Economic Benefits of Cycling Infrastructure


Very pleased to see that my colleagues at Queensland Department of Transport and Main Roads and Aurecon will be presenting our analysis on the economic benefits of cycling infrastructure at the National Traffic and Transport Conference of AITPM in mid-August.  The abstract is available here:


Image: Southbank, Brisbane. Source: Brisbane Tourism.

Anatomy of an Economic Decision


Clear thinking is a prerequisite for good economics.  This leads to improved decision making, and that creates better outcomes.

The next time someone claims to be making an economic decision or proposes an economic course of action; dissect their claim or assertion.  You do not need to be an economist to do that.  There are five simple signs for good economic decision making:

  1. Decision to be made is articulated
  2. Available choices are considered
  3. Measurable objectives are described
  4. Input variables are identified
  5. Relationship between variables is determined

Without these famous five, the risk is the economic decision may be dead on arrival.

Significance of O&M in Infrastructure


Installation of new infrastructure assets creates streams of services and improvements to existing services for users. Benefits accrue to these uses as well as a wider set of stakeholders. Maintaining the service potential is a critical element in ensuring that value for money is achieved from the initial capital investment.

However, many governments and asset managers are under significant pressure to trim maintenance budgets and scrimp on operating costs. In some contexts, this emerges as an extreme build-neglect-build scenario. Many Pacific Island nations experience this, as do a number of smaller Australian local government authorities. The full lifecycle cost of infrastructure assets is not factored into the budget planning processes of these organisations. Similarly, many private sector operators of infrastructure have commercial and financial incentives to focus on next quarter financial performance rather than long-term service provision from these assets.

The back end of infrastructure is seen as much less interesting, but it is where all the benefits are generated. So approaches to operating and maintaining these infrastructure assets is as equally critical as the planning and investment decisions to deliver them.

Two broad maintenance strategies are predictive maintenance and condition based maintenance. Predictive maintenance is like regular scheduled servicing based on the design performance of an infrastructure asset. It is less costly to implement but also less likely to match the actual performance of the asset. Condition based maintenance requires the collection of data and information about the actual performance of the asset and provision of a tailored asset maintenance response.

The approaches set up an economic challenge. Should an infrastructure manager simply maintain its assets according to schedule and only collect data and information on condition at the times of regularly scheduled servicing? Or should some initial data costs be incurred to change and adapt design-based, predictive maintenance? Decisions to underfund reasonable maintenance activities need to be made with good information and in an appropriate strategic context.

So it depends. In one sector, for example, the response is clear but not clear-cut. Analysis of wind turbine maintenance to address gearbox, generator and blade failure scenarios shows that for small wind turbines, predictive maintenance is more cost effective than condition based maintenance. Condition based strategies were based on an array of sensor data (optical, oil, vibration and temperature). However, for larger turbines, condition based maintenance where there is a high expected gearbox failure rate is a much better approach. In that instance, the cost of collecting additional data and information enables timelier and more appropriate servicing of the turbines.

For these reasons, infrastructure owners and managers need to ensure there are effective asset management and maintenance policies included in their strategic asset management frameworks. It is not enough to supply the assets, as only the services from them will be able to generate the full suite of expected benefits. This can only be achieved when the design potential of these assets is realised over time.

Performance of Australian Aid

campaign for australian aid logo
Devex recently identified six key takeaways from the 2015-16 review of Australian Aid, which I have been looking at:
1. The hardest target (gender) is the weakest link
2. Programs targeting agriculture, fisheries and water need more support (only 8% of overall budget)
3. Partnerships with disabled peoples’ organisations are wanted
4. Innovation has not been widely adopted in the aid program despite a facility to do this
5. The World Health Organisation continues to underperform according to donors
6. Strong performance and high funding are not necessarily linked (PNG was an example)
A summary of the review is available at:
The review was released in the week before the Federal Budget and the full report is on the DFAT website:

Household Debt and House Prices


Lytton Advisory was at the Economic Society 2017 Business Lunch in Brisbane yesterday. RBA Governor, Philip Lowe, gave a very lucid presentation on Australian household debt and house prices.

Over 25% of mortgagees have a buffer of three or more years on their home loans.  The top two household quintiles by income are carrying the largest debt burdens.

Recent regulatory changes imposed on banks by the Australian Prudential Regulatory Authority will tighten up lending to property investors.  This may create some short-term breathing room to address fundamental supply-demand imbalances in some of the Australian property markets. It may also take a bit of the speculative heat out of the Sydney and Melbourne property markets.

The RBA Governor touched on a number of other issues as well.  Details can be found at:

Cross River Rail Dice Roll?


In this note we consider there is a 25% possibility that Cross River Rail may fail to achieve a positive economic net present value and explain how we arrive at that opinion.

Building Queensland reported in its cost benefit analysis summary that Cross River Rail produces a Net Present Value (NPV) of $966 million with a Benefit Cost Ratio (BCR) of 1.21. However, its summary did not publish the actual present value totals of the benefits or costs from the study. The full report is not available for public scrutiny.  Also, the government’s website for Cross River Rail has still not published the business case.

The BCR was expressed in terms of P50, which implies there is a 50% probability that it could be lower than 1.21. Similarly, if the NPV was expressed as P50 that implies a 50% probability the NPV could be less than $966 million. Interestingly, no formal sensitivity analysis was presented in the summary.

Is it possible to assess the probability that the net present value of the project could be less than zero or the benefit cost ratio less than one?

Using the NPV and BCR information from the summary we calculate the implied present value of benefits (B) and the present value of costs (C). Since NPV = B – C = $966 million, and BCR = B / C = 1.21, we can solve for C. This gives us a present value figure for C of $4,742 million. Therefore, the present value for B is $5,738 million.

Since we do not know the risk profile of these values, let’s assume variability in the estimates are normally distributed around the benefit and cost values implied by the NPV and BCR figures. This is a generous interpretation of the variability of the actual result compared to the estimate because we know that costs are typically skewed towards overruns and realized benefits fall short of estimates more often than exceed them.

We assume a standard deviation that is approximately 20% for each cost and benefit estimate. We assume in the absence of any guidance that the estimate is the mean for the purpose of this analysis. This applies both to costs and benefits. Under a standard normal distribution the estimate statistic is also a P50 estimate.

Benefits and costs in the tails of each distribution are likely to be extreme values. We assume that values in the 5% tails either side of the mean are not sampled. That is, values are drawn from a normal distribution that represents 90% of possible values for benefits and costs.

One final consideration – no correlation is assumed between benefits and costs. What it costs to build and operate Cross River Rail has no influence on the level of demand achieved. The same project is delivered irrespective of cost.

Running @Risk probability software over this, we find that running the NPV calculation through 1,000 iterations there is a 25% chance that the project will generate a negative NPV. No formal consideration is given to optimism bias, which would tend to increase this value.

Is this a risk worth taking? Hard to say because some of the fundamental information is still not in the public domain. Also, components of both benefit and cost may be well identified and estimated. As a consequence, their probability profiles might be within a much smaller range.

Within the project, further work would be required to minimise and mitigate risks that could affect benefit realisation or lead to increased costs. Release of further detail about the project would enable the public to assess this.

Image: Brisbane Times.


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Economists often talk about “laws” in economics. Two of the most basic ‘laws” are the law of supply and the law of demand. Nearly every economic event results from the interaction of these two laws. The law of supply says that the quantity of a good supplied (i.e., the amount owners or producers offer for sale) rises as the market price rises, and falls as the price falls. Economists do not really have a “law” of supply, though they talk and write as though they do.

An important function of markets is to find “equilibrium” prices. These are prices that balance the supplies of and demands for goods and services.

Economists often talk of “supply curves.” A supply curve traces the quantity of a good that sellers will produce at various prices. As the price falls, so does the number of units supplied. Equilibrium is the point at which the demand and supply curves intersect–a single price at which the quantity demanded matches the quantity supplied.

Why does the quantity supplied rise as the price rises and fall as the price falls? There are some good reasons. First, consider the case of a company that makes a consumer product. Acting rationally, the company will logically buy the lowest cost materials for a given level of quality. As production (supply) increases, the company has to buy progressively more expensive (i.e., less efficient) materials or labor, and its costs increase. It charges a higher price to offset its rising unit costs.


This Micro Brief is part of an ongoing series provided as a general public information service.  These concepts underpin modern economic analysis.  Find out more about smarter capital investment decisions using economics at