Monthly Archives: October 2010

175 – Environmental valuation: policy challenges

In recent years, environmental economists in Australia have increasingly used a number of methods to estimate dollar values for the benefits provided by the environment. However, one hears these economists expressing disappointment and frustration about the lack of interest by policy makers and environmental managers in this work. Why aren’t they more interested?

The methods are known collectively as “non-market valuation”. The most widely used are survey-based techniques, “choice modeling” and “contingent valuation”. Although I am not an expert in these techniques, I understand them well and I work with people who are experts.

Also, I have been involved in developing and applying INFFER, a framework for evaluating environmental investments (Pannell et al. 2010), which includes environmental significance or value as one of its important inputs. Usually in INFFER we measure significance using a scoring system, although it is also possible to use non-market valuation.

Discussing INFFER with people in a number of environmental organisations has given me some insight into why they are sometimes resistant to environmental valuation. A number of reasons have emerged. The first five issues are not specific to non-market valuation, but are equally applicable to the sort of scoring system we usually use in INFFER.

1. Ignorance is bliss. Information about the values of different environmental assets may be unwelcome because it reduces the flexibility of politicians or managers to take actions that they prefer for one reason or another (e.g. political rather than environmental reasons). A Federal Ministerial advisor was once quite open and explicit about this to me.

2. Avoidance of controversy. A senior manager in a state agency expressed concern about the risk of information about environmental values becoming controversial. It may conflict with the preferences or preconceptions of vocal or influential stakeholders, resulting in high transaction costs and stress for the agency. Avoidance of controversy is often one of the key requirements that ministers impose on their agencies.

3. Lack of any administrative process that could make use of the information. Organisations can only make use of information if they use some process or framework into which the information can be fed. In most processes or frameworks currently used by environmental organisations, there is no scope to include information about community valuation of environmental assets. Ideally, it would feed into a Benefit: Cost Analysis, but these are almost never conducted by environmental agencies. One of our motivations in developing INFFER was to provide a framework into which essential, but often-neglected, information could be fed, including information about environmental significance.

4. Satisfaction with existing methods. Although I consider most of the existing environmental decision frameworks I have seen in use by Australian environmental organisations to be weak, people tend to be highly satisfied with their existing tools and approaches. People often don’t recognise the weaknesses in their decision processes, or the consequences for decision making. However, in detailed tests of different decision metrics, I found that environmental outcomes are highly sensitive to weaknesses in the process (see PD158). Dealing properly with all relevant information really matters.

5. Subjectivity of valuation. Some people object to the subjectivity of valuation. They would prefer to limit the process to things that can be measured more objectively. However, it seems obvious that you should not ignore the fact that some environmental assets are much more significant than others (e.g. the Great Barrier Reef versus a small patch of bush in the wheatbelt), and it is equally obvious that any such comparison of values is unavoidably subjective, however the comparison is made.

Beyond these general concerns about any method for quantifying environmental significance or value, there are a number of factors that relate specifically to non-market valuation:

6. Philosophical objections to monetisation of the environment. This is not uncommon, especially amongst people with a strong interest in the environment. The counter argument is that monetisation is just a tool to facilitate trade-offs between various real outcomes, but some of these people resist the very idea of making trade-offs, so that argument may not help much. Of course, trade-offs are unavoidable, and doing them well can improve environmental outcomes, so this purist position can be self-defeating.

7. Timing issues. Conducting non-market valuation studies in response to current policy needs would usually take too long for the policy time-frame. In practice, policy requirements for such information usually need to be anticipated well in advance, but policy agencies generally don’t do much of this sort of thing ahead of time.

8. Legitimate concerns about limitations of the methods. Some environmental decision makers are aware that there has been a spirited debate about non-market valuation amongst economists. Indeed, some economists have expressed highly critical views about particular non-market valuation techniques (e.g. see quotes in Pannell, 2004). These tend to be rather technical in nature, but one non-technical issue is the challenge of obtaining reliable responses from even quite simple survey questions. Non-market valuation surveys make pretty high demands of people to think about complex issues in abstract ways, so reliability certainly can be a challenge.

9. Preference for expert or policy-maker judgments. Economists usually argue that the people whose valuations matter are the general population. Public policy should serve the wishes of the public, not least because they are the ones whose taxes are going to pay for the environmental works. However, most environmental organisations are accustomed to relying on experts for advice, not just about scientific matters, but also (implicitly) about values. Sometimes the experts themselves don’t realise that the advice they are giving is value-laden. On the other hand, the surveyed community members in a non-market valuation study may know little or nothing about the environmental issues at stake. It’s a dilemma. In my view, it does sometimes make sense to use experts to judge values, either because of their superior knowledge, or because it is an efficient way to approximate community values. Even then, however, such values should be recorded explicitly, for purposes of transparency and accountability.

10. The high cost of doing it. A reliable non-market valuation survey requires a significant level of expenditure. Environmental managers are not used to having to bear this cost, and probably don’t have the budget to do it in all relevant cases.

The following issues have never been expressed or implied to me by someone from an environmental organisation, but in my judgment they are both relevant.

11. The incremental benefits may be modest. As noted above, environmental organisations often use expert judgments to approximate community values. Another option could be to hold community meetings or focus group discussions. Given that we have these relatively cheap and simple fall-back options, what is the incremental value of a high-quality non-market valuation survey of the community? Using information economics theory to guide our thinking about this, the value of the improved information would depend on: (a) how much better the information from a non-market valuation study would be compared to an easier information source; (b) how much difference that improvement in information would make to the decisions that are taken; and (c) the extent to which the differences in decisions would eventually improve the value of environmental outcomes. In my experience, when you do the sums, the value of more precise information is often quite a bit less than people expect. Approximate information can often be nearly as valuable (e.g. see PD159), so it could be rational to use a simpler, cheaper approach to environmental valuation.

Another source of approximate values can be “benefit transfer” — taking results from past non-market valuation studies in analogous situations. Although this would have lower accuracy than purpose-done surveys, it is obviously much cheaper.

12. There are many other information requirements. Environmental valuation is far from being the only information you need to prioritise environmental investments — it’s just one of the (roughly) 10 things you need to know about each investment option. In practice, we find that the biggest sources of uncertainty in these prioritisation decisions are usually uncertainty about human behavioural responses to the intervention, and about the cause-and-effect relationships between actions and environmental outcomes. These other sources of high uncertainty put a limit on the potential for greater accuracy about environmental values to improve environmental decisions. It may not be the most important information gap to fill first.

Some of the reasons given for not using non-market valuation don’t stand up to scrutiny (1, 2, 4, 5 and 6, I would suggest) or could be easily addressed (3, 7). On the other hand, some of the issues raised could favour use of simpler, less costly approaches to quantifying environmental values in particular cases (8, 9, 10, 11, 12), potentially including benefit transfer.

The fact that there are so many items on this list suggests that proponents of non-market valuation face quite significant challenges in getting the approach more widely and routinely used in real decision making. We are finding with INFFER that, with sufficient persistence, creativity and good communication, we can get environmental managers to accept the need for some method for quantifying environmental values, and this may be a stepping stone to increased demand for non-market valuation. The later issues on the list are, however, likely to continue to dampen that demand, at least for purpose-conducted studies.

David Pannell, The University of Western Australia

Further reading

Pannell, D.J. (2004). Heathens in the chapel? Application of economics to biodiversity, Pacific Conservation Biology 10(2/3): 88-105. Full paper (109K)

Pannell, D.J., Roberts, A.M., Park, G., Curatolo, A. and Marsh, S. (2010). INFFER (Investment Framework For Environmental Resources): Practical and Theoretical Underpinnings, INFFER Working Paper 1001, University of Western Australia. Full paper (107K)

174 – Assessment of the National Action Plan for Salinity and Water Quality

Next month marks 10 years since the announcement by then Prime Minister John Howard of the National Action Plan for Salinity and Water Quality. Anna Roberts and I conducted a comprehensive retrospective assessment of the program and its achievements, and this has just been published in the Australian Journal of Agricultural and Resource Economics. The assessment is highly negative.

The National Action Plan (or NAP) was the policy response to a perceived salinity “crisis”. It spent A$1.4 billion of public funds (and drew in a larger volume of private funds) in 1700 projects over seven years.

When it was announced, I was publicly critical of its design. In fact, my anger at its obvious failings was what first got me actively engaged with environmental policy. I wrote a brief paper called “Salinity policy: A tale of fallacies, misconceptions and hidden assumptions”, which went viral in salinity circles, and I mouthed off in the media and at a national conference held at that time. I gave presentations to anybody who would listen, including to senior people in the Department of Agriculture, Fisheries and Forestry, who were responsible for the program. I kept up my criticisms throughout the life of the program, but also was constructive and co-developed decision tools and frameworks to overcome some of the problems (Ridley and Pannell, 2005; Pannell, 2008).

It wasn’t just me who was unhappy. There were four government reviews of the program conducted during its life (two by the Australian National Audit Office (ANAO), one by a Senate committee and one by a House of Representatives committee), and all of them identified serious concerns.

The NAP did not result in the large-scale land-use change in dryland landscapes that would be needed to contain salinity. A consultant’s report near the end of the program concluded that “NAP investment by itself was always unlikely to do so, due to the lack of suitable landscape ‘best practice’ options, the scale of investment and the time required to implement landscape change and achieve a landscape response.” That was more or less what I was saying at the start of the program. A program that took account of these understandings would have been designed completely differently.

The ANAO’s 2008 review was particularly damning: “There is little evidence as yet that the programs are adequately achieving the anticipated national outcomes” (Auditor General, 2008, p. 16). “Where the impact [of NAP investment] on resource condition is identified by regional bodies, the expected results were often low (frequently less than one per cent of the longer-term resource condition target)” (Auditor General, 2008, p. 19-20).

I’ve heard people claim that the ANAO report did not conclude that the program was ineffective, just that they couldn’t tell whether or not it was effective. That last quote makes clear that this claim is not true.

In our recently published assessment of the program (Pannell and Roberts 2010), we identified 12 criteria that it would have had to meet to be successful.

  1. Appropriate prioritization of potential projects
  2. Use of appropriate policy mechanisms
  3. Use of technical information
  4. Use of socio-economic information
  5. Balance of investment between current works and knowledge or technology
  6. Balance of investment between mitigation and adaptation
  7. Avoidance of adverse side-effects
  8. Monitoring and enforcement of compliance
  9. Setting appropriate targets
  10. Monitoring and evaluation linked to management
  11. Supporting, and creating appropriate incentives for, environmental managers
  12. Consistency with an appropriate role for government

The National Action Plan didn’t meet any of the criteria. Overall, with a few exceptions, its 1700 projects generated few worthwhile salinity mitigation benefits and will have little enduring benefit.

One of my big lessons from the NAP experience is how difficult it is to change a policy program once it has been announced. Despite me putting forward what I still feel were compelling and very serious criticisms, and despite those criticisms basically being confirmed in the various government reviews, no fundamental changes were made to the program. Pretty early on I came to the conclusion that we would have to wait until we’d wasted that $1.4 billion before there would be an opportunity for meaningful change, and so it proved to be.

David Pannell, The University of Western Australia

Further reading

Auditor General (2008). Regional Delivery Model for the Natural Heritage Trust and the National Action Plan for Salinity and Water Quality, Report No. 21 2007–08, Performance Audit, Australian National Audit Office, Canberra.

Pannell, D.J. (2001). Dryland Salinity: Economic, Scientific, Social and Policy Dimensions, Australian Journal of Agricultural and Resource Economics 45(4): 517-546. Full journal paper (212K pdf) also available via the Journal homepage: here

Pannell, D.J. (2001). Salinity policy: A tale of fallacies, misconceptions and hidden assumptions, Agricultural Science 14(1): 35-37.* Full paper (26K)

Pannell, D.J. (2008). Public benefits, private benefits, and policy intervention for land-use change for environmental benefits, Land Economics 84(2): 225-240. Full paper (140K)

Pannell, D.J. and Roberts, A.M. (2010). The National Action Plan for Salinity and Water Quality: A retrospective assessment, Australian Journal of Agricultural and Resource Economics, 54, 437-456. Journal web site here

Ridley, A., and Pannell, D.J. (2005). The role of plants and plant-based R&D in managing dryland salinity in Australia, Australian Journal of Experimental Agriculture, 45: 1341-1355. Full journal paper (127K pdf)

173 – Indirect influences of policy on environmental outcomes

There are many policy programs around the world that aim to influence the activities of farmers in order to benefit the environment. Sometimes people fall into the trap of thinking and talking about these programs as if they were mechanistic in their impacts on the environment — you pull a policy lever and get an outcome. Of course, the reality is not that simple. The influence of policy actions on the environment is indirect and compromised by other factors, making life rather difficult for policy makers who wish to achieve particular outcomes.

The difficulty is that, in practice, in a democracy it is not in society’s power to select a particular sustainable farming system, because the government cannot simply order farmers to adopt the chosen system. Rather we are constrained by the effectiveness of the various tools that can be used to encourage adoption of different practices. The farming system that comes into existence will be that which results from farmers’ reactions to the government policies and institutions in place, allowing for other constraints and considerations.

Figure 1 illustrates these ideas. It shows that an environmental body (e.g. government agency, Catchment Management Authority, or NGO) concerned with land use can influence the decisions of private landholders (box E) through the selection and application of policy mechanisms (box A). The mechanism options include things such as regulation, education, subsidies, conservation tenders and research. The figure highlights that the environmental body is only one of a number of broad influences on land-use decisions, others including the economic environment, social factors, and bio-physical conditions. Clearly, the ability of environmental bodies to control land use is partial and often highly uncertain.

Figure 1. The indirect and partial effect of policy (through choice of policy mechanisms – box A) on land use and natural resource outcomes.

Actual land use has a set of economic, social and environmental consequences (box G) which may or may not align with the objectives of the policy maker (box H). If they do not, the environmental body can attempt to improve the alignment by modifying the policy mechanisms being used (link back to box A).

An alternative route to achieve policy objectives is for the body to undertake required works itself (box D). For example, governments may choose to establish national parks, to repossess private land in order to alter its management, or to implement engineering works to protect environmental assets.

Science may influence land use through several channels. These include giving landholders better knowledge of the relevant biophysical or economic conditions (boxes F and B) and their influence on outcomes from different land uses; through developing improved technologies that provide new land-use options (altering the influence of box E on box G), or indirectly through better informing policy makers.

Note that land-use change is occurring continuously, irrespective of policies or science, as a result of changes in economic, social or bio-physical conditions or changes in technology. It may also occur as a result of other policies that are not intended to target land use, such as taxation or trade policy. Overall, the influences of policy and science are complex, and often indirect.

A lot of environmental modelling doesn’t do justice to the complexity of this system. Economists are better than most in this regard. There are at least some numerical models that represent policy mechanisms affecting farm business decisions, flowing through to environmental consequences (e.g. Doole, 2010). Another relevant approach is the ‘Principal Agent Model’, which explicitly represents the relationship between a principal (such as a government) and agents who the principal wishes to influence (such as farmers). These models are used to design policy mechanisms that will achieve the optimal balance between benefits and costs, given different objectives and different information levels between the principal and the agents. When applied to the environment, they typically involve only a simplistic representation of the biology, but they do at least represent the human behavioural aspects of the system explicitly.

David Pannell, The University of Western Australia

Further reading

Doole, G.J. (2010). Evaluating Input Standards for Non-Point Pollution Control under Firm Heterogeneity, Journal of Agricultural Economics 61, 680-696.

Pannell, D.J. 2003. Balancing economics and sustainability in building an integrated agricultural system, Pacific Conservation Biology 9 (1/2), 23-29.

Pannell, D.J. and Roberts, A.M. (2009). Conducting and delivering integrated research to influence land-use policy: salinity policy in Australia, Environmental Science and Policy 12(8): 1088-1099. Full paper (94K)Journal version on-line

172 – Peak oil

This week’s Pannell Discussion is a review of a book called ‘Oil panic and the global crisis: predictions and myths’ by Steven M. Gorelick. It’s a fascinating book that reaches conclusions that might be surprising if you aren’t familiar with details of the oil industry (as I wasn’t).

Before reading this book, my knowledge of the issues around peak oil was not great. I knew of the concept, of course, and understood the predicted consequences, but I had not read any of the arguments about the validity and usefulness of the idea. Steve Gorelick, a Professor in the Department of Environmental Earth System Science at Stanford University, has fixed that. This highly readable and interesting book presents both sides of a complex and important debate.

The central concept at issue is the idea, originally proposed by M. King Hubbert, that oil production over time is destined to follow a particular pattern. He predicted that it would take the shape of a classic bell-shaped curve (a normal distribution or logistic function), rising to a peak, turning over and then falling away to nothing. He predicted that the bell would be symmetrical, falling in the same pattern as it had previously risen.

After setting the scene in Chapter 1 by describing Hubbert’s idea, its appeal and its initial predictive success, Gorelick puts it aside in Chapter 2 while he provides us with detailed background on the global oil landscape. This was very valuable for a non-expert like me, covering issues such as the energy density of different fuels, the oil business, OPEC, assessments of how much oil there is, where oil is produced and consumed, oil quality, oil pricing, the price elasticity of petrol (gasoline) and petrol price variability. I was struck by the range of retail petrol prices in different countries (depending mainly on taxes and subsidies), ranging in March 2008 from US$2.30 per litre in Norway down to US$0.03 per litre in Venezuela!

Chapter 3 covers the historical resource depletion debate, starting with Malthus, via the Club of Rome and the 70s oil crises, and then returning to the ideas and predictions of Hubbert. A variety of evidence is presented supporting the argument that global oil is depleting. Indeed, the presentation of quantitative evidence is a very strong feature of the book. There are numerous graphs and tables of empirical data, almost one per page, looking at the issues from every possible angle. They show us, for example, that oil production has exceeded oil discovery since about 1980, that global oil discovery peaked in the early 1960s, that discovery of giant oil fields has particularly declined, and that projected growth in oil consumption by developing countries suggests great strain on future supplies. Using similar approaches to Hubbert’s, bodies such as the US Department of Energy (DOE) have predicted that the date of global peak oil production is getting close. Specifically, under its high-growth scenario, the DOE predicted in 2004 that the peak would occur around 2030, and would be followed by rapid declines in production.

By this stage of the book, the reader feels rather pessimistic – the evidence for imminent oil depletion looks so convincing – but then in Chapter 4 Gorelick presents the counter arguments. We learn that predictions of production rates based on Hubbert’s approach have consistently been too low, sometimes spectacularly so. “Analysts using Hubbert’s approach have the habit of ignoring their earlier predictions of the time of peak oil every so often and providing later and later dates based on larger and larger values of the global oil endowment” (p.98). Even in the US, which has done the most thorough job of finding and extracting its oil, official estimates of oil endowment have grown consistently over time, such that at any point in time there appears to be enough oil to last the next 35 years. The same applies at the global scale, except that the number is 45 years. Global oil reserves have consistently grown (e.g. they have doubled since 1980), mainly due to reassessment of how much oil there is in existing oil fields. There may be a lot more oil still to find; “The Middle East, Eastern Europe and Africa contain three-quarters of world oil reserves and yet account for only one-seventh of exploratory drilling” (p. 182). Lower recent rates of oil discovery are at least partly due to low levels of exploration during the 1980s and 1990s, due to low prices. Gorelick points out that resource economists have consistently been more optimistic about future resource scarcity than have neo-Malthusians, due to their accounting for factors such as price signals and technological change. And so on. The counter arguments to oil pessimism are many and varied.

Finally, in Chapter 5, titled “Beyond Panic”, Gorelick attempts to pull it all together and draw conclusions. He emphasises that the debate is not just about optimism and pessimism. “Informed positions transcend attitudes” (p. 221). The positions taken by different protagonists can be explained by the key assumptions they have made. Hubbert’s mass balance approach is based on the assumptions that the global oil endowment can be estimated accurately (which is palpably wrong), and that oil use is limited by production (ignoring the demand side of the market). On the other side of the debate, analysts have allowed for oil resources from unconventional sources, have considered the dynamics of oil demand, and have anticipated the role of technological change. Ultimately, Gorelick sides with the latter group. “If there is a peak and decline in global oil production during the next two decades, it is more likely that it will reflect a decrease in global oil demand, rather than production choked by critically low global availability” (p. 224). He concludes that we will probably move away from reliance on conventional oil long before the oil runs out.

A particularly nice feature of the book is the inclusion of key summary points at the end of each chapter. These sum up the essence of the material of the chapter in a set of well-selected dot points. A time-pressed or casually interested person could learn a lot just by reading these sections.

But that would be a shame. The book deserves to be read in full. For me, at least, it was a page turner. There is plenty of detailed information to allow readers to form their own judgements, but it is presented in a way that does not overwhelm the story. The lessons of the book are highly relevant to resource economists, and to anybody interested in energy.

David Pannell, The University of Western Australia

Further reading

Gorelick, S.M. (2009). Oil Panic and the Global Crisis: Predictions and Myths, Wiley-Blackwell Publishers, Oxford, UK.