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Omitted variable bias in crash reduction factors.
  • Published Date:
    2015-09-01
  • Language:
    English
Filetype[PDF-2.41 MB]


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  • Abstract:
    Transportation planners and traffic engineers are increasingly turning to crash reduction factors to evaluate changes in road

    geometric and design features in order to reduce crashes. Crash reduction factors are typically estimated based on segmenting a

    highway and associating crashes with geometric features; this allows statistical methods to be applied to the data. Concurrently

    there is a stream of research that relies on spatial units of analysis to examine crashes; these typically use broad features of the

    road network combined with socio-economic and demographic factors that are associated with crashes. In this paper, we

    examine whether omission of these spatial factors in a link-based geometric model results in omitted variable bias. Our results

    suggest that there is no change in coefficient signs, but that there is a reduction in the magnitude of estimates. The sign of spatial

    variables, however, is quite different when combined into a link-based model. We also find substantial variability in coefficient

    estimates, and discuss the implications of these results for the use of crash reduction factors.

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