Addressing endogeneity between hazardous actions and motorcyclist injury severity by integrating generalized...

Motorcyclist hazardous actions (e.g., particularly speed too fast or failing to stop in assured clear distance (ACD)) are commonly identified as risk factors that significantly impact the motorcyclist injury severity. However, endogenous effects resulting from motorcyclist hazardous actions have seldom been considered, which may cause the biased estimates. Specifically, two important sources of endogeneities (i.e., endogeneity arising from observed confounding factors and endogeneity caused by unobserved confounders) tend to yield a biased relationship between hazardous actions and motorcyclist injury severity. To jointly account for two sources of endogeneities and provide more robust estimates, the study tries to assess the effects of speed-too-fast and failing to stop in ACD on motorcyclist injury severity via a hybrid method by integrating the generalized propensity score approach with instrumental variable model. Specifically, we adopt a generalized propensity score matching method to reduce the endogeneity bias arising from observed confounders. Furthermore, the matched data are used to develop an instrumental variable model with random parameters to handle the endogeneity resulting from unobserved confounders and unobserved heterogeneity, which consists of random parameters binary logit models modelling the motorcyclist hazardous actions in the first stage and a random parameters logit model with heterogeneity in means modelling the motorcyclist injury severity in the second stage. The proposed approach is estimated based on Michigan motorcycle crash data from 2015 to 2018. Results suggest that alcohol use leads motorcyclists to engage in speed-too-fast, while alcohol use and signal control cause motorcyclists to be involved in failing to stop in ACD. Middle-aged and elderly motorcyclists, alcohol use, speed too fast, speed limit ≥50 mph, wet surface, and head-on/angle crashes significantly increase the injury severity of motorcyclists. Moreover, failing to stop in ACD produces a random parameter with heterogeneity in means, while intersection increases the mean effects of failing to stop in ACD on motorcyclist minor injury. These findings further provide insights for a better understanding of hazardous actions and motorcyclist injury severity via the impact analysis of various explanatory variables.