Publications
To what extent protectionism affects growth and (de)stabilizes the economies? Although the impact of protectionism on growth has been widely explored without reaching a consensus, few has been said on its impact on macroeconomic stability. The present paper attempts to gauge more precisely its implications using a Barro-type (Barro, 1990) endogenous growth model with public debt and credit constraint where tariffs are a proxy of protectionism. Our main result is to show that when the debt level is high, and the share of foreign goods in total consumption is large enough, increasing tariffs may have a destabilizing effect generating some expectation coordination failures between multiple equilibria. We also exhibit some trade-off between tariffs and growth as tariffs are beneficial only to the low growth equilibrium which may only appear when the international interest rate is low enough. Finally, focusing on the local stability property, we show that the high BGP is always characterized by local indeterminacy, while the low BGP is always a saddle point. We then prove that tariffs may be responsible for the existence of large self-fulfilling fluctuations.
We introduce a new approach to apply the boosted difference of convex functions algorithm (BDCA) for solving non-convex and non-differentiable problems involving difference of two convex functions (DC functions). Supposing the first DC component differentiable and the second one possibly non-differentiable, the main idea of BDCA is to use the point computed by the DC algorithm (DCA) to define a descent direction and perform a monotone line search to improve the decreasing the objetive function accelerating the convergence of the DCA. However, if the first DC component is non-differentiable, then the direction computed by BDCA can be an ascent direction and a monotone line search cannot be performed. Our approach uses a non-monotone line search in the BDCA (nmBDCA) to enable a possible growth in the objective function values controlled by a parameter. Under suitable assumptions, we show that any cluster point of the sequence generated by the nmBDCA is a critical point of the problem under consideration and provide some iteration-complexity bounds. Furthermore, if the first DC component is differentiable, we present different iteration-complexity bounds and prove the full convergence of the sequence under the Kurdyka-\L{}ojasiewicz property of the objective function. Some numerical experiments show that the nmBDCA outperforms the DCA such as its monotone version.
Several factors can deeply affect employees’ quality of life at work. Work-life balance, subjective well-being and job satisfaction are three of these factors and it is in the best interest of companies to handle these topics carefully. This is a sine qua non condition of the strength and the quality of relationships with employees. It is also a source of confidence for employees, especially where this is being mediated through Human Resource (HR) processes. Our article studies the quality of life at work in the particular context of an MAR healthcare pathway that exacerbates the consequences for employees. Our work with hundreds of people enduring an MAR process shows that depending on whether firms take this situation into account or not, employees will feel either well-being or ill-being and will have different burnout or job satisfaction levels. All these variables influence their commitment and job performance. These links between a healthcare pathway and quality of life at work on the one hand, and between the quality of work and performance on the other hand, should lead employers to support employees in a personal vulnerable situation. The strength and the quality of the support provided by the HR function and the management is therefore a key point in the level of confidence that exists between firms and their employees.
Many studies have investigated the role of socio-demographic factors (including gender, age, race), cognitive ability and cultural factors on time and risk preferences. Yet, research regarding the effect of mindfulness on risk and time preferences has been limited. This study investigates the association between mindfulness and time/risk preferences. We conducted a survey on a representative sample of the French adult population (N = 1154) in Spring 2020. We assessed individual mindfulness through the Mindful Attention Awareness Scale (MAAS), and measured time and risk preferences with incentive-compatible economic games as well as self-reported questionnaires. Our results suggest that a higher level of mindfulness is associated with higher risk aversion and patience for stated preferences, but we found no relationship for revealed ones. We also observe that a higher level of mindfulness is related to greater time consistency, as we found a negative and significant association between the MAAS and the present and future biases.
Many studies have investigated the role of socio-demographic factors (including gender, age, race), cognitive ability and cultural factors on time and risk preferences. Yet, research regarding the effect of mindfulness on risk and time preferences has been limited. This study investigates the association between mindfulness and time/risk preferences. We conducted a survey on a representative sample of the French adult population (N = 1154) in Spring 2020. We assessed individual mindfulness through the Mindful Attention Awareness Scale (MAAS), and measured time and risk preferences with incentive-compatible economic games as well as self-reported questionnaires. Our results suggest that a higher level of mindfulness is associated with higher risk aversion and patience for stated preferences, but we found no relationship for revealed ones. We also observe that a higher level of mindfulness is related to greater time consistency, as we found a negative and significant association between the MAAS and the present and future biases.
We provide a unified framework with demand for housing over the life cycle and financial frictions to analyze the existence and macroeconomic effects of rational housing bubbles. We distinguish a housing price bubble, defined as the difference between the housing market price and its fundamental value, from a housing demand bubble, which corresponds to a situation where a pure speculative housing demand exists. In an overlapping generation exchange economy, we show that no housing price bubble occurs. However, a housing demand bubble may occur, generating a boom in housing prices and a drop in the interest rate, when households face a binding borrowing constraint. The multiplicity of steady states and endogenous fluctuations can occur when credit market imperfections are moderate. These fluctuations involve transitions between equilibria with and without a housing demand bubble that generate large fluctuations in housing prices consistent with observed patterns. We finally extend the basic framework to a production economy and we show that a housing demand bubble increases housing prices, which can still be characterized by large fluctuations.
Introduction
Alors que la vaccination contre la COVID-19 a été ouverte à l'ensemble de la population française adulte à partir du 31 mai 2021, la dynamique vaccinale a connu un ralentissement à partir de l’été 2021. Pour faire face à ce phénomène, le gouvernement a mis en place des mesures restrictives destinées exclusivement aux personnes non vaccinées. Cette étude analyse l'impact de l'arrêt de l'accès gratuit aux tests de dépistage COVID-19 sans prescription médicale pour les adultes non-vaccinés sur leur décision vaccinale.
Méthodes
La date d'arrêt de l'accès gratuit aux tests de dépistage a été fixée au 15 octobre 2021 (date de « l'événement » étudié) dans l'ensemble des départements de France métropolitaine. Nous utilisons les données longitudinales de Santé publique France pour la période allant du 17 juillet 2021 au 13 janvier 2022 (trois mois avant et après l'événement). Nous estimons une régression segmentée sur des données de panel avec le nombre quotidien de personnes ayant reçu une première injection de vaccin anti-COVID-19 comme variable d'intérêt : yit=αit+βafterit+γ1dateit+γ2dateit×afterit+ δXit+εit où yit est le nombre quotidien de premières doses de vaccin COVID-19 pour le département i à la date t, afterit est une variable indicatrice, qui vaut 1 lorsque la date est postérieure à l’évènement, 0 sinon ; dateit est le nombre de jours avant (valeurs négatives) ou après (valeurs positives) l’évènement ; Xit est un ensemble de variables de contrôle (caractéristiques socio-économiques au niveau départemental, mortalité hospitalière et mesure de la sévérité des restrictions) et αit est un effet fixe. Nous procédons ensuite à plusieurs tests de robustesse (l'approche « donut hole », choix optimal de la période d'estimation, test du placebo, mortalité décalée).
Résultats
Nous constatons que l'arrêt de l'accès gratuit aux tests de dépistage COVID-19 pour la population adulte française non vaccinée a eu un impact positif et significatif sur l'adhésion à la vaccination dans tous les départements métropolitains. Alors que nombre de premières doses s'effondre entre fin août et septembre 2021, il augmente légèrement après l'événement. Un taux de pauvreté plus élevé, la part des bénéficiaires d'une affection de longue durée plus importante et la mortalité hospitalière accrue augmentent le nombre de primo-vaccinations, tandis qu'un indice de vieillissement ou le taux de chômage plus élevés, tout comme la proportion plus forte des non-diplômés dans le département de résidence ont un impact négatif et significatif sur la décision vaccinale. Ces résultats restent robustes lorsque l'on réalise les différents tests mentionnés ci-dessus.
Conclusion
Bien que nous trouvions un impact significatif et positif de l'arrêt de l'accès gratuit aux tests de dépistage sur les primo-vaccinations, l'hésitation vaccinale elle-même pourrait subsister. En outre, les mesures coercitives pourraient compromettre la confiance dans les autorités sanitaires, contribuant ainsi encore plus à l'hésitation vaccinale. Une approche plus globale est nécessaire pour lutter contre ce phénomène
We show that the development of abstract reasoning and cognitive empathy (theory of mind) is severely hindered when children are deprived of the stimulation of a school environment. We document significantly lower abstract reasoning and cognitive empathy scores in elementary school children who returned from an extended school closure caused by the Covid-19 pandemic relative to proximate pre-pandemic cohorts. This developmental delay has a significant socioeconomic gradient, with underprivileged children experiencing more substantial delays. We also document a significant disruption in the development of socioemotional skills: 0.24 sd lower grit, 0.43 sd lower emotional empathy, 0.06 sd lower epistemic curiosity, and 0.24 sd higher impulsivity. About eight months of school exposure results in a remarkable recovery in abstract reasoning and theory of mind for all socioeconomic groups. However, the measured levels still indicate significant delays relative to the expected developmental trajectories. No notable improvements are observed in socioemotional skills except for curiosity. These findings reveal that the damage school closures inflicted on children goes beyond well-documented academic losses and highlight the crucial role of the school environment in fostering fundamental cognition and socioemotional development in children.
This paper develops a theoretical framework to think about employees' effort choices, and applies this framework to assess the ability of existing experimental designs to identify the effect of pay inequality on worker effort. The analysis shows that failure to control for a number of confounds—such as reciprocity towards the employer in multi-lateral gift-exchange games (vertical fairness), or the incentive to increase effort when feeling underpaid under piece rates (income targeting)—may lead to inaccurate interpretation of evidence of treatment effects. In light of these findings, the paper provides a set of recommendations on how to improve identification in the design of controlled experiments in the future.
Given that poor individuals face worse survival conditions than non-poor individuals, one can expect that a steeper income gradient in mortality leads, through stronger income-based selection, to a lower poverty rate at the old age (i.e. the "missing poor" hypothesis). This paper uses U.S. state-level data on poverty at age 65+ and life expectancy by income levels to provide an empirical test of the missing poor hypothesis. Using average temperature as an instrument for mortality differentials, we show that instrumented changes in mortality differentials have a negative and statistically significant effect on old-age poverty: a 1 % increase in the mortality differential implies a 16 % decrease in the 65+ headcount poverty rate. Using those regression results, we compute hypothetical old-age poverty rates while neutralizing the impact of the income gradient in mortality, and show that correcting for heterogeneity in income-based selection effects modifies the comparison of old-age poverty prevalence across states.
