1. The road maintenance backlog in South Africa
Matthew Townshend School of Economics, University of Cape Town, South Africa Professor Don Ross School of Economics, University of Cape Town, South Africa School of Sociology, Philosophy, Criminology, Government, and Politics, University College Cork, Ireland Center for Economic Analysis of Risk, J. Mack Robinson College of Business, Georgia State University, Atlanta, GA, USA
University of Cape Town
Southern African Transport Conference, 8-11 July 2019

2. Application of a backlog estimate
Road maintenance backlog estimate
Budget processes
Prioritisation exercises
Funding models
State of the roads sector
Budget asks
University of Cape Town

3. Presentation structure
Updates to the existing backlog estimate
Estimation methodology
Aggregated backlog
Functional and technical needs backlog
Unit costs
Cost escalation factors
Road maintenance backlog estimates
Economic frames for the backlog
Questions
University of Cape Town

4. Updates to the backlog estimate
R197 billion reported road maintenance backlog from COTO’s Condition and Budget Needs 2014 report
COTO: 2013 VCI data
Ross & Townshend: 2017 VCI data
National road network
Provincial road network
COTO: 2003 VCI data / 3.8% sample
Ross & Townshend: 2017 VCI data / 54.4% sample
Municipal road network
COTO: Aggregated AADT and environment
Ross & Townshend: Disaggregated AADT and environment
Unit costs
Figure: Comparative updates to the COTO data and methodology
University of Cape Town

5. Estimation methodology
Proclaimed/Unproclaimed
Paved/Gravel
High AADT
Dry
Flat
Steep
Wet
Medium AADT
Low AADT
Step 1: Assign deteriorated roads into one of 48 categories
Step 2: Apply average Rand/km rehabilitation cost for each category
Step 3: The aggregate backlog cost is the matrix product of the total km of deteriorated roads in each category and the cost to rehabilitate each such km
University of Cape Town

6. Technical needs backlog
Aggregated backlog
Authority
Volume of roads (km)
Functional backlog
Technical needs backlog
Gravel to surface
Paved
Gravel
High-vol
All
National
222
N/A
2 442
Provincial
10 834
79 330
15 728
96 703
13 506
Metropolitan municipalities
5 117
1 229
1 157
14 461
District municipalities
5 000
9 065
7 992
Unproclaimed
Total
16 056
32 352
22 655
Table: The volume of road maintenance backlogs, 2017
University of Cape Town

7. Technical needs backlog
Figure: Technical needs road maintenance backlogs, 2017
University of Cape Town

8. Functional backlog Figure: Functional road maintenance backlogs, 2017
University of Cape Town

9. Unit costs Maintenance activity Low-volume Medium-volume High-volume
National roads
Rehabilitation of a paved road R R R R
Rehabilitation of a gravel road R R R
N/A
Gravel to surface upgrade R R R
Table: Standard road rehabilitation and upgrade costs per km, 2017
University of Cape Town

10. Cost escalation factors
Region and activity
Low-volume road
Medium-volume road
High-volume road
High moisture region
Gravel road rehabilitation
25.0%
69.7%
Paved road rehabilitation
20.0%
Gravel to surface upgrade
60.0%
49.0%
Steep road gradient
50.0%
67.3%
35.0%
30.0%
58.0%
50.4%
31.8%
Table: Climate and topographic cost escalation factors, 2017
University of Cape Town

11. Paved road maintenance backlog
Figure: Maintenance backlog for paved roads, 2017
University of Cape Town

12. Gravel road maintenance backlog
Figure: Maintenance backlog for gravel roads, 2017
University of Cape Town

13. Gravel to surface backlog
Figure: Gravel to surface backlog, 2017
University of Cape Town

14. Aggregate backlog accounting
The total technical needs backlog is R416.6 billion
Provincial road maintenance backlog is R150.7 billion
≈ 6 X annual expenditure
Municipal road maintenance backlog is R242.9 billion
≈ 8 X annual expenditure
University of Cape Town

15. Economic frames for the backlog
Covering this backlog in 5-years can be framed in 3 policy contexts:
The entire new economic stimulus plan (R400.0 billion); or
An extra 4.0% added to the VAT rate; or
An extra R3.0 added to the national fuel levy.
The opportunity cost to infrastructure policy is vast for option 1
The macroeconomic cost is enormous for option 2
But the welfare cost of option 3 seems relatively bearable
Important for development of the Integrated Funding Model
University of Cape Town

16. Southern African Transport Conference, 8-11 July 2019
Thank you!
Questions?
University of Cape Town
Southern African Transport Conference, 8-11 July 2019