Using the Revenues from the German HGV Toll - Economic Efficiency and Long-Term Dynamics
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Transcript of Using the Revenues from the German HGV Toll - Economic Efficiency and Long-Term Dynamics
Using the Revenues from the German HGV Toll - Economic Efficiency and Long-Term Dynamics
Claus Doll
REVENUE Final Seminar
Brussels, 29.-30. November 2005
Background
2000: Final report of the governmental commission on transport infrastructure financing: Recommendation to replace tax finance of federal roads by a system of user charges to ensure good network quality.
2001: Decision of federal cabinet to replace the EuroVignette-System by distance-depending motorway charges according to DIR 199962/EC.
2001: Tendering of toll collection.
2002: Contract to the Toll Collect Consortium (DaimerChrysler, German Telekom) to install and operate a satellite-based toll system.
2003: Parliament and council pass the act on use of toll revenues and on the foundation of an infrastructure financing society (VIFG).
2005: Toll system went into operation after a delay of 18 months without major problems.
Design of the German HGV toll system
Average tariff 12.4 ct./km differentiated by emission standards and axles according to DIR 1999/62/EC.
Of total revenues Toll Collect receives an annual sum of 620 mill. € for operation and enforcement. The contract runs until 2015.
Toll Collect has guaranteed a minimum of 90 % of recognising free riders. Per year 10 million vehicles are checked by Toll collect and by the Federal Office for Goods Transport.
According to council legislation of 5 / 2003 charges are transferred to the Transport Infrastructure Financing Society (VIFG) which is obliged to distribute them to
- road (50 %), - rail (38 %) and to - inland waterways`(12%).
Research Questions
Primary research questions:
1. Should revenues be re-invested in new infrastructure capacity or in maintenance?
2. Should there be a cross-subsidisation between modes or road classes?
3. Should revenues be partly or fully transferred to the state?
Secondary research questions:
4. How should revenues between motorways and trunk roads be allocated?
5. Which role do different pricing rules play with revenue allocation decisions?
Dual Model Approach
Social welfare measures
Equity by income groups
Accounts of agents
Economic, environmental and Finanical indicators over time
Detailed modes, sectors and areas
MOLINO:
Partial transport sector equilibrium model
ASTRA:
Integrated transport-economicsystem dynamics model
Synthesis and Interpretation
Charging + revenue spending scenarios
Demand, Networks
etc.
Scenario treatment by assessment tool
MOLINO ASTRA
Q1: Maintenance vs. New construction
Modelling with external inputs
No – but possible
Q2: Cross-subsidisation of rail/IWW
Investment in rail/IWWinfrastructure
Rail investments intracks and vehicles
Q3: Revenue transfer to the general budget
Proportional tax reform;sensitivity with Swiss MCF
With limited scenarios
Q4: Cross-financing of secondary road network
50% maintenanceexpenditures
No – but possible
Q5: General budget allocation with different pricing rules
ACP HGVs / all vehicles / MCP all vehicles
No internal MCP-computation possible
Use of the MOLINO welfare model
Scope: Pricing of all inter-urban surface transport modes (road, rail/IWW) with focus on average cost pricing of HGVs on motorways.
Geography: Consideration of entire networks.
Modes: Federal roads (motorways + trunk roads) vs. mass transport (rail + IWW). (IWW freight only, others passenger + freight).
Institutions: Infrastructure charging instead of final user charging; distinction between infrastructure investor and infrastructure operator.
MOLINO Pricing Rules
Scheme A: Reference case, no road charging, rail/IWW as current.
Scheme B: Current pricing scheme: HGV motorway charges calculated from average costs of constructing, maintaining and operating the networks. Road operation public, rail/IWW operation private (with public subsidies).
Scheme C: Average infrastructure cost pricing for all vehicles on all road network types.
Scheme D: SMCP on all modes.
Pricing, management and investment under public procurement in all scenarios.
Decisive welfare determinants
Elasticities of substitution: Calibration by studies on market reactions of transport on pricing measures.
The marginal cost of public funds: Value for Germany taken out of Kleven and Krainer (2003). Values for Germany (2.21) are very high compared to other OECD countries (average 1.55).
Set-up of the ASTRA model
ASTRA is an aggregated system-dynamics model for the EU-15 with several network levels, 4 functional regions per country and 25 economic sectors.
It does not compute neoclassical welfare measures but models economic processes more detailed than MOLINO.
Single pricing rule: Average infrastructure cost pricing for all inter-urban road users.
Three revenue spending scenarios:
• Road: Re-investment of all revenues in the road sector.
• Cross: Cross-subsidisation of rail investments and maintenance.
• DT: Reduction of direct taxes.
Research question 1: Maintenance vs. new investments
Consideration by MOLINO only.
External modelling of:
• time-variant asset deterioration required.
• level of maintenance requirements and maintenance costs.
• speed to maintenance elasticity.
Results:
• Total welfare (society as a whole) prefers maintenance activities in order to prevent future re-investment costs and in order not to provoke induced traffic with all its negative implications (environment, congestion, etc.).
• Users (low and high income) prefer new investments due to reduced time and resource costs.
ACP of HGVs on motorways, full earmarking for transport, 50% road / 50% rail/IWW
-30
-20
-10
0
10
20
30
40
50
75% 50% 25%
Share of revenues used for maintenance measures
Wel
fare
(m
ill.
€ 20
00-2
020)
Total welfare High income users Low income users
Research question 2: Road vs. cross-subsidisation of rail/IWW
Consideration by MOLINO and ASTRA.
Results:
• MOLINO recommends the earmarking of funds for the road sector from the perspective of total welfare as well as from the users' point of view.
• Reason: Rail investments are more cost-effective but road has much higher demand => preference will improve as rail share increases.
• Considering several indicators (GDP, GVA, exports, etc.) ASTRA also results in slightly more positive values in case of earmarking revenues to road.
• This preference of the ASTRA model is, however, negligible.
Effect of marginal capacity extension Rail-IWW / road
Change in travel speed by extra capacity unit
0.85
Time saving per trip by extra capacity unit
1.33
Capacity unit per investment amount
1.32
Demand 0.48
Total travel time savings 0.86
ACP of HGVs on motorways, full earmarking for transport, 50% maintenance expenditures
-30
-20
-10
0
10
20
30
40
50
60
100% 75% 50% 25%
Share of revenues earmarked to road transport
Wel
fare
(m
ill.
€ 20
00-2
020)
Total welfare High income users Low income users
Change of GDP in Germanycompared to BAU scenario
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
[%]
ch
an
ge
to
BA
U
Interurban-Road
Interurban-Cross
Interurban-DT
Research question 3: Earmarking for transport vs. transfer to public hand
This question has been investigated by both models.
Assumption: state uses revenues to lower (direct) taxes proportional to income.
Alternative ways of revenue use (investment in education, health sector support, etc.) are out of the scope of the models.
Direct use of "marginal cost of public funds" (MOLINO) vs. endogenous computation of costs of public funds via behavioural consumption models (ASTRA).
Results:
• MOLINO clearly recommends the transfer of all revenues to the state.
• Results are much less expressed when using alternative MCPF-values.
• In the long run ASTRA finds much better results when earmarking revenues to transport due to incentives for productivity improvements.
ACP of HGVs on motorways, 50% of transport expenditures for road, 50% for maintenance
-40-20
020406080
100120140160180
100% 75% 50% 25%
Share of revenues earmarked for the transport sector
Wel
fare
(m
ill.
€ 20
00-2
020)
Total welfare High income users Low income users
Change of Disposable Income in Germanycompared to BAU scenario
-4.0
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
[%]
ch
an
ge
to
BA
U
Interurban-Road
Interurban-Cross
Interurban-DT
Change of GVA of chemicals and trade sector in Germany compared to BAU scenario
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
[%]
ch
an
ge
to
BA
U
Chemicals Interurban-Road Chemicals Interurban-Cross
Chemicals Interurban-DT Trade Interurban-Road
Trade Interurban-Cross Trade Interurban-DT
Conclusions (1)
MOLINO and ASTRA agree in the following items:
1. In general average cost pricing has a negative impact on total welfare.
• From the perspective of transport users this, however, looks different.
• MOLINO finds positive welfare measures for MSCP.
2. If revenues are to be earmarked to transport, maintenance activities in road should be prioritised.
• This MOLINO result holds for society in total.
• In contrast, transport users would prefer investments in capacity extension.
Conclusions (2)
The models disagree in the welfare effect of transferring revenues to the general budget.
• MOLINO and ASTRA short run results prefer transferring revenues to the public household.
• In the log run incentive and productivity effects make the re-investment cases perform much better in the ASTRA framework.
• MOLINO: Appropriate to model welfare effects on a limited local level.
• However, more research is required on the effects of cross-subsidising other sectors (e.g. health, social security or education).
• Conclusion: The transfer of transport pricing revenues to the general budget is to be considered with care.
Additional material
Molino decision tree in the multi-modal case "M"
Level 3 UtilityLevel 3 Utility
Level 2 In-house production´/ Domestic markets
TransportLevel 2 In-house production´/ Domestic markets
Transport
Level 1 Peak Off-peakLevel 1 Peak Off-peak
Level Rail/IWWRoad Road Rail/IWWLevel Rail/IWWRoad Road Rail/IWW
Molino decision tree in the multi road level case "R"
Level 3 Utility
Level 2 In-house production´/ Domestic marketsOther modes
TransportLevel 2 In-house production´/ Domestic marketsOther modes
Transport
Level 1 Peak Off-peakLevel 1 Peak Off-peak
Level Trunkroads
Motor-ways
Motor-ways
Trunk-roads
Level Trunkroads
Motor-ways
Motor-ways
Trunk-roads
Decision Tree Case "R": Multi-Network-LevelAnalysis in Road Transport
Agents and their inter-relations
Users individual and public transport operators (car users, hauliers, train service operators, shippers)
The infrastructure operators take decisions on maintenance activities and bears the costs of network capital and maintenance costs, which they can charge to the users. .
The network managers (=owners or investors) take decisions on capacity expansions and bear the respective costs for new investments which they can charge to the operators.
Users
Infrastructureoperators
Infrastructureinvestors
Central government
Infrastructurefund
Localgovernment
VehicleRegistration tax
Fuel tax
Loss, prifit orProfit tax
InfrastructureUse tolls
InfrastructureInvestment charges
Investment contribution
State subsidyor allocation to
public sector Revenues –operationcontributions
Structure of the ASTRA system-dynamics model
8 modules which are interfering in every time step (3 months).
Feedback loops and reaction delay functions aim at capturing second-round effects of policy measures (e.g. endogenous generation of costs of public funds).
Geographical coverage: EU15 (25) with 4 functional zones per country.
Emphasis on transport sector.
POP
MAC
FOT
REM
TRA
WEM
ENV
VFT
Potential Labour Force Population Structure
Dis
posa
ble
Inco
me
Con
sum
ptio
n, I
nves
tmen
t in
Veh
icle
s, V
AT
GDP, (Un-)Employment, Sectoral Output
Population Change
VK
T
Sectoral Goods Flows
Car
Fle
et
Fuel Price
GDP, Productivity
Exports, Imports
Transport Expenditure, Performance, Time
VAT Revenue Fuel Tax Revenue
GDP, Employment, ....
Fue
l P
rice
Emissions, Noise, Accidents
Transport Cost, Time OD
Transport Demand OD
POP = Population Module MAC = Macroeconomics Module REM = Regional Economics Module FOT = Foreign Trade Module
Abbreviations:
TRA = Transport Module ENV = Environment Module VFT = Vehicle Fleet Module WEM = Welfare Measurement Module
ASTRA Modules and Main Interfaces
Generalized Cost OD
Fleet Structure
Determination of MOLINO input parametersDemand: Levels and growth rate by federal investment plan
Network speed-flow curves:
• Road: Network model outputs for different demand levels
• Rail/IWW: Network impacts of big investment projects
Marginal costs of capacity expansion: 50% of network replacement costs to capture the effect of targeted investments in bottlenecks.
Speed-Flow relationship by road network type
0
20
40
60
80
100
120
140
0,50 0,70 0,90 1,10 1,30 1,50
Relative level of dem and
Ave
rag
e s
pe
ed
(kp
h)
Motorways
Trunk roads
All roads
Speed-Flow relationships rail
0
20
40
60
80
100
120
140
0 0,5 1 1,5 2 2,5
relative level of dem and
Tra
vel s
pe
ed
(kp
h)
Iso-Elas tic speeds :
Linear speeds :
Question 4: Different forms of ACP vs. MSCP
Assessment by MOLINO only.
Pricing regimes:
• ACP HGVs >12t on motorways (0.58 ct./tkm)
• ACP cars (1.88 ct./pkm) and HGVs (1.55 ct./tkm) on all roads#
• MSCP on roads (11-18 ct./pkm, 10-13 ct./tkm) and rail/IWW (13-18 ct./pkm, 3-10 ct,/tkm)
Results:
• Pricing schemes matter much more than revenue allocation rules.
• Welfare results extreme for MSCP, driven by positive effect of reduced traffic.
• User-specific results contradict positive total welfare with MSCP.
ACP on roads vs. MSCP for all modes, 100% of revenues for transport, 50% for road, 50% for maintenance
-1'500
-1'000
-500
0
500
1'000
1'500
2'000
2'500
3'000
ACP HGVs on motorways
ACP all vehiclesall roads
MSCP all vehiclesall modes
Wel
fare
(m
ill.
€ 20
00-2
020)
Total welfare High income users Low income users
Question 5: Public administration vs. private sector operation
Investigated by MOLINO only.
Here only presentation of cases with full earmarking of revenues to transport.
Different levels of cross-subsidisation between (both private) modes.
Profit-maximising price regime (Nash equilibrium) due to elasticities of substitution < 1 not possible => ACP raised by 50% to simulate profit margin.
Results:
• For 100% as well as for 50% earmarking of revenues for road public sector involvement is much worse than public administration of the road network.
• Remarkably, cross-subsidisation of rail/IWW is favoured even by private sector.
• Results are confirmed by user-specific welfare measures.
ACP all road vehicles, 100% of revenues for transport, 50% for maintenance
-600
-500
-400
-300
-200
-100
0
100
Public administration,
100% road
Private operation, 100% road
Public administration,
50% road
Private operation, 50% road
Wel
fare
(m
ill.
€ 20
00-2
020)
Total welfare High income users Low income users
Question 6: Investment in motorways vs. trunk roads
Assessment with MOLINO only.
Assumptions: 100% earmarking of revenues to transport, 50% us3e for maintenance activities.
Results:
• Total welfare perspective: 75% use for motorways optimal.
• User perspective: 25% for motorways, 75% for motorways.
• Explanation: Detouring traffic causes environmental, noise and safety problems.
ACP of HGVs on motorways, full earmarking for transport, 50% maintenance expenditures
-20
-10
0
10
20
30
40
50
100% 75% 50% 25%
Share of revenues earmarked for motorways
Wel
fare
(m
ill.
€ 20
00-2
020)
Total welfare High income users Low income users
Change of Export in Germanycompared to BAU scenario
-1,6
-1,4
-1,2
-1,0
-0,8
-0,6
-0,4
-0,2
0,0
0,2
2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
[%]
ch
an
ge
to
BA
U
Interurban-Road
Interurban-Cross
Interurban-DT
Change of Employment in Germanycompared to BAU scenario
-3,0
-2,5
-2,0
-1,5
-1,0
-0,5
0,0
0,5
2000 2003 2006 2009 2012 2015 2018
[%]
ch
an
ge
to
BA
U
Interurban-Road
Interurban-Cross
Interurban-DT
Change of Consumption in Germanycompared to BAU scenario
-4.0
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
[%]
ch
an
ge
to
BA
U
Interurban-Road
Interurban-Cross
Interurban-DT
Change of Transport CO2 Emissions in Germanycompared to BAU scenario
-6,0
-5,0
-4,0
-3,0
-2,0
-1,0
0,0
2000 2003 2006 2009 2012 2015 2018
[%]
ch
an
ge
to
BA
U
Interurban-Road
Interurban-Cross
Interurban-DT