Contrats de recherche

Dates

01 janvier 2021 - 31 décembre 2025

Résumé

Les institutions contribuent à la stabilité économique et sociale. Par conséquent, leur remise en cause est souvent à l'origine d'un accroissement notable de l'incertitude économique. L'un des exemples les récents est le Brexit: voté en juin 2016 et toujours en cours de négociations 3 ans après. Cette période de confusion pèse sur les décisions des agents et est à l'origine de fragilités économiques.

Partant de ce constat, ce projet s'intéresse au comportement des entreprises et des gouvernements lorsqu'ils évoluent dans un environnement incertain. Son objectif est d'évaluer la manière dont ces agents réagissent à l'incertitude et dans quelle mesure leurs décisions peuvent elles-mêmes être source d'incertitude. 

Ce projet propose d'améliorer la compréhension: (1) du comportement des entreprises en univers incertain à travers leurs décisions d'emploi et d'investissement, (2) du lien entre les décisions des entreprises et l'incertitude engendrée par politiques gouvernementales.

Summary

Institutions contribute to social and economic stability. Therefore, increasing institutional weaknesses may be a source of deep economic uncertainty. One striking example is the Brexit: the referendum took place in 2016 and negotiations are still ongoing 3 years after. This period of doubtless alters agents' decisions and might generate economic fragilities. 

Based on this fact, this project focuses on firms' and governments' behavior in an uncertain environment. It seeks to assess how those agents react to uncertainty and whether their decisions can by themselves be a source of uncertainty. 

This project proposes to provide a better understanding of (1) firms' labor and investment decisions when they face uncertainty, (2) the link between firms' behavior and economic policy uncertainty.

Mots clés

Incertitude macroéconomique, données micro, décisions de firmes

Keywords

Macroeconomics; monetary economics; economic growth

Financeur

ANR

Contact

Céline Poilly (celine.poilly@univ-amu.fr)

Dates

01 octobre 2017 - 30 juin 2024

Résumé

Le logement constitue un objectif fondamental de politique publique en France et l'effort de la Nation en termes de transferts liés aux politiques du logement en 2014 dépasse 40 milliards d'euros. Ces politiques comprennent par exemple les allocations logement, les taxes foncières et d’habitation et les subventions à la construction mais s'étendent aussi au logement social et au contrôle des loyers. La redistribution et les défaillances du marché, par exemple en raison d’externalités, constituent la justification économique de ces politiques publiques.En France, il existe un sous-investissement important dans les recherches en économie du logement par rapport à l'économie du travail par exemple. Les évaluations restent limitées à des résultats sur les impacts de court terme qui utilisent des quasi-expériences naturelles. Les impacts à moyen ou long terme en termes d'efficacité ou de redistribution restent peu étudiés. Un exemple en est fourni par les allocations logement pour lesquelles nous avons des études de très bonne qualité sur les effets à court terme alors qu’aucune analyse en équilibre général ne nous indique comment les prix reflètent l'existence de ces allocations.C'est pourquoi l’objectif scientifique premier de notre projet est la meilleure compréhension de l'impact à long terme des politiques du logement sur les inégalités de logement en France et dans d’autres pays. La tâche centrale de notre projet de recherche est de construire un modèle structurel dynamique des décisions de logement des ménages au cours du cycle de vie et de calibrer ce modèle à l'aide de données observationnelles françaises. Il n'existe aucun modèle empirique pour la France alors que de tels modèles ont été construits pour les États-Unis, certes récemment. Ce modèle de base servira à évaluer les répercussions à long terme des politiques du logement, comme les allocations logement, les prêts à taux zéro pour les primo-accédants etc. En particulier, cela permettra d’estimer l'ordre de grandeur de la réduction des inégalités de logement obtenue par le moyen de ces politiques publiques. Deuxièmement, la validation empirique d'un tel modèle nécessite d'avoir des évaluations descriptives de grande qualité des inégalités de logement et des évaluations des effets des politiques publiques au cours des dernières années au niveau national et dans d’autres pays, afin de les comparer aux effets obtenus dans les modèles macroéconomiques. C'est la deuxième tâche de ce projet de recherche de mener ces travaux empiriques innovants.Le modèle de référence sera  enrichi dans des directions complémentaires. Une dimension clé est l'offre de logement et plus précisément la construction de nouveaux bâtiments. Nous visons aussi à analyser l'effet des subventions publiques, telles que les incitations fiscales, sur le nombre d'unités nouvellement construites et leur taille. Un autre sous-projet cherchera à utiliser des données de panel microéconomiques et des méthodes économétriques nouvelles pour estimer de manière plus robuste et précise, les paramètres de préférences des ménages. Enfin, le logement social et le contrôle des loyers sont d’autres éléments clés des politiques de logement en France. Un sous-projet met l'accent sur l'économie politique du logement social modélisée comme un jeu de vote entre des communes où les propriétaires et les locataires ont des préférences radicalement différentes. Un second sous-projet en économie géographique traite de la question du gradient des prix des logements et des loyers à l’intérieur des villes. Il utilisera un ensemble de données sur les prix des logements et les loyers qui seront collectés par l'équipe sur Internet. L'analyse empirique de ces données améliorera notre compréhension du chômage urbain et la façon dont les déplacements affectent négativement l'emploi dans les villes.

Financeur

ANR

Contact

Alain Trannoy (alain.trannoy[at]univ-amu.fr)

Dates

01 février 2022 - 31 janvier 2026

Résumé

Les inégalités économiques augmentent et vont s’aggraver avec la crise du Covid19 dans la zone euro. Nous supposons que la fragmentation financière et bancaire crée des opportunités de financement et de revenus différentes entre les pays, les ménages et les entreprises, et donc contribue à cette dynamique. Notre objectif est d'évaluer les effets redistributifs des secteurs bancaires et financiers face à la dispersion des revenus et des richesses dans la zone euro. Nous considèrerons d’abord l’impact de l’intermédiation bancaire sur les inégalités, via les distorsions dans l’accès au crédit qu’induit la fragmentation. Nous nous interrogeons alors sur la stratégie optimale de la BCE permettant une croissance plus inclusive. Nous étudions ensuite les principaux déterminants d'un cercle vertueux entre les financements de marchés et la réduction des inégalités. Nous souhaitons montrer qu’une intégration financière et bancaire régionale complète peut contribuer à une Europe plus juste.

Summary

Economic inequalities rise and are accentuated by the Covid19 crisis in the Eurozone. We assume that financial and banking fragmentation implies different financing and income opportunities between countries, households and firms and thus fuels this dynamic. Our purpose is to assess the redistributive effects of financial markets and the banking sector considering income and wealth dispersion in the Eurozone. We first focus on the impact of banking intermediation on inequalities, via the distortions in the access to credit that the fragmentation induces. We therefore question the optimal ECB strategy for a more inclusive growth. We then study the main determinants of a virtuous circle between market financing and the reduction of inequalities. Our aim is to show that full regional financial and banking integration can contribute to a fairer Europe.

Mots clés

fragmentation financière, dispersion des revenus, union monétaire

Keywords

financial fragmentation, income dispersion, monetary union

Financeur

ANR

Contact

Céline GIMET (celine.gimet[at]sciencespo-aix.fr)

Dates

01 décembre 2021 - 30 novembre 2024

Summary

Neurodegenerative diseases represent one of the main public health issues in our western societies and one of the greatest challenges in drug development. Prevention policies have become essential to address these issues: primary prevention to prevent disease onset by acting on actionable risk factors, or secondary prevention to slow disease progression with very early therapeutic interventions, ideally at pre-symptomatic stages. Key to the implementation of such prevention measures is the identification of at-risk patients, at the point of care, and preferably long before disease onset.
Our project, LeMeReND, proposes to use electronic health records (EHR) to identify biomedical risk factors through studying previous diagnoses (preclinical comorbidities), drug prescription, clinical care usage, and biological test results. This analysis will use longitudinal data in EHR registries including millions of patients who have been followed for at least 10 years before diagnosis in 4 different healthcare systems: Australia, France, the UK and Sweden and across 4 therapeutic areas: Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies and motor neuron diseases. We will identify the biomedical risk factors that are common to these diseases and the ones differentiating them.
We will stratify patients based on the progression profile of their exposure to the set of risk factors, in order to design tailored primary prevention measures. We will also design a screening tool which will give each patient a propensity score to develop one of these neurodegenerative diseases.
Such a tool could be deployed at the point of care to prioritise at-risk individuals for further inclusion in secondary prevention trials. We will evaluate the economic and social benefits of this new generation of precision prevention measures. We will study the public acceptability of a secondary-prevention effort, among the French population, and the feasibility of its implementation in primary care practices in France, Australia, and Sweden. Eventually, we will progress our understanding of the genetic and imaging markers of the disorders by studying the identified prodromal biomedical factors, using the UK BioBank and GWAS summary statistics. This will progress our understanding of the pathological processes which result in an increased risk to develop a specific neurodegenerative disease.
LeMeReND gathers a multidisciplinary research group with a leading expertise in epidemiology, statistics and machine learning, in particular for the analysis of longitudinal EHR data. Partners have demonstrated a strong track record on neurodegenerative diseases (Sweden, France, Australia), analyses of large-scale data including neuroimaging (France), genetics (Australia), longitudinal modelling (Sweden, France), and machine learning (Australia, France). An expert team in health economics and health policy complements the consortium.
LeMeReND will therefore provide invaluable insights to inform health policies and highlight possible new therapeutic targets. It will provide unique screening tools to facilitate the large-scale recruitment of patients in secondary prevention trials.

Résumé (anglais uniquement)

Neurodegenerative diseases represent one of the main public health issues in our western societies and one of the greatest challenges in drug development. Prevention policies have become essential to address these issues: primary prevention to prevent disease onset by acting on actionable risk factors, or secondary prevention to slow disease progression with very early therapeutic interventions, ideally at pre-symptomatic stages. Key to the implementation of such prevention measures is the identification of at-risk patients, at the point of care, and preferably long before disease onset.
Our project, LeMeReND, proposes to use electronic health records (EHR) to identify biomedical risk factors through studying previous diagnoses (preclinical comorbidities), drug prescription, clinical care usage, and biological test results. This analysis will use longitudinal data in EHR registries including millions of patients who have been followed for at least 10 years before diagnosis in 4 different healthcare systems: Australia, France, the UK and Sweden and across 4 therapeutic areas: Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies and motor neuron diseases. We will identify the biomedical risk factors that are common to these diseases and the ones differentiating them.
We will stratify patients based on the progression profile of their exposure to the set of risk factors, in order to design tailored primary prevention measures. We will also design a screening tool which will give each patient a propensity score to develop one of these neurodegenerative diseases.
Such a tool could be deployed at the point of care to prioritise at-risk individuals for further inclusion in secondary prevention trials. We will evaluate the economic and social benefits of this new generation of precision prevention measures. We will study the public acceptability of a secondary-prevention effort, among the French population, and the feasibility of its implementation in primary care practices in France, Australia, and Sweden. Eventually, we will progress our understanding of the genetic and imaging markers of the disorders by studying the identified prodromal biomedical factors, using the UK BioBank and GWAS summary statistics. This will progress our understanding of the pathological processes which result in an increased risk to develop a specific neurodegenerative disease.
LeMeReND gathers a multidisciplinary research group with a leading expertise in epidemiology, statistics and machine learning, in particular for the analysis of longitudinal EHR data. Partners have demonstrated a strong track record on neurodegenerative diseases (Sweden, France, Australia), analyses of large-scale data including neuroimaging (France), genetics (Australia), longitudinal modelling (Sweden, France), and machine learning (Australia, France). An expert team in health economics and health policy complements the consortium.
LeMeReND will therefore provide invaluable insights to inform health policies and highlight possible new therapeutic targets. It will provide unique screening tools to facilitate the large-scale recruitment of patients in secondary prevention trials.

Financeur

ANR JPcofuND 2 - IP

Contact

Bruno Ventelou (bruno.ventelou[at]univ-amu.fr)

Dates

01 janvier 2020 - 30 septembre 2024

Summary

Concerns about inequality and questions of social justice and cohesion have re-entered the public arena and animate public debate, provoked by the well-documented recent rapid increases in crosssectional income inequality. While much has been learnt from the recent literature on inequality,Deaton's (2015) Nobel lecture outlines several imperatives that are key to understanding inequalities and formulating welfare-enhancing policies, i.e.:(i) differences in resources across individuals should be measured not only at specific points in time but also across the life course; (ii) direct economic measures of well-being should be developed in order to assess better socioeconomic outcomes; and (iii) data should be reconciled with lifecycle models to investigate the causal mechanisms behind socio-economic outcomes. Our research proposal is built on these imperatives, and brings together several coherently linked work packages (WPs) that focus,from a life-course perspective,on the causes of inequalities (income and wealth) and income fluctuations (income risk and mobility),their welfare and policy implications.Empirically, coherence is achieved by working with a common unique data source, the SOEP-RV (housed at team member DIW) which matches to the German Socio-Economic Panel (SOEP) exactly linked administrative records from the statutory German Pension system. These data are thus unique in their accurate recording of labour market events and income histories over the life-course during the active and retirement phase, while adding to administrative side the rich contextual data contained in SOEP available at individual and household-level. We also extend the traditional life-cycle perspective beyond the usual retirement data (labelled below the “extended life-cycle”). Our central research questions are: 1. How can the life-course dynamics of individual incomes be characterised? 2. How can we systematically evaluate the effects of negative events (unemployment or health shocks), or positive ones (job changes) on individual trajectories and well-being? 3. How can we construct comprehensive measures of economic inequality and mobility taking into account wealth, income and the uncertainty of future incomes? 4. Taking a comprehensive life course view, how can policy intervene effectively to combat inequality? What is the equity-efficiency trade-off? LINDY is organised as a set of four integrated WPs that address these questions, moving from descriptive and statistical work in WP1 to explanations using dynamic models in WP2 that seek to distinguish between events (e.g. bad health shock) and individual decisions given constraints. Having characterised the life-course dynamics, in WP3 we develop integrated measures of economic capacity that allow to measure inequality in a comprehensive way, going beyond the common focus on current-period incomes. WP4 synthesizes the results and puts forward policy measures to efficiently combat inequality.

Résumé (anglais uniquement)

Concerns about inequality and questions of social justice and cohesion have re-entered the public arena and animate public debate, provoked by the well-documented recent rapid increases in crosssectional income inequality. While much has been learnt from the recent literature on inequality,Deaton's (2015) Nobel lecture outlines several imperatives that are key to understanding inequalities and formulating welfare-enhancing policies, i.e.:(i) differences in resources across individuals should be measured not only at specific points in time but also across the life course; (ii) direct economic measures of well-being should be developed in order to assess better socioeconomic outcomes; and (iii) data should be reconciled with lifecycle models to investigate the causal mechanisms behind socio-economic outcomes. Our research proposal is built on these imperatives, and brings together several coherently linked work packages (WPs) that focus,from a life-course perspective,on the causes of inequalities (income and wealth) and income fluctuations (income risk and mobility),their welfare and policy implications.Empirically, coherence is achieved by working with a common unique data source, the SOEP-RV (housed at team member DIW) which matches to the German Socio-Economic Panel (SOEP) exactly linked administrative records from the statutory German Pension system. These data are thus unique in their accurate recording of labour market events and income histories over the life-course during the active and retirement phase, while adding to administrative side the rich contextual data contained in SOEP available at individual and household-level. We also extend the traditional life-cycle perspective beyond the usual retirement data (labelled below the “extended life-cycle”). Our central research questions are: 1. How can the life-course dynamics of individual incomes be characterised? 2. How can we systematically evaluate the effects of negative events (unemployment or health shocks), or positive ones (job changes) on individual trajectories and well-being? 3. How can we construct comprehensive measures of economic inequality and mobility taking into account wealth, income and the uncertainty of future incomes? 4. Taking a comprehensive life course view, how can policy intervene effectively to combat inequality? What is the equity-efficiency trade-off? LINDY is organised as a set of four integrated WPs that address these questions, moving from descriptive and statistical work in WP1 to explanations using dynamic models in WP2 that seek to distinguish between events (e.g. bad health shock) and individual decisions given constraints. Having characterised the life-course dynamics, in WP3 we develop integrated measures of economic capacity that allow to measure inequality in a comprehensive way, going beyond the common focus on current-period incomes. WP4 synthesizes the results and puts forward policy measures to efficiently combat inequality.

Keywords

Inequality, life cycle, wealth, income risks

Financeur

ANR

Contact

Emmanuel Flachaire (emmanuel.flachaire@univ-amu.fr)

Dates

01 octobre 2018 - 31 mars 2024

Résumé

Dans un environnement économique complexe, la gestion du risque est un aspect essentiel des décisions économiques, et affecte sensiblement le développement économique et les inégalités. La gestion du risque est façonnée par deux facteurs principaux : le niveau de protection en cas de chocs négatifs sur les revenus, et le niveau d’information disponible sur l’environnement économique. Les réseaux économiques et sociaux jouent un rôle déterminant dans les deux dimensions. En effet, les réseaux sont un vecteur essentiel de partage de risque entre familles dans les économies en développement ou entre institutions financières; en outre, les réseaux sont des canaux naturels de transmission d’information. Deux phénomènes majeurs récent, la mondialisation des échanges et l’explosion  des  technologies  numériques,  créent  plus  d’interdépendances  entre  les  agents
économiques, et renforcent ainsi les effets des réseaux. Comment ces changements affectent-ils l’impact des réseaux sur la gestion du risque, sur le développement économique et sur les inégalités ? Ce projet a pour but d’étudier l’impact des réseaux économiques et sociaux sur la gestion du risque, le développement économique et les inégalités. Nous utiliserons à la fois des investigations théoriques, expérimentales et empiriques pour étudier l’impact des réseaux sur la gestion du risque. Dans un premier ensemble de contributions, nous étudierons les réseaux comme vecteurs de partage de risque. L’accroissement des interdépendances entre agents économiques inhérent à la mondialisation rend cette question très actuelle. Nous explorerons les relations entre prise de risque et partage de risque tant au niveau individuel qu’au niveau des entreprises. Au niveau individuel, nous analyserons la tension entre les comportements de prise de risque et les règles de partage de risque optimales sur les réseaux, et nous examinerons l’interaction entre prise de risque et altruisme dans les réseaux sociaux. Au niveau de l’entreprise, nous explorerons les liens entre prise de risque et le risque systémique d’une part, et propagation des défauts d’autre part. Les secteurs productif et financier méritent tous deux investigations, et nous les traiterons séparément. Dans un second ensemble de contributions, nous étudierons les réseaux comme canaux de transmission d’information. Cette question doit amener une réflexion renouvelée car l’émergence récente des technologies numériques dans nos sociétés modernes modifie les ensembles d’information des agents de même que leurs perceptions sur le réseau. Nous étudierons la diffusion de l’information dans des contextes économiques variés. Nous établirons les liens entre opportunités économiques et transmission stratégique d’information dans les réseaux. Nous analyserons aussi la diffusion d’opinions ou de croyances, et nous explorerons comment les agents peuvent séparer les effets d’influence sociale des sources intrinsèques d’information transmises sur les réseaux. Nous explorerons enfin les questions de perception individuelle de l’information dans les réseaux. Les décisions individuelles étant souvent façonnées par des normes sociales et par des biais de perception, nous explorerons comment les réseaux affectent ces biais de perception, et nous étudierons comment l’information sur le réseaux affecte les décisions économiques. Ce projet se base sur la collaboration de membres de l’AMSE et d’autres universités, incluant des universités méditerranéennes et d’autres universités prestigieuses telles que Stanford, Kent, et les universités affiliées à PSE. L’équipe constituée pour ce projet a une longue expérience en économie des réseaux. Ce projet serait une occasion exceptionnelle de fédérer toutes ces forces, à la fois en France et dans d’autres pays.

Summary

In a complex economic environment, managing risk is a key aspect of economic decisions, and it has a huge impact on economic development and inequalities. Risk management is mould by two main factors: the level of protection in case of bad shocks, and the available information about the economic environment. Social and economic networks play a prominent role in both dimensions. Indeed, networks are channels for risk sharing between households in developing economies or between financial institutions; also, networks are conduits for information transmission. Two recent major phenomena, the globalization of exchanges and the explosion of numerical technologies, create more interdependencies between economic agents, and thus reinforce network effects. How do these changes affect the impact of networks on the management of risk, on economic development and on inequalities? This project aims at studying the impact of economic and social networks on risk management, economic development and inequalities. We will use theoretical, experimental and empirical investigations to study the impact of networks on risk management. In a first set of contributions, we will study networks as risk sharing devices. The increase of interdependencies between economic agents due to globalization makes this a current issue. We will explore the interplay between risk taking and risk sharing at both individual and firm level. At the individual level, we will analyze the tension between risk taking behaviors and optimal risk sharing rules on networks, and we will examine the relationship between risk taking and altruism in social networks.  At the firm level, we will explore how risk taking affects systemic risk and contagion of default. Both financial and production sectors deserve interest, and we will treat them separately. In a second set of contributions, we will study networks as information sharing devices. This is a hot topic because the recent surge of numerical technologies in our modern societies modifies the information sets of agents as well as their perceptions about the network. We will investigate the diffusion of information in various contexts. We will study how the existence of economic opportunities can lead to strategic information transmission in networks. We will also examine the diffusion of opinions or beliefs, and we will track how agents can uncouple social influence from accurate information transmitted on networks. We will also investigate the individual perception of information in networks. Agents’ decisions being often shaped by social norms and perception biases, we will explore how networks affect these perception biases, and we will study how information on the network structure affects economic decisions. This project relies extensively on the collaboration of different members of GREQAM and other universities, including Mediterranean universities and other prestigious ones such as Stanford, Kent, and universities affiliated to PSE. The team constituted for this project has a long experience in the economics of networks. This project would be an exceptional occasion to federate all these forces, both in France and in other countries.

Keywords

networks, risk management, information transmission, public policy

Financeur

ANR

Contact

Frédéric Deroïan (frederic.deroian[at]univ-amu.fr)

Dates

01 octobre 2019 - 30 septembre 2024

Résumé

Ce projet de recherche mobilise les instruments de l’économie politique et de la théorie de la fiscalité optimale pour apporter un éclairage croisé sur le lien entre inégalités, migration et démocratie. Le volet 1 explorera les modalités de redistribution des richesses, avec un focus particulier sur la charge fiscale pesant sur les classes moyennes. Le volet 2 aura pour objectif d’estimer l’impact de l’évolution, à la fois réelle ou telle que relayée par les médias, du système socio-fiscal sur le vote d’extrême- droite. Cette analyse nous permettra d’éclairer la montée récente de l’extrême-droite chez les classes moyennes dans le monde occidental. Dans le premier volet, nous chercherons tout d’abord à mesurer l’évolution des inégalités de revenus avant et après redistribution en France depuis le début du XXème siècle et à quantifier l’ampleur de la redistribution opérée par les prélèvements obligatoires et la dépense publique sur longue période. Nous étudierons ensuite comment la fiscalité affecte le comportement des ménages français les plus riches à travers deux analyses complémentaires. La première étudiera comment la fiscalité influence la décision des plus hauts revenus de rester (ou non) sur le territoire national en fonction de leur niveau d’imposition. La seconde cherchera à estimer l’impact des modalités d’imposition des plus riches sur l’offre de travail ou le recours à l’optimisation fiscale de ces derniers. Nous pourrons sur cette base déterminer le sommet de la « courbe de Laffer » des ménages les plus riches, c’est-à-dire calculer le taux d’imposition le plus élevé qui ne conduit pas à une destruction de richesse pure et simple dont pâtirait l’ensemble de la population Des taux observés inférieurs à ces taux imputés témoigneraient de marges de redistributions inexploitées, et donc de réformes fiscales potentielles qui pourraient être mobilisées pour redistribuer une partie du fardeau fiscal des classes moyennes vers les plus aisées. De telles réformes, compatibles avec l’efficacité économique, renforceraient également l’équité du système socio-fiscal. La question qui se pose alors est celle de leur faisabilité politique. Nous explorerons cette question dans un cadre théorique novateur permettant d'introduire le processus de décision politique dans un modèle de redistribution optimale des richesses, tout en tenant compte des possibilités de nomadisme des citoyens. Dans le second volet, nous chercherons tout d’abord à mesurer l’effet de la fiscalité et de ses évolutions sur le vote d’extrême droite en France. Cette analyse permettra ensuite de mener une comparaison entre l’intensité des effets de la fiscalité sur le vote d’extrême-droite, d’une part, et l’impact estimé des déterminants socio-économiques mis en évidence dans la littérature, d’autre part, à savoir le chômage, l’exposition de la main d’œuvre peu qualifiée à la concurrence des pays à bas salaires, ou encore l’immigration. A l’aide d’un modèle structurel de vote, nous mènerons une analyse contrefactuelle ayant pour objectif de quantifier l’impact sur le vote d’extrême droite de réformes fiscales qui viseraient à redistribuer une partie du fardeau fiscal des classes moyennes vers les classes plus aisées. Nous analyserons ensuite le rôle des médias, à la fois traditionnels (presse écrite, radio et télévision) et sociaux (à l’image de Twitter) dans l’évolution du vote d’extrême droite. Plus particulièrement, nous estimerons l’effet de la couverture médiatique des pratiques d’évasion et d’optimisation fiscales observées au niveau individuel (i.e., opérés par des individus ou des entreprises) sur le vote d’extrême droite.

Summary

This project lies at the intersection of the political economy literature and the theory of optimal taxation. Its objective is to initiate an analysis on the links between inequalities, migration, and democracy. The first working package focuses on income redistribution, with an emphasis on middle classes. The second working package’s ambition is to estimate the impact of the tax and transfer system, and its media coverage, on far-right parties’ voting shares. This analysis will shed light on the determinants of the rising propensity of the middle class to vote in favor of these far-right parties. In the first working package, we first aim at measuring the evolution of pre-tax and post-tax income inequality and evaluating the redistributive impact of taxes and transfers on inequality in France since the beginning of the XXth century. We will then conduct two complementary analysis of behavioral responses to taxation among top income earners. The first study will analyze how taxation affects the decision of top income earners to emigrate. The second study will estimate how the design of income taxes may influence labor supply responses and/or the use of tax optimization strategies. Next, we will use the estimated behavioral responses to determine the top of the Laffer curve, that is, the rate of taxation at which tax revenue is maximized. Current top tax rates ranging below this estimated tax rate would suggest the existence of unexploited margins of redistribution, and therefore opportunities to implement tax reforms that would redistribute a part of the tax burden from the middle class to top- income earners. Such reforms, consistent with economic efficiency, would also improve the equity of the tax-and -transfer system. Finally, we turn our analysis into their political feasibility. We will explore this issue by providing theoretical foundations to the political process underlying redistributive policies in a context of international migration. In the second working package, we will first evaluate the effect of taxation and its evolution on the far-right vote in France. This quantitative analysis will allow us to compare the effect of taxation with that of other socio-economic determinants of the far-right vote identified by the literature, such as unemployment, exposure of low skill workers to import competition, or immigration. Using a structural model of vote, we will then conduct a counterfactual exercise allowing us to quantify the impact of tax reforms favoring the middle class on the far-right vote. We will finally analyze the role of media (traditional or social) on the evolution of the far-right vote. More precisely, we will estimate the effect of the media coverage of tax evasion or tax optimization strategies implemented by individuals or firms on the far-right vote. This project lies at the intersection of the political economy literature and the theory of optimal taxation. Its objective is to initiate an analysis on the links between inequalities, migration, and democracy. The first working package focuses on income redistribution, with an emphasis on middle classes. The second working package’s ambition is to estimate the impact of the tax and transfer system, and its media coverage, on far-right parties’ voting shares. This analysis will shed light on the determinants of the rising propensity of the middle class to vote in favor of these far-right parties. In the first working package, we first aim at measuring the evolution of pre-tax and post-tax income inequality and evaluating the redistributive impact of taxes and transfers on inequality in France since the beginning of the XXth century. We will then conduct two complementary analysis of behavioral responses to taxation among top income earners. The first study will analyze how taxation affects the decision of top income earners to emigrate. The second study will estimate how the design of income taxes may influence labor supply responses and/or the use of tax optimization strategies. Next, we will use the estimated behavioral responses to determine the top of the Laffer curve, that is, the rate of taxation at which tax revenue is maximized. Current top tax rates ranging below this estimated tax rate would suggest the existence of unexploited margins of redistribution, and therefore opportunities to implement tax reforms that would redistribute a part of the tax burden from the middle class to top- income earners. Such reforms, consistent with economic efficiency, would also improve the equity of the tax-and -transfer system. Finally, we turn our analysis into their political feasibility. We will explore this issue by providing theoretical foundations to the political process underlying redistributive policies in a context of international migration. In the second working package, we will first evaluate the effect of taxation and its evolution on the far-right vote in France. This quantitative analysis will allow us to compare the effect of taxation with that of other socio-economic determinants of the far-right vote identified by the literature, such as unemployment, exposure of low skill workers to import competition, or immigration. Using a structural model of vote, we will then conduct a counterfactual exercise allowing us to quantify the impact of tax reforms favoring the middle class on the far-right vote. We will finally analyze the role of media (traditional or social) on the evolution of the far-right vote. More precisely, we will estimate the effect of the media coverage of tax evasion or tax optimization strategies implemented by individuals or firms on the far-right vote.

Mots clés

inégalités ; migrations ; radicalisation ; fiscalité ; démocratie ; classes moyennes

Keywords

inequality, democracy, middleclasses

Financeur

ANR

Contact

Alain Trannoy

Dates

01 décembre 2021 - 31 mai 2025

Summary

The growing use of artificial intelligence and Machine Learning (ML) by banks and Fintech companies is one of the most significant changes in technology being integrated in the financial industry over past decades. In a recent report (ACPR, 2018), the French Prudential Supervision and Resolution Authority evaluates the disruptive potential of ML and concludes that it raises subject to mixed judgements. On the one hand, this set of new techniques holds great promise for the future of financial services. On the other hand, its practical applications still face many unresolved challenges. Within this context, the MLEforRisk project aims to provide better understanding of the usefulness of the combination of ML and econometrics for financial risk measurement. MLEforRisk is a multi-disciplinary project in the fields of finance and financial econometrics, which brings together senior and junior researchers in business, economics, and applied mathematics.

Résumé (anglais uniquement)

The growing use of artificial intelligence and Machine Learning (ML) by banks and Fintech companies is one of the most significant changes in technology being integrated in the financial industry over past decades. In a recent report (ACPR, 2018), the French Prudential Supervision and Resolution Authority evaluates the disruptive potential of ML and concludes that it raises subject to mixed judgements. On the one hand, this set of new techniques holds great promise for the future of financial services. On the other hand, its practical applications still face many unresolved challenges. Within this context, the MLEforRisk project aims to provide better understanding of the usefulness of the combination of ML and econometrics for financial risk measurement. MLEforRisk is a multi-disciplinary project in the fields of finance and financial econometrics, which brings together senior and junior researchers in business, economics, and applied mathematics.

Financeur

ANR

Contact

Sébastien LAURENT (sebastien.laurent[at]univ-amu.fr)

Dates

01 mars 2021 - 31 octobre 2025

Résumé

Dans un contexte d’économie circulaire, le projet RECALL propose d’extraire les métaux de valeur (fer et métaux critiques) dans un déchet minier : les résidus de bauxite. Du fait de l’importance économique des métaux critiques (ils sont présents dans de nombreuses applications émergentes) et leur fort risque d’approvisionnement, la production de ces métaux à partir de sources secondaires apparaît comme une voie inévitable pour de pérenniser ces nouvelles filières économiques. Ainsi, ce projet propose de développer des procédés "doux" d’extraction (procédés physico-chimique et bio-inspiré) en se basant sur une caractérisation fine des déchets et de la spéciation des métaux et sur une analyse socio-économique. Ce projet sera un tremplin pour cette thématique identifiée comme stratégique par le CEREGE et permettra d’initier des collaborations internationales (Horizon Europe). Ce projet d’intérêt scientifique, économique et sociétal est soutenu par l’institut de l’économie circulaire.

Summary

In the context of a circular economy, the RECALL project aims at extracting valuable metals in mining waste: bauxite residues. Due to the economic importance of critical metals (they are present in many emerging applications) and their high supply risk, production from secondary resources appears to be inevitable in order to sustain these new economic sectors. Thus, this project proposes to develop environmentally sustainable extraction processes (soft physico-chemical and bio-inspired processes) to recover these metals, with thorough characterization of the waste and metal speciation and the evaluation of social welfare associated with the process being developed. This research project will be a springboard for this research topic identified as strategic by the CEREGE lab and for initiating collaborative project (EU calls, Horizon Europe). This project, not only of scientific interest, but also of economic and societal interest, is supported by the French Institute of Circular Economy.

Financeur

ANR

Contact

Dominique Ami (dominique.ami[at]univ-amu.fr)

Dates

01 décembre 2021 - 29 juin 2026

Résumé

Le comportement prosocial est motivé non seulement par les incitations formelles, mais aussi par des préoccupations d'image, image de soi et image sociale. Alors qu'il existe une littérature sur préoccupations d'image et comportement éthique, les interactions entre l'image de soi et l'image sociale n'ont pas encore été étudiées. Dans SOSELF, nous proposons de combler cette lacune en utilisant une combinaison de théorie, d'expériences de laboratoire et de méthodes empiriques. Nous explorerons comment l’image sociale et l'image de soi sont liées par un principe de cohérence et comment leurs interactions entraînent des réponses comportementales à l'environnement. Nous étudierons ensuite l’effet de l'une des principales interventions utilisées pour promouvoir un comportement prosocial, les rappels moraux. SOSELF peut éclairer les politiques publiques dans un large éventail de domaines, et nous étudierons en particulier l'impact d'interventions comportementales sur la culture d’entreprise.

Summary

Prosocial behavior is driven, not only by formal incentives, but also by image concerns, both self- and social image. While there is a growing literature on the consequences of image concerns on ethical behavior, the interactions between self-and social-image have not been studied yet. In SOSELF, we propose a comprehensive approach to fill this gap. Our project will use a combination of theory, laboratory experiments and empirical methods relying on an interdisciplinary team. We will explore how social and self-image are tied together by a principle of coherence and how their interactions drive behavioral responses to the environment. Building on these results, we will study the optimal design of one of the main interventions used to promote prosocial behavior: moral reminders. SOSELF can inform policy in a wide range of domains, from fighting the circulation of fake news to fighting against corruption. We will in particular focus on how behavioral interventions modify firm culture

Financeur

ANR

Contact

Stéphane Luchini (stephane.luchini[at]univ-amu.fr)

Dates

01 avril 2022 - 31 mars 2026

Summary

Digitalization is the sociotechnical phenomenon of adopting information and communication technologies. Beyond wages and employment, this can have important effects on non-pecuniary (NP) working conditions, job satisfaction and wellbeing at work. Our objective is to understand how digitalization affects these dimensions of work, as well as how it affects the way individuals tradeoff wages and NP work conditions. The nature of social distancing during the COVID pandemic and the reliance of telecommuting on digital technologies have pushed these issues into the limelight. Therefore, we will also study the effects of digitalization in the context of the pandemic.

We ask whether and how digitalization impacts various dimensions of working conditions – hours, flexibility, mobility, physical effort, autonomy, team work, etc. – and thus job satisfaction and occupational choices. Taking into account non-pecuniary aspects of job quality is important because both wages and NP work conditions are considered by workers deciding on labor supply – and by employers deciding on labor demand – and there is reason to believe that they have not evolved in lockstep. One of the goals of project WRKCOV19 is to deepen our understanding of how new digital technologies (DTs) affect the joint evolution of wage and working conditions. The importance of this issue has recently been magnified by the COVID-19 crisis, as many employers and workers have dramatically increased their use of DTs in order to promote remote work and limit human contact in the workplace. Little is known about the impact of this radical re-organization on working conditions and wellbeing at work. And while vaccination campaigns will gradually remove many such barriers, much of the working conditions landscape will not return to the status quo ante.

Résumé (anglais uniquement)

Digitalization is the sociotechnical phenomenon of adopting information and communication technologies. Beyond wages and employment, this can have important effects on non-pecuniary (NP) working conditions, job satisfaction and wellbeing at work. Our objective is to understand how digitalization affects these dimensions of work, as well as how it affects the way individuals tradeoff wages and NP work conditions. The nature of social distancing during the COVID pandemic and the reliance of telecommuting on digital technologies have pushed these issues into the limelight. Therefore, we will also study the effects of digitalization in the context of the pandemic.

We ask whether and how digitalization impacts various dimensions of working conditions – hours, flexibility, mobility, physical effort, autonomy, team work, etc. – and thus job satisfaction and occupational choices. Taking into account non-pecuniary aspects of job quality is important because both wages and NP work conditions are considered by workers deciding on labor supply – and by employers deciding on labor demand – and there is reason to believe that they have not evolved in lockstep. One of the goals of project WRKCOV19 is to deepen our understanding of how new digital technologies (DTs) affect the joint evolution of wage and working conditions. The importance of this issue has recently been magnified by the COVID-19 crisis, as many employers and workers have dramatically increased their use of DTs in order to promote remote work and limit human contact in the workplace. Little is known about the impact of this radical re-organization on working conditions and wellbeing at work. And while vaccination campaigns will gradually remove many such barriers, much of the working conditions landscape will not return to the status quo ante.

Financeur

ANR

Contact

Eva Moreno-Galbis (eva.moreno-galbis[at]univ-amu.fr)