The 2020 emissions projections confirm our long stated position that Australia will not need Kyoto carryover credits to meet the Paris 2030 emissions target.
Much is made of whether the Federal Government will meet Australia’s 2030 emissions target or adopt a net zero target for 2050. But all States have announced net zero emissions targets by 2050, so the lack of formal acceptance of the target at Federal level is more symbolic.
For 2030, the combination of current State 2030 emissions targets should see Australia on track for a 33% reduction of 2005 emissions, which is more than required to meet the National target of 26-28% by 2030 and closer to the 36% 2030 target that we recommended in 2015[1].
State and Territory targets provide a floor on emissions reductions. For Australia to miss the 2030 national emissions targets, it would require failure at both Federal and State level to meet respective targets.
Australia currently has a national emissions target of 26-28% reduction on 2005 levels by 2030. However, almost all State and Territory Governments (with the exception of WA and NT) have announced more ambitious 2030 targets as pathways to net zero targets that all states and territories have announced for 2050.
Table 1 summarises the State and Territory ambitions and the implications of these targets for the national target. The combination of State 2030 emissions targets should see Australia on track for a 33% reduction of 2005 emissions, which is more than required to meet the national target of 26-28% by 2030.
The following are most noteworthy:
If all State and Territory targets are achieved, then Australia should comfortably meet the national target.
It follows that if Australia is to miss the national target then this would require failure at both the Federal and the State level in meeting applicable targets. More formal bipartisan collaboration on achieving common targets would be welcome in climate and energy policy in Australia.
To continue reading this bulletin, please download the full article using the button below.
[1] https://www.frontier-economics.com.au/australian-targets-emissions-36-by-2030/
DOWNLOAD FULL PUBLICATIONGovernment policy is increasingly putting green infrastructure front and centre of its vision for the future cities where most of us will live. Urban green infrastructure refers to the canopy, parks, waterways, vegetation, wetlands and lakes in our cities. More than just urban nature: these features are assets which deliver valuable services. They can make our cities cooler, healthier, more ecologically sustainable, and attractive places to live and work. To realise a policy vision of greener cities and change our future urban landscapes, we need to start treating green infrastructure in the same way we treat traditional physical ‘grey’ infrastructure ─ by subjecting it to rigorous economic assessment and assurance processes.This isn’t easy, but it can be done. Right now there is significant opportunity to embed green infrastructure in growth areas as part of the urban fabric, especially in areas with large greenfield developments in the planning phases (such as in NSW). But the clock is ticking as development continues, and this needs to happen quickly. This bulletin explores how we can build green infrastructure into our infrastructure planning processes and what challenges still lie ahead for greener urban communities.
The NSW State Government in Australia recently released two documents that, together, indicate a policy vision for the role of green infrastructure in the urban environment. ‘Greener Places’ from Government Architect NSW outlines what green (and blue) infrastructure is in the urban context and how it can improve our cities. In addition, the discussion paper and draft ‘50-year vision for Greater Sydney’s Open Space and Parklands’ outlined four key strategic directions to grow and improve parks, open spaces, connectivity and greenery, and resilience.
Both documents convey a fundamental shift in thinking which considers urban nature as genuine infrastructure that delivers valuable services to the community and which merits policy and planning priority. They recognise that the natural green (and blue) assets of a city can deliver real public benefits like mitigating the urban heat island effect, protecting and restoring ecological health, promoting active lifestyles, and providing beautiful places to live, work and play. These benefits can be measured and quantified in dollar terms such that they are no longer an incidental bonus of investment, but part of the baseline justification and cost-effectiveness of green infrastructure in delivering critical services to the community.
A clear government policy vision for green infrastructure is a good (and necessary) start. But for green infrastructure to be funded it must be robustly integrated into formal proposal, evaluation and assurance processes. Realising a vision for greener cities will depend on how effectively we can develop rigorous processes, methods, resources, datasets, and capabilities to value and assess green infrastructure as an ongoing, long-term package of service-delivering investments.
There are different ways we could embed active consideration of green infrastructure into our planning and decision-making processes on a more equal footing with traditional ‘grey’ infrastructure options.
For example, government policy could mandate investment in green infrastructure. But green infrastructure will not always be the best option in all circumstances and prescribing a one-size-fits-all approach does not guarantee smart investments. The alternative approach is to assess green infrastructure proposals on their individual merits—by requiring a fair, rigorous, quantitative assessment of the economic, environmental and social impacts of each investment—as we do with traditional physical ‘grey’ infrastructure. Investment would then occur where and when it can be demonstrated to deliver genuine community value relative to the alternative levers available.
However, green infrastructure impacts can be tricky to evaluate because:
We look at each of these issues below.
Decisions to invest in infrastructure by governments or other parties are (or should be) determined by the relative weight of benefits to costs. A cost-benefit analysis is the formally preferred evaluation tool of state treasuries and infrastructure agencies around the country and is essential to ensure that limited public money is used as wisely as possible.
Although measuring the costs of green infrastructure is (mostly) straightforward, many of its benefits are not as easy to identify or measure. This can lead to a cost side of the equation that looks robust, ‘real’, and in many cases relatively large, but a benefit side of the equation that looks vague, unreliable and risky.
Take the example of a neighbourhood park. The costs of building and maintaining it are easy to estimate. We could look at what other, similar parks have actually cost. Or, a landscaping firm could provide an estimate of the cost of design, earthworks, materials, park benches, tree planting, tree trimming, etcetera. But how do we measure the benefits of that park to the local community? It’s irrefutable that we value relaxing, exercising, and socialising in parks. Parks clearly provide a range of identifiable community services for mental and physical health, amenity, and aesthetic enjoyment (and others). But none of those benefits are directly paid for per use or otherwise traded directly in a market (for most parks). This means there’s often no observable price to provide some indication of the value of park visits – a so-called ‘non-market’ benefit.
But this does not mean those benefits aren’t real. It does not mean that the community will be better off if we choose not to build that park, or preserve urban canopy, or restore an urban waterway. It simply means that we have to work harder and smarter to identify the end-use benefits of these investments, quantify these (with scientific and engineering tools), and convert those benefits to a robust and fair estimate of value in dollar terms.
Economics has a range of methodologies that can assist (e.g. willingness-to-pay methods, hedonic pricing modelling, productivity cost methods, and more). While these methods require assumptions and are affected by uncertainties, they are a great deal better than nothing and can be refined over time as more and better data become available. The key is executing these methods well. This means exploring (rather than shying from) core uncertainties in the modelling, be those assumptions or data inputs.
To ensure a consistent and systematic treatment of non-market impacts of green infrastructure, it is also important to understand what effects green infrastructure actually has in the urban environment.
A core principle of good cost-benefit analysis is that we only compare costs and benefits that are clearly and exclusively caused by the proposed investment, and not those which would happen anyway, or which would happen under every alternative option. This is the incremental impact of investment, and this is the end measure we convert to a monetary value to tally up different types of costs and benefits.
Nailing down the incremental impact of an investment with rigour can be the most difficult, resource-intensive step in the evaluation process. This is because it requires both a) a defensible case that green infrastructure causes the impact, then b) a defensible measure of how big that impact is.
Demonstrating causal links for green infrastructure is challenging, partly because scientific research and data cannot always readily establish a) and b) above. Further, green infrastructure evaluation can require multiple causal chains to be articulated and linked in a sequence to establish the final incremental impact of investment. This can be extremely complex.
A key policy concern is the risk to health, life, and urban amenity of extreme city temperatures. Climate change will likely increase the number of ‘very hot’ (over 35 degrees) days, exacerbated further by the urban heat island effect. This heat can have serious consequences for health, and is a contributing factor for mortality, especially among the elderly and infants. It is also an extreme (and expensive) stress on our electricity infrastructure.
Urban canopy is one form of green infrastructure that can help reduce these impacts. The natural evapotranspiration processes of trees can cool surrounding air temperature. But the first step to evaluating the cooling benefits of urban canopy is to estimate, for the specific site and proposed investment (including what kind of trees, in what numbers, in what kind of environment, at what scale, etc.), the amount of cooling caused by increasing urban canopy. This is a non-trivial exercise, heavily reliant on the state of scientific research and site-specific modelling. Even once achieved, this will only establish one quantified causal chain – how much change in air temperature will result from additional urban canopy (a similar process applies to the case of cooling from retaining water in the landscape).
The second step involves quantifying the causal link between air temperature changes to human health, electricity infrastructure requirements, and potentially other recreation-related outcomes. Again, this would require scientific research and is a data-intensive task.
But both steps are required to eventually establish the benefits, in monetary terms, that result from investment in urban canopy. Recent work in Western Sydney indicates that these benefits can be significant, and more than outweigh the additional costs.
This example demonstrates that that if this process is to be applied as the standard for green infrastructure proposals, it will require developing, accessing and expertly using high-quality, localised primary research and data. Much of this data will be scientific in nature. However, empirical economic data is also critical. Economic research using best-practice research methods is required to uncover the best possible estimates of what value the community places on alternative possible services provided by green infrastructure.
Being able to assess good green infrastructure options from bad is critical. Valuation is a key element and as we have seen, can be a difficult process. Too often this step is avoided, with the focus on ‘how to invest’ (e.g. funding, delivery, governance etc), prior to answering the question ‘should we invest’.
This may be accomplished more easily in some sectors than others. Water utilities, for example, already have experience in the kind of robust green infrastructure evaluation processes described above. This is because many of the ‘assets’ they build and manage include multi-service delivering natural features. For example, from a traditional water industry perspective, an urban wetland might be one way to manage stormwater quantity, quality and floodplain issues. This is one manifestation of Water Sensitive Urban Design (WSUD), which is now a standard industry concept that prioritises smarter use of nature and its materials to provide services in all stages of the water cycle.
But that wetland is also a piece of green infrastructure that delivers open space, recreational opportunities, wildlife habitat, and possibly other services (for example, large water in the landscape might also be able to cool urban temperatures). The water industry has developed capability because of the regulatory framework that requires scrutiny of spending by utilities. The resultant expertise, datasets, and experience includes quantification of impacts of green infrastructure and the values placed on these impacts by the community (for example, impacts of WSUD options on water quality and species diversity). Sharing and accessing the information held by various sectors will be a key part of unlocking the data and skill required in the valuation process across different forms of green infrastructure.
Government policy encouraging different industry sectors to view our future urban environments with a green infrastructure focus invigorates the approach to infrastructure development and broadens the horizons for what our future urban landscapes can become. Policies should encourage industry players to factor in liveability, amenity, sustainability, the circular economy and a range of other urban policy goals in infrastructure development. However, demonstrating the value that could result from these investments (or broader interventions) is critical. If we genuinely see these investments as value-enhancing community infrastructure, this step must come first. Further, it must be done well if the case is to be made convincingly and for the long-term that multi-servicing delivering green infrastructure is a sound use of the community’s resources.
DOWNLOAD FULL PUBLICATIONStandard techniques used to appraise commercial and government investments often ignore the value of flexibility to adapt investment strategies as circumstances change. Misvaluation of this kind can result in suboptimal investments being chosen. This problem can be particularly acute for infrastructure projects, which typically involve large sunk costs and uncertainty over long asset lives. Real options analysis addresses this shortcoming by valuing flexibility explicitly, thereby promoting better decision-making.
The 6th of June 1944 marked the beginning of the Battle of Normandy, a decisive turning-point in World War II that led to the liberation of Western Europe. Under General Dwight D. Eisenhower’s bold plan, 160,000 Allied troops would cross the English Channel under cover of darkness, land on several beaches in Northern France and push deep into German-held territory. The Normandy landings remain the largest seaborne invasion ever recorded, and one of the most successful Allied campaigns during World War II. However, the whole endeavour was nearly scuppered by the most mundane of things: bad weather.
The landings were originally planned for the 5th of June. However, it became clear by the 4th that heavy winds and rough seas would make the audacious landings impossible. Meteorologists advising Eisenhower forecast that conditions would improve sufficiently by the 6th for the invasion to proceed. The Allied Commander wisely heeded the advice to delay, changed plans that had taken months of meticulous preparation—and the rest, as they say, is history.
Flexibility when making decisions is valuable not just in military strategy. All of us adjust our plans in response to changing circumstances and new information—whether that entails taking a different route home from the usual one to avoid traffic, or more life-changing choices, like whether to buy a house when the outlook for the property market is highly uncertain.
Commercial and public investment decisions are no exception. Businesses and governments making major investment choices often do so in the face of significant uncertainty about the future. Rarely are the investment choices completely fixed. Investment plans can often be adapted—for example, by waiting to see what happens rather than taking a decision now, or by pursuing a different investment strategy—when confronted with new information that affects the value of the investment.
Bizarrely, even though many investors do in practice change their behaviour in response to new information, the techniques typically used to value investments ignore this flexibility. For example, standard Net Present Value (NPV) analysis used in commercial investment appraisals and cost-benefit analysis (CBA) used to assess the net public benefits of government investments generally assume fixed investment plans that cannot be revised, regardless of how circumstances change.
If the flexibility to change investment strategies is valuable—and it can be materially so in many situations—then standard NPV analysis and CBA will understate the value of investments. Investors who realise this often resort to ad hoc, qualitative judgment in order to take account of the value of flexibility—usually an excellent way to make bad decisions.
Worse still, what happens if two competing investment options are being considered side-by-side, but one presents the investor with more (or different kinds of) flexibility than the other? How are those two options to be compared on a like-for-like basis? Unless the flexibility is valued quantitatively, there is every chance that the two investment opportunities will not be compared on a level playing field, and the wrong (i.e., value-destroying) investment may inadvertently be selected.
Figure 1 presents a simple example, which shows that when faced with uncertainty, flexibility to respond to new information can increase the value of an investment.
Consider two investment options available to an investor.
Under Option 1, the investor can invest at Time 0 at a cost of $10 million. The investment will provide a guaranteed cash flow of $1.25 million at Time 1. However, the cash flows at Time 2 (and thereafter) are uncertain: with equal probability they will either rise to $2 million, or fall to $0.5 million. This uncertainty resolves only at Time 1. Under Option 1, this occurs after the investment decision has been. If the investor takes Option 1, the expected NPV of the investment (at a constant discount rate of 10%) would be $2.5 million.
Note that the expected NPV represents the average outcome, given that there is a 50/50 chance of cash flows from Time 2 onwards increasing or falling significantly. If the investor is unlucky and cash flows drop, then the actual NPV of the investment would be -$6.59 million. The investment would have turned out to be a very bad one.
Under Option 2, the investor could—in recognition of uncertainty about the future—wait until Time 1 and choose to invest only if the cash flow at each point in time increases to $2 million. This would mean giving up a guaranteed cash flow of $1.25 million at Time 1. However, in exchange, the investor can avoid an outcome where the cash flow drops significantly and forever to $0.5 million, producing a loss-making investment. If the investor takes Option 2, the expected NPV of the investment would be $4.55 million—significantly higher than under Option 1, where the investment would occur immediately regardless of future uncertainty. By selecting Option 2, the worst the investor can do is avoid losses by not investing if the cash flows decline.
The difference in the NPVs under Options 1 and 2, $2.05 million, represents the economic value of flexibility (the ‘option value’) to change the investment strategy in response to new information.
Real options analysis (ROA) is a technique that allows the systematic quantification of the economic value of flexible decision-making. Unlike standard NPV analysis or CBA, ROA recognises that investors can alter the way a project is rolled out as circumstances change and calculates the value of the project under different possible investment strategies rather than a single, fixed strategy.
Examples of flexibility in decision-making that ROA can account for include the options to:
ROA has two main advantages over standard NPV analysis and CBA:
A key insight from the ROA literature is that the value of flexibility can be particularly large if:
This means ROA can be particularly useful when valuing infrastructure investments—such as: roads, rail lines, ports, airports, water networks, desalination plants, water recycling plants, telecommunications networks, mining and exploration assets, gas pipelines, electricity grids and power stations.
This is because infrastructure investments tend to be long-lived (so economic conditions can change materially over the life of such assets), and typically involve billions in sunk costs.
With a forecast peak funding requirement of $51 billion, the National Broadband Network (NBN) represents the largest infrastructure project ever undertaken in Australia.
Given the size of the project, it is astonishing that the Rudd Labor government, which pledged to deliver the NBN, refused to conduct a CBA to assess its merits. Indeed, the Federal Communications Minister at the time argued that the benefits of the NBN to Australia were self-evident, and that conducting a CBA would be a “waste of time, waste of effort, waste of money.”
The most contentious aspect of Labor’s NBN plan was a commitment to deliver fibre to the premises to 93% of the population with broadband speeds of up to 100 megabits per second. The ambitious choice to build fibre to the premises was intended to deliver a network with sufficient capacity to last for generations, but also involved the highest construction costs.
The decision to roll out fibre to the premises was particularly controversial because it was unclear in 2009, when the plan was first announced, that there would be sufficient future demand to justify the broadband speeds and build costs associated with a fibre to the premises network. Whether fibre to the premises would be truly worthwhile depended on what sort of applications would emerge, and how consumers would choose to use broadband services, in future. However, the government of the day pressed on with its plans for a “Rolls-Royce” NBN as though such speeds would definitely be required, regardless of the uncertainty over future demand. No account was taken of the option to delay or to build gradually.
When Labor lost the 2013 general election, the incoming Coalition government commissioned a CBA of the project. That study assessed the net benefits to taxpayers of three options for rolling out the NBN. It concluded that, against the base case scenario of halting the project immediately:
The study suggested that Labor had picked the worst of all rollout options.
A commendable aspect of the CBA—which made it stand out compared to most other government CBAs—was that it made some effort to account for optionality. The CBA recognised that a key uncertainty was the extent of future growth in demand for high-speed broadband. The study concluded that whilst a multi-technology mix rollout would offer slower speeds than a fibre to the premises rollout, it would allow the NBN to be upgraded at a later date, if demand turned out to be higher than anticipated.
The authors of the CBA modelled the net benefits of having the ability to upgrade later if required, under a multi-technology mix rollout, instead of building full fibre to the premises capability upfront. Figure 2 presents the value of the multi-technology mix rollout over and above the fibre to the premises rollout if:
This analysis demonstrated two important things:
Based on these results, the CBA concluded that:
Overall the [multi-technology mix ] MTM scenario has significantly greater option value than the [fibre to the premises] FTTP scenario. The MTM scenario leaves more options for the future open because it avoids high up‐front costs while still allowing the capture of benefits if, and when, they emerge. It is, in that sense, far more ‘future proof’ in economic terms: should future demand grow more slowly than expected, it avoids the high sunk costs of having deployed FTTP. On the other hand, should future demand grow more rapidly than expected, the rapid deployment of the MTM scenario allows more of that growth to be secured early on, with scope to then upgrade to ensure the network can support very high speeds once demand reaches those levels.
John Maynard Keynes is often credited with saying “When the facts change, I change my mind. What do you do, sir?” In fact, the actual source of this quote was not Keynes, but Paul Samuelson, another famous economist.
Regardless of who actually said the words, the sentiment behind them makes intuitive sense to most of us. We do not go through life following a perfect linear path, regardless of what life throws at us. We adapt our plans as circumstances change because doing so makes us better off.
Commercial and government investment decisions are much the same. Yet, standard NPV analysis and CBAs used to appraise such investments typically ignore the value that can be gained from changing the investment strategy in response to new information. This can result in the value of investments—particularly those that are long-lived, exposed to significant future uncertainty and involving large sunk costs—being mis-estimated. This, in turn, can lead to suboptimal investments being selected, at significant cost to shareholders or taxpayers.
ROA addresses this problem by quantifying explicitly the value of flexibility, and allowing identification of optimal investment strategies, thereby improving decision-making.
To download this publication in full (including references), click the button below.DOWNLOAD FULL PUBLICATION
