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Impact des institutions sur les politiques et stratégies de lutte contre la corruption et de promotion de la bonne gouvernance : Cas de la Guinée

Date : Jeudi | 2024-02-08 Ă  12h30
Lieu : Salle des thĂšses

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Saikou Amadou DIALLO (LEO, UniversitĂ© d’OrlĂ©ans - ANLCPBG GuinĂ©e Conakry)

Le dĂ©veloppement de politiques publiques et de stratĂ©gies nationales dans les pays en dĂ©veloppement est essentiellement basĂ© sur la volontĂ© des dĂ©cideurs politiques. De mĂȘme, la faiblesse des institutions dans ces pays nĂ©cessite la construction/reconstruction d’institutions stables et pĂ©rennes. Ainsi, l’utilisation des donnĂ©es, des faits est prĂ©pondĂ©rante dans les prises de dĂ©cisions et dans le dĂ©veloppement des politiques nationales sur des thĂšmes aussi important que la lutte contre la corruption et la promotion de la bonne gouvernance. Dans le cadre de cette thĂšse, une enquĂȘte sur l’utilisation des paiements Ă©lectroniques et une autre sur la perception de la corruption ont Ă©tĂ© rĂ©alisĂ©es en GuinĂ©e. Les rĂ©sultats de ces enquĂȘtes permettront d’évaluer l’impact de la construction d’institutions stables et pĂ©rennes sur la lutte contre la corruption dans les pays en dĂ©veloppement. De mĂȘme, les rĂ©sultats permettront d’évaluer l’impact de la digitalisation notamment les paiements Ă©lectroniques ainsi que l’inclusion financiĂšre sur la rĂ©duction de la corruption. Enfin, l’impact des bonnes pratiques de gouvernance sur le dĂ©veloppement socio - Ă©conomique de la GuinĂ©e sera evaluĂ©.

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Recommender Systems Unplugged: Effects of explaining algorithmic recommendations in music consumption, an experimental approach

Date : Jeudi | 2024-02-01 Ă  12h30
Lieu : Salle des thĂšses

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Julien M'BARKI (Chaire PcEn, Université Paris 1 Panthéon-Sorbonne)

Music streaming services make massive use of algorithms in their music recommender systems (MRS) to guide users to tracks they are likely to enjoy. However, the black-box nature of these algorithms makes them difficult for users to understand, both in terms of how they work and the music they predict. The field of explainable AI (XAI), and in particular its “explanation” side, has emerged to make the uses of AI (including MRSs) more comprehensible to users. This paper aims to observe, using an experimental method, whether the explanation of an MRS algorithm induces a change in listening behavior on music streaming services. In a theoretical framework, we model two types of users' behaviors, namely “study” and “browse” behaviors. We then test in the lab the explanation effects on these behaviors by explaining two simplified MRSs, taking into account only certain music recommendation criteria.

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First-year PhD. Students Presentation

Date : Jeudi | 2023-01-25 Ă  12h30
Lieu : Salle B.103

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S P E C I A L       S E S S I O N

 

Three new PhD. Students from the LEO (Université d'Orléans) will present their thesis projects. Each of them will give a 15 minutes presentation followed by a 15 minutes discussion :

  • Alexandra Amani (Econometrics Team)
  • Anne-CĂ©cile Baptiste Giuliana (International Economics/Sustainable Development Team)
  • Flavien Vilbert (Macro/Finance Team)

 

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Managing a Lazy Investment: Being Actively Passive

Date : Jeudi | 2024-01-18 Ă  12h30
Lieu : Salle B103

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Indigo JONES (LEO, UniversitĂ© d’OrlĂ©ans)

While passively managed financial instruments do not require intervention from their investors, some investors actively manage them anyway. To understand why and how we use a novel micro-level dataset of 6,247 robo-advisor clients who made 9,250 changes to their investment portfolios between 2015 and 2022. Micro-level demographic and financial variables as well as macro-level market returns and volatility are factors in the decision to change one's passively managed portfolio. In addition, how these changes affected investors' returns are studied. A counterfactual test showed that on average accounts which adjusted their portfolio allocation outperformed identical hypothetical accounts in which no changes were made, but this result was not replicated in the field using a more constrained dataset including only realized gains (i.e., closed accounts).

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« 29th International Panel Data » Conference

Date : July 4&5, 2024
Lieu : University of Orléans

Organisateur(s) : LÉO

The aim of the conference is to bring together economists, econometricians, statisticians and social scientists using panel data for their applied and/or theoretical research. The conference provides an active forum for researchers to discuss their findings from theoretical or empirical viewpoints, seek feedback, exchange ideas for future research and promote active collaboration in all areas of panel data analysis. The International Panel Data Conference started in 1977.

 

Keynotes Speakers :

  • Marine Carrasco, University of Montreal

  • Serena Ng, Columbia University

  • Hashem Pesaran, Cambridge University & University Of Southern California

  • Olivier Scaillet, University of Geneve

 

Important dates :
  • Submission deadline: March 1st, 2024
  • Notification of acceptance: March 31th, 2024
  • Opening registration: April 1st, 2024
  • Registration deadline for presenters’: April 30th, 2024
  • Registration deadline for attendees’: May 20th, 2024

 

Local Organizing Committee - Coordinator :
  • Christophe HURLIN, Full Professor
  • Marcel VOIA, Full Professor
  • Cristina STRANGO, PhD Student

 

Contact :

admin@ipdc2024.org

 

Website Conference
IPDC2024 - Call for paper-1_page-0001
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