The road maintenance backlog in South Africa Matthew Townshend School of Economics, University of Cape Town, South Africa matthew@cornerstonesa.net 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 don.ross931@gmail.com University of Cape Town Southern African Transport Conference, 8-11 July 2019

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

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

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

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

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 13 506 173 732 Metropolitan municipalities 5 117 1 229 1 157 14 461 District municipalities 5 000 215 797 9 065 242 439 7 992 266 416 Unproclaimed 131 919 Total 16 056 295 127 32 352 340 371 22 655 586 528 Table: The volume of road maintenance backlogs, 2017 University of Cape Town

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

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

Unit costs Maintenance activity Low-volume Medium-volume High-volume National roads Rehabilitation of a paved road R2 100 000 R3 680 000 R6 300 000 R8 939 792 Rehabilitation of a gravel road R800 000 R840 000 R1 010 000 N/A Gravel to surface upgrade R3 500 000 R4 030 000 R6 410 000 Table: Standard road rehabilitation and upgrade costs per km, 2017 University of Cape Town

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

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

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

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

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

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

Southern African Transport Conference, 8-11 July 2019 Thank you! Questions? matthew@cornerstonesa.net don.ross931@gmail.com University of Cape Town Southern African Transport Conference, 8-11 July 2019