Publications
Worrisome topics, such as climate change, economic crises, or pandemics including Covid-19, are increasingly present and pervasive due to digital media and social networks. Do worries triggered by such topics affect the cognitive capacities of young adults? In an online experiment during the Covid-19 pandemic (N=1503), we test how the cognitive performance of university students responds when exposed to topics discussing (i) current adverse mental health consequences of social restrictions or (ii) future labor market hardships linked to the economic contraction. Moreover, we study how such a response is affected by a performance goal. We find that the labor market topic increases cognitive performance when it is motivated by a goal, consistent with a ‘tunneling effect’ of scarcity or a positive stress effect. However, we show that the positive reaction is mainly concentrated among students with larger financial and social resources, pointing to an inequality-widening mechanism. Conversely, we find limited support for a negative stress effect or a ‘cognitive load effect’ of scarcity, as the mental health topic has a negative but insignificant average effect on cognitive performance. Yet, there is a negative response among psychologically vulnerable individuals when the payout is not conditioned on reaching a goal.
What is the role of income polarization for explaining differentials in public funding of education? To answer this question, we provide a new theoretical modelling for the income distribution that can directly monitor income polarization. It leads to a new income polarization index where the middle class is represented by an interval. We implement this distribution in a political economy model with endogenous fertility and public/private educational choices. We show that when households vote on public schooling expenditures, polarization matters for explaining disparities in public education funding across communities. Using micro-data covering two groups of school districts, we find that both income polarization and income inequality affect public school funding with opposite signs whether there exist a Tax Limitation Expenditure (TLE) or not.
This paper introduces an autoregressive conditional beta (ACB) model that allows regressions with dynamic betas (or slope coefficients) and residuals with GARCH conditional volatility. The model fits in the (quasi) score-driven approach recently proposed in the literature, and it is semi-parametric in the sense that the distributions of the innovations are not necessarily specified. The time-varying betas are allowed to depend on past shocks and exogenous variables. We establish the existence of a stationary solution for the ACB model, the invertibility of the score-driven filter for the time-varying betas, and the asymptotic properties of one-step and multistep QMLEs for the new ACB model. The finite sample properties of these estimators are studied by means of an extensive Monte Carlo study. Finally, we also propose a strategy to test for the constancy of the conditional betas. In a financial application, we find evidence for time-varying conditional betas and highlight the empirical relevance of the ACB model in a portfolio and risk management empirical exercise.
Lower tariffs typically raise productivity, production, and trade, increasing the benefits from building infrastructure. Infrastructure spending by governments should therefore increase after countries open up to trade. I test this hypothesis empirically using a trade reform in India and find that a 1 percentage point reduction in tariffs increased states’ infrastructure spending by 0.5% between 1991 and 2001. To understand the mechanisms behind my empirical findings, I develop and calibrate a multi-region model of international trade, private capital accumulation, and infrastructure spending, in which each government chooses such spending to maximize their state’s welfare. I find if governments choose infrastructure following the reform optimally, infrastructure would have increased by 60% on average. The actual increase, based on my empirical findings, was about 29%. Counterfactual exercises show that raising aggregate infrastructure towards its optimal following the trade reform will result in state GDP to increase by 7% points on average.
Lors des élections françaises, les médias belges et suisses interfèrent régulièrement en publiant des sondages et des prédictions avant la fermeture des bureaux de vote. Nous utilisons la précocité et le degré de confiance inhabituels des sondages au second tour de l’élection présidentielle de 2017 pour étudier leurs effets sur la participation électorale. Notre analyse compare les taux de participation à différents horaires, aux premier et second tours, et par rapport aux élections de 2012 et 2022. Les résultats montrent une baisse significative de la participation après la publication des sondages à la sortie des urnes. L’effet s’élève à 1,1 point de pourcentage dans l’analyse en triples differences avec l’élection de 2022 et il est plus fort dans les départements limitrophes de la Belgique. Nous constatons également un léger effet underdog pouvant réduire la marge de victoire jusqu’à 1 point de pourcentage.
Objectives This study aims to establish an inventory of the teaching of Therapeutic Patient Education (TPE) in the initial training of French midwives. Method: A descriptive quantitative study was conducted in France. An online questionnaire comprising 27 questions was distributed to 35 French midwifery schools. Results: Out of 19 schools that responded to the survey, 11 taught TPE, 8 did not address it in training. This teaching is mainly transversal. The obstacles to the teaching of TPE are the current density of the program, the absence of a text regulating this teaching and the difficulties in circumscribing the field of TPE in relation to that of prevention, promotion and health education. The simulation is used in only one school. Discussion: This survey shows a willingness of educational teams to invest in the teaching of health education, including TPE. For this, it is a question of strengthening the training of teachers in order to clarify the areas of intervention of the midwife calling for health promotion, prevention and health education; to offer specific internships to students and to use simulation. Extending the duration of initial training is an opportunity to plan specific teaching and to discuss the place of the health service.
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Using data on roughly half a million cases and 10,000 judges from Pakistan and India, Mehmood et al. estimate the impact of the Ramadan fasting ritual on criminal sentencing decisions. They find that fasting increases judicial leniency and reduces reversals of decisions in higher courts. We estimate the impact of the Ramadan fasting ritual on criminal sentencing decisions in Pakistan and India from half a century of daily data. We use random case assignment and exogenous variation in fasting intensity during Ramadan due to the rotating Islamic calendar and the geographical latitude of the district courts to document the large effects of Ramadan fasting on decision-making. Our sample comprises roughly a half million cases and 10,000 judges from Pakistan and India. Ritual intensity increases Muslim judges' acquittal rates, lowers their appeal and reversal rates, and does not come at the cost of increased recidivism or heightened outgroup bias. Overall, our results indicate that the Ramadan fasting ritual followed by a billion Muslims worldwide induces more lenient decisions.
Despite their high predictive performance, random forest and gradient boosting are often considered as black boxes which has raised concerns from practitioners and regulators. As an alternative, we suggest using partial linear models that are inherently interpretable. Specifically, we propose to combine parametric and non-parametric functions to accurately capture linearities and non-linearities prevailing between dependent and explanatory variables, and a variable selection procedure to control for overfitting issues. Estimation relies on a two-step procedure building upon the double residual method. We illustrate the predictive performance and interpretability of our approach on a regression problem.
