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the changes in these two factors. “With regard to estimating the change in the pre-project impact
levels, many factors besides the project improvement impact such parameters as travel time and
accident frequency, and assessing the effect of such project improvement is often difficult”
(Kulkarni et al., 2004 p. 151). For example, variability in travel times may be omitted from CBAs
despite unreliability in travel times imposing significant costs on motorists (Peer, Koopmans, &
Verhoef, 2012). A number of scholars have indicated that variable costs can be an important factor,
accounting for 10 to 15 percent of travel time costs (Eliasson, 2006; Fosgerau et al., 2008). Peer
et al. (2012) used both an expected constant travel time for a particular road over a certain time
period and travel times based on factors that are unique to a certain day such as weather. They
argued that mean travel time can be used to predict variable travel times and that longer delays are
related to higher variability. Benefits like improved rideability may also be difficult to measure by
a CBA because they are not easily quantified.
A single project is sometimes framed as combinations of several smaller interrelated projects,
which makes developing a comprehensive CBA problematic (Lawrence et al., 2014). Inaccurate
or missing data, an inconsistent or methodologically unsound framework, or the absence of tools
to facilitate analysis can also pose significant obstacles when performing a CBA. These issues can
lead to omitted values, double counting, inaccurate discounting, and other errors that undermine a
CBA’s usefulness. Questions have been raised about how to value time savings versus human lives
in the context of transportation safety projects (Hauer, 2011). By discounting the value of deaths
prevented by safety improvements, Hauer argues that CBA can produce results biased against
projects that emphasize safety. Policymakers should also keep in mind that a CBA is a decision
tool — it does not favor outcomes on moral grounds (Adler & Posner, 1999). Many agencies do
not perform CBAs because there are few resources available to do so once the challenges of
mandatory planning, environmental analysis, and other assessments have been tackled. Political
influence can dampen the influence of CBAs as well, which is a result of competing constituencies
and interest groups lobbying for specific projects irrespective of their costs and benefits.
CBA has limitations when applied to large-scale projects, such as statewide highway plans
(Kulkarni et al., 2004). But it has been used to measure the impacts of significant corridor projects
(Balducci, 2012), intercity bus service (Guo et al., 2008), and winter maintenance approaches
(Veneziano et al., 2010) through road weather management (RWM) programs (Lawrence et al.,
2014). Because transportation projects often generate impacts outside of the local area in which
they are constructed, properly delineating the area that should be included in a CBA is critical
(Bartin et al., 2012). The geographic area analysis that is focused on significantly influences
results. For example, traffic levels can affect how specific projects are valued. As such, projects
focused on rural areas may yield fewer calculated benefits; policymakers may use this information
to argue projects in areas with low traffic do not merit funding because projects in more populated
areas will produce greater returns. When examining a statewide plan, there are a large number and
variety of projects that improve various facets of the transportation system. Projects in different
regions may also have differences in construction costs, which can affect a CBA. Geographic
variability is likely to be more problematic for states with a large footprint.