Joe Branigan - University of Wollongong - Infrastructure cost drivers and financial sustainability...
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Transcript of Joe Branigan - University of Wollongong - Infrastructure cost drivers and financial sustainability...
Infrastructure Cost Drivers Study The Future of Infrastructure Conference
19 August 2014
MELBOURNE
Joe Branigan, Senior Research Fellow SMART
Outline
(i) Description of Infrastructure Cost Drivers Study
(ii) Progress so far
(iii) Hypothesis “Perfect Storm”
(iv) Top-Down estimate of magnitude of potential reform benefit
(v) The Future of Infrastructure…A wish list
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Study Description
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Project Objectives
• The Need – we can’t learn if we don’t reflect, and we can’t reflect if we don’t have the information
• Understanding rising costs over time (longitudinal) – Ideally would like to test to what extent increasing regulation has
caused rising costs • Environmental regulation • Technical and Design standards • Health and safety standards
– Other relevant factors include: • Economic cycle (mining boom and GFC stimulus spending) • Dealing with increased Complexity (brownfields v greenfields, planning)
• Understanding cost differences between Australian jurisdictions (cross-sectional) – Jurisdictions want to know how they compare with their neighbours – Likely that there will be common drivers as well as drivers unique to
states
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Methodology
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- Attempt to bring regulatory issues into a S-D framework, along with scarcity - Because prices/costs are also affected by regulations that add to the cost of
tendering for projects , designing projects, and building infrastructure - Cyclical Drivers
- Economic cycle - Mining boom - GFC stimulus
- Structural Drivers (more onerous regulation) - Environmental regulations - Planning requirements - Health & Safety - Increased density of cities
- Matched case studies to isolate cost drivers e.g. 10 km road, same terrain, mining boom v non mining boom e.g. 10 km rail, same terrain, different jurisdiction
- Interview to fill in the gaps - Particularly changes in standards and requirements over time
Project Participants and Data
• Queensland (2007-2013)
– Roads (21 case studies)
– Rail (6 case studies)
– Some previous studies
– Interviews
• NSW (early 1990s – 2013)
– Roads (62 case studies)
– Rail (10 case studies)
– NSW Upper House Inquiry (Rail)
– Interviews
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• Victoria
– Roads (Should receive data by end of August 2014)
– Rail (Should receive data by end of August 2014)
– Interviews
• Wish List (Phase 2)
– Other Australian jurisdictions (esp. WA and NT)
– NZ
– Singapore
Progress so far
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Early results from the case studies
• Wide variation in costs per km because wide variation in types of infrastructure
– Roads, rail, tunnels, bridges, greenfields, brownfields, rock type etc
– Obviously difficult to get exactly matched case studies and currently seeking a longer time series of data from participating jurisdictions
• Early findings (not full dataset)
– Clear increases in costs per km across time for matched projects; some suspects:
• Property acquisition (increased brownfields development)
• Technical and Project Management (inc. design costs, environmental management, stakeholder engagement) (both increased rates and more work to do)
• Audit and Legal costs
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Wide variation in costs per km (roads example)
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Project1
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Cost per km ($millions)
Average = $15.2 million per km Standard Deviation = $10.0 million per km
Variation in Road Costs across 17 Case Studies
Productivity Commission found similar variation in urban passenger rail
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Information from interviews (1)
• Mining construction boom (esp. Queensland)
– Materials shortages
– Engineers/designers shortages
– Cost escalation very common through mid- to late-2000s
• Environmental legislation
– EPBC
– EIS requirements (massive increased workload)
• Planning Approvals delays – Significant increase in waiting times over the 2000s
• Design costs
– Increased complexity (more brownfields, less greenfields)
– Environmental management requirements
– OH&S management requirements
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• Technical standards – Qld had its own standards for road building up until 2012, when it reverted to the
national standard
• Health and Safety standards – More bright lights and witches hats, but where is the trade-off point
• Lack of competition – Esp. during the boom – Alliance model is expensive
• Public projects not cost controlled (scope creep and political interference) • Longer defect liability period and other legal costs • More substantial works to meet increased loads and traffic volumes (ie.
‘benefits’ greater) – See technical standards above
• Fixed/Variable cost trade-offs – Loose fiscal environment (favour capex over opex) (mid-late 2000s) – Very different story now with constrained public finances
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Information from interviews (2)
“Perfect Storm” hypothesis
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Conceptual Framework
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- Attempt to bring regulatory issues into a S-D framework - Ultimately, costs borne by governments reflect the prices
paid for services - Prices rise and fall depending on resource scarcity (e.g.
mining boom) - But prices are also affected by regulations that add costs to
tendering for projects , designing projects and building infrastructure
- Cyclical Drivers - Mining boom - GFC stimulus
- Structural Drivers - More onerous regulation
The rise in public investment in Queensland through the mining boom was unprecedented
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Public investment competing with mining boom investment led to resource scarcity and rising costs per unit of infrastructure built
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The mining boom states (Queensland and WA) were more affected than other states…
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Australia NSW VIC Qld WA
Index (Sept 2003 = 100) ABS Road & Bridge Construction Index, Impact of Mining Boom
By the end of the boom, road construction and maintenance costs were 25% higher than the PPI
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RCMPI
ABS RBCI
PPI
The costs of Road Construction and Maintenance are running significantly ahead of the Producer Price Index.
Index 1989-90 = 100
15-25% higher
The boom has ended but Engineering Design and Consulting Services wages have remained relatively elevated
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Another factor – increased complexity
• Higher population density and much higher land values
– Increases disruption associated with major works
– And cost of land resumption
• More brownfields assets needing expanding or ‘decongesting’
• Fewer vacant corridors
– Imposes very costly solutions such as tunnelling
• Greater environmental restrictions and more responsiveness to community concerns
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Magnitude of potential benefits from infrastructure reform
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“Top-Down” estimate of magnitude of potential benefits – not based on Case Study data
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- SMART has estimated a “top-down” ‘potential benefits’ from infrastructure reform figure
- This estimate is based on publicly available data, including: - ABS National Accounts (State Accounts, Public GFCF) - State Budget Papers - Interviews with stakeholders - Recent PC Inquiry Report on Public Infrastructure
- We find a potential benefit of between $4-$5 billion per year - This is around 12% of current total public new infrastructure investment, which
translates to 6% of current total public investment (new construction + maintenance)
- At 4%, the potential benefit is $2.8 billion per year - At 8%, the potential benefit is $5.7 billion per year
- Clearly, the potential benefits from reform are significant
The Future of Infrastructure
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A wish list…
• No more bad mega-projects
– Potential for significant welfare losses
– More independent and transparent project prioritisation and selection processes
• Independent review of CBAs
– A counter-weight to short-term political imperatives
• Economic regulation of roads
– Like electricity and water, but (hopefully) without the mistakes
– Improved price signal
• Improved alignment of revenue-raising, spending and service delivery standards between Commonwealth and States
– Remove regulatory duplication
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Thank You
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