Impact of socioeconomic determinants on the speed of epidemic diseases: a comparative analysisJournal articleGilles Dufrénot, Ewen Gallic, Pierre Michel, Norgile Midopkè Bonou, Ségui Gnaba and Iness Slaoui, Oxford Economic Papers, pp. gpae003, 2024

We study the impact of socioeconomic factors on two key parameters of epidemic dynamics. Specifically, we investigate a parameter capturing the rate of deceleration at the very start of an epidemic, and a parameter that reflects the pre-peak and post-peak dynamics at the turning point of an epidemic like coronavirus disease 2019 (COVID-19). We find two important results. The policies to fight COVID-19 (such as social distancing and containment) have been effective in reducing the overall number of new infections, because they influence not only the epidemic peaks, but also the speed of spread of the disease in its early stages. The second important result of our research concerns the role of healthcare infrastructure. They are just as effective as anti-COVID policies, not only in preventing an epidemic from spreading too quickly at the outset, but also in creating the desired dynamic around peaks: slow spreading, then rapid disappearance.

Optimal Transport for Counterfactual Estimation: A Method for Causal InferenceBook chapterArthur Charpentier, Emmanuel Flachaire and Ewen Gallic, In: Optimal Transport Statistics for Economics and Related Topics, Nguyen Ngoc Thach, Vladik Kreinovich, Doan Thanh Ha and Nguyen Duc Trung (Eds.), 2024, pp. 45-89, Springer Nature Switzerland, 2024

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).

Optimal lockdowns for COVID-19 pandemics: Analyzing the efficiency of sanitary policies in EuropeJournal articleEwen Gallic, Michel Lubrano and Pierre Michel, Journal of Public Economic Theory, Volume 24, Issue 5, pp. 944-967, 2022

Two main nonpharmaceutical policy strategies have been used in Europe in response to the COVID-19 epidemic: one aimed at natural herd immunity and the other at avoiding saturation of hospital capacity by crushing the curve. The two strategies lead to different results in terms of the number of lives saved on the one hand and production loss on the other hand. Using a susceptible–infected–recovered–dead model, we investigate and compare these two strategies. As the results are sensitive to the initial reproduction number, we estimate the latter for 10 European countries for each wave from January 2020 till March 2021 using a double sigmoid statistical model and the Oxford COVID-19 Government Response Tracker data set. Our results show that Denmark, which opted for crushing the curve, managed to minimize both economic and human losses. Natural herd immunity, sought by Sweden and the Netherlands does not appear to have been a particularly effective strategy, especially for Sweden, both in economic terms and in terms of lives saved. The results are more mixed for other countries, but with no evident trade-off between deaths and production losses.

Weather shocksJournal articleEwen Gallic and Gauthier Vermandel, European Economic Review, Volume 124, pp. 103409, 2020

How much do weather shocks matter? The literature addresses this question in two isolated ways: either by looking at long-term effects through the prism of calibrated theoretical models, or by focusing on both short and long terms through the lens of empirical models. We propose a framework that reconciles these two approaches by taking the theory to the data in two complementary ways. We first document the propagation mechanism of a weather shock using a Vector Auto-Regressive model on New Zealand Data. To explain the mechanism, we build and estimate a general equilibrium model with a weather-dependent agricultural sector to investigate the weather’s business cycle implications. We find that weather shocks: (i) explain about 35% of GDP and agricultural output fluctuations in New Zealand; (ii) entail a welfare cost of 0.30% of permanent consumption; (iii) critically increases the macroeconomic volatility under climate change, resulting in a higher welfare cost peaking to 0.46% in the worst case scenario of climate change.

La démographie historique peut-elle tirer profit des données collaboratives des sites de généalogie ?Journal articleArthur Charpentier and Ewen Gallic, Population, Volume 75, Issue 2-3, pp. 391-421, 2020

Les sites qui proposent à leurs utilisateurs de reconstituer en ligne leur arbre généalogique fleurissent sur Internet. Cet article analyse le travail de collecte et de saisie effectué par ces utilisateurs et comment il pourrait être utilisé en démographie historique, afin de compléter la connaissance des générations du passé. Pour cela, les résultats obtenus à partir de la base Geneanet sont confrontés à ceux connus de la littérature, et concernent les enregistrements de 2 457 450 individus français ou d'origine française ayant vécu au xixe siècle. Est ainsi mis en évidence un biais important du rapport de masculinité (sous-représentation des femmes). La fécondité est elle aussi fortement sous-estimée. Quant à la mortalité, (par comparaison aux valeurs historiques), ces données sous-estiment la mortalité des hommes jusqu’à 40 ans environ et celle des femmes jusqu’à 25 ans, puis elles la surestiment. Enfin, la richesse des caractéristiques spatiales contenues dans les arbres généalogiques est également exploitée pour produire de nouvelles données sur les migrations internes au xixe siècle.

Using collaborative genealogy data to study migration: a research noteJournal articleArthur Charpentier and Ewen Gallic, The History of the Family, Volume 25, Issue 1, pp. 1-21, 2020

The digital age allows data collection to be done on a large scale and at low cost. This is the case of genealogy trees, which flourish on numerous digital platforms thanks to the collaboration of a mass of individuals wishing to trace their origins and share them with other users. The family trees constituted in this way contain information on the links between individuals and their ancestors, which can be used in historical demography, and more particularly to study migration phenomena. The case of 19th century France is taken as an example, using data from the family trees of 238,009 users of the Geneanet website, or 2.5 million (unique) individuals. Using the geographical coordinates of the birthplaces of 25,485 ancestors born in France between 1800 and 1804 and those of their descendants (24,516 children, 29,715 grandchildren and 62,165 great-grandchildren), we study migration between generations at several geographical scales. We start with a broad scale, that of the departments, to reach a much finer one, that of the cities. Our results are consistent with those of the literature traditionally based on the parish or civil status registers. The results show that the use of collaborative genealogy data not only makes it possible to support previous findings of the literature, but also to enrich them.

Predicting musculoskeletal disorders risk using tree-based ensemble methodsJournal articleAlain Paraponaris, A. Ba, Ewen Gallic, Q. Liance and Pierre Michel, European Journal of Public Health, Volume 29, Issue Supplement_4, 2019

Musculoskeletal disorders (MSD) can cause short-term disorders and permanent disabilities which may all result in serious limitations in ac

L’impact de la crise financière sur la performance de la politique monétaire conventionnelle de la zone euroJournal articleEwen Gallic, Jean-Christophe Poutineau and Gauthier Vermandel, Revue Économique, Volume 68, Issue HS1, pp. 63-86, 2017

Cet article évalue dans quelle mesure la crise financière de 2007 a affecté la mise en œuvre d’une politique monétaire conventionnelle dans la zone euro. Cette question est abordée dans un cadre théorique reprenant le modèle de synthèse de la nouvelle économie keynésienne qui prévalait avant la crise de 2007. On observe que la crise a fortement réduit la performance de la politique conventionnelle après la détérioration de l’arbitrage entre la variance de l’inflation et celle de l’activité (telle que définie par la courbe de Taylor), et après la dégradation de son efficacité (telle que mesurée à partir de l’écart à la courbe de Taylor provenant d’une forte augmentation de la contribution de l’output gap). Les valeurs de taux d’intérêt simulées par notre modèle montrent que la BCE aurait dû fixer des taux d’intérêt inférieurs à ceux observés, qui plus est négatifs en fin de période. De nouveaux instruments non conventionnels s’avèrent de fait nécessaires afin de suppléer à une pratique de la politique monétaire qui était centrée prioritairement sur la stabilité des prix, dans un environnement macroéconomique calme.

Kernel density estimation based on Ripley’s correctionJournal articleArthur Charpentier and Ewen Gallic, GeoInformatica, Volume 20, Issue 1, pp. 95-116, 2016

In this paper, we investigate a technique inspired by Ripley’s circumference method to correct bias of density estimation of edges (or frontiers) of regions. The idea of the method was theoretical and difficult to implement. We provide a simple technique – based of properties of Gaussian kernels – to efficiently compute weights to correct border bias on frontiers of the region of interest, with an automatic selection of an optimal radius for the method. We illustrate the use of that technique to visualize hot spots of car accidents and campsite locations, as well as location of bike thefts.