Assessing Climate-Related Health Risks in Morocco: Towards an Econometric Data-Driven Early Warning System

This article assesses climate-related health risks in Morocco by proposing an econometric data-driven early warning system. Using a Vector Autoregression (VAR) model applied to annual data from 2000 to 2020, we analyze the dynamic interactions between life expectancy (LE), CO₂ emissions, the overall health budget (BGS), the number of inhabitants per physician (NHM), and the number of inhabitants per healthcare facility (NHE). Stationarity tests confirm the stability of the series in logarithmic differences, and model diagnostics validate its specification.The results show that LE in Morocco exhibits high inertia, with more than 94% of its variance explained by its own past shocks. CO₂ emissions, although positively correlated with LE in descriptive analyses, account for only about 1.35% of the variance in LE over a ten-year horizon, with a delayed effect. The health budget (BGS) contributes moderately (approximately 2%), confirming the importance of public health investments. Impulse response functions reveal that CO₂ shocks do not have a significant immediate impact on LE, suggesting a relative resilience of Morocco's health system to climate variability during the study period, possibly mitigated by the country's low emission levels and energy transition policies.This work provides an operational econometric framework for monitoring the impact of climate and health variables. It highlights the predominance of structural health determinants and argues for the targeted integration of climate indicators into epidemiological surveillance systems, enabling proactive health policy adapted to environmental challenges.