Effects of Truck Driver Wages and Working Conditions on Highway Safety: Case Study

What is it about?

The role that human capital and occupational factors play in influencing driver safety outcomes has gained increased attention from trucking firms and policy-makers. This paper examines the role of these factors, in addition to demographic factors, in influencing crash frequency at the driver level. A unique driver-level dataset from a large truckload firm collected over a period of 26 months is used for estimating regression models of crash counts. Based on estimates from a zero inflated Poisson regression model, results suggest that human capital and occupational factors, such as pay, tenure at the job, and percent of miles driven during winter months, have a significantly better explanatory power of crash frequency than demographic factors. Taking into account both the zero-inflation and the count model, results suggest that higher pay rates and getting a pay raise are related to lower expected crash counts and to a higher probability of having no crashes at all, all else held equal. Although the data for the study come from a single firm, the evidence provided is a first step in examining the structural causes of unsafe driving behavior, such as driver economic rewards, and crash outcomes. These results can motivate other firms in modifying operations and driver hiring practices. They also support the need for a broader examination of the relationship between driver compensation and driver safety.

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