In estimating wage-risk trade-offs, the value of a statistical life (VSL) literature primarily utilizes cross-sectional analyses that are susceptible to bias from unobserved time-invariant factors. Further, many occupational death data have considerable non-classical measurement error. This paper addresses these shortcomings by estimating the VSL of truck drivers employed between 1979 and 2002. Due to measurement error, utilizing a difference-in-differences (DID) strategy will form a VSL lower bound, while an Instrumental Variable (IV) strategy will form an upper bound when using another mismeasured risk report as an instrument. Both strategies control for unobserved time-invariant factors. By examining wages within a competitive occupation, this analysis controls for occupation-specific productivity shocks and worker risk tolerance. Risk measures are created from the National Highway Traffic Safety Administration—Fatality Analysis Reporting System (NHTSA-FARS), the census of all traffic fatalities on public U.S. roadways. Wage data are obtained from the Current Population Survey—Outgoing Rotations Group (CPS-ORG). The DID estimator returns a VSL lower bound of $0.4 million while the IV estimator returns a VSL upper bound of about $4.2 million. This study also utilizes a pooled cross-section estimator to reproduce biases in the cross-sectional literature. The pooled cross-section estimates range from $7.5 million to $11 million, in the middle of the VSL literature’s cross-section estimates. This suggests that time-invariant factors bias VSL estimates upward by several million dollars. Although not nationally representative sample, this paper illustrates the need to control for time-invariant factors in the VSL literature. When estimating a VSL, future research should reduce sample measurement error and control for time-invariant factors with panel data.