The impact of macroeconomic variables on the selected type of traffic crash: a study based on ARDL technique

Abstract

Urban Jordan has witnessed substantial traffic growth in recent years. This study examines the long-term and dynamic nexus between crash rates in urban Jordan cities and macroeconomic explanatory variables. Three types of crashes have been studied including, vehicle rollover, vehicle-pedestrian crashes, and vehicle-vehicle crashes against the following explanatory variables; the proportion of the population living in urban areas, GDP growth rate, the total length of road networks, vehicle number growth rate, and spaces of the newly added building. Accordingly, a case study method has been used, covering the timeframe from 2004 to 2022, by employing the autoregressive distributed lag (ARDL) technique. The ARDL estimates showed the presence of long-run cointegration between variables for all types of crashes. Furthermore, the ARDL estimates on the long- and short-run indicate a varying effect of the considered explanatory variables by crash type. The results indicate that the expansion of the urban population and GDP growth rate play a significant role in determining crash rate in urban cities. Moreover, this study urges decision-makers to monitor the impact of expected migration on traffic safety, whether from the countryside or neighbouring countries experiencing crises.