ESTIMATION OF MARGINAL SOCIAL COST, ISSUES AND SUGGESTIONS: The case for Namibian roads Presenter: Helvi Petrus Promoter: Stephan Krygsman

Outline Introduction Literature Data Results Conclusion

Introduction 2.3 million population 826 000 square metre 48 000 km 370 000 vehicle population Currency 1N$=1ZAR Popoulation 2.3million, vehicle population 370 thou, road network 47km, exchange rate 1:1

National Road Network Interest for transport policy to tackle the negative externalities attracted notable studies on estimating marginal social cost (MSC). Remarkable EU studies seems to form fundamental methodology on MSC (UNITE,2003, Infra, 2004, GRACE, 2008 and IMPACT, 2008). Studies on MSC in developing countries and SSA in particular still at infant stage. The use-pay principle aimed at holding the road user accountable for the full cost of they impose when utilising the roads. The concepts forms part of the policies documents without further knowledge on value of such externalities (Petrus and Krygsman, 2018). The Namibian Transportation policy (2017) calls for the refinement on the RUCs.

Economic theory-Marginal Social Costs MSC MPC VOC Travel time Insurance MEC Infrastructure costs Environmental costs Congestion costs Accident costs Although road users are faced with both private and external costs, this paper places its focus on estimating the marginal external costs that road users rare take into account. Marginal social costs comprise two main components the marginal private cost (MPC) and marginal external cost (MEC) of road use. MPC represent the cost that the road users bear or take into consideration before undertaking a journey. MEC are the costs that arise with the use of the road it is rare that road users consider such costs when deciding to undertake a journey

Components of Marginal External Costs Marginal Congestion Costs Marginal Infrastructure Costs Marginal Accident Costs Marginal Environmental Costs

Literature It is quite complex to measure and implement the SRMC (Rothengatter, 2003). First-best road pricing would improve the road sector funding and financing status quo (Verhoef, 1996). Roads in Africa do not experience widespread and persistent road congestion Setting prices equal to SRMC will result in large financing deficit (Heggie, 1995) Low demand and excess capacity, SRMC is likely not to cover the fixed costs (Kahn, 1988). Depending on demand, RUC at SRMC could lead to deficits or surplus (Proost and van Dender, 2003). Estimation of the optimal user charges and see whether it yield into a deficit or surplus should serves as a departure point (Walter, 1968).

Research Focus Motivation “ if road investment and maintenance planning is assumed to be relevant, and if road pricing should comprises of marginal costs in order to influence present and future road use, then why not use planning models (PMSs) such as HDM4 to determine marginal costs?” (Bruzelius, 2004). The Namibian Road Authority uses the pavement management system (PMS) HDM-4 model for planning purposes. If the road agency presume that such planning models are relevant to influence the present and future network needs. Why not use the same planning models to internalise the marginal costs of road use?(Bruzelius, 2004). The use of the pavement management system to influence the present and future road pricing remains a grey area in the authority domain.

Objectives Compare MSC pricing to AC pricing To explore the estimation of the marginal externality costs for road use. To identify the financial implication of implementing road user charge set at SRMC . Estimate MSC Compare MSC pricing to AC pricing Compare MSC per veh/km to Fuel levy per veh/km Available secondary data were utilised for the period 2011 to 2016, obtained mainly from annual financial reports and budget documents from road agencies.

Data HDM-4 Workspace Source: Henry and Kerali, 2000 Road Work (pavement condition data), Vehicle Fleet, Maintenance and Improvement strategies, Cost Data of Maintenance and improvement worksHDM-4 Workspace and Shape files obtained from Namibia Road Authority (Disclaimer form as signed). Case study base analysis The study area covers the national road network and includes the followings: The three main road types (trunk, main and district roads) the location and road type (paved) are very crucial to congestion and accident costs. Six representative vehicle classes (pickups, articulated trucks, busses, heavy trucks, medium cars and mini busses) cost per kilometre as well as revenue heavily depends on vehicle type. and Traffic volumes influence time-period, flow speeds, congestion and environmental cost, therefore time-periods is a crucial component. Cost relevant for road use to calculation both short-run marginal costs and average costs of the four components. Source: Henry and Kerali, 2000

Study area The case study represent a sample of a district-paved road of the national road network. The road is 61.05 km in length and carries averaged daily traffic of 224 motor vehicles including 69 4x4, 17 mini buses, 20 articulated trucks, 1 bus, 12 heavy trucks. The HDM-4 analysis was conducted for the period of 20 years at interest rate of 10%. The maintenance strategy applied-overlay when roughness (IRI) exceeds 5.23, a partial resurfacing if more than 10.61% of the area suffer all structural cracking or a partial resurfacing if rutting exceeds 13mm.

Steps followed for the case study (HDM-4 analysis) District Paved road- 61.05km AADT 224 (69 4x4, 20 articulated trucks, 1 bus, 12 heavy trucks, 105 medium cars, and 17 mini buses). Overlay when roughness exceeds 5.23, partial resurfacing if more than 10.61% of the road area suffer all structural cracking, or partial overlay if rutting exceeds 13mm.

Calculations Calculation performed based on the output results from HDM-4 run. Estimation based on the NPV of an action. Difference of no case (AADT) vs with Case (AADT+1). ESAL as a main factor of influence. Output of HDM-4 Provide input to estimates a time loss of a certain action. A correction was made for PCSE and time (hours/minutes) HDM-4 run provide input data for calculating total accident costs per causalities (fatal, injury and damage only) Influence factors includes accident rate per 100 million vehicle per km, road category and kilometer traveled. Calculate the GWG utilising HDM-4 outputs

Results: Average costs pricing Average cost pricing approach estimates the total financial costs of financing a particular service and divides by the number of units (AADT) to obtain the appropriate user charges. Why AC? 1. most commonly way in which user charges are currently set, 2. only consider financial costs, 3. easier to calculate and offer great justification for (group charges) allocation to vehicle classes.

Results: Marginal Costs Pricing

Results: Costs vs Revenue Average Costs Pricing Marginal Costs Pricing

Results SRMC on National road network Marginal and Average Costs– District road(Cents/km) As output expands, the cost per unit falls at least up to point E. At any point before average costs are decreasing, implying that MC of providing an additional unit of service fall below the AC (shaded area). This means applying (SRMC) efficient user charges that are less than AVC will results in financial deficit. How should these deficit be funded? 1. subsidy from consolidation funds, 2. maintaining charges at AC, 3. reconciling the efficiency objective of public sector pricing and the need to cover financial costs of providing public service in an efficient and equitable manner as possible.

Conclusion The paper demystified the marginal externality estimation for road use in Namibia. It is possible to use the HDM-4 to estimate the marginal cost of road use depending on the quality of available data and the specification and calibration are accurate. The disparities between heavy vehicles and light vehicles is very wide. RUCs charged at SRMC would have a high chance of resulting in deficit……(Heggies, 1995) Environmental costs presented a good chance to be also incorporated into fuel levy and not only accident costs………(Link et al., 2016 as well as Parry et al., 2007. There is a need for second-best optimal pricing approach for the Namibian roads Estimating the marginal cost of providing another unit of a particular service requires the identification of the additional costs arising from the incremental expansion.

Contribution The use of HDM-4 to estimate marginal social cost. Contribution to the MSC literature- Developing Countries (SSA). Estimate of MSC on expansive roads-sparsely vehicle population-act as a base for the entire network. A base to improve the user charges from an efficiency perspective. Results could guide planner and policymakers.

Thank you! Email: 21438293@sun.ac.za