Spatiotemporal Context for Vehicular Crash Fatalities Days Before and Days After Daylight Saving Time Transitions

Authors

  • Edmund Zolnik *

    Schar School of Policy and Government, George Mason University, Arlington, Virginia 22201, USA

  • Patrick Baxter

    Schar School of Policy and Government, George Mason University, Arlington, Virginia 22201, USA

DOI:

https://doi.org/10.55121/tdr.v2i2.310

Keywords:

Daylight Saving Time (DST), Vehicular Crash Fatalities, Spatiotemporal Context, Multilevel Model, Contiguous United States

Abstract

Vehicular crashes are historically a major cause of unintentional death in the United States. The empirical literature on safe transportation is rich with research on how human behavior results in lethal vehicular crash outcomes.
Given the stubborn persistence in such outcomes, public policy that may contribute to unintentional deaths is worthy of scrutiny. Annual transitions to and from daylight saving time (DST) are an example. Unfortunately, agreement on the sign and magnitude of the effect of DST transitions on vehicular crash fatalities is scarce in the empirical literature. Further, notable gaps in the empirical literature are evident on how to realistically model temporal and spatial heterogeneity in vehicular crash outcomes. To fill this specific gap, the study adopts a multilevel approach to control for temporal and spatial heterogeneity in the specification of a statistical model that pools twenty years of fatal crash data on DST transition days and on days before and after DST transitions. Results suggest the probability of one more vehicular crash fatality increases by +2.29% on the Sunday of the spring transition (ST). Results also suggest the probability of one more vehicular crash fatality increases by +0.99% on the Sunday seven days after the ST. These results highlight the importance of law enforcement interdictions targeting alcohol and drug involvement on the Sunday of the ST and seven days following it, in order to reduce vehicular crash fatalities.

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