Addressing endogeneity in modeling speed enforcement, crash risk and crash severity simultaneously

Abstract

Speeding is one of the major significant causes of high crash risk and the associated injury severity outcomes. To combat such significant safety concerns, a speed limit enforcement system has been adopted widely around the world. This study aims to present an econometric approach that estimates the casual effect of speed enforcement on safety while addressing the endogeneity issue by employing an instrumental variable approach within a maximum simulated likelihood framework. In our study, safety enforcement is represented as the number of speeding tickets issued from the speed camera systems, while safety profile is presented as two dimensions of interest, including total crash risk and crashes by injury severity levels. The proposed econometric model takes the form of a correlated panel random parameters model with speed enforcement endogeneity. In estimating the joint panel model, speed enforcement and crash severity components are modeled by employing Random Parameters Ordered Logit Fractional Split technique, while ‘ is modeled by employing Random Parameters Negative Binomial regression technique. In the current study context, the ‘operational duration of speed camera’ serves as the instrumental variable for controlling the endogeneity between speed enforcement and safety. Further, the analysis is augmented by a detailed policy scenario analysis. The empirical analysis is demonstrated by employing roadway segment-level crash data and speeding tickets data from Queensland, Australia, for the years 2010 through 2013. From the policy analysis, it is found that a stricter speed enforcement for serious level of speeding offenses is likely to have greater safety benefits in reducing crash severity levels. Moreover, a targeted increase in operation duration along with stricter citations for major speeding is likely to have significant safety gain. The outcome of the study will allow the decision-makers to identify a robust resource allocation and speed camera deployment plan.