Economists at Large have undertaken a review of the report, Impact on North Stradbroke Island from ceasing sand mining (the Unimin Report), conducted by Synergies Economic Consulting (the Consultants) for Unimin Australia (now Sibelco) and released in June 2010.  Save Straddie Alliance asked Economists at Large to review the Report.  We found three main flaws in the report:

• Failure to consider planned mine closures: Closure of the Yarraman mine, planned for 2015, will reduce the volume of mineral sands mined on the island by 34%.  This reduction was included in the Unimin Report.  This omission results in the value of sand mining on the North Stradbroke Island (NSI) being overstated by as much as 37% for gross output value and 57% for government revenues.  A thorough economic impact assessment should ascertain what level of impact is likely to occur against a business as usual scenario, in this case, where mining is phased out at the end of the life of the mines.  This approach was not taken for the Unimin Report.
• Confused scope for impacts: Impacts that will be felt at a state or national level are often considered to be impacts on the NSI economy.  For example, it is correct to include the reduction in gross regional product in wider regional analysis, but it needs to be made clear this does not translate to a welfare loss of this magnitude for the NSI community.
• Modelled impacts on NSI economy are overstated: The combination of the points above results in the modelled impacts being highly overstated (section 4.4).  While we have not attempted to calculate more accurate impacts, they are likely to be much less than estimated in the Unimin Report.  Furthermore, the method of modelling used may not be appropriate for this type of analysis and more details of the results should have been presented.

In addition to the points above, Economists at Large believe that the Unimin Report is narrow in its analysis and fails to consider externalities and opportunity costs of mining and the broader economic structure of the NSI economy.  This is not a fault of the report itself, but rather a caution to decision makers and the community reviewing the findings.

Economists at Large recommend that decision makers and the local community conduct more thorough analysis of the net benefits and costs to the NSI economy as a result of sand mining.

Download the full review: ECOLARGE-NSI-SandMining-Economics-FINAL.

For more information, please contact us.

Image from Courier Mail website

Stradbroke Island has been in the news recently, following revelations that Belgian mining company, Sibelco, spent $91,000 at the last Queensland election in a successful attempt to unseat a politician opposed to extending its sand mining operations on the island.  The former government’s policy was to end sand mining on North Stradbroke Island in 2019, while the incoming Newman government is proposing to extend mining to 2035, with the support of Sibelco.

In 2011 Economists at Large reviewed earlier assessment of Stradbroke sand mining for local group, Friends of Stradbroke Island.

A reader of our site recently asked us to take a look at the report, North Stradbroke Island  – economic impact of mineral sands mining.  While the report is published by the Queensland Department of State Development, Infrastructure and Planning, the economic assessment has been carried out by a private firm, Synergies Consulting, who were commissioned by Sibelco (see page 10 of the report, confusingly p28 of the pdf file).

Both the 2013 and the 2010 reports are based on a type of economic modelling called “input-output modelling”.  While this methodology is widely used in Australia, its use in this case is surprising given the Queensland DIP’s involvement in publishing the research.  The DIP’s policy is that projects should not be evaluated with input-output models, but through cost benefit analysis:

The primary method of economic evaluation of public sector policies and projects is cost- benefit analysis. Input-output methodology (or the use of multipliers) is not a preferred methodology for economic evaluations. (Qld DIP, 2011)p18

The reason why DIP and most Australian government departments prefer not to use input-output models is that they tend to exaggerate benefits and ignore costs completely.  As Synergies point out:

The economic and environmental costs are not readily available and therefore the analysis assumed that the economic costs are already funded. (p10)

By ignoring the costs of sand mining, Synergies’ results overstate the economic case for the project.  Furthermore, benefits are overstated as input-output models:

• Lack resource constraints – ie they assume resources are not taken away from other industries, or in this case, it assumes people currently working in sand mines will not work in any other industry or project.  In reality, people with mining and engineering skills find work easily in other projects or industries.
• Assume fixed prices – ie they assume that wage levels and input costs would stay the same with or without the projects, whereas some reduction in these costs would result in the expansion of other industries.
• Are not appropriate for small areas – generally inputs to the models are based on state-wide estimates that do not reflect local conditions.  The 2010 report claims to have developed a North Stradbroke Island-specific table, but no details are available.

Because of these limitations, the use of input output modelling for project assessment has been labelled “biased”, “abused” and “deficient” by the ABS ( 2011), the Productivity Commission and the NSW Land and Environment Court (Gretton, 2013; Preston, 2013).  We believe the published results are a heavy overstatement.  If cost benefit analysis had been conducted, the analysts would have had to address difficult issues:

• The company is foreign owned, so the vast bulk of financial benefits go offshore.
• Commodity price forecasts on which benefits are calculated are not mentioned in this report.  Project proponents often use optimistic price estimates to make their projects seem more profitable, particularly if they do not need to disclose what prices they have used.  In the current assessment, there is no way of assessing if estimates of profits and revenues are likely to be met as no price forecasts are provided.
• Royalty and tax rates are not mentioned.  Analysts often use theoretical royalty and tax rates, but in reality many exemptions and write-offs lower government benefits from projects.  No royalty and tax discussion is provided in this report.
•  Environmental costs are not considered.  No estimate of how much rehabilitation might cost and to what extent it will be able to mitigate the damage to the Stradbroke environment.  This can be a major cost for proponents and of course for communities if rehabilitation is inadequate.

If thorough cost benefit analysis was conducted on the sand mining operations on North Stradbroke Island, it is likely that the results would suggest the economic welfare of the Island would be barely affected.  While the extension of mining leases beyond their scheduled end would provide a windfall for Sibelco and their direct employees, these profits go overseas and most employees would soon find jobs in other mining projects and industries.  Environmental costs and potential impacts on the tourism industry are, however, borne by the wider community and may be considerable.  We hope economic analysis in line with DIP guidelines will be carried out before any decision is made.

References:

ABS. (2011). Australian National Accounts: Input-Output Tables – Electronic Publication, Final release 2006-07 tables. Australian Bureau of Statistics. Retrieved from http://www.abs.gov.au/AUSSTATS/[email protected]/Previousproducts/5209.0.55.001Main Features4Final release 2006-07 tables?opendocument&tabname=Summary&prodno=5209.0.55.001&issue=Final release 2006-07 tables&num=&view=

Gretton, P. (2013). On input-output tables: uses and abuses. Staff Research Note, Productivity Commission, Canberra. Retrieved from http://www.pc.gov.au/__data/assets/pdf_file/0008/128294/input-output-tables.pdf

Preston, B. (2013). Judgement on Bulga Milbrodale Progress Association Inc v Minister for Planning and Infrastructure and Warkworth Mining Limited. Judgement in the Land and Environment Court, New South Wales. Retrieved from http://www.edo.org.au/edonsw/site/pdf/casesum/Warkworth_judgment.pdf

Qld DIP. (2011). Project Assurance Framework: Cost Benefit Analysis. Analysis. Queensland Department of Infrastructure and Planning. Retrieved from http://www.treasury.qld.gov.au/office/knowledge/docs/project-assurance-framework-guidelines/paf-cost-benefit-analysis.pdf

Earlier this year Economists at Large and wrote a snappily-titled report for the Nature Conservation Council of NSW, Economic assessment of environmentally damaging mining and gas developments in NSW.  In the report we summarise and assess some of the work that we and TAI have done for NSW community groups looking at coal and coal seam gas studies.  Our main conclusions are that economic assessments of these projects:

• Overstate economic benefits
• Downplay environmental costs
• Downplay greenhouse gas emissions
• Overstate employment benefits
• Ignore costs to other industries
• Ignore health costs

One of the mines discussed in the report is the Ashton Mine, owned by Yancoal in the Hunter Valley.  In the report we wrote:

Increases in greenhouse gas emissions associated with the project’s impact on coal consumption are not included, potentially overstating the project’s value to the world by $460m.

Since writing the report we have examined the project more closely and feel we need to correct this statement as it seems likely to heavily overstate the greenhouse impact of the mine’s production.  The reason for the overstatement is our assumption that the mine’s production would be sold largely for use as thermal coal burned in power stations.  This production would have the effect of marginally lowering the price of thermal coal, and therefore coal-fired power generation, displacing energy generation by less greenhouse intensive means.  We believe such a marginal effect should be considered in relation to thermal coal projects.

However, from examining Yancoal’s reports and those of independent analysts, we find that this assumption was wrong. Most of the Ashton Mine’s production is sold onto metallurgical coal markets.  To our knowledge there is no less emissions intensive method for steel production than to use coal – although we are unsure of the emissions implications of use of semi soft coking coal as opposed to higher quality coking coals.

If the project proponents are able to sell most of their coal onto metallurgical coal markets and if use of lower quality coking coal does not have a major effect on the emissions of steel production, then it seems the original assessment is correct that the project will not result in major increases in emissions at a global level.

The same overstatement may apply to a lesser degree to other projects listed in table 2 of the report, particularly Maules Creek, which we understand is likely to sell a considerable part of its production onto met coal markets.

Coal and Allied’s litter control program in action near the Warkworth mine

I just had a quick look at a report written by PwC for the NSW Minerals Council, Potential to unlock value in the mining sector through planning reforms in NSW (you have to scroll through to the PwC section).  The report highlights the recent Warkworth decision in the NSW Land and Environment Court as a factor contributing to “delay and uncertainty” for the NSW mining industry.  Terrifyingly, this could lead to “29,000 jobs at risk”.

Gee, that sounds bad….but recall that a key factor in the Warkworth judgement was Judge Preston finding:

I am not satisfied that the economic analysis provided on behalf of Warkworth support the conclusion urged by both Warkworth and the Minister, namely that the economic benefits  of the project outweigh the environmental, social and other costs.

Part of that economic analysis that didn’t convince the judge was input-output modelling.  The Warkworth proponents’ consultants, the Hunter Valley Research Foundation, had used input-output analysis to estimate that the project would “create” 44,000 jobs.  Preston CJ found:

The [input-output] analysis is a limited form of economic analysis…The deficiencies in the data and assumptions used affect the reliability of the conclusions as to the net economic benefits of approval.  More fundamentally, however, the [input-output] analysis does not assist in weighting the economic factors relative to the various environmental and social factors…

So when a judgement has criticised your claims based on an input-output study, what’s a lobby group to do?  I know!  Commission another one!  Does anyone else see the irony in commissioning an input output study as a rebuttal to a judgement that smacked down input output studies????  Did no one at PwC think about this before writing:

Results indicate that up to 6,450 fewer direct jobs would be generated compared to a business as usual case for this scenario. Using an input output multiplier, this could mean up to 22,400 fewer indirect jobs.

I could go on at length about why these figures are misguided, but the most simple explanation is because the model assumes that there is a limitless pool of qualified, unemployed coal miners sitting around in NSW with nothing better to do and that they won’t be taken away from other jobs or other industries.

Where are the economists who think this is decent analysis?  Can we expect Ross Garnaut or Warwick McKibbin to come out in defence of this?  Not likely.  How about an officer from the ABS or NSW Treasury….maybe….oh no, hang on, they said this:

Input-Output (Multiplier) Analysis is commonly used to assess the regional impacts of a project. In the simplest form of input-output analysis, input-output multipliers are applied to measures of direct impact to determine estimates of flow-on impacts in terms of income and employment. All such analysis is subject to significant limitations, and extreme care should be taken in its interpretation. NSW Treasury (2007) p12

Production of [input output] multipliers was discontinued with the 2001–02 issue for several reasons. There was considerable debate in the user community as to their suitability for the purposes to which they were most commonly applied, that is, to produce measures of the size and impact of a particular project to support bids for industry assistance of various forms. ABS

So there you have it.  If your first study doesn’t succeed, try, try again.  Peter Martin in the SMH predicted a while back that the Warkworth judgement meant that

It will never again be safe to come up with a big number for jobs created (”direct and indirect”) expecting the decision-maker to give it a tick because it’s the outcome of an economic model.

Don’t bet on it, Peter, don’t bet on it!

Over the last two years, Economists at Large has undertaken a number of pieces of work looking at economic assessments of mining projects. These are usually done in response to Environmental Impact Statements (EIS) prepared by project proponents. Economists at Large is typically asked to assess the economics chapter of EIS’s by community groups that may be concerned about the impacts of a project and the purported benefits and costs.

Having undertaken so many of these counter-assessments, we’ve spotted a number of consistent themes that result in misleading figures being presented to the public and the various planning departments around Australia.

To rectify this issue and empower communities and other stakeholders, we are looking to launch a project that would create guidelines or standards for economic assessment of mining projects. Some of the issues we would tackle are:

• The importance of assumptions.
• Sensitivity analysis.
• Appropriate definition of scope.
• The use of indirect impacts and input-output, simple multipliers or CGE modelling.
• Distributional impacts.
• Valuing non-market costs and benefits.
• And more.

The purpose of the guidelines would be to help all stakeholders understand the true nature of the economic impacts of a particular project against best-practice standards in economic project assessment.

The Australian Financial Review published an article on the 30th May 2012 titled “Boom under threat from higher costs“. The article discussed the findings of a report by Port Jackson Partners and commissioned by the Minerals Council of Australia. The body of the article continued in much the same vein as the title, highlighting that high labour, energy and transport costs have made Australia “among the most expensive in the world to develop”.

The authors continue to dutifully report that “the resources industry hopes the report will help shift the debate from spreading the benefits of the resources boom through taxation to lowering costs for the industry”. In the words of Mitch Hooke, chief executive of the Minerals Council of Australia:

The MCA is urging the government to shift gears from spreading the benefits of the boom [through higher and ineffective taxes such as the carbon tax, ad hoc spending, and increased regulation] to tackling  the real challenges of fiscal sustainability, productivity growth, expanding supply-side capacity and enhancing the economy’s structural flexibility.

It’s hard to know exactly what the MCA wants from this short quote, but basically they seem to be asking for lower taxes, less regulation, and greater availability of cheaper (potentially foreign) labour. Hardly a surprising a request for an industry body.

This article and the ensuing attention on the plight of the miners facing ‘increased costs’ spilled over into an article in The Age the following day (yesterday), “Gillard takes on mining bosses“. It’s a pity really because behind the fog of the news is a very interesting piece of research by Port Jackson Partners that tells a more nuanced story than has been reported.  And here’s what we learnt when we passed the news filter and went straight to the source, the summary of PJP’s research entitled “Regaining our competitive edge in minerals resources”.

Let’s begin with the summary, PJP make four main points here:

1. Developing world transformation continues to deliver sustained demand growth.
2. Capturing this means growing volumes – the ‘free kick’ from price is over.
3. As competitors multiply, our declining competitiveness means we will not capture our fair share of these volumes.
4. Regaining our competitive edge will require immediate and coordinated effort.

Last week Mantle Mining withdrew an application to explore for brown coal in the Deans Marsh area southwest of Melbourne.  We were interested due to our involvement with other coal projects that have been controversial with local communities such as the Boggabri Mine in NSW.

The local residents were opposed to any mining development and claimed their “victory” was due to the strength of their community.  As far as communities go, it is a tough one for a miner to take on – a Greens senator lives there, much of the local economy is based on tourism, a lot of the agriculture trades on being clean and green.  There’s not a lot of mining in the area and old-growth logging in the Otways recently ended after years of campaigning.

Mantle mining emphasised their commitment to environmental and social values, demonstrated by walking away from the deal.

All good stuff and all of these things play a part, I’m sure.  But at the bottom of Mantle’s piece on the withdrawal, they say:

Mantle has taken a pragmatic decision to withdraw its application for an exploration licence in order to focus its resources on other higher priority projects. 

So part of the decision was related to potential conflict with the community and the costs that entails, but part of it was also that Mantle have other less risky, more profitable projects to pursue.  Mantle haven’t made a loss – at least no more than the difference between the Dean’s Marsh project and whatever they will do instead.

This idea of the “next-best” project is often overlooked, as public attention tends to be on a particular project and “victory” or “loss” for opponents or proponents.  The planning process also tends to focus on single projects and what net present value (NPV) would be “lost” or “gained” by it.  The opportunity cost of the next-best project is rarely considered.  This project may also be profitable/positive NPV, but be more acceptable to opponents.  We’ve been trying to point this out in recent papers relating to the Boggabri Coal extension project.

While we keep trying to point that out, best of luck to the Deans Marsh community and to Mantle Mining and their next best project – I see they have one not far away in Bacchus Marsh.

Economists at Large have undertaken a review of the report, Impact on North Stradbroke Island from ceasing sand mining (the Unimin Report), conducted by Synergies Economic Consulting (the Consultants) for Unimin Australia (now Sibelco) and released in June 2010.  Save Straddie Alliance asked Economists at Large to review the Report.  We found three main flaws in the report:

• Failure to consider planned mine closures: Closure of the Yarraman mine, planned for 2015, will reduce the volume of mineral sands mined on the island by 34%.  This reduction was included in the Unimin Report.  This omission results in the value of sand mining on the North Stradbroke Island (NSI) being overstated by as much as 37% for gross output value and 57% for government revenues.  A thorough economic impact assessment should ascertain what level of impact is likely to occur against a business as usual scenario, in this case, where mining is phased out at the end of the life of the mines.  This approach was not taken for the Unimin Report.
• Confused scope for impacts: Impacts that will be felt at a state or national level are often considered to be impacts on the NSI economy.  For example, it is correct to include the reduction in gross regional product in wider regional analysis, but it needs to be made clear this does not translate to a welfare loss of this magnitude for the NSI community.
• Modelled impacts on NSI economy are overstated: The combination of the points above results in the modelled impacts being highly overstated (section 4.4).  While we have not attempted to calculate more accurate impacts, they are likely to be much less than estimated in the Unimin Report.  Furthermore, the method of modelling used may not be appropriate for this type of analysis and more details of the results should have been presented.

In addition to the points above, Economists at Large believe that the Unimin Report is narrow in its analysis and fails to consider externalities and opportunity costs of mining and the broader economic structure of the NSI economy.  This is not a fault of the report itself, but rather a caution to decision makers and the community reviewing the findings.

Economists at Large recommend that decision makers and the local community conduct more thorough analysis of the net benefits and costs to the NSI economy as a result of sand mining.

Download the full review: ECOLARGE-NSI-SandMining-Economics-FINAL.

For more information, please contact us.

The East West Link appears to be a classic example of a major project driven by politics rather than planning.  While some of the political angles are being explored, we also need to ask how such projects are helped along by planners and economists who should know better.

Many major projects over the last few decades have resulted in massive cost over-runs and often minimal benefits. While we have more data and more computing power than ever before, the accuracy of project evaluation seems not to have advanced at all. Two psychologists Daniel Kahneman and Amos Tversky describe this recurrence of errors in planning and decision-making as “planning fallacy”.[1]

Kahneman and Tversky found that planners tend to be optimistic regarding their own projects, known as “optimism bias”. In order to compensate for this misjudgement, planners should focus on the “outside view”. This involves examining other similar projects which have been completed in the past, and is known as “reference class forecasting.”

Bent Flyvbjerg applied this forecasting method to practical planning and decision-making. He emphasizes that the  following three steps are required when undertaking reference class forecasting:

Firstly, a sufficient number of similar projects completed in the past must be identified. Secondly, a probability distribution must be established, and lastly the current project must be compared with the reference class distribution. Ideally this should result in more accurate forecasts which are based on sound assumptions and not only wishful positive thinking.

There seems to be plenty of positive thinking out there.  9 out of 10 transport projects not only fail to meet targets, but also result in cost overruns. Transport isn’t unique. Museums, exhibition halls, aerospace projects, dams, sports arenas and oil and gas extraction projects are frequently affected by the same problems. Flyvbjerg states that the list of cost overruns and benefit shortfalls seem endless. The Transbay Transit Center in San Francisco, the Skytrain in Bangkok, the Sydney Opera House, the Scottish Parliament, the Berlin airport, the Millennium Dome in London, the 2004 Olympics in Greece and the Eurofighter aircraft are just a few projects characterised by significant miscalculations; and this is by no means an exhaustive list.

Miscalculations also appear on a smaller scale, for example, the installation of lights on Castle Hill in Queensland. This work was initially estimated to cost $650,000, but is now reported to cost $900,000. When asked why the figure initially fell short, Herbert MP Mr Jones admitted that “when we made a promise for $650,000 we did it in good faith;” this being a prime example of optimism bias.

Optimism bias is generally unintentional – planners do genuinely have the best intentions. It is a different matter when planners deliberately provide overestimated benefits and underestimated costs. Flyvbjerg describes this as “strategic misrepresentation”. The negative results are the same as the optimism bias, but the causes and the potential cure are different. The reasons for strategic misrepresentation can occur due to political-economic pressures. For example, planners seek approval for a project and compete with other projects for funding – every project appears more favourable if the costs are low and the benefits are high.

Every planner, economist and engineer is aware of this. Thus the incentive to generate misleading figures is enormous. In fact lying is economically rational for the planner and he or she is rewarded when a project is approved, despite the project not being economically worthwhile from the public point of view. Strategic misrepresentation results in “a negated Darwinism, with survival of the unfittest”, where the projects which look good on the paper but not in reality, are built.

Albeit hard to find evidence that planners provided misleading figures intentionally, Martin Wachs conducted a small number of interviews with planners in 1990 and published his findings. He points out that erroneous’ forecasts were the result of planners, engineers and economists who admitted that they were “cooking” their calculations in order to get their projects started. The number of cases where planners provided unrealistic calculations was not very high in Wachs’ study, however Flyvbjerg’s findings support Wachs’ claim that lying is commonly used for getting projects started.

Unfortunately reference class forecasting would not solely prevent this type of information asymmetry from occurring, as planners with the intent to defraud are not interested in obtaining correct and realistic calculations. Flyvbjerg recommends a set of accountability measures to ensure that forecasts are not defective. These include discretionary grants being capped, independent peer reviews being established, information regarding the project being available to the public, criticism from stakeholders being permitted and  miscalculated projects being ceased. In addition, he states that projects with realistic estimates should be rewarded, and those who consistently generate inaccurate forecasts be penalised.

In the so called age of big data, more and more data is available and easily accessible. Planners, economists and engineers can obtain data easier than 10 or 20 years ago, in order to build their own reference classes. With the right amount of data and the correct set of tools there are certainly fewer excuses for flawed economic forecasts. Without any doubt political-economic pressures and optimism bias will not disappear from one day to the other. However, as demonstrated in this article, reference class forecasting, and increased transparency and accountability are very useful measures to overcome too optimistic and deceptive economic analysis; in Australia and anywhere else in the world.

From time to time, we will public a blog post on a specific environmental economics topic. Today’s is brought to you by Economist at Large, William Li, who put together this excellent summary of methodologies used to value ‘green space’. We did some work with William on this in 2013 and thought this might be a handy resource for anybody working in the area.

It is not difficult to see that green spaces are valuable in highly urbanised settings. There are numerous benefits in being able to access green spaces including recreational opportunities, aesthetic enjoyment, environmental and agricultural functions, as well as value from preserving open spaces for future generations (Brander and Koetse, 2011).

However, as green spaces typically have public good characteristics, they tend to be underprovided in the absence of policy intervention (Kotchen and Powers, 2006; Smith et al, 2002), due to an inability to calculate exactly how much we value these types of assets.

Economists have developed a number of techniques to evaluate the value of environmental assets, but the values produced by each technique can vary noticeably. The most commonly used techniques employed by economists in the literature are hedonic pricing models (HPM), contingent valuation studies (CVM) and travel cost analyses (TCM).

Hedonic pricing model

What is it?

A hedonic pricing model(HPM) estimates the impact of economic value that parks and environmental variables to market prices. This is most commonly seen in housing prices, where it is assumed the price of houses reflect the characteristics of that house, including its access to particular environmental assets.

Unlike other valuation methods such as the travel cost method and the contingent valuation method, hedonic pricing does not rely on survey data, and instead uses property data, which is typically more robust.

Examples

Although there have been many studies using HPMs, the studies display wide variation in their characteristics with respect to model specification, sample size, study area and time period. Brander and Koetse (2011) collected more than 52 hedonic pricing studies on open space, and performed a meta-analysis on the results of 12 of those studies. They found that house prices demonstrated an average increase in house price of 0.1% when they are 10 m closer to open space. However, they found this relationship is non-linear; increases in house prices are stronger the closer the house is to the green space. These findings reveal that the further a house is located from open space, the smaller the price effect of moving closer to the open space. This implies that HPMs largely capture personal consumption values, and that aspects such as preservation for future generations are not as significant a factor.

Other papers have looked at more specific questions using hedonic pricing models, such as the value of tree cover (McPherson et al, 2011), the value of bodies of water (Kerstens et al, 2004) and the value of farmland (Johnston et al, 2001), all of which have found positive relationships between sale price and greater accessibility to the environmental asset.

 Method

As with all regressions, the first step is to collect data. In the case of a hedonic pricing model, this would be the selling price and location of residential properties in the area, as well as the details of the qualities of each house that would affect the selling price, including a number of property and neighbourhood characteristics. Included in this would be the accessibility and proximity to an environmental asset.

This data is then regressed against the house price, and the relationship between housing price and the key environmental attributes is defined.

Potential issues

• Hedonic pricing will only capture benefits from environmental assets insofar as they affect housing prices.
• The results depend heavily on the model specification.
• Hedonic pricing is generally more suited to general questions as opposed to a more specific valuation. The value of parks on housing prices in general would be easier for the model to identify as opposed to the value of a particular park, as there would be less pertinent data.

Travel cost method

What is it?

The travel cost method (TCM) aims to value assets such as ecosystems or parks by inferring the demand and economic surplus for these assets through visitor travel costs. As travel costs and time increase with distance from the location, each zone of travel is treated as a different “price” at which visitors are willing to pay to visit the site.
Once calculated, this demand is compared to the cost of operating and maintaining the asset, and when combined, these two values provide the total economic surplus that the asset provides.
The travel cost method is most appropriate when the environmental asset is in itself a destination that attracts visitors, and so is best suited for valuation of assets such as national parks and/or wildlife reserves.

Examples

In most cases, the travel cost method has been used in the economic literature to value national parks or particular tourists attractions (Loomis et al, 2000; Twerefou and Adjei-Ababio, 2012). Ultimately, comparison across these different studies is fairly arbitrary, as each site will have its own particulars and context that will differ from each other site, and so it is difficult to say whether these values are high or low. However, a meta-analysis by Shrestha and Loomis (2003) of outdoor recreation over the past 30 years in the USA predicted an average consumer surplus of $47.10 USD per day per person. Other meta-analyses have also been undertaken for studies in other locations (Zanderson and Tol, 2009; Johnston et al, 2005).

Method

The TCM uses survey data taken from a sample of visitors to the site. Firstly, zones are defined by their distance from the location. The exact number and definition of the zones is largely arbitrary, and more zones will result in greater differentiation, but will typically be more work and may require more data.

Visitors are then grouped into “zones”, determined by the distance they travelled to get to the location, and the total visits per zone is calculated. The visitation rate is then determined by dividing the total visits per zone by the zone’s population in thousands.

The average round trip travel costs is then calculated for each zone, assuming that people in the closest zone (Zone 0) have a zero cost of travel to get to the location. This will involve the average cost of travel (petrol/plane tickets) as well as the average cost of time (usually the average hourly wage). Any additional admission fees are also included in determining the average WTP of visitors.

These figures are then used (with a number of other variables) to produce a regression model, which can then be used to derive the demand curve for the asset. The area under this curve is thus the total estimate of the economic benefits of the asset.

Potential issues

• The TCM assumes that the visitation or usage of the site is the primary reason for the individual’s trip. If there are other reasons that an individual has travelled to the location, that visitor’s travel cost will be overestimated.
• The TCM does not capture non-use values of the asset, as it would only survey individuals who have come to visit the site. This could also (and would likely) introduce sampling bias to the results and is likely to underestimate the value of the asset.
• There could be individuals who live near the site and thus have low travel costs to the location but nonetheless value the asset highly.

Contingent valuation method

What is it?

The contingent valuation method (CVM) involves directly asking individuals how much they would be willing to pay to use a particular asset or the amount of compensation they would require to give up the asset. The name of the method derives from the fact that individuals are asked for their willingness to pay contingent on a specific hypothetical scenario.
CVM is quite flexible in being able to value more or less anything, and also captures individual’s valuations for both use and non-use purposes.

Examples

While there are many questions regarding how accurately stated preferences translate into actual behaviour, CVM remains a widely used technique in the literature. Brander and Koetse (2011) performed a meta-analysis of 20 CVM studies, finding the value of open space in an area with ‘average characteristics’ (average hectare size, GDP per capita and population density) has a value of approximately $1,550 USD/ha/year.

They also found recreation was much more highly valued (322% higher value per hectare) than environmental/agricultural benefits, which contrasted with previous results found by Kline and Wilchelns (1998) and Kotchen and Powers (2006), who found evidence of stronger preference for agricultural land over other types of open space. Brander and Koetse (2011) also observed a significant and positive relationship between the value of open space and population density.

There have also been a number of papers that have found no significant income effect for the value of open space (Romero and Lieserio, 2002; Kline and Wilchens, 1994) although Brander and Koetse (2011) suggest this may be the case people prefer to consume private open space (e.g, private gardens) rather than public open space as their income increases.

Method

More so than any other technique, the design of the survey for the CVM is the most important part of the method, as it deals with a high level of subjectivity and conjecture that arises from using non-observational data. A number of different aspects of the survey must be considered when designing the questions:

• Who is the asset valuable/relevant to?
• How large will the sample space be?
• What method of survey distribution and collection will be used?

Further to this, the questions and survey must be tested and refined to ensure that all the relevant information is provided and there are no ambiguities in the phrasing of questions. This ensures the data is as accurate and representational as possible, although the reality is it is highly unlikely to remove all biases from the survey.

Potential issues

• Of the methods used to evaluate non-use goods, CVM is one of the most controversial, as the valuation data is based on what respondents say they would do rather than observing their actions. For any number of reasons, individuals may overstate or understate their valuation of an asset and this may bias the result. This is a major criticism of CVM, and while proper survey design and effective complementing analysis can help minimize this issue, it is unlikely to remove its impact entirely.
• CVM relies on responses to a hypothetical situation, and it can be reasonably argued that what people say they will do in a hypothetical situation will differ to when they are required to pay the amount.
• The design of the survey and questions can heavily influence the results.

Other methods of valuation

While not as analytically rigorous as the above three methods, the values below should not be ignored, as they may provide complementary or supporting valuation of environmental assets.

Land value (simple)

What is it?

Land value looks at the prices of the land of the asset in question. This usually reflects the total commercial value of the land.

Potential issues

• Land value primarily takes into account market-based and commercial benefits of the land, and will usually fail to incorporate all of its non-market and non-use benefits.

Investment or development value (in the case of a park)

What is it?

The development value of a park represents the potential commercial gains due to the increased tourism/jobs that could be realised if amenities and facilities such as houses, hotel and restaurants were built in the area.

Method

The development value will typically be a function of the number of individuals that visit a location multiplied by the average amount of money a visitor would spend at the location.

Potential issues

• Like land value, development value primarily deals with commercial benefits, and would ignore the potential damage that development could have on the non-market benefits of the asset, such as congestion, additional waste etc…

Urban heat island effects

What is it?

An urban heat island is a metropolitan area that is significantly warmer than its surrounding area due to human activities. This leads to increased rainfall in these areas, as well as a decrease in local air and water quality. Green space can be valuable for its contribution in mitigating the urban heat island effect.

Method

The effect of green spaces in mitigating urban heat islands can be seen in measuring the air temperature around the green spaces, typically several years after their setup.

Potential issues

• While the mitigation of urban heat islands is a positive aspect of green space, it is difficult to value the benefits of the impact of the green space, given how little consumers are likely to feel the impacts. Ultimately, it may be implicitly captured in other models, but it would be difficult to capture this value in its entirety.

BIBLIOGRAPHY

Brander, L.M. and Koetse, M.J. (2011). The value of urban open space: meta-analyses of contingent valuation and hedonic pricing results, Journal of Environmental Management, 92: 2763-2773. 

Kotchen, M.J. and Powers, S.M. (2006), Explaining the appearance and success of voter referenda for open-space conservation, Journal of Environmental Economics and Management, 52(1): 373-390.

Smith, V.K., Poulos, C., Kim, H. (2002), Treating open space as an urban amenity, Resource and Energy Economics, 24: 107-129.

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