1. Benchmarking regional maintenance costs on England’s Strategic Road Network
ETC 2017, Barcelona
Adam Spencer-Bickle,
Principal Economist, ORR

2. Overview
Background on Road Reform, Road Investment Strategy and ORR’s role
A brief introduction to econometric efficiency benchmarking analysis
Data, results and conclusions from our initial analysis
Given the stage of the analysis, the results do not represent ORR’s view of Highways England’s efficiency

3. Background on Roads Reform and the RIS

4. Roads Reform and the Road Investment Strategy
ORR’s highways role
“Our Highways role has been established to place a greater level of scrutiny on the company than has been the case in the past. We hold Highways England to account for its management of the strategic road network – including delivery of performance and efficiency.
We also advise the UK Government on the levels of funding and performance requirements for future road periods to help frame challenging and deliverable performance and efficiency requirements.”
Strategic Vision
Investment plan
Performance Specification
Statement of Funds Available

5. RIS2 Efficiency Review
provide advice… on whether… proposed requirements are deliverable with the proposed financial resources, and the extent to which the Draft SBP is challenging and deliverable, including with regard to levels of efficiency
Capability Reviews of Highways England’s:
1. procurement and contract management
2. project and programme management
3. asset management
Benchmarking studies with an analytical focus on:
1. Regional intra-company comparisons
2. Comparisons to other UK regulated sectors
Sample testing the draft SBP to assess whether individual expenditure lines are supported by robust analysis about efficient costs
Bringing the evidence together with a review of the efficiency improvements built into SBP, an assessment of efficiencies achieved in Road Period 1 and evidence from phases 1 to 3 of our work

6. Overview of the programme of work to date
Capability reviews and sample testing provide a more ‘bottom-up’ assessment of efficiency. So benchmarking focusing on:
more ‘top-down’ methods for efficiency, as a sense check; and
performance.
Efficiency
Performance

7. Brief intro to econometric efficiency analysis

8. Econometric efficiency benchmarking
Efficiency gap

9. Econometric efficiency benchmarking
1. Estimate the cost function:
2. Establish the efficient frontier (minimum cost):
3. Measure the efficiency gap:
COLS is very simple – all cost difference treated as inefficiency
SFA models split the error term into uit (inefficiency) and vit (noise or unobserved heterogeneity)
𝑙𝑛𝐶 𝑖𝑡 =𝛼+ 𝛽 1 𝑙𝑛 𝑄 1𝑖𝑡 + 𝛽 2 𝑙𝑛 𝑄 2𝑖𝑡 + 𝜀 𝑖𝑡
𝑙𝑛 𝐶′ 𝑖𝑡 = 𝛼 +𝑚𝑖𝑛 𝜀 𝑖𝑡 + 𝛽 1 𝑙𝑛 𝑄 1𝑖𝑡 + 𝛽 2 𝑙𝑛 𝑄 2𝑖𝑡 + 𝑢 𝑖𝑡
𝑒𝑓𝑓 𝑖𝑡 = min 𝑐𝑜𝑠𝑡 𝑎𝑐𝑡𝑢𝑎𝑙 𝑐𝑜𝑠𝑡 = 𝑒 𝛼 𝑄 1𝑖𝑡 𝛽 1 𝑄 2𝑖𝑡 𝛽 𝑒 𝛼 𝑄 1𝑖𝑡 𝛽 1 𝑄 2𝑖𝑡 𝛽 2 𝑒 𝑢 𝑖𝑡 = 1 𝑒 𝑢 𝑖𝑡 =𝑒𝑥𝑝 − 𝑢 𝑖𝑡

10. Data, results and conclusions from initial analysis

11. Comparing the potential data sources
Highways England’s Performance Monitoring Statements:
Maintenance
Renewals
General operations
Traffic management
PFI payments
Support costs
Capital M&R
By region, with separate “centrally managed” category
From
Highways Agency cost of maintaining the network KPI:
All renewal of roads and structures
Proportion of MAC routine and winter maintenance spending
Proportion of PFI/DBFO payments
All technology maintenance and renewal spending
By region (with no “centrally managed” category)
Consistent lane and vehicle (from an accompanying KPI) miles
From

12. Comparing the potential data sources
Also sourced data for Scotland and Wales
Balanced panel of 8 “i’s” and 7 years
Lane miles and vehicle miles as only candidate cost drivers

13. Developing the cost function
Preferred model and estimation results:
Need to include Scottish and Welsh data
uncertainty about cost comparability so tested a range
model performs better with “low” cost data.
Lane elasticities = 1 => constant returns to scale
Vehicle density elasticities in line with existing evidence
Link et al (2008) found a range of for renewals / maintenance and renewals
𝑙𝑛𝐶 𝑖𝑡 =𝛼+ 𝛽 1 𝑙𝑛 𝐿𝑎𝑛𝑒 𝑖𝑡 + 𝛽 2 𝑙𝑛 𝑉𝑒ℎ𝑖𝑐𝑙𝑒𝐷𝑒𝑛 𝑖𝑡 + 𝑡𝑖𝑚𝑒 𝑡 + 𝜀 𝑖𝑡
Lane miles
Vehicle density
‘pure' lane miles
S&W ‘high’
S&W ‘low’
COLS
1.56*
1.42*
0.26
0.51*
1.30*
0.91*
PSFA
1.92*
1.86*
0.38
0.73*
1.54*
1.13*
P&L(81)
1.78*
1.68*
0.26*
0.54*
1.52
1.14* RE
1.60*
1.44*
0.39*
0.61*
1.21*
0.83*
CSSRE
1.35*
0.33
0.53*
1.23*
0.82*
Cuesta
1.84*
1.73*
0.24
0.76*
1.60
0.97*

14. Efficiency scores
Given the stage of the analysis, the results do not represent ORR’s view of Highways England’s efficiency
Average theoretical efficiency scores across Highways England regions
Model to
S&W ‘high’
S&W ‘low’
COLS NA
84%
82%
Pooled SFA
80%
79%
Pitt and Lee (’81)
78%
Random Effects
CSSRE
75%
73%
Cuesta

15. Conclusions and development priorities
Cost function and aggregate efficiency scores appear plausible
Priorities for development include:
Consistency of Scottish and Welsh data
Disaggregating lane and vehicle mile variables
Other measures of network ‘quality’
Potential to widen the panel

16. Questions and contact details?