Depuis plusieurs décennies, les prix des énergies sont sujets à une volatilité croissante pesant considérablement sur l’ensemble de l’économie. Comparée aux prix des autres matières premières (comme, par exemple, les métaux précieux, ou encore les produits agricoles), l’évolution des produits énergétiques est apparue exceptionnellement incertaine, tant à long terme qu’à court terme. Dans un contexte économique global, ce phénomène acquiert toute son importance tant les dommages sur l’économie réelle d’une forte variation des prix des matières premières peuvent être conséquents. Cette thèse s’intéresse donc aux causes profondes expliquant ces fluctuations. Plus spécifiquement, en unissant les différents champs de l’économie de l’énergie, de l’économétrie, de la finance et de la psychologie, elle s’attache à comprendre le phénomène de financiarisation des commodités et les relations étroites entre marchés financiers et marchés des matières premières. Cette réflexion s’articule en trois thèmes : d’une part la relation entre les prix des différentes énergies et leurs propriétés financières est analysée, d’autre part les aspects émotionnels et comportementaux des marchés sont étudiés, enfin les liens directs entre marchés boursiers et marchés de commodités sont abordés. / Since decades, energy prices are subject to increasing volatility affecting the whole economy. Compared to other commodity prices (for example precious metals and agro-industrial), energy price dynamics appear to be extremely uncertain both at short and long run. In a global economic context, this phenomenon is very important since intense variations of commodity prices can be tragic to real economy. This thesis focuses on the true nature of these movements. More formally, we investigate the commodity markets’ financialization, as well as the relationships between commodity and stock markets by unifying the fields of energy economics, econometrics, finance and psychology. This analysis is based on three themes: first energy prices relationships and their financial properties are analyzed, and then the behavioral and emotional specification of energy markets are studied, finally comovements between stock and commodity markets’ volatility are considered

Les tests de résistance, qui évaluent la capacité des banques à soutenir la détérioration de la situation économique et financière, sont devenus un outil qui aide les banques centrales à exercer leur nouveau pouvoir de supervision et à promouvoir un système financier stable. En outre, la récente crise financière mondiale a déplacé le centre d'attention de la supervision financière d'une perspective microprudentielle, basée sur la résilience des institutions individuelles, à une perspective plus macroprudentielle, qui englobe la résilience globale du système financier. Par conséquent, les tests de résistance microprudentiels mettent l'accent sur le rôle traditionnel du capital bancaire en tant que coussin de protection contre les pertes, tandis que les tests de résistance macroprudentiels se concentrent sur le système bancaire dans son ensemble. La crise financière mondiale a également souligné le rôle crucial du risque de liquidité dans la détérioration de la stabilité du système financier international. Le premier article passe en revue le premier test de résistance de la BCE, en le comparant à la littérature et aux autres tests de résistance effectués de par le monde, et contextualise ses résultats. Il donne un aperçu des tests de résistance et une liste d'améliorations potentielles. Le second article cherche à construire une méthodologie qui couvre certaines lacunes (effet de spillovers et interactions entre solvabilité et liquidité) identifiée dans le premier chapitre et l'utilise pour évaluer la fragilité actuelle du système bancaire de la zone euro selon différents scénarios. Enfin, le troisième chapitre analyse le lien entre la solvabilité et les coûts de financement. / Stress tests, which evaluate banks' capacity to withstand deteriorating economic and financial condition, have become a tool that helps central banks to fulfil their new supervisory power and promote a stable financial system. Additionally, the global financial crisis shifted the perspective of financial supervision from a microprudential perspective, based on the resilience of individual institutions, to a more macroprudential perspective, which encompasses the whole financial system resilience. Hence, microprudential stress tests emphasize the traditional role of bank capital as a buffer against loss, shielding the deposit insurance agency, while, macroprudential stress tests focus on whether the banking system as a whole has the balance, sheet capacity to support the economy. The global financial crisis also highlighted the crucial role of liquidity risk in undermining the stability of the international financial system. The first paper reviews the first ECB stress test, comparing it to the literature and other stress tests conducted, and contextualize its results. It provides an overview of stress tests as a tool and give a list of potential improvements. The second paper, seeks to construct methodology that covers some shortcomings (spillovers and interaction between solvency and liquidity) identified in the first chapter and uses it to assess the current fragility of the Eurozone banking system to various scenarios. Finally, the third chapter analyses the link between solvency and funding costs as a potential source of second round losses in the stress testing framework.

Doctorat en sciences sociales, politiques et économiques / info:eu-repo/semantics/nonPublished

This thesis contains three essays in the field of real-time econometrics, and more particularly<p>forecasting.<p>The issue of using data as available in real-time to forecasters, policymakers or financial<p>markets is an important one which has only recently been taken on board in the empirical<p>literature. Data available and used in real-time are preliminary and differ from ex-post<p>revised data, and given that data revisions may be quite substantial, the use of latest<p>available instead of real-time can substantially affect empirical findings (see, among others,<p>Croushore’s (2011) survey). Furthermore, as variables are released on different dates<p>and with varying degrees of publication lags, in order not to disregard timely information,<p>datasets are characterized by the so-called “ragged-edge”structure problem. Hence, special<p>econometric frameworks, such as developed by Giannone, Reichlin and Small (2008) must<p>be used.<p>The first Chapter, “The impact of macroeconomic news on bond yields: (in)stabilities over<p>time and relative importance”, studies the reaction of U.S. Treasury bond yields to real-time<p>market-based news in the daily flow of macroeconomic releases which provide most of the<p>relevant information on their fundamentals, i.e. the state of the economy and inflation. We<p>find that yields react systematically to a set of news consisting of the soft data, which have<p>very short publication lags, and the most timely hard data, with the employment report<p>being the most important release. However, sub-samples evidence reveals that parameter<p>instability in terms of absolute and relative size of yields response to news, as well as<p>significance, is present. Especially, the often cited dominance to markets of the employment<p>report has been evolving over time, as the size of the yields reaction to it was steadily<p>increasing. Moreover, over the recent crisis period there has been an overall switch in the<p>relative importance of soft and hard data compared to the pre-crisis period, with the latter<p>becoming more important even if less timely, and the scope of hard data to which markets<p>react has increased and is more balanced as less concentrated on the employment report.<p>Markets have become more reactive to news over the recent crisis period, particularly to<p>hard data. This is a consequence of the fact that in periods of high uncertainty (bad state),<p>markets starve for information and attach a higher value to the marginal information content<p>of these news releases.<p>The second and third Chapters focus on the real-time ability of models to now-and-forecast<p>in a data-rich environment. It uses an econometric framework, that can deal with large<p>panels that have a “ragged-edge”structure, and to evaluate the models in real-time, we<p>constructed a database of vintages for US variables reproducing the exact information that<p>was available to a real-time forecaster.<p>The second Chapter, “Real-time nowcasting of GDP: a factor model versus professional<p>forecasters”, performs a fully real-time nowcasting (forecasting) exercise of US real GDP<p>growth using Giannone, Reichlin and Smalls (2008), henceforth (GRS), dynamic factor<p>model (DFM) framework which enables to handle large unbalanced datasets as available<p>in real-time. We track the daily evolution throughout the current and next quarter of the<p>model nowcasting performance. Similarly to GRS’s pseudo real-time results, we find that<p>the precision of the nowcasts increases with information releases. Moreover, the Survey of<p>Professional Forecasters does not carry additional information with respect to the model,<p>suggesting that the often cited superiority of the former, attributable to judgment, is weak<p>over our sample. As one moves forward along the real-time data flow, the continuous<p>updating of the model provides a more precise estimate of current quarter GDP growth and<p>the Survey of Professional Forecasters becomes stale. These results are robust to the recent<p>recession period.<p>The last Chapter, “Real-time forecasting in a data-rich environment”, evaluates the ability<p>of different models, to forecast key real and nominal U.S. monthly macroeconomic variables<p>in a data-rich environment and from the perspective of a real-time forecaster. Among<p>the approaches used to forecast in a data-rich environment, we use pooling of bi-variate<p>forecasts which is an indirect way to exploit large cross-section and the directly pooling of<p>information using a high-dimensional model (DFM and Bayesian VAR). Furthermore forecasts<p>combination schemes are used, to overcome the choice of model specification faced by<p>the practitioner (e.g. which criteria to use to select the parametrization of the model), as<p>we seek for evidence regarding the performance of a model that is robust across specifications/<p>combination schemes. Our findings show that predictability of the real variables is<p>confined over the recent recession/crisis period. This in line with the findings of D’Agostino<p>and Giannone (2012) over an earlier period, that gains in relative performance of models<p>using large datasets over univariate models are driven by downturn periods which are characterized<p>by higher comovements. These results are robust to the combination schemes<p>or models used. A point worth mentioning is that for nowcasting GDP exploiting crosssectional<p>information along the real-time data flow also helps over the end of the great moderation period. Since this is a quarterly aggregate proxying the state of the economy,<p>monthly variables carry information content for GDP. But similarly to the findings for the<p>monthly variables, predictability, as measured by the gains relative to the naive random<p>walk model, is higher during crisis/recession period than during tranquil times. Regarding<p>inflation, results are stable across time, but predictability is mainly found at nowcasting<p>and forecasting one-month ahead, with the BVAR standing out at nowcasting. The results<p>show that the forecasting gains at these short horizons stem mainly from exploiting timely<p>information. The results also show that direct pooling of information using a high dimensional<p>model (DFM or BVAR) which takes into account the cross-correlation between the<p>variables and efficiently deals with the “ragged-edge”structure of the dataset, yields more<p>accurate forecasts than the indirect pooling of bi-variate forecasts/models. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

This Thesis is composed by three independent papers that investigate<p>central debates in empirical macroeconomic modeling.<p><p>Chapter 1, entitled “A Model for Real-Time Data Assessment with an Application to GDP Growth Rates”, provides a model for the data<p>revisions of macroeconomic variables that distinguishes between rational expectation updates and noise corrections. Thus, the model encompasses the two polar views regarding the publication process of statistical agencies: noise versus news. Most of the studies previous studies that analyze data revisions are based<p>on the classical noise and news regression approach introduced by Mankiew, Runkle and Shapiro (1984). The problem is that the statistical tests available do not formulate both extreme hypotheses as collectively exhaustive, as recognized by Aruoba (2008). That is, it would be possible to reject or accept both of them simultaneously. In turn, the model for the<p>DPP presented here allows for the simultaneous presence of both noise and news. While the “regression approach” followed by Faust et al. (2005), along the lines of Mankiew et al. (1984), identifies noise in the preliminary<p>figures, it is not possible for them to quantify it, as done by our model. <p><p>The second and third chapters acknowledge the possibility that macroeconomic data is measured with errors, but the approach followed to model the missmeasurement is extremely stylized and does not capture the complexity of the revision process that we describe in the first chapter.<p><p><p>Chapter 2, entitled “Revisiting the Success of the RBC model”, proposes the use of dynamic factor models as an alternative to the VAR based tools for the empirical validation of dynamic stochastic general equilibrium (DSGE) theories. Along the lines of Giannone et al. (2006), we use the state-space parameterisation of the factor models proposed by Forni et al. (2007) as a competitive benchmark that is able to capture weak statistical restrictions that DSGE models impose on the data. Our empirical illustration compares the out-of-sample forecasting performance of a simple RBC model augmented with a serially correlated noise component against several specifications belonging to classes of dynamic factor and VAR models. Although the performance of the RBC model is comparable<p>to that of the reduced form models, a formal test of predictive accuracy reveals that the weak restrictions are more useful at forecasting than the strong behavioral assumptions imposed by the microfoundations in the model economy.<p><p>The last chapter, “What are Shocks Capturing in DSGE modeling”, contributes to current debates on the use and interpretation of larger DSGE<p>models. Recent tendency in academic work and at central banks is to develop and estimate large DSGE models for policy analysis and forecasting. These models typically have many shocks (e.g. Smets and Wouters, 2003 and Adolfson, Laseen, Linde and Villani, 2005). On the other hand, empirical studies point out that few large shocks are sufficient to capture the covariance structure of macro data (Giannone, Reichlin and<p>Sala, 2005, Uhlig, 2004). In this Chapter, we propose to reconcile both views by considering an alternative DSGE estimation approach which<p>models explicitly the statistical agency along the lines of Sargent (1989). This enables us to distinguish whether the exogenous shocks in DSGE<p>modeling are structural or instead serve the purpose of fitting the data in presence of misspecification and measurement problems. When applied to the original Smets and Wouters (2007) model, we find that the explanatory power of the structural shocks decreases at high frequencies. This allows us to back out a smoother measure of the natural output gap than that<p>resulting from the original specification. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

This thesis examines empirical and theoretical issues related to the role of uninsurable individual risk and heterogeneity in macroeconomics. The thesis includes four chapters. The first chapter uses data from the Panel Study of Income Dynamics (PSID) to test full risk-sharing among North American households. The second chapter is a short essay where I use simulated data to show how the method applied in the previous chapter can be used to distinguish between partial risk sharing and imperfect credit markets. The third chapter develops a heterogeneous agent dynamic general equilibrium model which jointly models aggregate saving and employment. Finally, the fourth chapter investigates empirically the ability of financial market incompleteness to help explaining the equity premium puzzle. The central motivation throughout this dissertation is the recognition that the interaction between cross-sectional volatility and aggregate volatility is of fundamental importance to understand the way we should model macroeconomic aggregates such as aggregate consumption, asset prices and business cycle fluctuations.<p><p> / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

Face aux enjeux socioéconomiques, démocratiques, et environnementaux, la croissance économique comme fin en soi, ou comme condition nécessaire au « développement », est de nouveau remise en cause. Depuis le début du XXIème siècle, suscitant un intérêt grandissant et de vifs échanges, la Décroissance se fraie une place dans le débat. Après avoir resitué son émergence dans la perspective historique de la controverse qui s'est développée, au cours de la deuxième moitié du XXe siècle, autour de la croissance et du modèle de développement des pays industrialisés, nous suggérons une synthèse des principales idées et des propositions concrètes actuellement portées par ses partisans. Celles-ci soulèvent un certain nombre de questions complexes, pour lesquelles nous proposons d'apporter quelques éclairages à travers un exercice de modélisation prospective. Nous réalisons pour cela une série d'entretiens, qui visent à recueillir différentes visions détaillées et quantifiées de ce que pourraient être, selon les participants, des scénarios de Décroissance, ou - plus largement- des scénarios de transitions souhaitables et soutenables, notamment en termes d'évolution des institutions, des modes de vie et de consommation, pour la France. En parallèle de ces entretiens, nous développons un modèle spécifique de simulation dynamique de l'économie française, construit autour de l'analyse entrées-sorties, sur la base de données publiques, et incorporant un haut niveau de détail. A l'aide de cet outil macroéconomique, nous proposons alors d'explorer, sur un horizon à long terme (2060) les implications possibles de différents scénarios, dont ceux élaborés à partir des entretiens. Nous nous intéressons par exemple aux conséquences possibles en termes d'emploi, de finances publiques, de consommation d'énergie, d'émissions de polluants atmosphériques, et de production de déchets. Les résultats des simulations soulignent l'importance des choix institutionnels, des facteurs culturels, comportementaux, et « non-techniques », et le potentiel de certaines propositions des mouvements de la Décroissance. Ils invitent ainsi à ouvrir le débat autour de la construction collective d'un nouveau projet de société. Dans cette perspective, notre approche offre un support simple et efficace pour la compréhension commune et la délibération collective. / The development paths followed by industrial societies in the last decades have led them in front of complex socioeconomic, democratic and environmental crises, which question the relevance of economic growth, either as a goal in itself, or as a way to achieve “development”. With the emergence of the degrowth movement at the beginning of the 21st century, the call for transitions towards sustainable “post-growth societies” is now consolidating into a multifaceted political project. For the “wealthiest” countries, where the ecological footprint per capita is greater than the global sustainable level, this project may be envisioned as a voluntary, socially sustainable, equitable and smooth downscaling of production and consumption, and thus throughput, to an environmentally sustainable level. Such a project raises numerous questions, for instance: what concrete proposals could initiate such a transition? What could such paths induce in terms of employment, public debt, energy consumption, waste, or greenhouse gas emission mitigation? What structural or institutional obstacles must be overcome and how? Etc. In this research, we offer to discuss such questions with the help of prospective modeling. Our approach involves a series of interviews, conducted, among others, with actors within the Degrowth movement. These are aimed at collecting detailed and quantified visions or narratives about what Degrowth scenarios or – more broadly speaking– scenarios of transition towards sustainable and desirable societies could look like, for France, in the mind of participants, especially in terms of institutions, lifestyles and consumption patterns. In parallel, we have designed and developed a specific dynamic simulation model of the French monetary economy, featuring a high level of detail and disaggregation, based on input-output analysis, and built using public data. Using this macroeconomic tool, we investigate, over the long term (2060), the possible outcomes of different scenarios, including those inferred from the interviews, in terms of employment, public debt, energy consumption, waste and atmospheric emissions. We discuss the potential strengths and weaknesses of the different visions they reflect. Our results highlight in particular the importance of cultural, social, behavioral and “non-technical” factors, stress the potential of various degrowth proposals, and recall the critical need for the collective elaboration of a societal project. In this perspective, our modeling approach provides a simple, yet powerful tool for common understanding and collective deliberation.

La prévision macroéconomique à court terme est un exercice aussi complexe qu’essentiel pour la définition de la politique économique et monétaire. Les crises financières récentes ainsi que les récessions qu’ont endurées et qu’endurent aujourd’hui encore, en ce début d’année 2014, nombre de pays parmi les plus riches, témoignent de la difficulté d’anticiper les fluctuations économiques, même à des horizons proches. Les recherches effectuées dans le cadre de la thèse de doctorat qui est présentée dans ce manuscrit se sont attachées à étudier, analyser et développer des modélisations pour la prévision de croissance économique. L’ensemble d’informations à partir duquel construire une méthodologie prédictive est vaste mais également hétérogène. Celle-ci doit en effet concilier le mélange des fréquences d’échantillonnage des données et la parcimonie nécessaire à son estimation. Nous évoquons à cet effet dans un premier chapitre les éléments économétriques fondamentaux de la modélisation multi-fréquentielle. Le deuxième chapitre illustre l’apport prédictif macroéconomique que constitue l’utilisation de la volatilité des variables financières en période de retournement conjoncturel. Le troisième chapitre s’étend ensuite sur l’inférence bayésienne et nous présentons par ce biais un travail empirique issu de l’adjonction d’une volatilité stochastique à notre modèle. Enfin, le quatrième chapitre propose une étude des techniques de sélection de variables à fréquence multiple dans l’optique d’améliorer la capacité prédictive de nos modélisations. Diverses méthodologies sont à cet égard développées, leurs aptitudes empiriques sont comparées, et certains faits stylisés sont esquissés. / Economic downturn and recession that many countries experienced in the wake of the global financial crisis demonstrate how important but difficult it is to forecast macroeconomic fluctuations, especially within a short time horizon. The doctoral dissertation studies, analyses and develops models for economic growth forecasting. The set of information coming from economic activity is vast and disparate. In fact, time series coming from real and financial economy do not have the same characteristics, both in terms of sampling frequency and predictive power. Therefore short-term forecasting models should both allow the use of mixed-frequency data and parsimony. The first chapter is dedicated to time series econometrics within a mixed-frequency framework. The second chapter contains two empirical works that sheds light on macro-financial linkages by assessing the leading role of the daily financial volatility in macroeconomic prediction during the Great Recession. The third chapter extends mixed-frequency model into a Bayesian framework and presents an empirical study using a stochastic volatility augmented mixed data sampling model. The fourth chapter focuses on variable selection techniques in mixed-frequency models for short-term forecasting. We address the selection issue by developing mixed-frequency-based dimension reduction techniques in a cross-validation procedure that allows automatic in-sample selection based on recent forecasting performances. Our model succeeds in constructing an objective variable selection with broad applicability.

Le Luxembourg est le 3ème exportateur mondial de services financiers. Il figure parmi les pays qui accueillent le plus d’investissements directs en provenance de l’étranger, ce qui indique l’intensité de ses liens avec l’économie mondiale. Le but de ce travail est d’analyser l’influence éventuelle d’une économie mondiale caractérisée par l’interdépendance des marchés réels et financiers sur l’économie Luxembourgeoise. Chapitre 1 présente une analyse des interactions de l’économie Luxembourgeoise avec le monde extérieur. Le chapitre suivant est consacré à la revue de la littérature portant sur la modélisation de l’intermédiation financière au niveau macroéconomique, couvrant plusieurs types d’approches de modélisations. Enfin, le troisième chapitre comporte un modèle macroéconométrique multi-pays construit et analysé afin de simuler les scénarios plausibles. Le modèle y est présenté avec ses fondements théoriques, les résultats des simulations et une comparaison avec d’autres modèles. La nouveauté du modèle réside dans sa prise en compte du commerce international désagrégé en services financiers et autres, et des investissements internationaux en portefeuille avec leurs flux de titres et de capitaux, ainsi que de leur impact sur la croissance économique. Les résultats des simulations montrent que ce cadre d’analyse donne parfois des résultats différents par rapport aux modèles standards. Nombre de scénarios qui ne peuvent être simulés par d’autres modèles, tels que la baisse des flux internationaux d’investissements de portefeuille, sont également analysés et confirment la forte vulnérabilité du Luxembourg aux chocs externes qui ont lieu sur les marchés financiers. / Luxembourg is world’s third financial services exporter and one of world’s top recipients of foreign direct investment in value as well as per capita terms, which highlight its strong linkages with world economy. The objective of this dissertation is to analyze possible outcomes for the very small and very open economy of Luxembourg in a world environment, where real and financial markets affect each other. To better understand the characteristics of the economy and economic mechanisms behind them, a thorough analysis with emphasis put on the interactions with the outside world based on available data and relevant literature is presented (Chapter 1). Subsequently a survey of literature devoted to modeling financial intermediation at macroeconomic level across various types of modeling approaches is offered (Chapter 2). Finally, a multi-country macroeconometric model built to simulate possible scenarios is presented and analyzed (Chapter 3) with its theoretical background, simulations’ results and comparison with other models. The model is novel in that it accounts for international trade disaggregated into financial services and the rest, and international portfolio investment in securities and equity flows, that have a significant impact on the country’s economic growth. Simulations’ results show that such a framework generates sometimes markedly different results than more standard models. A number of scenarios which cannot be simulated in other models, such as American stock market fall or a decrease in international portfolio flows, are also analyzed and confirm the high vulnerability of Luxembourg economy to external shocks originating in financial markets.

Cette thèse est consacrée à l‘étude de la relation entre la croissance économique et l’environnement, en tenant compte des décisions altruistes des ménages envers leurs enfants en termes de legs économique, éducatif et environnemental. Ce travail s’articule autour de trois chapitres. Le premier se focalise sur les premiers stades de développement, marquant un tournant majeur de cette relation, et met en exergue le rôle des interactions des sphères économique, démographique et environnementale dans l’émergence d’un processus d’industrialisation polluante. Il illustre également les grandes disparités observées historiquement avec des économies piégées dans une trappe à pauvreté et d’autres se développant au prix d’une pollution élevée. Les chapitres suivants s’intéressent à des économies développées. Le deuxième chapitre prend en compte l’endogénéité des préférences environnementales pour analyser une politique environnementale composée d’outils usuels (taxe sur la pollution et dépenses de dépollution) et d’un outil éducatif visant à sensibiliser les ménages à l'environnement. Nous montrons qu’un tel "policy mix" peut permettre à la fois d’éviter des inégalités intergénérationnelles, provenant de fluctuations des préférences, et de favoriser la croissance économique. Le troisième chapitre traite des effets de la pollution sur l’espérance de vie et de l’aspect inégalitaire de leur répartition au sein de la population. Nous trouvons qu’il existe une trappe à inégalités, où les disparités empirent constamment mais qu’une politique environnementale peut permettre d’échapper à cette trappe et d’augmenter la croissance de l’économie, par ses effets sur la santé et l’éducation. / This thesis is devoted to the analysis of the relationship between economic growth and the environment, when considering the altruistic choices of parents toward their children, through environmental, economic and educative bequests. This work is organized around three chapters. The first focuses on the first stages of economic development, corresponding to a major turning point of this relationship. It highlights the role of interactions between economic, demographic and environmental spheres in the emergence of a polluting industrialization. Moreover, it illustrates the great disparities, historically observed, with economies stuck in a poverty trap and others developing at expense of their environment. The others chapter deals with developed economies. The second chapter takes into account the endogeneity of environmental preferences in order to analyze the implications of an environmental policy composed of usual tools (pollution tax and abatement activities) and an educative tool aiming to raise households’ environmental awareness. We show that such a policy mix may allow to avoid intergenerational inequalities, coming from fluctuations in preferences, and to enhance economic growth. The third chapter considers the effects of pollution on longevity and their unequal repartition across population. We highlight that there exists an inequality trap, where disparities are persistently widening, but also that an environmental policy may allow an economy to escape from this trap and to improve economic growth, through its positive effects on health and on the returns to education.