus respecting the ICU resources while not unnecessarily limiting economic activity. In a final phase, regulation is lifted. We call this strategy "filling the box". The cost under the optimal strategy is obtained in closed form as an explicit function of economic and medical fundamentals. We show that the policy is optimal also when there, in addition, is a small cost associated with the number of infected. The tighter the ICU constraint, the wider is the range of such cost for which the policy is still optimal. This suggests the primary focus of poor countries (with few ICU resources) should be to protect the health-care system, while richer countries (with extensive ICU resources) may strive to reduce the number of infected even more. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Published: 2022

30. Dispersal syndromes in challenging environments: a cross‐species experiment

Author: Julien Cote, Maxime Dahirel, Nicolas Schtickzelle, Florian Altermatt, Armelle Ansart, Simon Blanchet, Alexis S. Chaine, Frederik De Laender, Jonathan De Raedt, Bart Haegeman, Staffan Jacob, Oliver Kaltz, Estelle Laurent, Chelsea J. Little, Luc Madec, Florent Manzi, Stefano Masier, Felix Pellerin, Frank Pennekamp, Lieven Therry, Alexandre Vong, Laurane Winandy, Dries Bonte, Emanuel A. Fronhofer, Delphine Legrand, Evolution et Diversité Biologique (EDB), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Universiteit Gent = Ghent University (UGENT), Université Catholique de Louvain = Catholic University of Louvain (UCL), Swiss Federal Insitute of Aquatic Science and Technology [Dübendorf] (EAWAG), Universität Zürich [Zürich] = University of Zurich (UZH), Station d'Ecologie Théorique et Expérimentale (SETE), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Agrobiosciences, Interactions et Biodiversité (FR AIB), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Namur [Namur] (UNamur), Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), ANR-10-LABX-0041,TULIP,Towards a Unified theory of biotic Interactions: the roLe of environmental(2010), ANR-11-INBS-0001,ANAEE-FR,ANAEE-Services(2011), European Project: ERC-2018-CoG-817779,ECOFEED, University of Zurich, Cote, Julien, and UCL - SST/ELI/ELIB - Biodiversity
Subjects: DYNAMICS, STRATEGIES, FITNESS, UFSP13-8 Global Change and Biodiversity, Evolution, context-dependent dispersal, context, 10127 Institute of Evolutionary Biology and Environmental Studies, MOVEMENT, Behavior and Systematics, Distributed experiment, predation risk, Animals, resource limitation, HETEROGENEITY, dispersal strategy, Ecology, Evolution, Behavior and Systematics, Ecosystem, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Ecology, dependent dispersal, Biology and Life Sciences, Syndrome, Biological Evolution, distributed experiment, Resource limitation, 1105 Ecology, Evolution, Behavior and Systematics, Phenotype, Context- dependent dispersal, 570 Life sciences, biology, 590 Animals (Zoology), Predation risk, Dispersal strategy, BEHAVIOR
Abstract: Dispersal is a central biological process tightly integrated into life-histories, morphology, physiology and behaviour. Such associations, or syndromes, are anticipated to impact the eco-evolutionary dynamics of spatially structured populations, and cascade into ecosystem processes. As for dispersal on its own, these syndromes are likely neither fixed nor random, but conditional on the experienced environment. We experimentally studied how dispersal propensity varies with individuals' phenotype and local environmental harshness using 15 species ranging from protists to vertebrates. We reveal a general phenotypic dispersal syndrome across studied species, with dispersers being larger, more active and having a marked locomotion-oriented morphology and a strengthening of the link between dispersal and some phenotypic traits with environmental harshness. Our proof-of-concept metacommunity model further reveals cascading effects of context-dependent syndromes on the local and regional organisation of functional diversity. Our study opens new avenues to advance our understanding of the functioning of spatially structured populations, communities and ecosystems.
Published: 2022

31. Climate adaptive response of rice yield in Vietnam: new insight through panel data modeling with heterogeneous slopes

Author: Nguyen, Thanh Viet, Michel, Simioni, Vo, Hung Trung, Perez, Isabelle, University of Akureyi, Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) (UMR MoISA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Thu Dau Mot University, and Partenaires INRAE
Subjects: JEL: C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C23 - Panel Data Models • Spatio-temporal Models, Vietnam, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q1 - Agriculture/Q.Q1.Q15 - Land Ownership and Tenure • Land Reform • Land Use • Irrigation • Agriculture and Environment, Large panel data, Mean observation, Climate change, Adaptation, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q5 - Environmental Economics/Q.Q5.Q54 - Climate • Natural Disasters and Their Management • Global Warming, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q5 - Environmental Economics/Q.Q5.Q55 - Technological Innovation, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, [SHS.ECO] Humanities and Social Sciences/Economics and Finance, Rice yield, JEL: D - Microeconomics/D.D2 - Production and Organizations/D.D2.D24 - Production • Cost • Capital • Capital, Total Factor, and Multifactor Productivity • Capacity
Abstract: International audience; Rice production is central to the Vietnamese economy, not only in terms of contribution to Vietnam's GDP, but also to the food security of its population. However, Vietnam is one of the countries most threatened by climate change in the coming decades, and its rice production in particular. This paper focuses on rice yields and investigates their evolution over time and between provinces over the period 1987-2015, depending on climatic conditions. Special attention is devoted to the impact of heat stress. This impact is measured taking into account the potential adaptation of farmers to these extreme events. To this end, a dynamic production function allowing for spatial and temporal heterogeneity in rice yield responses of to climatic conditions is estimated. Data descriptive analysis shows that the provinces with favorable conditions for rice growth are also those that face the most risk of heat stress. Estimation results show that these provinces adapt to heat stress conditions and that their adaptation eort begins to decrease when heat stress risk becomes too high. Taking adaptation into account then makes it possible to qualify the forecasts made regarding rice yields in the presence of climate change.
Published: 2022

32. Fairness in Machine Learning and Econometrics

Author: Centorrino, Samuele, Florens, Jean-Pierre, Loubès, Jean-Michel, Chan, Felix, Mátyás, László, Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Mathématiques de Toulouse UMR5219 (IMT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Curtin University [Perth], Planning and Transport Research Centre (PATREC), and Central European University [Budapest, Hongrie] (CEU)
Subjects: [SHS.ECO]Humanities and Social Sciences/Economics and Finance
Abstract: National audience; A supervised machine learning algorithm determines a model from a learning sample that will be used to predict new observations. To this end, it aggregates individual characteristics of the observations of the learning sample. But this information aggregation does not consider any potential selection on unobservables and any status quo biases which may be contained in the training sample. The latter bias has raised concerns around the so-called fairness of machine learning algorithms, especially towards disadvantaged groups. In this chapter, we review the issue of fairness in machine learning through the lenses of structural econometrics models in which the unknown index is the solution of a functional equation and issues of endogeneity are explicitly taken into account. We model fairness as a linear operator whose null space contains the set of strictly fair indexes. A fair solution is obtained by projecting the unconstrained index into the null space of this operator or by directly finding the closest solution of the functional equation into this null space.We also acknowledge that policymakers may incur costs when moving away from the status quo. Approximate fairness is thus introduced as an intermediate set-up between the status quo and a fully fair solution via a fairness-specific penalty in the objective function of the learning model.
Published: 2022

33. Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models

Author: Stéphane Girard, Gilles Stupfler, Antoine Usseglio-Carleve, IUT Avignon-Département Statistique et Traitement Informatique des Données (STID-IUT Avignon), Avignon Université (AU), Modèles statistiques bayésiens et des valeurs extrêmes pour données structurées et de grande dimension (STATIFY), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Centre de Recherche en Economie et Statistique [Bruz] (CREST), Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] (ENSAI), Chaire Stress Test - BNP Paribas/Ecole polytechnique/Fondation de l'X., ANR-15-IDEX-0002,UGA,IDEX UGA(2015), Laboratoire Jean Kuntzmann (LJK), Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Chair Stress Test, led by the French École Polytechnique and its Foundation and sponsored by BNP Paribas, AXA Research Fund Award on 'Mitigating risk in the wake of the COVID-19 pandemic', ANR-19-CE40-0013,ExtremReg,Régression extrême avec applications à l'économétrie, l'environnement et à la finance(2019), ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017), Girard, Stephane, IDEX UGA - - UGA2015 - ANR-15-IDEX-0002 - IDEX - VALID, Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI), Ensai, Ecole Nationale de la Statistique et de l'Analyse de l'Information, This research was supported by the French National Research Agency under the grant ANR-19-CE40-0013/ExtremReg project. S. Girard gratefully acknowledges the support of the Chair Stress Test, led by the French Ecole Polytechnique and its Foundation and sponsored by BNP Paribas, and the support of the French National Research Agency in the framework of the Investissements d’Avenir program (ANR-15-IDEX02)., ANR-15-IDEX-02,UGA,IDEX UGA(2016), and ANR-19-CE40-0013,ExtremReg,Extremal Regression with Applications to Econometrics, Environment and Finance(2019)
Subjects: Statistics and Probability, Expectiles, 05 social sciences, Tail empirical process of residuals, Regression models, Heteroscedasticity, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, 01 natural sciences, 010104 statistics & probability, heteroscedas- ticity, Single-indes model, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], single-index model, Residual-based estimators, 0502 economics and business, Heavy-tailed distribution, Statistics::Methodology, 0101 mathematics, Statistics, Probability and Uncertainty, Extreme value analysis, B- ECONOMIE ET FINANCE, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], 050205 econometrics
Abstract: Expectiles define a least squares analogue of quantiles. They have been the focus of a substantial quantity of research in the context of actuarial and financial risk assessment over the last 10 years. Unlike quantiles, expectiles induce coherent risk measures and are calculated using tail expectations rather than merely tail probabilities ; contrary to the popular quantile-based Expected Shortfall, they define elicitable risk measures. The behaviour and estimation of extreme expectiles using independent and identically distributed heavy-tailed observations has been investigated in a recent series of papers. The case of extreme conditional expectile estimation has, however, not been addressed so far in the literature. We build here a general theory for the estimation of extreme conditional expectiles in heteroscedastic regression models with heavy-tailed noise; an important feature of our approach is that it is intended to cope with covariates having a large but fixed dimension. We demonstrate how our results can be applied to a wide class of important examples, among which linear heteroscedastic models, heteroscedastic single-index models and autoregressive time series models. Our estimators are showcased on a numerical simulation study, as well as on real sets of actuarial and financial data.
Published: 2021

34. Nonstochastic Bandits with Composite Anonymous Feedback

Author: Cesa-Bianchi, Nicolò, Cesari, Tommaso, Colomboni, Roberto, Gentile, Claudio, Mansour, Yishay, Cesari, Tommaso, Artificial and Natural Intelligence Toulouse Institute - - ANITI2019 - ANR-19-P3IA-0004 - P3IA - VALID, Au delà de l'apprentissage séquentiel pour de meilleures prises de décisions - - BOLD2019 - ANR-19-CE23-0026 - AAPG2019 - VALID, Dipartimento di Informatica, Università degli Studi di Milano, Italy (UNIMI), Institut de Mathématiques de Toulouse UMR5219 (IMT), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Instituto Italiano di Tecnologia (IIT), Ministero dell'Istruzione-Ministero dell'Economia e Finanze, Google Research, Tel Aviv University [Tel Aviv], ANR-19-P3IA-0004,ANITI,Artificial and Natural Intelligence Toulouse Institute(2019), ANR-19-CE23-0026,BOLD,Au delà de l'apprentissage séquentiel pour de meilleures prises de décisions(2019), Università degli Studi di Milano = University of Milan (UNIMI), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Tel Aviv University (TAU)
Subjects: FOS: Computer and information sciences, Non-stochastic losses, Computer Science - Machine Learning, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Settore INF/01 - Informatica, Online learning, Multi-armed bandits, non-stochastic losses, composite losses, delayed feedback, online learning, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], Composite losses, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning, Delayed feedback, Machine Learning (cs.LG)
Abstract: We investigate a nonstochastic bandit setting in which the loss of an action is not immediately charged to the player, but rather spread over the subsequent rounds in an adversarial way. The instantaneous loss observed by the player at the end of each round is then a sum of many loss components of previously played actions. This setting encompasses as a special case the easier task of bandits with delayed feedback, a well-studied framework where the player observes the delayed losses individually. Our first contribution is a general reduction transforming a standard bandit algorithm into one that can operate in the harder setting: We bound the regret of the transformed algorithm in terms of the stability and regret of the original algorithm. Then, we show that the transformation of a suitably tuned FTRL with Tsallis entropy has a regret of order $\sqrt{(d+1)KT}$, where $d$ is the maximum delay, $K$ is the number of arms, and $T$ is the time horizon. Finally, we show that our results cannot be improved in general by exhibiting a matching (up to a log factor) lower bound on the regret of any algorithm operating in this setting.
Published: 2021

35. Bayesian Inference for Parametric Growth Incidence Curves

Author: Edwin Fourrier-Nicolai, Michel Lubrano, Aix-Marseille Sciences Economiques (AMSE), École des hautes études en sciences sociales (EHESS)-Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), School of Economics, Jiangxi University of Finance and Economics, ANR-17-EURE-0020,AMSE (EUR),Aix-Marseille School of Economics(2017), ANR-11-IDEX-0001,Amidex,INITIATIVE D'EXCELLENCE AIX MARSEILLE UNIVERSITE(2011), Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Lhuillier, Elisabeth, Aix-Marseille School of Economics - - AMSE (EUR)2017 - ANR-17-EURE-0020 - EURE - VALID, INITIATIVE D'EXCELLENCE AIX MARSEILLE UNIVERSITE - - Amidex2011 - ANR-11-IDEX-0001 - IDEX - VALID, and Sanghamitra Bandyopadhyay
Subjects: JEL: I - Health, Education, and Welfare/I.I3 - Welfare, Well-Being, and Poverty/I.I3.I31 - General Welfare, Well-Being, Bayesian inference, Monte Carlo method, 1. No poverty, Estimator, Lorenz curves, Quantile function, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Mixture model, JEL: C - Mathematical and Quantitative Methods/C.C1 - Econometric and Statistical Methods and Methodology: General/C.C1.C11 - Bayesian Analysis: General, JEL: D - Microeconomics/D.D3 - Distribution/D.D3.D31 - Personal Income, Wealth, and Their Distributions, Inequality, Distributional changes, Parametric model, Growth incidence curve, Applied mathematics, Mixtures of log-normals, Lorenz curve, [SHS.ECO] Humanities and Social Sciences/Economics and Finance, 10. No inequality, Mathematics, Parametric statistics
Abstract: International audience; The growth incidence curve of Ravallion and Chen (2003) is based on the quantile function. Its distribution-free estimator behaves erratically with usual sample sizes leading to problems in the tails. The authors propose a series of parametric models in a Bayesian framework. A first solution consists in modeling the underlying income distribution using simple densities for which the quantile function has a closed analytical form. This solution is extended by considering a mixture model for the underlying income distribution. However, in this case, the quantile function is semi-explicit and has to be evaluated numerically. The last solution consists in adjusting directly a functional form for the Lorenz curve and deriving its first-order derivative to find the corresponding quantile function. The authors compare these models by Monte Carlo simulations and using UK data from the Family Expenditure Survey. The authors devote a particular attention to the analysis of subgroups.
Published: 2021

36. Climate change in Viet Nam, impacts and adaptation: a COP26 assessment report of the GEMMES Viet Nam project

Author: Espagne, Etienne, Nguyen, Manh-Hung, Centre d'Études et de Recherches sur le Développement International (CERDI), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), AFD - Agence Française de Développement, and IRD - Institut de recherche pour le developpement
Subjects: [SDE]Environmental Sciences
Published: 2021

37. Statistique et causalité

Author: Frédéric Bertrand, Gilbert Saporta, Christine Thomas-Agnan, Laboratoire Informatique et Société Numérique (LIST3N), Université de Technologie de Troyes (UTT), CEDRIC. Méthodes statistiques de data-mining et apprentissage (CEDRIC - MSDMA), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire Modélisation et Sûreté des Systèmes (LM2S), Université de Technologie de Troyes (UTT)-Université de Technologie de Troyes (UTT), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], [MATH.MATH-HO]Mathematics [math]/History and Overview [math.HO], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract: International audience; À l’exception notable des essais contrôlés et randomisés, la statistique a longtemps évacué le problème de la causalité considérant qu’il relevait du domaine d’application et des théories afférentes. Bien souvent les cours et les manuels de statistique se contentent de rappeler que corrélation n’est pas causalité et passent rapidement à d’autres sujets. Or, que ce soit en économie, épidémiologie, génétique, médecine, marketing, pour ne citer que quelques domaines, la recherche de modèles causaux et de variables actionnables est incontournable. Aujourd’hui la mise à disposition de données massives ou de grande dimension repose la question de la causalité de manière aigüe.Dans le prolongement des travaux pionniers de Granger (prix Nobel d’économie en 2003), Pearl (prix Turing en 2011), Rosenbaum et Rubin, pour ne nommer qu'eux, une très large palette de modèles et méthodes pour l'analyse causale, éventuellement hors d'une expérience contrôlée, s'est peu à peu constituée depuis le début des années 1980. Citons entre autres les thèmes suivants : issues potentielles, données contrefactuelles, scores de propension, double-robustesse, diagramme de causalité, réseaux bayésiens, systèmes d'équations structurelles.Cet ouvrage est le fruit de la collaboration entre spécialistes réputés : Léon Bottou (Facebook AI Research), Antoine Chambaz (université de Paris), Daniel Commenges (Institut national de la santé et de la recherche médicale), Isabelle Drouet (université Paris-Sorbonne), Ron Kenett (KPA Group), Vivian Viallon (International Agency for Research on Cancer) réunis à l’occasion des 18e Journées d’étude en statistique organisées par la SFdS. Le lecteur y trouvera une synthèse des fondements et des travaux les plus récents dans le domaine de la causalité statistique, avec des applications dans des domaines variés.
Published: 2021

38. Li-Ion Batteries State-of-Charge Estimation Using Deep LSTM at Various Battery Specifications and Discharge Cycles

Author: Claudio Rossi, Rita Tse, Kei Long Wong, Giovanni Pau, Carlo Falcomer, Michael Bosello, Wong K.L., Bosello M., Tse R., Falcomer C., Rossi C., and Pau G.
Subjects: Battery (electricity), business.industry, Computer science, Fossil fuel, Recurrent neural network, Lithium-ion battery, Automotive engineering, Variety (cybernetics), State of charge, Electric devices, State of charge estimation, Hardware_GENERAL, Long short-term memory, Key (cryptography), European commission, business
Abstract: Lithium-ion battery technologies play a key role in transforming the economy reducing its dependency on fossil fuels. Transportation, manufacturing, and services are being electrified. The European Commission predicts that in Europe everything that can be electrified will be electrified within a decade. The ability to accurate state of charge (SOC) estimation is crucial to ensure the safety of the operation of battery-powered electric devices and to guide users taking behaviors that can extend battery life and re-usability. In this paper, we investigate how machine learning models can predict the SOC of cylindrical Li-Ion batteries considering a variety of cells under different charge-discharge cycles.
Published: 2021

39. Modelling and Visualizing People Flow in Smart Buildings

Author: Silvia Mirri, Paola Salomoni, Giovanni Pau, Rita Tse, Su-Kit Tang, Tse R., Mirri S., Tang S.-K., Pau G., and Salomoni P.
Subjects: Architectural engineering, People Flow Modelling, Coronavirus disease 2019 (COVID-19), Exploit, business.industry, Computer science, Data Visualization, Human-Centered Design, Limiting, University campus, Data visualization, Smart Campus, Internet of Thing, business, Internet of Things, User-centered design, Building automation
Abstract: The tremendous CoVid-19 outbreak has had a significant impact on the lives of people anywhere in the world. Several approaches have been presented with the aim of helping in limiting and mitigating the effect of CoVid-19 infections. This paper proposes a system that exploits Internet of Things (IoT) and Data Visualization to monitor the flow of people in buildings, with the aim of providing policymakers with a tool that visualize and highlight critical issues. The case study considered is a Smart University Campus located in Cesena, belonging to the University of Bologna.
Published: 2021

40. High-dimensional instrumental variables regression and confidence sets

Author: Gautier, Eric, Rose, Christiern, Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Queensland [Brisbane], ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017), European Project: 337665,EC:FP7:ERC,ERC-2013-StG,POEMH(2014), Toulouse School of Economics (TSE), École des hautes études en sciences sociales (EHESS)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, ANR: 17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017), Université Toulouse 1 Capitole (UT1), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Robustness to identification, Variable selection, Endogeneity, Confidence intervals, JEL: C - Mathematical and Quantitative Methods/C.C1 - Econometric and Statistical Methods and Methodology: General/C.C1.C13 - Estimation: General, Mathematics - Statistics Theory, Statistics Theory (math.ST), Instrumental variables, [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH], JEL: C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, 62J99, 62H12, G2P20, Unknown variance, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], FOS: Mathematics, Partial identification, Bias correction, Sparsity
Abstract: This article considers inference in linear models with d_X regressors, some or many of which could be endogenous, and d_Z instrumental variables (IVs). d_Z can range from less than d_X to any order smaller than an exponential in the sample size. For moderate d_X, identification robust confidence sets are obtained by solving a hierarchy of semidefinite programs. For large d_X, we propose the STIV estimator. The analysis of its error uses sensitivity characteristics introduced in this paper. Robust confidence sets are derived by solving linear programs. Results on rates of convergence, variable selection, and confidence sets which "adapt" to the sparsity are given. Generalizations include models with endogenous IVs and systems of equations with approximation errors. We also analyse confidence bands for vectors of linear functionals and functions using bias correction. The application is to a demand system with approximation errors, cross-equation restrictions, and thousands of endogenous regressors.
Published: 2021

41. The compliance of French purchasing behaviors with a healthy and sustainable diet: a 1-yr follow-up of regular customers in hypermarkets

Author: Edmond Rock, Anthony Fardet, Marion Desquilbet, Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Index (economics), Calorie, 030309 nutrition & dietetics, Principal component analysis, 030209 endocrinology & metabolism, Relative variety index, Animal products, Food choices, 03 medical and health sciences, 0302 clinical medicine, Environmental health, Sustainable agriculture, Ultra-processed foods, Global health, Hypermarket, ‘Varié’ (varied), Food diversity, 2. Zero hunger, 0303 health sciences, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Purchasing, Ultra-processed food, Sustainability, Food systems, ‘Végétal’ (plant), Business, Hypermarkets, Agronomy and Crop Science, Food Science
Abstract: In France, hypermarkets are the main shopping sites for food products. Therefore, the food-purchasing profiles of their regular customers may be a relevant indicator of the sustainability and health potentials of consumed diets. Knowing this information can be a step to address the issue of global health. The main objective of this study was to assess the sustainability and health potential of food-purchasing behaviors among regular adult customers, with or without children, of a leading French retailer. Secondarily, the cost of a sustainable food shopping cart was evaluated as regards the regular one, as calculated in this study. Purchasing receipts corresponding to 38,168 different food products were collected during one consecutive month for each four seasons in 2019 to assess compliance with a newly developed holistic indicator of food system sustainability, i.e., the 3V rule, recommending food consumption to be ‘Vegetal’/plant-based (≈15% animal calories/day), ‘Vrai’/real (max. 15% ultra-processed food calories/day, UPF) and ‘Varié’/varied. Participants were 708 regular buyers (aged ≥18 with different socio-economic profiles, with and without children) in 122 French hypermarkets. The plant rule was based on the animal and plant origin of food ingredients, including mixed products; the ‘real’ rule was evaluated with the Siga score according to the degree of processing to identify UPFs. The varied rule was defined based on a combination of food ‘categories × families’. The effect of children and season on the purchased animal and UPF calories and on the variety index was also evaluated. Multivariate and decision tree analyses were applied to compare consumers for their 3V rule profile similarities and differences, and to look for impacts of the presence or absence of children. Customers' purchases were far from the 3V rule, with a median of 41% animal and 61% UPF calories and a median variety index of 25% (compared to the consumer with the highest index set to 100%). There was no difference in purchased animal and UPF percentages neither according to seasons nor the presence of children. However, the presence of children was associated with a higher variety index (+33%, P < 0.05). Finally, the more the consumers purchased varied, the less they purchased UPFs. Compared to the average food basket, a 3V-based basket would cost 4.6% less. To make this basket accessible to everyone and to orientate consumer's purchasing behaviors toward more sustainable and healthier products, and hence food systems, hypermarkets should promote healthy eating and reassess their food offerings.
Published: 2021

42. Beyond social learning

Author: Pieter van den Berg, Guillaume Isabel, Thom Scott-Phillips, Edwin J. C. Van Leeuwen, Monica Tamariz, Alberto Acerbi, Christine A. Caldwell, Manvir Singh, Etienne Danchin, Maxime Derex, Lucas Molleman, Institute for Advanced Study in Toulouse (IAST), Brunel University London [Uxbridge], University of Stirling, Evolution et Diversité Biologique (EDB), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherches sur la Cognition Animale - UMR5169 (CRCA), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), Centre de Biologie Intégrative (CBI), University of Amsterdam [Amsterdam] (UvA), Central European University [Budapest, Hongrie] (CEU), Heriot-Watt University [Edinburgh] (HWU), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), University of Antwerp (UA), Royal Zoological Society of Antwerp (RZSA), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017), Centre National de la Recherche Scientifique (CNRS), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), DSR-SCD-UT1C, Service Publications, and Toulouse Graduate School défis en économie et sciences sociales quantitatives - - CHESS2017 - ANR-17-EURE-0010 - EURE - VALID
Subjects: adaptation, cultural evolution, culture, cumulative culture, mechanism, social learning, Humans, Cultural Evolution, Social Learning, Big Five personality traits and culture, Affect (psychology), Biochemistry, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, [SCCO]Cognitive science, 0302 clinical medicine, Sociology, Sociocultural evolution, Adaptation (computer science), Biology, B- ECONOMIE ET FINANCE, 030304 developmental biology, [SHS.ANTHRO-SE] Humanities and Social Sciences/Social Anthropology and ethnology, 0303 health sciences, Agricultural and Biological Sciences(all), Mechanism (biology), Biochemistry, Genetics and Molecular Biology(all), [SCCO] Cognitive science, [SHS.ANTHRO-SE]Humanities and Social Sciences/Social Anthropology and ethnology, Social learning, Epistemology, Part II: Unravelling the Mechanisms Underlying Cultural Evolution, [SCCO.PSYC]Cognitive science/Psychology, Human medicine, General Agricultural and Biological Sciences, Explanatory power, 030217 neurology & neurosurgery, Theme (narrative), Genetics and Molecular Biology(all)
Abstract: One contribution of 15 to a theme issue ‘Foundations of cultural evolution’ compiled and edited by Eva Boon, Lucas Molleman, Pieter van den Berg and Franz J. Weissing. © 2021 The Author(s). Cultural evolution requires the social transmission of information. For this reason, scholars have emphasized social learning when explaining how and why culture evolves. Yet cultural evolution results from many mechanisms operating in concert. Here, we argue that the emphasis on social learning has distracted scholars from appreciating both the full range of mechanisms contributing to cultural evolution and how interactions among those mechanisms and other factors affect the output of cultural evolution. We examine understudied mechanisms and other factors and call for a more inclusive programme of investigation that probes multiple levels of the organization, spanning the neural, cognitive-behavioural and populational levels. To guide our discussion, we focus on factors involved in three core topics of cultural evolution: the emergence of culture, the emergence of cumulative cultural evolution and the design of cultural traits. Studying mechanisms across levels can add explanatory power while revealing gaps and misconceptions in our knowledge. ANR Institute for Advanced Study in Toulouse funding (grant ANR-17-EURE-0010 (Investissements d'Avenir program)); European Research Council (ERC) Consolidator Grant (No. 648841 RATCHETCOG). European Research Council, under the European Union's Seventh Framework Programme (FP'l/2007-2013)/ERC grant agreement no. 609819 (Somics project); European Union's Horizon 2020 Research and Innovation Programme (under Marie Sklodowska-Curie grant agreement number 748310).
Published: 2021

43. ReSPEcT: privacy respecting thermal-based specific person recognition

Author: Ngai Seng Chan, Giovanni Pau, Su-Kit Tang, Rita Tse, Ka Ian Chan, Jiang, Xudong, Chan N.S., Chan K.I., Tse R., Tang S.-K., and Pau G.
Subjects: Machine Learning, Thermal Video Analytic, Human–computer interaction, Computer science, Ethical AI, Person recognition, Privacy Preserving Computing
Abstract: Video analytic techniques have been used to extract high level information from video streams. The technique leverages advances on machine learning to summarize complex image data into simple alert-signal to attract the attention of human operators. For example, in a station for the underground video analytic can help the operator to focus on an event from a specific camera rather than leaving this only to the human eye. A concern of such techniques is privacy as they expose people identity and enable profiling of personal habits and orientations. This work introduces ReSPEcT (Privacy Respecting theRmal basEd Specific Person rECogniTion), a privacy preserving video analytic system based on thermal video streams. ReSPEcT is able to identify a specific-human in thermal video streams from low-cost, low resolution cameras. The system leverages recent advances in machine learning (CNNs) and a plethora of pre-processing mechanisms, such as image automatic labeling, image segmentation, and image augmentation to reduce the stream background noise, improve resilience, strengthen human-body classification, and finally enable a specific human-target identification. ReSPEcT’s automatic labeling tool significantly reduces time thus automatically performing labeling using a model that can be retrained by an interactive web application. The experimental evaluation shows that overall ReSPEcT achieve 96.83% accuracy in identifying a specific person. Furthermore, is important to notice that while ReSPEcT can identify a specific human, the tool is not aware of the real-identity as it operates only on thermal images. ReSPEcT paves the way to use video analytic in a variety of privacy-protected scenarios, such as confidential meetings, sensitive spaces, or even public toilets.
Published: 2021

44. Cytometry inference through adaptive atomic deconvolution

Author: Pauline Gonnord, Laurent Risser, Manon Costa, Sébastien Gadat, Institut de Mathématiques de Toulouse UMR5219 (IMT), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE), École des hautes études en sciences sociales (EHESS)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse 1 Capitole (UT1), Centre de Physiopathologie Toulouse Purpan ex IFR 30 et IFR 150 (CPTP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Toulouse III - Paul Sabatier (UT3), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Centre de Physiopathologie Toulouse Purpan (CPTP), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Recherche Agronomique (INRA)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Toulouse 1 Capitole (UT1), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Inverse problems, Statistics and Probability, Atomic deconvolution, Inverse problems MSC2010: Primary: 62G07 Secondary: 62G20, Inference, Mathematics - Statistics Theory, Statistics Theory (math.ST), 01 natural sciences, 010104 statistics & probability, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], 0502 economics and business, FOS: Mathematics, 0101 mathematics, B- ECONOMIE ET FINANCE, Reliability (statistics), 050205 econometrics, Mathematics, Biological data, 05 social sciences, Inverse problem, Mixture model, 62P10, Adaptive kernel estimators, Deconvolution, Statistics, Probability and Uncertainty, Mixture models, Algorithm, Cytometry
Abstract: In this paper we consider a statistical estimation problem known as atomic deconvolution. Introduced in reliability, this model has a direct application when considering biological data produced by flow cytometers. In these experiments, biologists measure the fluorescence emission of treated cells and compare them with their natural emission to study the presence of specific molecules on the cells' surface. They observe a signal which is composed of a noise (the natural fluorescence) plus some additional signal related to the quantity of molecule present on the surface if any. From a statistical point of view, we aim at inferring the percentage of cells expressing the selected molecule and the probability distribution function associated with its fluorescence emission. We propose here an adap-tive estimation procedure based on a previous deconvolution procedure introduced by [vEGS08, GvES11]. For both estimating the mixing parameter and the mixing density automatically, we use the Lepskii method based on the optimal choice of a bandwidth using a bias-variance decomposition. We then derive some concentration inequalities for our estimators and obtain the convergence rates, that are shown to be minimax optimal (up to some log terms) in Sobolev classes. Finally, we apply our algorithm on simulated and real biological data.
Published: 2019

45. Nonparametric classes for identification in random coefficients models when regressors have limited variation

Author: Gaillac, Christophe, Gautier, Eric, Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Toulouse (UT), ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017), European Project: 337665,EC:FP7:ERC,ERC-2013-StG,POEMH(2014), Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Université Fédérale Toulouse Midi-Pyrénées
Subjects: Statistics::Theory, Identification, 62P20, 42A99, 62G07, 62G08, Random Coefficients, Mathematics - Statistics Theory, Statistics Theory (math.ST), Deconvolution, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Quasi-analyticity, secondary 42A99, 62G08, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], FOS: Mathematics, 62G07, Statistics::Methodology, Deconvolution AMS 2010 Subject Classification: Primary 62P20
Abstract: This paper studies point identification of the distribution of the coefficients in some random coefficients models with exogenous regressors when their support is a proper subset, possibly discrete but countable. We exhibit trade-offs between restrictions on the distribution of the random coefficients and the support of the regressors. We consider linear models including those with nonlinear transforms of a baseline regressor, with an infinite number of regressors and deconvolution, the binary choice model, and panel data models such as single-index panel data models and an extension of the Kotlarski lemma.
Published: 2021

46. The sample complexity of level set approximation

Author: François Bachoc, Tommaso Renato Cesari, Sébastien Gerchinovitz, Institut de Mathématiques de Toulouse UMR5219 (IMT), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), IRT Saint Exupéry - Institut de Recherche Technologique, ANR-19-P3IA-0004,ANITI,Artificial and Natural Intelligence Toulouse Institute(2019), ANR-19-CE23-0026,BOLD,Au delà de l'apprentissage séquentiel pour de meilleures prises de décisions(2019), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Université Toulouse 1 Capitole (UT1)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), and Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: FOS: Computer and information sciences, Level sets estimation, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistics - Machine Learning, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], FOS: Mathematics, Mathematics - Statistics Theory, Machine Learning (stat.ML), Global optimization, Statistics Theory (math.ST), Bandit Algorithms
Abstract: International audience; We study the problem of approximating the level set of an unknown function by sequentially querying its values. We introduce a family of algorithms called Bisect and Approximate through which we reduce the level set approximation problem to a local function approximation problem. We then show how this approach leads to rate-optimal sample complexity guarantees for Hölder functions, and we investigate how such rates improve when additional smoothness or other structural assumptions hold true.
Published: 2021

47. Adequate statistical modelling and data selection are essential when analysing abundance and diversity trends

Author: Marion Desquilbet, Pierre-André Cornillon, Laurence Gaume, Jean-Marc Bonmatin, Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Recherche Mathématique de Rennes (IRMAR), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre de biophysique moléculaire (CBM), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université d'Orléans (UO), grant ANR-17-EURE-0010 under the, Agence Nationale de la Recherche, ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017), ANR-16-IDEX-0006,MUSE,MUSE(2016), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université d'Orléans (UO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011), Frapart, Isabelle, Toulouse Graduate School défis en économie et sciences sociales quantitatives - - CHESS2017 - ANR-17-EURE-0010 - EURE - VALID, MUSE - - MUSE2016 - ANR-16-IDEX-0006 - IDEX - VALID, and Université d'Orléans (UO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)
Subjects: 0106 biological sciences, Insecta, media_common.quotation_subject, Insect decline, MEDLINE, Biodiversity, Biodiversity denial, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, 010603 evolutionary biology, 01 natural sciences, [SDV.BV.BOT] Life Sciences [q-bio]/Vegetal Biology/Botanics, 03 medical and health sciences, Methodological bias, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Abundance (ecology), [SDV.BID.SPT] Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, [SDV.EE.ECO] Life Sciences [q-bio]/Ecology, environment/Ecosystems, Animals, B- ECONOMIE ET FINANCE, Global change, Ecology, Evolution, Behavior and Systematics, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, media_common, 0303 health sciences, Models, Statistical, Ecology, Statistical model, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, Meta-analysis, Geography, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Data selection, Diversity (politics)
Abstract: International audience
Published: 2021

48. Animal welfare: Antispeciesism, veganism and a 'life worth living'

Author: Romain Espinosa, Nicolas Treich, Centre de recherche en économie et management (CREM), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017), ANR-19-CE21-0005,EPDAW,Economie de l'alimentation végétale et de la condition animale(2019), Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU), Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Normandie Université (NU)-Normandie Université (NU)-Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Economics and Econometrics, media_common.quotation_subject, antispeciesism, life worth living, animal welfare, [SHS]Humanities and Social Sciences, Animal welfare, 0502 economics and business, Economics, 050207 economics, B- ECONOMIE ET FINANCE, meat consumption, Social policy, media_common, 2. Zero hunger, Consumption (economics), Public economics, 05 social sciences, 0402 animal and dairy science, 04 agricultural and veterinary sciences, rearing conditions, 040201 dairy & animal science, Social welfare function, International political economy, veganism, Welfare, Social choice theory, farm animals, Social Sciences (miscellaneous), Public finance
Abstract: International audience; While antispeciesism is an ethical notion, veganism is behavioral. In this paper, we examine the links between the two. Building on Blackorby and Donaldson (1992), we consider a two-species model in which humans consume animals. The level of antispeciesism is conceived as the weight on animals' welfare in the utilitarian social welfare function. We show that more antispeciesism increases meat consumption if and only if animals' utility is positive. That is, the critical condition is whether farm animals' lives are worth living. We then empirically explore this condition using a survey. We find that farm-animal experts and frequent meat eaters are more likely to believe that the lives of farm animals are worth living. We finally discuss some issues in the study of animal welfare in economics and social choice.
Published: 2021

49. ExpectHill estimation, extreme risk and heavy tails

Author: Stéphane Girard, Abdelaati Daouia, Gilles Stupfler, Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Modelling and Inference of Complex and Structured Stochastic Systems (MISTIS), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Modèles statistiques bayésiens et des valeurs extrêmes pour données structurées et de grande dimension (STATIFY), Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] (ENSAI), Chaire Stress Test - BNP Paribas/Ecole polytechnique/Fondation de l'X., ANR-19-CE40-0013,ExtremReg,Régression extrême avec applications à l'économétrie, l'environnement et à la finance(2019), ANR-15-IDEX-0002,UGA,IDEX UGA(2015), Université Toulouse 1 Capitole (UT1)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut National Polytechnique de Grenoble (INPG), Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI), Ensai, Ecole Nationale de la Statistique et de l'Analyse de l'Information, ANR-19-CE40-0013,ExtremReg,Extremal Regression with Applications to Econometrics, Environment and Finance(2019), ANR-15-IDEX-02,UGA,IDEX UGA(2016), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Economics and Econometrics, Extremes, Extrapolation, Expected shortfall, 01 natural sciences, Least squares, Expectile, 010104 statistics & probability, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], 0502 economics and business, Coherent risk measures, Econometrics, 0101 mathematics, Extreme value theory, B- ECONOMIE ET FINANCE, 050205 econometrics, Mathematics, Applied Mathematics, 05 social sciences, Order statistic, Estimator, Asymmetric least squares, Coherence (statistics), Asymptotic theory (statistics), Heavy tails, Tail index, Quantile
Abstract: International audience; Risk measures of a financial position are, from an empirical point of view, mainly based on quantiles. Replacing quantiles with their least squares analogues, called expectiles, has recently received increasing attention. The novel expectile-based risk measures satisfy all coherence requirements. We revisit their extreme value estimation for heavy-tailed distributions. First, we estimate the underlying tail index via weighted combinations of top order statistics and asymmetric least squares estimates. The resulting expectHill estimators are then used as the basis for estimating tail expectiles and Expected Shortfall. The asymptotic theory of the proposed estimators is provided, along with numerical simulations and applications to actuarial and financial data.
Published: 2021

50. A Class of Explicit optimal contracts in the face of shutdown

Author: Martin, Jessica, Villeneuve, Stéphane, Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT), Toulouse School of Economics (TSE-R), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ANR-17-EURE-0010,CHESS,Toulouse Graduate School défis en économie et sciences sociales quantitatives(2017), Institut National des Sciences Appliquées (INSA), Toulouse School of Economics (TSE), Université Toulouse 1 Capitole (UT1), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Probability (math.PR), Principal-Agent problems, Computational Finance (q-fin.CP), Hamilton-Jacobi Bellman equations, [QFIN.RM]Quantitative Finance [q-fin]/Risk Management [q-fin.RM], [QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP], FOS: Economics and business, [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], Quantitative Finance - Computational Finance, Optimization and Control (math.OC), Default risk, Risk Management (q-fin.RM), FOS: Mathematics, Mathematics - Optimization and Control, Mathematics - Probability, Quantitative Finance - Risk Management
Abstract: What type of delegation contract should be offered when facing a risk of the magnitude of the pandemic we are currently experiencing and how does the likelihood of an exogenous early termination of the relationship modify the terms of a full-commitment contract? We study these questions by considering a dynamic principal-agent model that naturally extends the classical Holmstr{\"o}m-Milgrom setting to include a risk of default whose origin is independent of the inherent agency problem. We obtain an explicit characterization of the optimal wage along with the optimal action provided by the agent. The optimal contract is linear by offering both a fixed share of the output which is similar to the standard shutdown-free Holmstr{\"o}m-Milgrom model and a linear prevention mechanism that is proportional to the random lifetime of the contract. We then tweak the model to add a possibility for risk mitigation through investment and study its optimality.
Published: 2021

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