Unraveling the short- and long-term dynamics of the causes and effects of road traffic accidents: the case of Tunisian road safety over the 1960-2021 period

This study examines the fundamental question of how socio-economic, behavioural, and environmental factors have shaped the occurrence of road traffic accidents in Tunisia from 1960 to 2021. Using the autoregressive distributed lag (ARDL) modelling framework, the research captures both short-term variations and long-term dynamics, identifying persistent drivers of accident trends. Using an autoregressive distributed lag (ARDL) model, we specified the persistent causes and interactions from the short to long term. The results reveal that in the short term, rising GDP, driver errors, and poor passenger behaviour significantly increase accident rates, and these factors continue to exert a harmful influence over the long term. Notably, poor environmental conditions do not have a significant long-term impact, while the steady growth of the vehicle fleet is a key contributor to the long-term rise in accidents. The analysis further uncovers a spatiotemporal interaction among these causes, amplifying the spread of accidents over time and space. These findings highlight the importance of designing sustainable road safety policies that specifically target the spatial and temporal dimensions of accident causes, enabling more effective and lasting interventions to reduce road accidents and improve public safety.