This paper explores aspects of highway safety with a focus on crashes involving older drivers. As the "baby boomers" age and move into retirement, a larger proportion of older drivers will be using the nation's roads. The analysis here develops and estimates econometric models using a panel dataset that includes each county in California and spans an 18-year period, 1981-1998. The models are estimated using feasible generalized least squares techniques that account for cross-section heterogeneity, adjust for county-specific first-order serial correlation, and correct for nonconstant variances due to the large differences in county sizes across the state. The results indicate that the set of explanatory variables for crashes involving older drivers is not identical to the set for crashes involving younger drivers. Among the factors that have large effects on older driver crashes are risk exposure, energy and alcohol prices, alcohol availability, and increased speed limits on higher speed roads.
Samenvatting