Abstract
The aims of this project were to examine trends in road trauma in New South
Wales and to fit explanatory time series models in order to assess the relationship between key socio-economic and weather data and the observed level of road trauma. The explanatory time series models revealed that an increase of 1% in the unemployment rate was associated with a 0.043% decrease in fatal crashes; an increase of 1% in alcohol sales (deflated by CPI) was associated with a 0.27% rise in all crashes; and an increase of 1% in average rainfall was associated with a 0.013% rise in casualty crashes and a 0.029% increase in all crashes.
Wales and to fit explanatory time series models in order to assess the relationship between key socio-economic and weather data and the observed level of road trauma. The explanatory time series models revealed that an increase of 1% in the unemployment rate was associated with a 0.043% decrease in fatal crashes; an increase of 1% in alcohol sales (deflated by CPI) was associated with a 0.27% rise in all crashes; and an increase of 1% in average rainfall was associated with a 0.013% rise in casualty crashes and a 0.029% increase in all crashes.
| Original language | English |
|---|---|
| Publisher | MUARC |
| Commissioning body | IAG - Insurance Australia Group Ltd |
| Number of pages | 74 |
| Publication status | Published - 2007 |
Keywords
- Time series analysis
- Road trauma
- Socio-economic factors
- Weather
