Presentation by Dr Phill Wheat and Dr Richard Batley 06/06/2014. www.its.leeds.ac.uk/people/p.wheat www.its.leeds.ac.uk/people/r.batley

1. Institute for Transport Studies
FACULTY OF ENVIRONMENT
Quantifying and decomposing the uncertainty in
appraisal value of travel time savings
Phill Wheat, Senior Research Fellow
and Richard Batley
06/06/2014

2. Highlights
• Work to quantify uncertainty in appraisal Values of Travel
Time Savings (VTTS) (non-work)
• Important as Travel Time Savings are often major benefits in
transport projects
– Uncertainty in VTTS implies uncertainty in CBAs which could impact
on rankings of projects – at least under sensitivity scenarios
• Statistical exercise, initially to motivate a new VTTS study in
Great Britain
• However in doing the analysis, some wider policy
implications for the best use of scarce research funds have
emerged:
– Do moderate sized VTTS studies often as this minimises uncertainty
in appraisal VTTS

3. Background – Appraisal VTTS
• Current non-work values in Britain (and general approach
taken in other countries e.g. Switzerland and Netherlands)
are estimated as follows:
– In 1994, Stated Preference data used to form a model for VTTS
Separate models were estimated for Commuting and “Other” leisure
travel.
Base VTTS = [/c].
Inc C
C
. . ,
C
Inc
Inc
 
















0 0

4. Background – Appraisal VTTS
– An overall distance-weighted average was obtained by weighting the
combinations according to the distribution (for all mechanised modes)
in the NTS 1995-2000 data defined in income and distance bands.
V =
 
y  Inc d 
D
V . N .
D
yd yd d
 
y  Inc d 
D
N .
D
yd d
– The base VTTS was then up rated by applying the income elasticity
from a separate meta analysis model – GDP elasticity of 0.8
0.8
GDP
AppraisalVTTS V t
1994

 


 

 
GDP
t
Thus Appraisal VTTS are much more than just the base VTTS – multiple
sources of uncertainty

5. Research approach
• Construct a confidence interval around the VTTS
estimates
– Interval estimation
– Gives a lower and upper bound estimate for the Appraisal
VTTS for a given statistical confidence level (typically
95%)
• Two stage process utilising both asymptotic
simulation (Krinsky and Robb, 1986) and the delta
method
– Quantifies uncertainty arising from the base VTTS and from the use
of an estimated GDP uprating factor

6. Results – Commuting All Modes
50.00
45.00
40.00
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00
1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080
Value of Travel Time Saving (pence per minute)
Year
Central VOTT estimate (p/min) Lower 95% CI Bound (p/min) Upper 95% CI Bound (p/min)

7. Results – Commuting All Modes
50.00
45.00
40.00
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00
Base VoTT (1994)
has relatively little
uncertainty
associated with it
Given the functional form,
uncertainty becomes
much larger once GDP
moves away from the
base level
1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080
Value of Travel Time Saving (pence per minute)
Year
Central VOTT estimate (p/min) Lower 95% CI Bound (p/min) Upper 95% CI Bound (p/min)
NOTE: the larger intervals for later years does not reflect uncertainty in GDP
forecasts, merely the effect of uncertainty in the GDP elasticity estimate

8. Improving the model
• Two questions:
– What would be the implication for uncertainty in Appraisal VTTS of a
new (base) VTTS study if that study was of a similar accuracy of the
previous study?
– What if such a study resulted in much greater precision (3 times more
precise base VTTS)
• Trade-off:
– More costly one-off study yielding greater accuracy
– Or Greater frequency of smaller scale studies
• Which of the above to go for in terms of spending finite research
funds?

9. Resampling in 2015
39%
narrower
in 2075

10. Resampling in 2015 – Improved
Precision
Only 3.4%
narrower
in 2075

11. Don’t ignore the GDP elasticity in
research…
60.00
50.00
40.00
30.00
20.00
10.00
0.00
1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080
Value of Travel Time (pence per minute)
Year
Central VoTT Updated Income Elasticity Lower CI Updated Upper CI Updated
Central VOTT Existing Income Elasticity Lower CI Existing Upper CI Existing
20%
narrower
in 2075
Updated GDP elasticity of 0.9 (from 0.8) (Abrantes and Wardman, 2011) (SE
reduced circa 33%)

12. Summary
• Scheme time saving benefits often arise five or even ten
years after a project begins
• Thus the necessary extrapolation of the base year VTTS to
Appraisal values adds a large degree of uncertainty (over
and above the uncertainty in the original VTTS modelling)
• Resampling is important, but not to get more precise
estimates, more to minimise the extent of extrapolation to
form Appraisal VTTS
– However estimates of base VTTS need to be unbiased
• The uncertainty in the uprating process is important – here
the GDP elasticity

13. Policy Recommendations
• When faced with a constrained set of research funds:
– Do moderate size resampling exercises frequently
• As opposed to very large size resampling exercises less
frequently
– Continue to review and update the uprating parameters
• Improvements to the precision of these can yield large reductions
in uncertainty of Appraisal VTTS