Disincentivising overbidding for toll road concessions

2 │ LITERATURE REVIEW
Moreover, since projects with a higher credit quality were likely to be over-represented in the study, the actual
incidence and magnitude of overestimation could be even greater in reality:
very poorly performing assets will remain under-represented in the sample and the results derived from our case
studies are likely to be flattered in comparison with average, global toll road forecasting performance. 13
The results of the Standard & Poor’s programme also seem to capture two further important concepts. First, the
tendency to overestimate, and the range of error in estimation, is greater in countries that are new to toll roads
(mean, 0.58; standard deviation, 0.26) than those with history in the sector (mean, 0.81, standard deviation, 0.24). 14
Second, there does not seem to be any systematic improvement in the accuracy of forecasts subsequent to the first
year (i.e., there is no demand ramp-up effect in later years).
The difference in findings between the Standard & Poor’s dataset and that of Flyvbjerg et al. is likely to stem from the
fact that the former focused exclusively on toll roads, while the latter primarily considered toll-free roads. Thus, the
Standard & Poor’s results will capture the strategic behaviour of bidders in the tendering process. 15 This appears to
be borne out by other studies that focus solely on toll roads:
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Baeza and Vassallo (2008) found that, for a sample of 14 Spanish toll roads, annual traffic was, on average,
35% below forecast in the first year of operations; 31% below forecast in the second year; and 27% below
forecast in the third year. 16 The authors conclude that there is ‘a clear bias towards overestimation of traffic
in the ramp-up period for toll motorway concessions in Spain’.
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A study of Australian toll roads undertaken by Li and Hensher (2010) found that actual traffic volumes using five
facilities (the M2, M7, Cross City Tunnel, Lane Cove Tunnel and EastLink) were 45% below forecast in the first
operational year, and, despite the gap reducing over time, remained 19% lower than forecast after six years. 17
The report was prepared before the opening of Brisbane’s CLEM7 Tunnel, which carries traffic volumes 80% lower
than predicted. 18
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Welde and Odeck (2011) found that actual traffic was, on average, 2.5% lower than forecast traffic across a
study of 25 Norwegian toll roads. 19 Although the mean overestimation is relatively small, forecasts were found
to have been overestimated in 16 (64%) of the 25 projects. Traffic for toll-free roads was found to have been
underestimated in the same study.
Discussion
The literature provides clear evidence that there is a systematic tendency for bidders to overestimate patronage in toll
road concessions. This has been observed in a number of studies, and across numerous jurisdictions. Importantly,
Flyvbjerg et al. (2002) and Bain (2009) both argue that technical errors alone do not adequately explain the observed
forecasting errors, since:
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forecasts do not appear to have become more accurate over time despite advancements in modelling; and
••
actual error distributions have been found to have means that are significantly different from zero.
Building on the above, the following section introduces and analyses alternative explanations for overbidding.
13 Bain, R. and Polakovic, L. (2005), ‘Traffic Forecasting Risk Study Update 2005: Through Ramp-Up and Beyond’, Standard & Poor’s, August 25th,
p. 8, available at http://www.robbain.com/Traffic%20Forecasting%20Risk%202005.pdf
14 Bain (2009), op. cit.
15 Baeza, M.A. and Vassallo, J.M. (2008), ‘Traffic Uncertainty in Toll Motorway Concessions in Spain: an Analysis of the Ramp-up Period’, TRANSyT
working paper, 2008-01, 1–18.
16 Ibid.
17 Li, Z. and Hensher, A. (2010), ‘Toll Roads in Australia: An Overview of Characteristics and Accuracy of Demand Forecasts’, Transport Reviews,
30:5.
18 Davidson, P. (2011), ‘Modelling toll roads – where have we gone wrong’, Australasian Transport Research Forum 2011 Proceedings, September.
19 Welde, M. and Odeck, J. (2011), ‘Do Planners Get it Right The Accuracy of Travel Demand Forecasting in Norway’, European Journal of Transport
and Infrastructure Research, 11:1, 80–95.
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