377 Does road safety cointegrate with socioeconomic conditions in rich developing countries?

<h3>Background</h3> Road safety is a global challenge threatening public health and economic sustainability. Despite improvements in high-income developed countries, low-income developing countries continue to experience high numbers of road crashes and poor road-safety performance. According to the World Health Organization (WHO), socioeconomic factors pose a barrier to effective road safety in developing countries. <h3>Objectives and Analysis Methods</h3> Utilizing the autoregressive distributed lag (ARDL) cointegration error-corrected model, this study examined dynamic long- and short-term cointegration as well as Granger causality between road safety and socioeconomic conditions in rich developing countries. The road crash severity index is used as the primary measure of road safety. It primarily focuses on assessing the severity of road crashes based on the outcome, specifically the proportion of fatal crashes compared to non-fatal injuries, providing an indication of the relative risk and seriousness of road crashes in terms of human casualties. This indirectly highlights the importance of efficient emergency medical response and rescue operations. Two key variables represent socioeconomic conditions in this study: gross domestic product (GDP) per capita growth and population density. <h3>Results</h3> Using the United Arab Emirates (UAE) as a case study and time-series data from 1980 to 2019, the study revealed an increasing trend in the UAE road crash severity index, which could potentially indicate the need for improved emergency medical services, better-equipped trauma centers, and rescue capabilities to address severe crashes and provide timely care. The study’s findings further indicate a cointegration or long-term relationship between socioeconomic conditions and road safety. The ARDL model suggests that road safety adjusts to its long-term equilibrium at a speed of about 53% each year, correcting short-term deviations from its expected relationship with socioeconomic factors. The study’s findings also establish Granger causality from per capita GDP growth to road safety. <h3>Conclusions</h3> Overall, using the ARDL model as an analytical tool, this study contributes to our understanding of the relationship between road safety and socioeconomic conditions in rich developing countries. Understanding these dynamics is crucial for formulating effective policies and interventions to mitigate road crashes and enhance the overall road safety outcomes.