Research

 This paper provides new evidence on the role of political alignment in natural disaster relief and its reward by voters at the municipal level. To analyze how political alignment between state and municipalities may influence the disaster declaration and the probability for citizens to get insurance compensations after a natural disaster, we exploit an original data set on natural disasters and French municipalities between 2008 and 2020. Using a difference-in-differences (DiD) strategy, we find that the political alignment between the local incumbent and the state significantly increases the probability of obtaining a natural disaster declaration from the state. To check whether citizens reward the incumbents who obtained a disaster declaration and therefore insurance compensation, we apply a Heckman model-based strategy to avoid selection bias. Although a natural disaster reduces the probability for the incumbents to be reelected, this negative effect is lower when the disaster declaration was decided by the state.

This paper investigates the indirect health effects of the pandemic, focusing on non-COVID mortality in France. Rather than examining the virus itself, we assess the broader consequences of the pandemic as a systemic shock that disrupted access to care, altered health behaviors, and increased psychosocial stress. Using the date of first COVID-19 hospitalization at the municipal level as an indicator of local exposure, we implement a staggered difference-in-differences design to estimate the causal impact of the pandemic on mortality. 

Despite growing evidence on the health effects of air pollution, few studies have examined its impact on COVID-19 hospitalizations and deaths, and none have explicitly accounted for preexisting comorbidities in a causal framework.  This study addresses this gap by investigating the relationship between PM2.5 exposure and COVID-19 severity. We place particular emphasis on the role of comorbidities, which can increase vulnerability to COVID-19 and may interact with air pollution exposure.  We use an exhaustive dataset covering the entire French territory over 2020--2021, totaling more than 3.5 million weekly observations. The data include information on COVID-19 mortality and hospitalizations, disaggregated by age, sex, and municipality, along with detailed records on preexisting conditions. To address endogeneity, we employ a two-stage least squares approach, using wind direction as an instrument for local PM2.5 concentrations.  We find no significant effect of PM2.5 exposure on COVID-19 mortality or hospitalizations among individuals without preexisting conditions. However, when accounting for comorbidities, we observe a significant increase in both, particularly among patients with respiratory and cardiovascular diseases. We find no significant differences between men and women, while age appears to be a major risk factor and vaccination is associated with a protective effect. These findings underscore the importance of incorporating comorbidities when assessing the health effects of air pollution during a pandemic. Our results also show that the effects of PM2.5 are driven by the oldest age groups, who are both more vulnerable to COVID-19 and more likely to have comorbidities.

Natural disasters can affect territories not just once but repeatedly, with increasing frequency and intensity. This paper analyzes the causal impact of natural disasters on municipalities' budgetary decisions, accounting for both the sporadic nature and repetition of these extreme events. Using an original dataset covering all French municipalities from 2000 to 2022, I employ a staggered difference-in-differences methodology with a non binary treatment approach. The findings reveal that each disaster triggers an immediate increase in municipal spending, followed by a long-term rise in tax revenues. Additionally, a heterogeneity analysis highlights variations across territories vulnerability and disaster types, shedding light on the specific factors that shape municipal responses.