Category Archives: Politics

265 – Fossil fuel subsidies

Amidst all the discussions about carbon taxes and emissions trading schemes for mitigating climate change, we hear very little about fossil fuel subsidies. You’d be forgiven for not knowing that they are, in fact, enormous.

This matters for several reasons, including that these subsidies encourage increased use of fossil fuels. From the perspective of climate-change policy, fossil-fuel subsidies make things even worse than they need to be. Climate policies are intended to push us in one direction, but fossil-fuel subsidies are pushing us in the opposite direction. It’s like running a race but starting well behind the start line.

I was surprised to learn that Australia has one of the highest levels of fossil fuel subsidies in the OECD, totalling US$8.5 billion of budgetary support and tax expenditures in 2011.

petrol_pumpWe have a bewildering array of schemes that subsidise fossil fuels. Federal subsidies include exemptions from crude oil excise for condensate, a reduced excise rate on aviation fuel, and the clean coal fund, plus there are numerous schemes at the state level. The biggest subsidy by far is the Fuel Tax Credits program, which provided almost $6 billion dollars of support to businesses for their fuel use in 2011.

Our total level of subsidies is behind the USA ($13 billion) but ahead of some economies that are much bigger than ours: Germany ($7 billion), the UK ($7 billion) and France ($4 billion).

We are told by our national government that our carbon tax is cripplingly expensive and has to go, but in 2012-13 it collected only $4.9 billion, not much more than half the cost of our fossil fuel subsidies. For some reason, the subsidies are not considered too expensive for us to bear. The most cost-effective way to make a start on reducing carbon emissions would probably be to remove these subsidies. At the same time, it would help to reduce our budget deficit.

The problem is even worse outside the OECD, with some staggeringly large subsidy programmes in Egypt ($19 billion), China ($20 billion), Russia ($23 billion), Venezuela ($24 billion), India ($34 billion), Saudi Arabia ($46 billion) and Iran ($65 billion). In Venezuela, fuel at the retail level is almost free – just a few cents per litre.

Fuel subsidies in these countries are often justified as a form of assistance to poor people, but it’s a really dumb way to try to help them. For one thing, most of the benefits go to people who are not poor. Secondly, the greatest needs of poor people might be something other than fuel – food or education, for example. Thirdly, big subsidies hold countries back economically, which ultimately is bad for poor people.

Getting rid of them is really hard, though, because the beneficiaries are used to them and see them as entitlements. Sometimes the subsidies are targeted at special interest groups, like farmers, who would fight really hard against any attempt to remove them.

It’s another illustration of the adage that we shouldn’t put any major policy in place that we might later want to remove, because special interests take hold and use the political system to defeat the public interest.

Further reading

Burniaux, J.M. and Chateau, J. (2011). Mitigation Potential of Removing Fossil Fuel Subsidies: A General Equilibrium Assessment, OECD, Paris, IDEAS page

OECD (2012). Inventory of Estimated Budgetary Support and Tax Expenditures for Fossil Fuels 2013, OECD, Paris, here

Whitley, S. (2013). Time to change the game: Fossil fuel subsidies and climate, Overseas Development Institute, here


259 – Increasing environmental benefits

It is obvious that the budgets of our public environmental programs are small relative to the cost of fixing all of our environmental problems. If we want to achieve greater environmental benefits from our public investments, what, in broad terms, are the options?

I remember seeing a graph last year – I think it was from the Australian Bureau of Statistics – showing the level of concern felt by the Australian community about environmental issues. It looked to have peaked a few years ago, and was pretty flat, or slightly declining. In that context, the prospects for a big increase in environmental spending over time don’t look good, particularly given the general tightness of government budgets. So I was wondering, if we wanted to double the environmental values protected or enhanced by our public programs, what are the options? I was able to identify several. I’ll list them here, and briefly comment on their potential effectiveness, cost and political feasibility.

  1. Double the budget. Effectiveness: high (in the sense that we could actually double the environmental benefits generated). Cost: high. Politics: very unlikely in the foreseeable future. It wouldn’t be my first priority, anyway. Increasing the budget would be more effective if we first delivered some of the strategies below.
  2. Improve the prioritisation of environmental investments. Improve the usage of evidence, the quality of decision metrics (Pannell 2013), and the quality of evaluation of proposals. Effectiveness: high (because most programs currently have major deficiencies in these areas). Cost: low, especially relative to doubling the budget. Politics: Implies a higher degree of selectivity, which some stakeholders dislike. Probably means funding fewer, larger projects. Achievable for part of the budget but the politics probably require a proportion to be spent along traditional lines (relatively unprioritised).
  3. murray_riverEncourage more voluntary pro-environmental action through education, persuasion, peer pressure and the like. Effectiveness: commonly low, moderate in some cases. Cost: moderate. Politics: favourable.
  4. Increase the share of environmental funds invested in research and development to create pro-environmental technologies (Pannell 2009). Note that this is about creation of new technologies, rather than information. Examples could include more effective baits for feral cats, new types of trees that are commercially viable in areas threatened by dryland salinity, or new renewable energy technologies. Feasibility: case-specific – high in some cases, low in others. Cost: moderate. Politics: requires a degree of patience which can be politically problematic. Also may conflict with community desire to spend resources directly on on-ground works (even if the existing technologies are not suitable). There tends to be a preference for research funding to come from the research budget rather than the environment budget, although this likely means that it is not as well targeted to solve the most important environmental problems.
  5. Improve the design of environmental projects and programs. Improve evidence basis for identifying required actions. Improve selection of delivery mechanisms. Improve the logical consistency of projects. Effectiveness: high (because a lot of existing projects are not well founded on evidence, and/or don’t use appropriate delivery mechanisms, and/or are lacking in internal logical consistency). Cost: low. Politics: Implies changes in the way that projects are developed, with longer lead times, which may not be popular. There may be a perception of high transaction costs from this strategy (although they would be low relative to the benefits) (Pannell et al. 2013).
  6. Increase the emphasis on learning and using better information. Strategies include greater use of detailed feasibility studies, improved outcome-oriented monitoring, and active adaptive management. Effectiveness: moderate to high. Would feed into, and further improve, options 2 and 5. Cost: low. Politics: main barrier is political impatience, and a view that decisions based on judgement are sufficient even in the absence of good information. Often that view is supported/excused by an argument that action cannot and should not wait (which is a reasonable argument in certain cases, but usually is not).
  7. Reform inefficient and environmentally damaging policies and programs. Examples include subsidies for fossil fuels, badly designed policies supporting biofuels in Europe and in the USA, and agricultural subsidies. This strategy is quite unlike the other strategies discussed here, but it has enormous potential to generate environmental benefits in countries that have these types of policies. Successful reform would be not just costless, but cost-saving. Effectiveness: very high in particular cases. Cost: negative. Politics: difficult to very difficult. People with a vested interest in existing policies fight hard to retain them. Environmental agencies don’t tend to fight for this, but there could be great benefits if they did.

In my judgement, for Australia, the top priorities should be strategies 2 and 5 followed by 6. Strategy 4 has good potential in certain cases. If these four strategies were delivered, the case for strategy 1 would be greatly increased (once the politics made that feasible). To succeed, strategies 2, 5 and 6 would need an investment in training and expert support within environmental organisations. Over time, in those environmental organisations that don’t already perform well in relation to strategies 2, 5 and 6 (i.e. most of them), there may be a need for cultural change, which requires leadership and patience.

In Europe and the USA, my first choice would be strategy 7, if it was politically feasible. After that, 2, 5, 6 and 4 again.

Further Reading

Garrick, D., McCann, L., Pannell, D.J. (2013). Transaction costs and environmental policy: Taking stock, looking forward, Ecological Economics 88, 182-184. Journal web site

Pannell, D.J., Roberts, A.M., Park, G. and Alexander, J. (2013). Improving environmental decisions: a transaction-costs story, Ecological Economics 88, 244-252. Journal web siteIDEAS page

Pannell, D.J. (2009). Technology change as a policy response to promote changes in land management for environmental benefits, Agricultural Economics 40(1), 95-102. Journal web page ◊ Prepublication version

Pannell, D.J. (2013). Ranking environmental projects, Working Paper 1312, School of Agricultural and Resource Economics, University of Western Australia. IDEAS page ◊ Blog series

226 – Modelling versus science

Mick Keogh, from the Australian Farm Institute, recently argued that “much greater caution is required when considering policy responses for issues where the main science available is based on modelled outcomes”. I broadly agree with that conclusion, although there were some points in the article that didn’t gel with me. 

In a recent feature article in Farm Institute Insights, the Institute’s Executive Director Mick Keogh identified increasing reliance on modelling as a problem in policy, particularly policy related to the environment and natural resources. He observed that “there is an increasing reliance on modelling, rather than actual science”. He discussed modelling by the National Land and Water Resources Audit (NLWRA) to predict salinity risk, modelling to establish benchmark river condition for the Murray-Darling Rivers, and modelling to predict future climate. He expressed concern that the modelling was based on inadequate data (salinity, river condition) or used poor methods (salinity) and that the modelling results are “unverifiable” and “not able to be scrutinised” (all three). He claimed that the reliance on modelling rather than “actual science” was contributing to poor policy outcomes.

While I’m fully on Mick’s side regarding the need for policy to be based on the best evidence, I do have some problems with some of his arguments in this article.

Firstly, there is the premise that “science and modelling are not the same”. The reality is nowhere near as black-and-white as that. Modelling of various types is ubiquitous throughout science, including in what might be considered the hard sciences. Every time a scientist conducts a statistical test using hard data, she or he is applying a numerical model. In a sense, all scientific conclusions are based on models.

I think what Mick really has in mind is a particular type of model: a synthesis or integrated model that pulls together data and relationships from a variety of sources (often of varying levels of quality) to make inferences or draw conclusions that cannot be tested by observation, usually because the issue is too complex. This is the type of model I’m often involved in building.

I agree that these models do require particular care, both by the modeller and by decision makers who wish to use results. In my view, integrated modellers are often too confident about the results of a model that they have worked hard to construct. If such models are actually to be used for decision making, it is crucial for integrated modellers to test the robustness of their conclusions (e.g. Pannell, 1997), and to communicate clearly the realistic level of confidence that decision makers can have in the results. In my view, modellers often don’t do this well enough.

But even in cases where they do, policy makers and policy advisors often tend to look for the simple message in model results, and to treat that message as if it was pretty much a fact. The salinity work that Mick criticises is a great example of this. While I agree with Mick that aspects of that work were seriously flawed, the way it was interpreted by policy makers was not consistent with caveats provided by the modellers. In particular, the report was widely interpreted as predicting that there would be 17 million hectares of salinity, whereas it actually said that there would be 17 million hectares with high “risk” or “hazard” of going saline. Of that area, only a proportion was ever expected to actually go saline. That proportion was never stated, but the researchers knew that the final result would be much less than 17 million. They probably should have been clearer and more explicit about that, but it wasn’t a secret.

The next concern expressed in the article was that models “are often not able to be scrutinised to the same extent as ‘normal’ science”. It’s not clear to me exactly what this means. Perhaps it means that the models are not available for others to scrutinise. To the extent that that’s true (and it is true sometimes), I agree that this is a serious problem. I’ve built and used enough models to know how easy it is for them to contain serious undetected bugs. For that reason, I think that when a model is used (or is expected to be used) in policy, the model should be freely available for others to check. It should be a requirement that all model code and data used in policy is made publicly available. If the modeller is not prepared to make it public, the results should not be used. Without this, we can’t have confidence that the information being used to drive decisions is reliable.

Once the model is made available, if the issue is important enough, somebody will check it, and any flaws can be discovered. Or if the time frame for decision making is too tight for that, government may need to commission its own checking process.

This requirement would cause  concerns to some scientists. In climate science, for example, some scientists have actively fought  requests for data and code. (Personally, I think the same requirement should be enforced for peer-reviewed publications, not just for work that contributes to policy. Some leading economics journals do this, but not many in other disciplines.)

Perhaps, instead, Mick intends to say that even if you can get your hands on a model, it is too hard to check. If that is what he means, I disagree. I don’t think checking models generally is harder than checking other types of research. In some ways it is easier, because you should be able to replicate the results exactly.

Then there is the claim that poor modelling is causing poor policy. Of course, that can happen, and probably has happened. But I wouldn’t overstate how great a problem this is at the moment, because model results are only one factor influencing policy decisions, and they often have a relatively minor influence.

Again, the salinity example is illustrative. Mick says that the faulty predictions of salinity extent were “used to allocate funding under the NAP”. Apparently they influenced decisions about which regions would qualify for funding from the salinity program. However, in my judgement, they had no bearing on how much funding each of the 22 eligible regions actually received. That depended mainly on how much and how quickly each state was prepared to allocate new money to match the available Federal money, coupled with a desire to make sure that no region or state missed out on an “equitable” share (irrespective of their salinity threat).

The NLWRA also reported that dryland salinity is often a highly intractable problem. Modelling indicated that, in most locations, a very large proportion of the landscape area would need to be planted to perennials to get salinity under control. This was actually even more important information than the predicted extent of salinity because it ran counter to the entire philosophy of the NAP, of spreading the available money thinly across numerous small projects. But this information, from the same report, was completely ignored by policy makers. The main cause of the failure of the national salinity policy was not that it embraced dodgy modelling about the future extent of salinity, but that it ignored much more soundly based modelling that showed that the strategy of the policy was fundamentally flawed.

Mick proposes that “Modellers may not necessarily be purely objective, and “rent seeking” can be just as prevalent in the science community as it is in the wider community.” The first part of that sentence definitely is true. The last part definitely is not. Yes, there are rent-seeking scientists, but most scientists are influenced to a greater-or-lesser extent by the explicit culture of honesty and commitment to knowledge that underpins science. The suggestion that, as a group, scientists are just as self-serving in their dealings with policy as other groups that lack this explicit culture is going too far.

Nevertheless, despite those points of disagreement, I do agree with Mick’s bottom line that “Governments need to adopt a more sceptical attitude to modelling ‘science’ in formulating future environmental policies”. This is not just about policy makers being alert to dodgy modellers. It’s also about policy makers using information wisely. The perceived need for a clear, simple answer for policy sometimes drives modellers to express results in a way that portrays a level of certainty that they do not deserve. Policy makers should be more accepting that the real world is messy and uncertain, and engage with modellers to help them grapple with that messiness and uncertainty.

Having said this, I’m not optimistic that it will actually happen. There are too many things stacked against it.

Perhaps one positive thing that could conceivably happen is adoption of Mick’s recommendation that “Governments should consider the establishment of truly independent review processes in such instances, and adopt iterative policy responses which can be adjusted as the science and associated models are improved.” You would want to choose carefully the cases when you commissioned a review, but there are cases when it would be a good idea.

Some scientists would probably argue that there is no need for this because their research has been through a process of “peer reviewed” before publication. However, I am of the view that peer review is not a sufficient level of scrutiny for research that is going to be used as the basis for large policy decisions. In most cases, peer review provides a very cursory level of scrutiny. For big policy decisions, it would be a good idea for key modelling results to be independently audited, replicated and evaluated.

Further reading

Keogh, M. (2012). Has modelling replaced science? Farm Institute Insights 9(3), 1-5.

Pannell, D.J. (1997). Sensitivity analysis of normative economic models: Theoretical framework and practical strategies. Agricultural Economics 16(2): 139-152. Full paper here ♦ IDEAS page for this paper

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 Economics54(4): 437-456. Journal web site here ♦ IDEAS page for this paper

192 – Transaction costs

If I buy something, I have to pay the asking price, but I may also incur a range of extra costs. These might include things like time, stress and travel costs involved in making the purchase. Economists call these extra costs ‘transaction costs’. There are also transaction costs involved in establishing, running or participating in a government program. I’ve become very interested in how transaction costs affect environmental programs.

I’m visiting China in October, so this week I applied for a visa. When I pick it up next week, it will cost me $30. However, that’s not the only cost I will have borne to get it. They have a new rule that you can’t apply by mail; you have to make a personal visit to the consulate. So far I have had to:

  • complete the application form, which was not straightforward, requiring me to make two queries to the people who are organising the visit;
  • look up the location of the Chinese consulate in Perth;
  • drive about 10 km to where I thought (mistakenly) it was, involving costs of fuel, vehicle wear and tear, and time;
  • pay for parking;
  • spend time walking around the area looking for it, unsuccessfully;
  • look at the street directory again and realise I was about a kilometre from the right place;
  • drive to the right place;
  • pay for parking again;
  • walk to the consulate;
  • wait in a slow-moving queue for about half an hour; and
  • drive home (more petrol, depreciation and time).

When I go to pick it up, I’ll need to invest more time, fuel and vehicle wear and tear. By the time I get the visa, the $30 cash cost will be pretty minor compared to the rest of the costs.

Economists call these other costs ‘transaction costs’. They are costs, using the term broadly, involved in undertaking a transaction, other than the direct financial cost of the transaction itself. They may include costs associated with thinking, analysing, negotiating, monitoring, enforcing, administering, learning, and so on.

In simple text-book economics, transaction costs aren’t accounted for, but in recent decades, economists have paid more attention to them. There have even been a couple of Nobel prizes awarded to people whose work included an emphasis on transaction costs.

I’m interested in transaction costs in environmental policy. I’ve been amazed at how big they can be. For example, under the National Action Plan for Salinity and Water Quality (Pannell and Roberts, 2010), the approximate allocation of Australian government funds to projects was as follows:

Category Budget ($ million)
On-ground works 220
Capacity building 260
R&D 44
Administration, planning, monitoring and evaluation 120

The last category is clearly solely transaction costs involved in getting the program delivered. They are large, but this number greatly understates the total transaction costs of the program. For one thing, the Australian Government took a large slice off the top for its own administration costs (to get the program established and run it), and that’s not included in the above figures. Also, the numbers in the first three categories include significant transaction costs involved in running those individual projects. As a rough guess, I estimate that the share of the Australian Government’s money in the program that was spent on transaction costs could have been about 40 per cent. That’s a lot of money not being spent on managing salinity.

Elsewhere in government, there were four reviews of the program during its life: two by the Australian National Audit Office, one by a committee of the House of Representatives and one by a Senate committee. Each of these involved substantial costs. And there were transaction costs prior to the program being established, as governments around Australia negotiated, discussed, and argued about the shape, the size and the rules of the program.

On top of that were the transaction costs borne by farmers and other organisations who were engaged with the program. They had to incur transaction costs in the course of negotiating with their partners and collaborators about involvement in projects, completing project application forms, completing reports to satisfy accountability requirements, meetings of various sorts, phone calls, and so on. Some of them would have incurred transaction costs from lobbying the government during the period when the program was being developed, or attempting to change aspects of the program once it was up and running.

These are even more invisible than the transaction costs incurred by government, and they are probably even more likely to be overlooked when a program is being designed or implemented.

For example, the first full round of competitive funding for the Caring for our Country program in Australia received about 1300 project applications, of which less than 10% were actually funded. These applications can be quite time consuming and difficult to prepare, but more than 1200 applicants must have felt like they had borne those transaction costs for no benefit. If this had been considered, I think the process would have been designed differently.

Focusing on the transaction costs in environmental programs could be beneficial for various purposes, including:

  • identifying cases where they seem excessive, guiding efforts to reduce transaction costs;
  • designing programs in a way that limits transaction costs to participants;
  • guiding better choices about policy mechanisms;
  • understanding why some policies achieve less than intended; and
  • understanding why people are unwilling to participate in programs in some cases.

Well-conducted studies of transaction costs in environmental programs should ultimately contribute to greater achievement of environmental outcomes from those programs, by encouraging greater participation and leaving more money to be spent on the problem.

David Pannell, The University of Western Australia

Further reading

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

188 – When is a carbon tax not a carbon tax?

The proposed carbon pricing policy in Australia is now routinely referred to as a carbon tax by both government and opposition. This is odd, because the proposed scheme is not actually a tax.   

It seems reasonably likely that Australia will, sooner or later, end up with an emissions trading scheme (ETS) for CO2.  An ETS works by setting a cap on emissions and requiring emitters to hold a permit for each tonne of CO2 that they emit. The level of the cap determines the number of permits available.

If emitters don’t already hold a permit, they must either cut back on their emissions or buy a permit from another emitter, who must then cut back. This means that a cost is imposed on emissions, equal to the price of buying or selling a permit. But, importantly, it’s not actually the price that causes the overall cuts in emissions. Rather, it’s the required cuts in emissions that cause the price. That is, permits have a value, because they allow you to avoid making cuts in emissions.

A carbon tax is sort of the opposite. A cost is added to all emissions, equal to the level of the tax, and this causes people to cut back their emissions. There is no cap on emissions in a tax-based system. People are free to emit as much or as little as they like, but if they do emit, they must pay the tax.

The system that the Australian Government is currently proposing to move to in the medium term is a standard ETS, not a carbon tax. But in the short term, there is a twist. The proposal is to fix the price of permits for the first few years, presumably to reduce uncertainty during the transition period after the scheme commences. It would still be an ETS, with a cap on emissions, and permits that can be traded, but the price of permits would be fixed by the Government.

Depending on how high the price is fixed during the early years of the scheme, it might be either the price or the cap that determines the level of emissions. If the fixed price of emissions is low, it would not create much incentive to reduce emissions, so the level of emissions would be determined by the cap on emissions. On the other hand, if the price is high enough, people might actually emit less than the maximum level set by the cap. In this case, the price of permits would be the main driver, not the cap, and there would be some unused permits.

You can see that there is a similarity between the fixed-price ETS approach and a carbon tax, in that it can be the price that determines output, although only when the price is set at a relatively high level. There still are important differences, however. In the Government’s proposed scheme, permits could still be traded among emitters and potential emitters, even in the period when there is a fixed price. That does not occur under a carbon-tax regime. When people pay a carbon tax, the revenue goes to the government. A fixed price ETS could be set up so that the initial revenue goes to the government (i.e. all the permits are sold by government at full price), but it could also work effectively even if some of the permits are given away (which the government is likely to do) provided that subsequent sales were only allowed at the fixed price or the cap is enforced. Revenue from subsequent transactions between emitters would go to the seller, not to the government.

As far as I can tell, from the perspective of households, the scheme will be no different in its fixed-price phase than in its later floating-price phase, other than in the level of carbon prices (which will rise over time) and the presence of price volatility. Households will not have to pay for emissions permits directly, but will do so indirectly as businesses pass on some or all of the higher costs they face. If the government had opted for a carbon tax, the result at the household level would not have been noticeably different. Higher costs would have been passed onto them through higher prices in a similar way. It would also have been possible to compensate low and middle income earners through reduced income tax or increased government payments, just as is planned under the ETS. In neither case would individuals have to put in any sort of tax return for their carbon emissions.

Despite the similarities described above, it is factually incorrect to call the proposed system a carbon tax. I can understand why the Opposition wants to call it a tax. It plays to people’s dislike of any sort of tax. But to me it seems odd that the Government has adopted the same language. Given the traction that Opposition Leader Tony Abbott got from his line about a “great big new tax on everything” during the last election campaign, you’d think that the government would avoid the “tax” word if they could. And they can. Their proposed initial approach is, in fact, not a carbon tax, but an ETS with a fixed price.

David Pannell, The University of Western Australia

p.s. 8 June 2011. I received several interesting responses to this PD.

Rob Fraser pointed out that, if the price of permits is fixed at a level below the market-clearing price, this would inhibit trade between emitters. My judgment is that, if all the permits were sold by government at the fixed price, this would not be a major problem. But if a lot of permits are given away (as is likely), they could easily end up in the hands of businesses that don’t have the highest marginal benefit from using them. In this case, the low fixed price would introduce significant inefficiencies to the market. This would not occur under a carbon tax. I don’t think this is a problem if the fixed price is above the market-clearing price.

Jerry Vanclay pointed out another likely important difference between a tax and an ETS: the transaction costs of the two systems. These are the costs of administering and participating in the market. “… one difference you didn’t canvass is the transaction costs for ETS and tax. My view is that there will be considerable costs associated with estimating and monitoring emissions and ETS trading – plus there will be volatility that [imposes] additional costs and uncertainty on industry. In contrast, a fossil carbon tax levied on those who dig up fossils, would be cheap and easy to implement – and may even save bureaucracy if it is made revenue-neutral by reducing income tax …”

David Alonso Love commented: “I agree the Federal Government is doing itself no favours by calling this a carbon tax, but I’m not sure “an ETS with a fixed price” quite cuts through. It would sound like goobledy-goo political speak to the punters.” I’m sure he’s right. Perhaps this is part of the reason for the government’s acquiescence.

p.p.s. 5 August 2011

I wrote the above prior to the government releasing details of the scheme. It turns out that trading amongst permit holders will not be possible during the fixed-price period. Permits can only be obtained from government. Emitters will have to buy permits (or be given them) in order to be permitted to make emissions. This means that the scheme is actually a bit more like a tax than it might have been during the fixed-price phase. However, it may still be like an ETS if it is the level of the cap, rather than the price, that determines the level of emissions. At this stage, it isn’t clear to me whether the price will be high enough for it really to behave like a tax.