Publications
Many problems ask a question that can be formulated as a causal question: what would have happened if...? For example, would the person have had surgery if he or she had been Black? To address this kind of questions, calculating an average treatment effect (ATE) is often uninformative, because one would like to know how much impact a variable (such as the skin color) has on a specific individual, characterized by certain covariates. Trying to calculate a conditional ATE (CATE) seems more appropriate. In causal inference, the propensity score approach assumes that the treatment is influenced by $$\boldsymbol{x}$$x, a collection of covariates. Here, we will have the dual view: doing an intervention, or changing the treatment (even just hypothetically, in a thought experiment, for example by asking what would have happened if a person had been Black) can have an impact on the values of $$\boldsymbol{x}$$x. We will see here that optimal transport allows us to change certain characteristics that are influenced by the variable whose effect we are trying to quantify. We propose here a mutatis mutandis version of the CATE, which will be done simply in dimension one by saying that the CATE must be computed relative to a level of probability, associated to the proportion of x (a single covariate) in the control population, and by looking for the equivalent quantile in the test population. In higher dimension, it will be necessary to go through transport, and an application will be proposed on the impact of some variables on the probability of having an unnatural birth (the fact that the mother smokes, or that the mother is Black).
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.
The Balassa-Samuelson effect is still an important phenomenon in the theory of economic development, as Balassa states, "As economic development is accompanied by greater inter-country differences in the productivity of tradable goods, differences in wages and service prices increase, and correspondingly so do differences in purchasing power parity and exchange rates." To the best of our knowledge, the Balassa-Samuelson effect has not been formally examined in the framework of optimal growth theory. By embedding the Balassa-Samuelson's original model in an optimal growth model setting, we investigate the validity of the Balassa-Samuelson effect in such a case and show that the Balassa-Samuelson effect follows from one of the properties of the optimal steady state.
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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.
We use data from Pakistan to establish a reciprocal exchange relationship between the judiciary and the government. We document large transfers in the form of expensive real estate from the government to the judiciary, and reciprocation in the form of pro-government rulings from the judiciary to the government. Our estimates indicate that the allocation of houses to judges increases pro-government rulings and reduces decisions on case merits. The allocation also incurs a cumulative cost of 0.03% of GDP to the government. However, it allows the government to expropriate additional land worth 0.2% of GDP in one year.
We use a distinctive methodology that leverages a fixed population of Twitter users located in France to gauge the mental health effects of repeated lockdown orders. To do so, we derive from our population a mental health indicator that measures the frequency of words expressing anger, anxiety and sadness. Our indicator did not reveal a statistically significant mental health response during the first lockdown, while the second lockdown triggered a sharp and persistent deterioration in all three emotions. Our estimates also show a more severe deterioration in mental health among women and younger users during the second lockdown. These results suggest that successive stay-at-home orders significantly worsen mental health across a large segment of the population. We also show that individuals who are closer to their social network were partially protected by this network during the first lockdown, but were no longer protected during the second, demonstrating the gravity of successive lockdowns for mental health.
This study investigates the effects of the investment-based presence of multinational enterprises (MNEs) on poverty in developing countries. The relationship is decomposed into different pathways corresponding to various facets of firms’ presence and activities, and monetary and multidimensional poverty. We hypothesize that depending on the pathways, the effects can be positive or negative in terms of poverty alleviation, and an overall conclusion has to be nuanced. The hypotheses are tested across 431 Indonesian administrative districts, observed in 2008, 2014 and 2018. Pooled instrumental variable regressions show that a higher presence of foreign MNEs does not reduce the number of people below the poverty line. It raises the depth and severity of poverty, and the population is also more exposed to pollutions. These results inform the ongoing debate, and offer important implications for policy makers eager to attract foreign direct investments, as well as for MNEs’ managers concerned with social responsibility and achieving sustainable development goals in host developing countries.
