[Because the following is long, it is also available in pdf format at http://www.nohairshirts.com/zomb.pdf ]

Even as London carbon trading desks shut down[1] in response to the crumbling European Trading System (ETS) , the zombie concept of carbon trading spreads to China. Because Robin Hahnel’s carbon trading defenses[2] offer the best pro-carbon market arguments to date, this article tackles carbon trading largely by answering Hahnel.

For those wondering “who the hell is Robin Hahnel?”, he is an underappreciated left economist. His 1999 book Panic Rules was one of the  best critical primers on globalization.  He is a long time critic of market fundamentalism, and of markets themselves. Unlike many carbon trading defenders, his support for carbon trading is based neither on market uber alles ideology  nor upon ties to the carbon trading industry. That makes his defense of carbon trading more intelligent and more aware of pitfalls.

Why does that make him worth answering? Anyone with confidence in their views on a controversial subject, such as carbon trading, should be willing to engage the best arguments the other side can muster, rather than only concentrating on easily dismissed talking points. Also, because Hahnel sincerely speaks from a left viewpoint, he is convincing to many leftists who are not well informed on climate change issues.   If implicit assumptions are included, Hahnel’s arguments are comprehensive enough that a full refutation of them is also a full refutation of carbon trading.  For all these reasons Hahnel’s arguments are well worth refuting. Please, however, don’t mistake my admiration for  Hahnel’s past work for reluctance to engage in tough debate against his current wrongheaded position.

Grist thanks its sponsors. Become one.

Common ground between supporters and many opponents of carbon trading

 Effective climate policy includes a limit on greenhouse gas (GHG) pollution, a cap. That cap should be lowered annually until net GHG pollution approaches zero.

Cap certainty and alternatives

Under cap-and-trade, polluters obtain permits for GHGs released. Yearly, fewer permits are issued until GHG pollution approaches zero. Cap-and-trade advocates often treat this as the only solution, arguing that There Is No Alternative (TINA).

Grist thanks its sponsors. Become one.

The power of cap-and-trade lies in deciding once how fast pollution must decline, then implementing that decision automatically. Automatic implementation makes the schedule of cuts politically harder to sabotage, and puts status quo bias on the side of continuing pollution reduction. Many possible automatic processes exist besides permits.

  • Cap-and-regulate: rules could restrict greenhouse gas pollution per unit of electricity, per building square foot, and set similar standards for transport, industry, agriculture, forestry, land use and waste. If those standards were tied to a cap, and scheduled to automatically increase in stringency, that automatic ratchet would let cap-and-regulate result in the same “certainty” as cap-and-trade.
  • Cap-and-invest: we could mandate worldwide public spending of trillions of dollars annually on ultra-low-pollution power and processes, such as wind generators and electric trains. Cap-and-invest could lock in continuing investments by automatic processes until targets were reached.
  • Cap-and-tax: a carbon price, rather than taking the form of permits, could be implemented by charging per unit of pollution – a carbon fee or a carbon tax. Under cap-and-fee or cap-and-tax emission prices could rise automatically until targets were reached.

The TINA argument is invalid.

Cap-and-trade & fairness

Cap-and-trade supporters, rather breathtakingly, claim carbon trading could promote international fairness between rich and poor nations. Carbon trading has displaced thousands of poor people from their homes to make way for tree plantations and other projects instituted in the name of carbon sequestration and clean energy[3].

The “fairness” argument begins with a true premise. If the people of the world are not to suffer even more horrendous consequences than are already locked in, the poor nations must develop along a path NOT based on fossil fuels at the same time the rich nations must phase out their own use of such fuels. Development without fossil fuels will come at a higher price than developing with fossil fuels, if health, global warming and other social costs are ignored.

Hahnel concludes from this that rich nations should accept stringent caps, and poor nations should accept less stringent ones. Rich nations could meet part of their caps by financing projects in poor nations that reduced poor nation emissions below agreed-upon ceilings. This, supposedly, would reduce rich nation costs and profit poor nations.

Proper targets to begin with, and agreed-upon compensation to poor nations could achieve the same goals Hahnel aims at. We have no reason to prefer a treaty that incorporates flawed targets at the start, and then relies on a carbon market to correct those flaws.

Carbon Markets and Political Feasibility I

Hahnel claims that because the largest institutions addressing climate change today are based on carbon trading, carbon trading is more politically feasible than alternatives. One answer: the world wide trading system he favors would be radically different from what we have now. A treaty that contains stringent caps for all nations and fair compensation for poor nations does not become a simple goal just because it is deformed to fit the carbon trading paradigm.

Aside from implementation difficulties, the system Hahnel advocates is problematic because international trading can only occur if some nations have less stringent national targets than are feasible. No nation can have emission reduction opportunities to sell if it has already committed to making all feasible reductions.

Already locked-in global warming ensures loss of agricultural production and coastline. We face likely huge losses of human life, and certain losses in economic output even if we implement fast emissions reductions. The goal: minimize those losses, and keep them below the point where technology is lost, and the human race loses much of its population to a great die-off whose survivors revert to feudalism or foraging. We should not seek to skip feasible reductions in the USA so that we can make them more cheaply in China. If we take the climate crisis seriously, every nation must reduce emissions as quickly and as completely as feasible.

If carbon trading does not determine distribution of caps among nations, but only compensation for poor nations, the policy arguments for international trading vanish, as do the political ones. Only if rich nations agreed to below-feasible targets for themselves could international carbon trading lead to the most stringent feasible targets for all nations. Then rich nations would need to buy permits from poor nations to adjust their targets to a reachable level. That is neither better policy nor more achievable politically than maximum feasible stringency from the start, with compensation for poor nations.

Carbon trading combines poorly with other policies

So far, this article has responded to TINA claims. This section begins to show that carbon trading is unambiguously worse than alternatives, by pointing out that carbon trading combines poorly with other policies. To the extent that carbon trading works, it works best alone.

Suppose we combine a permit system with a regulation requiring utilities provide a percentage of electricity renewably, a renewable portfolio standard (RPS). A successful RPS would reduce emissions from electricity, resulting in electricity generators buying fewer permits, driving down permit prices. Purchasers would buy the newly cheaper permits for other purposes. Cap-and-trade tries to set a ceiling above which GHG pollution cannot rise, but it can also serve as a floor. When combined with other policies, either carbon trading results in few cuts compared to what other policies would have achieved alone, or the other policies achieve little compared to unaided carbon trading. Either carbon trading proves redundant or everything else does. For example: within the European Trading System (ETS), worldwide recession resulted in lower emissions. Reduced emissions, in turn, made the ETS mostly redundant. Whereas policies like feed-in tariffs (minimum prices utilities must pay for renewable electricity) led to lower emissions even during the downturn.

Carbon price alone neither yields fastest nor least cost emissions cuts

Carbon trading’s incompatibility with other policies is dangerous because carbon price alone leads neither to the fastest nor lowest cost reductions. An example: businesses will bypass highly profitable energy investment opportunities in favor of less profitable investments that save labor[4]. Only economists will be surprised that managers sometimes step over a dollar to pick up a dime.

The strong bias towards labor saving over energy saving probably stems from the way the saving labor increases leverage over workers. Corporations collectively come out ahead by squeezing labor, even if it costs profits on a firm by firm basis.

To some extent this bias takes the form of a business culture that views energy savings as soft and fuzzy. But managers often demonstrate fully aware class consciousness. One case: Boeing managers chose to open a second assembly line in non-union South Carolina rather than in unionized Everett, WA, even though the non-union choice had a much higher overall short and medium term cost [5]. Further, the documented risk of flawed products and late delivery outweighed speculative long term savings. Both risks materialized, costing Boeing money, and further harming the reputation of an aircraft manufacturer already nicknamed “Boing”. Though not an energy example, Boeing top management consciously chose to take both a short and long term loss in order to weaken its union. Anyone who has been involved with the union movement can tell stories of companies willingly losing money to weaken unions or break strikes.

Profitable opportunities to save energy are also lost due to other market flaws[6], such as unequal access to capital[i], split incentives[ii], principle-agent conflicts[iii] and information asymmetry[iv]. Thus, in the absence of so called command-and-control regulations and public investment, a carbon price won’t achieve all feasible or profitable emission reductions.

Regulation and public investment don’t merely supplement carbon price mechanisms such as carbon fees/taxes or cap-and-trade. Historically, firms don’t build new large-scale infrastructure as risk-taking behavior in response to price changes. Large investors seek maximum profits with minimum risk. Private infrastructure investment flows along channels determined by public infrastructure.

Consider United States history. Canals, telegraphs, railroads, water systems, sewers, fuel pipelines, highways, roads, air and water ports could not have been built without grants of public land or special rights to cross private land. Such projects often required public money as well. Public investment is critical to both non-profit and for-profit large-scale infrastructure. Since solving the climate crisis will require an infrastructure transformation, large scale government spending will play a critical role.

A key implication for climate policy: because businesses and consumers miss significant opportunities to save energy at a profit, and because public infrastructure and public subsidies are critical to transformation of private infrastructure, market mechanisms alone cannot reduce emissions at maximum speed or at lowest cost. Large scale public investment in smart grids, trains, subsidizing energy savings in buildings, and efficiency and renewable requirements are more important than putting in place a cap-and-trade system or carbon tax. Anyone who takes the climate crisis seriously, even if they disagree with this ranking, will be in favor of combining public investment, rule based regulation AND some kind of carbon price. The interaction of all three types of policy will result in faster, more complete, and less expensive reductions than one or two policies alone. Of the two kinds of carbon pricing, only a carbon fee/tax works well in combination with so-called command-and-control regulations. Thus, the compatibility of a carbon fee/tax with other policies is a critical advantage for a carbon fee/carbon tax over cap-and-trade.

Carbon Markets and Political Feasibility II

Cap-and-trade as it exists, and Hahnel’s proposed reforms result in such different systems that any current political tailwind behind of cap-and-trade probably won’t carry over to the new proposals. In addition, the support cap-and-trade attracts from some powerful politicians and interest groups stems mostly from two sources: the ability to give away permits, and the ability to use offsets. Both undermine fairness, and both make carbon pricing less effective, as subsequent sections will document. Without these features, carbon trading would have no political advantage over other policy.

Why giving away permits undermines cap-and-trade effectiveness

Cap-and-trade divides the greenhouse gas pollution allowed in any one year into permits, which can be auctioned or given away to polluters. Giving away permits to large polluters is unfair, in part, because it clearly violates the “polluter pays” principle. How giveaways reduce climate policy effectiveness needs more explanation. Because permit giveaways are common in carbon trading, it is worth taking the time that explanation requires.

We can measure atmospheric concentrations very precisely through sampling, because greenhouse gases mix through the global atmosphere very quickly. One problem with any carbon price mechanism: we don’t and cannot measure single source emissions precisely or accurately. “Single source” refers to measurement of an upstream source such as a single mine or single oil field or gas field, or to a downstream source such as a single building or power plant or automobile, or a midstream source such as a single refinery.

Greenhouse gases that are many times stronger per ton than carbon dioxide leak during fossil fuel extraction and fossil fuel transport and are emitted during fossil fuel burning. Many of these secondary emissions occur during fossil fuel cycle processes where they are not easily measured or estimated. Maximum precision for measuring life-cycle single source greenhouse gas pollution with today’s best technology lies in the range of 5%[7] to 10%. Currently we don’t measure single source life-cycle greenhouse gas pollution nearly that precisely.

Now we can see why giving away permits will weaken climate policy. Assume 5% precision, the most optimistic life-cycle single-source case with the best technology. Imagine two polluters given differing amounts of free permits equal to their actual greenhouse gas pollution. Thanks to measurement error, Mr. Dirty, the larger polluter, only needs to use 95% of his permits and has 5% over left to sell. Ms. Clean pollutes less than Mr. Dirty, but is also given fewer free permits. Unfortunately for her, measurement error shows her pollution to be 5% worse than it actually is. So Ms. Clean has to buy pollution permits from Mr. Dirty. Mr. Dirty, who pollutes more, makes money. Ms. Clean, who pollutes less, spends money. What was just imprecision and inaccuracy has been transformed to qualitatively different level of error where intended incentives are reversed. (Translated into jargon: the sign of the incentive is now wrong.)

This perverse direct incentive may or may not be typical under a free permit system though such perverse direct incentives will occur at least occasionally under any system where most permits are given away for free. However, it reveals a second problem: the same process that will occasionally turn imprecision and inaccuracy into perverse incentives will frequently multiply the size of errors. 5% average inaccuracy and imprecision can easily be multiplied into a 10% to 15% measurement variance once carbon trading based upon permit giveaways starts. The effectiveness of a carbon price in motivating least cost measures, rather than simply providing a general incentive, depends on minimizing measurement imprecision and inaccuracy.

Reader support helps sustain our work. Donate today to keep our climate news free. All donations DOUBLED!

5% or 10% or even 15% errors may not seem significant when the goal is ~zero. However, the reason for an emissions phaseout is that we can’t eliminate emissions all at once. The most radical reduction proposal any government has submitted is to reduce emissions by 10% annually. Under that radical proposal, a 10% error is equal to 100% of the annual emissions target. A 5% error equals half that radical annual target. Multiplying even that small error by double or triple through permit giveaways would represent a significant weakening of the usefulness of a carbon pricing system. If, as much evidence shows, life-cycle single source measurement of local emissions cannot come close to that level of precision, then not giving away permits is even more essential. That also applies if annual reduction targets below 10% are chosen, as they are in almost all global proposals. 5% remains the optimistic (and disputed) estimate of achievable single source measurement precision with best available technology. It does not represent what we are doing today.

Carbon pricing still provides an incentive to use less carbon. But this imprecision shows that free permits greatly weaken carbon pricing effectiveness. Even without multiplication due to free permits, imprecise measurement of single source emissions implies that we should not over-rely on carbon pricing. Regardless, one great source of political advantage for cap-and-trade over a carbon fee/tax, the ability to give away free permits, is a major policy disadvantage.

Offsets as they currently exist

Offsets, a second feature that attracts some elites to carbon trading, also weaken greenhouse gas emission pricing mechanisms. The idea behind offsets: let entrepreneurs in Bangladesh (or another poor nation), which has not agreed to reduce emissions, cut greenhouse gas pollution somewhere, and document that they have done so, with verification by international regulators. The Bangladeshi entrepreneurs can then sell Certified Emission Reductions (CERs) based on that reduction to a nation, such as the United Kingdom(UK), which has capped its total emissions. UK coal power plants can buy CERs more cheaply from Bangladesh than from European Trading System (ETS), and continue to pollute at little cost. Powerful corporations in rich nations can outsource pollution reduction to the same poor nations whose deadly sweatshops produce their T-shirts.

As might be expected with outsourcing, the offset mechanism described, the Clean Development Mechanism (CDM) hurts the poor. CDM projects have driven people off their land[8], or provided revenue streams to local polluters, allowing the sources of cancer clusters to continue to remain open when they had otherwise been scheduled to close.

Although the gospel of offsetting pretends that offsets lower the cost of legitimately meeting emission-lowering targets and transfer money to the poor, the truth is they do neither. According to Carbon Retirement, less than 30% of the final sales price of a CDM offset is spent on capital and operating expenses for supposedly emission saving projects[9]. According to the same source, more than half the total price ends up the hands of various intermediaries and governments in rich nations. Most of what remains ends up in the hands of the rich in poor nations rather than those of the poor there. So the vast majority of offset revenue neither pays direct capital or operating costs of emission reducing projects nor reaches the poor.

Please note: CDM does not reduce emissions overall. An emissions reduction in one place is made up for by allowing continuing pollution in another that would otherwise be forbidden. Zeroing out climate benefits, is the source of CDM profit. CDM, at best, is supposed to be climate neutral, providing a reduction in costs for rich nations, and an infusion of capital to poor ones.

But a CDM project that sells certificates is not climate neutral if those certificates represent, entirely or partially, emission reductions that would have happened in any case. Nor is it climate neutral if pollution is increased in order to collect money for reducing it. Certificates based on such projects are partially or totally bogus.

Historically, most claimed reductions from CDM were projects that reduced high global warming potential (GWP) gases such as fluoroform, the vast majority of which are at least partially bogus[10]. This type of CDM project became such a scandal, they have been banned within the CDM system as of June 2013[11]. New projects mainly take the form of wind and hydro-electric generation. Sadly, most of these are bogus as well[12]. In nations with growing electricity demands both wind and hydroelectricity are usually profitable without CDM funding. Banks don’t like to finance projects that depend upon CDM funding. They prefer what are called “anyway projects” , projects that would happen without CDM funding. Given that CDM generates permits for projects in rich nations to pollute, “anyway projects” are bogus. The jargon term for this particular form of bogus offset is “non-additional”.

Many of the leading supporters of CDM agree that CDM as it exists is mostly non-additional[13], though they want to fix it rather than eliminate it. The World Bank calls CDM[14]: “…the worst of both worlds: high transaction cost with substantial nonadditionality. A growing consensus views determination of additionality as quixotic at the project level…”

CDM additionality tends to fail for multiple reasons. Regulators carry all the burden of determining whether a CDM offset is bogus. Neither the buyer nor seller has reason to care, so long as the offset has been approved by regulators and serves as a permit to pollute.

Even worse, measuring additionality is impossible. Every project compares what is actually happening (something that may or may not be measured correctly) to what would have happened if the project had not received CDM money. Offsets are generated by the difference between what is, and a story about what might have been. CERs, in practice, pay for storytelling. Literary prizes are wonderful, but not when awarded for creative accounting.

Hahnel’s general offset fix

As a fix to today’s broken offset system, Hahnel offers a variation on a proposal by Tom Athanasiou and Paul Baer. A treaty, says Hahnel, should ensure there is a “new sheriff in town”. Offsets should only be sold within nations that have agreed to caps, who would also regulate them. Cleverly, each offset approved by a nation ALSO lowers its cap by the amount of that offset. The nation regulating offsets is liable for each emission reduction that nation certifies. If it proves bogus, the nation that approved that offset is responsible to lower emissions in some other way. The penalty of having to make up for bogus offsets supposedly will motivate governments to mostly approve valid offsets.

However, incentives have limits. An economist with strong faith in incentives who jumped off the roof of a ninety-story building would have powerful motivation to flap his arms and fly. The likely result of the experiment, though, would be a splat as he hit the street.

Penalizing nations for bogus offset projects would face a similar limit. Knowing aggregate emissions for a nation reveals nothing about emissions saved by one offset project. Determining emissions saved at the project level remains impossible. Under Hahnel’s system, an offset still compares what actually happens to a hypothetical about what have might been. It remains a just-so story. If a nation fails to meet its target, maybe it was due to a particular project not being additional. Maybe that failure was due to some other project failing. Maybe other actions the nation took resulted in that failure and all the offset projects were great. We can guess that a target failure was due to offsets, but can we prove it?

Logical impossibility aside, determining project-based offset validity is impractical. Neither buyers nor sellers have incentives to produce valid offsets if bogus offsets can get past regulations. As with current CDM, Hahnel’s proposal puts all of the burden on regulators.

Since bogus offsets are much cheaper to produce than real ones, offset producers, offset buyers, and offset financers all have strong incentives to oppose strong, well-funded regulation. We can find many cases where government agencies are underfunded, especially when the government’s losses are private industry’s gain. The United States Internal Revenue Service (IRS) provides an example. “Thrift” is the excuse, but many dollars in revenue are lost for each dollar saved by not hiring enough IRS agents.

The idea that building national penalties into a law (in this case a treaty) will necessarily motivate national governments to do what is required to avoid those penalties has been proven false by experience. The 2008 financial crisis provides one example. Account guarantees that cumulatively totaled in the trillions of dollars did not ensure that regulators kept banks from betting the money behind such accounts on obviously foolish investments. As with the penalties in the treaty Hahnel proposes, only the public is punished for failures. Politicians and regulators don’t suffer personally. Penalties against the public don’t sufficiently motivate government officials.

As with existing offsets, project developers will take advantage of weak regulations. WikiLeaks released a cable from the 2008 United States State department consulate in Mumbai, India that says[15]:

“… Santonu Kashyap of Asia Carbon maintains that Indian projects can never fulfill the additionality requirement as no developer will risk investing in a project unless he is certain of a revenue stream independent of the CDM incentive. In a separate discussion with GAO analysts and ConGenoff, Jamshed Irani, Director of Tata Sons and the Chairman of the Tata group’s Steering Committee on Sustainability, agreed that no Indian company is brave enough to rely entirely on a CDM-driven revenue stream.”

Note that one of the biggest CDM funders is Goldman-Sachs. Under the type of treaty Hahnel favors, might not leading financial institutions successfully push for weak regulation and underfunding of regulators? Why does Hahnel expect national liability for actions by the same financial giants that caused the current international recession to achieve better results in a climate treaty? National liability does NOT provide sufficient incentive to ensure that bogus credits are not approved, even assuming bogus credits can be individually detected.

Thus the proposed treaty, at best, will require poor nations to make up for bogus projects, and cheat them out of compensation. If the treaty requirements to make up for bogus offsets with real reductions are honored then that unfairness won’t damage the climate, though that unfairness itself is strong reason to oppose offsets. As the immediately following section shows, that same unfairness makes it overwhelmingly likely that the penalties Hahnel proposes will NOT be implemented.

Project-level offsets undermine global caps.

The unfair results Hahnel’s proposal would produce are likely to undermine global caps. Nations are much more likely to violate a treaty that leads to their being repeatedly, publicly and humiliatingly cheated than to dishonor a treaty that treats them fairly. We can move beyond this common sense argument to analysis, data and studies.

The same powerful forces that will want regulations weakened will have an incentive to oppose honoring penalties in a treaty. If governments have to make up for bogus projects they might try to hold those who submitted the bogus projects responsible.

Besides, regulators don’t like to admit they approved bogus projects. Government officials will prefer to claim the failure to meet targets is itself bogus – caused by mismeasurement, or that failures are due to climate feedbacks outside their control, and thus penalties are illegitimate.

Furthermore, when a regulator approves an offset project, that regulator accepts a contingent liability. Government officials tend to assume in practice that contingent liabilities won’t materialize. When regulators approve an offset, they believe – or pretend – that the same project that increases cap stringency also lowers emissions sufficiently to fulfill the new, lower cap. They will treat approving an offset as incurring a liability and simultaneously meeting it. Offset failure will always come as a surprise, either in reality or in a Renaultian pantomime of shock.

Because offset failure always comes as a surprise, compensating for offset failure requires spending revenue that has been received and deposited. In contrast, stringent targets to begin with trade future cuts for future benefits. If a nation misses agreed upon targets, it does not receive payment. Spending revenue and not receiving revenue are mathematically equivalent, but don’t provoke equivalent institutional responses.

This is a psychological point – but a well documented one, and as much a part of social psychology as individual psychology. Not making a gain, and suffering a loss may be exactly the same thing in abstract models. But real people and real institutions have strong loss aversions. People and institutions are MUCH more reluctant to give up something they have already received than they are to forgo a gain[16]. Agreeing to a more stringent target in return for compensation, missing the target, and not receiving the compensation is one thing. Receiving offset funds, and then having to spend them to compensate for failure, is another.

As shown in the previous citation, extensive literature exists on loss aversion in individuals and institutions alike. Loss aversion in financial institutions is documentably the rule, not the exception. When a bank or other financial institution achieves what they consider industry standard returns, they tend to make comparatively cautious investment choices. But when they suffer losses, or even achieve lower gains than industry standard, they take extreme risks to “catch up” [v]. Anyone who has seen losing gamblers double down on bets will recognize the phenomenon. The national penalty for offset failure under Hahnel’s proposal offers a perfect storm of conditions for loss aversion: uncertainty, information asymmetry, principle/agent conflict, sunk costs unexpectedly shown to be bad investments, powerful lobbies, and blows to national pride.

We even have a real life case where reactions to penalties similar to the ones Hahnel proposes demonstrated loss aversion specifically in GHG emission offsets. China, whose electricity demand had increased massively and rapidly, submitted every wind and hydroelectric project in their nation for CDM credits. Understandably, the CDM board rejected most of these. China grumbled but accepted the rejection[17].

China was also one of the world’s biggest generators of fluoroform (HFC23) CDM credits. Destroying HFC23 became so profitable that factories ran 24 hours a day to maximize the amount of HFC23 created, to earn payment for incinerating it. Normal factory output became byproducts. Incinerating HFC23 turned into the main profit source. There were similar problems with other high global warming potential (GWP) gases.

The European Union (EU) determined this degree of fakery was not tolerable and decided to cancel all Certified Emission Reductions (CERs) from high GWP industrial gases. China pointed out that it had warehouses full of HFC23 waiting to be incinerated, and threatened to release these stocks into the atmosphere if existing CERs were canceled[18]. In 2011 the EU backed down. Not only would existing CERs not be canceled. New ones would be validated through June of 2013[19].

This example from China is a classic example of loss aversion. China accepted rejection of hydro and wind CDM credits, because they had not already received approval for those CERs. But cancellation of existing certificates was another matter. They were ready to make extreme threats and take extreme measures to prevent this from happening. The problem these penalties remedied was the same Hahnel intends to solve: bogus offsets. The penalty was similar. In the CDM case, the canceled certificates would have become valueless. Under Hahnel’s proposal, the certificates would have retained their value, but China would have been required to replace the emission cuts the certificates represented. That replacement would have cost China all the revenue those certificates generated, probably more. Thus, not only does extensive peer reviewed literature show loss aversion in both individuals and institutions. Not only does Hahnel’s proposal replicate every condition that leads to institutional loss aversion within the peer reviewed literature. We have a real life case involving the same problem Hahnel attempts to remedy with his offset fix, non-additionality, and an extremely similar penalty. In this real life case we see strong pushback against canceling offset certificates that we do not see for refusing to grant those same certificates to begin with.

Thus, Hahnel’s proposed fix neither prevents offsets from harming the poor nor from weakening climate treaties.

Political Feasibility III

So far we have seen that carbon trading is less effective than other policies, and that any political advantage it enjoys over other policies is mostly based on features that contribute to that ineffectiveness. One added carbon trading flaw: it can weaken the political coalitions needed to win a strong climate treaty. Hahnel inadvertently hints at this weakness when he favors nationalization of large parts of the financial industry, or tougher regulation of that same industry, to ensure that bankers don’t undermine his proposed climate treaty.

The climate crisis is not going to be tackled with anything approaching the rigor required in the context of growing inequality, with elites gaining more power, with increasing corporate rule. We won’t win strong climate reform in the absence of other changes. Opponents of strong climate action[vi] control businesses possessing a majority of global business net worth, and enjoying a majority of global business profits. Overcoming that opposition will require grassroots power, not just sweet reason.

It is unlikely that a such a change will happen centered around the climate crisis. We will win reforms that help tackle the climate crisis only as part of a coalition that reverses today’s international rightward drift on a variety of issues. It is hard to imagine victory for a movement that only opposes the corporations on climate issues, that fails to tackle other issues including joblessness, wage stagnation and austerity. Hahnel is right to seek climate justice. It is difficult imagine gaining support for climate justice outside of a movement pushing for plain old justice. What reform proposal contributes to building such a coalition? Will putting a price on carbon via cap-and-trade or even carbon taxes bring supporters into the street? Isn’t it likely that large scale job-creating public investment might be more important in that kind coalition building? This is not to say that we can’t support something along the lines of a carbon fee with funds rebated equally to those living in the area where the tax is collected. But the need for coalition does suggest that political feasibility depends largely on the compatibility of proposals with the rest of a popular program advancing the interests of the 99% over the interests of 1%. Building leverage to get to the point where progressive demands in general can be advanced is critical. Climate demands within such a movement should center upon advocacy for public investment and rule based regulation, with a carbon price a supplementary policy. Fortunately, the most politically feasible approach is also better policy than Hahnel’s proposal.

Net emissions and cap stringency

 Hahnel says[20]:

“Cap net emissions. Net emissions are what matters with regard to climate change, and surprisingly, as already explained, measuring national annual net emissions is as straightforward as measuring only national annual emissions. Capping net emissions rather than capping only emissions would solve an important problem arising from projects selling offsets for sequestration increases. Under Kyoto if a project increases carbon sequestration it can receive CERs. So creating a tree plantation can qualify for CERs because it is easy to demonstrate that new trees planted are sequestering carbon… But… Kyoto does not give credit for carbon stored and sequestered by existing forests that are conserved because it is difficult to know whether or not the forest would have been preserved in any case. This creates a perverse incentive to replace existing forests with tree plantations.”

Why deal with this rather obscure proposal? Hahnel points out a real problem, but suggests a poorly thought-out solution. And the flaws in that proposal also illuminate the flaws in Reducing Emissions from Deforestation and Forest Degradation (REDD) and other forestry offset programs.

Before tackling fundamental flaws, let’s examine one political consequence of negotiating on the basis of net, not gross, emissions. Currently negotiations frame targets as percent reductions of gross emissions from a specified year. For example, the Obama administration’s publicly stated goal is an (absurdly lax) 17% reduction by the United States from 2005 emissions. The following table shows the difference in this goal on a net and gross emissions basis.

 

Year

2005

2011

Obama Emissions Goal

(-17% from 2005)

Emissions Drop from 2005

Emissions Drop from 2011

Gross Emissions(millions of metric tons)

7,195

6,702

5,972

1,223

730

Net Emissions (millions of metric tons)

6,197

5,797

5,114

1,054

653

Data on gross and net emissions from Environmental Protection Agency 2013 Inventory of Greenhouse Gas Emissions and Sinks: 1990-2011:Table ES2,p7. Washington DC: The Environmental Protection Agency. http://www.epa.gov/climatechange/Downloads/ghgemissions/US-GHG-Inventory-2013-Main-Text.pdf

As the table above shows, a 17% drop in United States emissions from 2005 on a gross basis would reduce emissions by 1,223 million metric tons. On a net basis, the same 17% percentage drop would only require a 1,054 million metric ton reduction. The same percentage target results in a less stringent reduction for the United States on a net rather than gross basis. Alternatively, to achieve a given million ton reduction, the nominal percentage target for the United States would have to be more stringent on a net rather than gross basis. Nor does this apply only to the United States. Among the rich nations, only five have net emissions rather than net sequestration from land use changes and forestry (LUCF)[21].

Won’t a new measurement standard requiring steeper percentage cuts to achieve a given target make negotiations even more difficult than they already are? Even if Hahnel thinks this added hurdle is a price worth paying, he should mention this consequence, and suggest some means of adjustment. In the many articles Hahnel published advocating “reformed” carbon trading, he never suggested compensating for the side effects of measuring emissions by his favored method. It is almost as though Hahnel proposed a radical change in the measurement of national emissions without thinking through the consequences of his proposal.

More importantly, we cannot meaningfully measure sequestration from forests and other plant canopy within a single year. With or without human intervention, such systems will hold different amounts of carbon[22] from season to season, from year to year, sometimes from day to day. Thus what is important about sequestration is the long term trend. At best, this trend can be calculated from snapshots taken over the course of three or four years, probably much longer. The dynamic nature of ecosystems results in imprecise, uncertain numbers. This imprecision stems primarily from fitting equations to noisy data determined by multiple factors, when the relative importance of those multiple factors to each another varies over time.

Even more importantly: the same dynamic nature of biological systems that means that sequestration can only be measured roughly and over a long period of time also means that the permanence of biological sequestration is highly uncertain. If we close a coal mine, the coal will probably stay in the ground as long as we don’t reopen it[vii]. Emission reductions from leaving fossil fuel in the ground are mostly permanent, if we make the right future choices. However, a significant portion of carbon sequestration in forests and grasslands and so forth is NOT mostly permanent, even if we make the best possible choices. Fires, storms, pests and diseases can all release sequestered carbon. Some of these releases will be due to past bad choices. Some would have happened regardless of past human intervention. Only a portion of biological carbon release in any year is under human control during that year.

An additional problem: long term net sequestration can still mask bad land use policy and lead to its opposite. For example, current long term United States Land Use Change and Forestry (LUCF) sequestrates more carbon than any other nation, though United States fossil fuel emissions greatly exceed that carbon removal. However, the United States Department of Agriculture predicts that current United States policy will eventually lead to United States LUCF becoming a net emitter of carbon[23]. If we continue business as usual, by the time this transformation happens, bad land use policy will make the transformation of our forests from carbon sink to carbon source difficult or impossible to reverse. Sequestration or emission of carbon from LUCF are almost always the result of decades of previous actions. Rewarding or punishing today’s results alone, without measuring changes whose results may take decades to show up will just be another form of perverse incentive.

Thus , a climate treaty should NOT be based on a single annual net emissions target for each nation. Emissions can be measured annually with a fair degree of reliability. Sequestration can only be measured meaningfully over the course of many years, and even then the numbers are much rougher than the numbers for emissions. Avoided emissions are mostly permanent in a way that sequestration is not, which makes even long term sequestration numbers of questionable value. In addition, actions that have very tiny effects on immediate emissions or sequestration from LUCF will have serious long term effects. To encourage sequestration, we can’t rely only on measuring effects; we need to measure causes as well. Thus, it makes no sense to combine into a single number processes that need to be measured over varying time scales, with varying degrees of precisions, with varying certainty of permanence, and with differing long term dependencies. Overall ecosystem health is almost certainly more important than sequestration numbers, even if carbon sequestration is your primary concern. Healthy ecosystems will sequester more carbon in the long run than unhealthy ones. If various feedbacks transform plant canopy and soils from sinks into sources, a possibility many climate scientists worry about, healthy ecosystems will have a better chance of surviving such transformation, and in the case of such a catastrophe will be smaller sources than unhealthy ones. The bottom line: combining gross emissions and net sequestration into a single number is a serious error. It is an error for all the reasons mentioned, and because shutting down coal plants should not be an excuse for clear cutting forests, nor should preserving forests be an excuse for continuing to run coal plants.

This error also has political implications. A single net number will reduce cap stringency for most rich nation and many poor ones. Alternatively it will require nominally more stringent targets in order to achieve the same effective caps.

Hahnel did identify a real and serious problem with the structure of today’s negotiations. But the solution is NOT to calculate a single number with more rigor. The solution is a new focus on separate categories of gross emission reduction and ecosystem health and resilience preservation and restoration. Long term national sequestration trends is also worth incentivizing for its own sake, and as one indicator among many of ecosystem health.

Conclusion

Carbon trading has strong disadvantages over other policies, including incompatibility with non-market measures that are as or more critical than emissions pricing in confronting the climate crisis. In addition, the greater political support for carbon trading by those elites willing to tackle climate change stems from the ability to give away free permits, and the ability to incorporate offsets. Free permits and offsets both undercut the fairness and effectiveness of climate policies. Hahnel’s attempt at a radical offset fix fails to solve either offset problem. Hahnel also ignores the political reality that the size and speed of the cuts needed won’t come from an environmental movement standing alone, but only one acting in coalition with other forces. Massive public investment which will produce large numbers of jobs is much more critical to such a coalition than any form of carbon pricing.

Hahnel’s proposal to reverse perverse incentives when it comes to wilderness preservation by measuring net, instead of gross, emissions ignores both political reality and climate science. Politically, measurement on a net emission basis would either let most rich nations, and many poor ones, off the hook by requiring less stringent reductions for a given percentage target, or require nominally more severe percentage targets to produce a given real reduction. Scientifically, emissions and biological sequestration are not directly comparable. Biological sequestration of carbon can’t be measured as precisely as emissions, nor can it be measured on as short a time scale. Because of the dynamic nature of plant canopy and soil carbon, and their vulnerability to storms, pests, fires and other disasters, biological removal of carbon is also not as permanent as avoided emissions. Ecosystem health and resilience preservation and restoration are probably more critical than sequestration measurement, but long term sequestration is still worth measuring and incentivizing, both for its own sake, and as one among many indicators of ecosystem health.

Carbon trading and basing climate targets on net emissions look attractive at a high level of abstraction. Both fail once finer grained analysis is used, and proposals are tested against evidence and messy details.

End Notes

Reference List

Abadie, Ramon Luis Maria and Arigoni Ortiz and Ibon Galarraga. 2012. The Determinants of Energy Efficiency Investments in the U.S. Energy Policy 45(Jun):551-56.

Abdellaoui, Mohammed, Bleichrodt, Han, Kammoun, Hilda. 2013. Do financial professionals behave according to prospect theory? An experimental study. Theory & Decision 74(3): 411-429.

Alam, Nafis, Tang, Kin Boon. 2012. Risk-taking behaviour of Islamic banks: application of prospect theory. Qualitative Research in Financial Markets 4(2/3): 156 – 64

Alexeew, J., Bergset, L., Meyer, K., Petersen, J., Schneider,L. And Unger, C. 2010. An analysis of the relationship between the additionality of CDM projects and their contribution to sustainable development. International Environmental Agreements 10(3):233-248.

Anderson, Soren T. and Richard G. Newell. 2004. Information programs for technology adoption: the case of energy-efficiency audits. Resource and Energy Economics 26(1):27-50.

Bone, J., Hey, J., Suckling, J. (1999). Are Groups More (or Less) Consistent than Individuals? Journal of Risk and Uncertainty 18(1):63-81.

Cames, M., Anger, N., Böhringer, C., Harthan, R. and Schneider, L. 2007. Long-term prospects of CDM and JI. Dessau, Germany: The Federal Ministry Of the Environment, Nature Conservation and Nuclear Safety. http://www.umweltdaten.de/publikationen/fpdf-l/3294.pdf..

Carbon Retirement. 2009. The Efficiency of Carbon Offsetting Through the CDM. London: Carbon Retirement. http://www.carbonretirement.com/sites/default/files/The%20efficiency%20of%20offsetting%20with%20CDM%20credits.pdf.. Accessed 16/Feb/2012.

Chih, Hsiang-Lin, Shen, Chung-Hua. 2005. Investor protection, prospect theory, and earnings management: An international comparison of the banking industry. Journal of Banking & Finance 29(10): 2675-697.

Chomitz, K., Akhmetova,D., Hutton, S., Demberel,U., Pinglo, M.E., Shaliz, Z., Gray, C., Taylor-Dormond, M.,Wallich, C., Tenev, S., Thomas, V., Chikkatur, A, Kelly, L., Salvemini, D., Liebenthal, A., Ligot, J., Mason, C., Meisner, C., Nelson, A., Ozen, A., Rossi, F., Schenck, R., Schneider, R., Shalizi, Z., Fall, C.M.,Wolf, J., Fan Zhang and Fuqiu Zhou. 2010. Phase II: The Challenge of Low-Carbon Development—Climate Change and the World Bank Group.. Washington, DC: The World Bank. http://siteresources.worldbank.org/EXTCCPHASEII/Resources/cc2_full_eval.pdf

Cooremans, Catherine. 2012. Investment in energy efficiency: do the characteristics of investments matter? Energy Efficiency 5(4): 497-518.

Ekblad, A. and P. Högberg. 2001. Natural abundance of 13C in CO2 respired from forest soils reveals speed of link between tree photosynthesis and root respiration. Oecologia 127(3): 304-8. DOI 10.1007/s004420100667.

Environmental Protection Agency. 2013. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-1911. Washington DC: The Environmental Protection Agency. http://www.epa.gov/climatechange/Downloads/ghgemissions/US-GHG-Inventory-2013-Main-Text.pdf

European Commission. 2011. Europa Press Release: Emissions Trading: Commission welcomes vote to ban certain industrial gas credits. Brussels:European Union. http://europa.eu/rapid/press-release_IP-11-56_en.htm.. Accessed 16/Feb/2013.

Fielding, R. 2010. Chinese renewable firms vent anger at UN over CDM rejections. Business Green 6-Aug. http://www.businessgreen.com/bg/news/1804572/chinese-renewable-firms-vent-anger-un-cdm-rejections.. Accessed 16/Jan/2012.

Fiegenbaum, Avi.1990. Prospect theory and the risk-return association: An empirical examination in 85 industries. Journal of Economic Behavior & Organization 14(2): 187-203.

Gill, D. Prowse V. 2012. A structural analysis of disappointment aversion in a real effort competition. American Economic Review 102 (1): 469–503.

Gurevich, G., Kliger, D.,Levy, O. 2009. Decision-making under uncertainty: A field study of cumulative prospect theory. Journal of Banking and Finance 33(7) 1221–229.

Hahnel, R. 2012a. Left Clouds Over Climate Change Policy. Review of Radical Political Economics 44(2): 141-159.

Hahnel, R. 2012b. Desperately Seeking Left Unity on Climate Change Policy. Capitalism, Nature, Socialism (23, 4).

Hahnel, R. 2013a. An Open Letter to the Climate Justice Movement. New Politics:4-Nov. http://newpol.org/content/open-letter-climate-justice-movement

Hahnel, R. 2013b. Guessing at Failure: On Climate Change, Nuclear Disaster, and Geoengineering. Portland, ME: Common Dreams. http://www.commondreams.org/view/2013/11/19

Hansen, Matthew C.,Stehman, Stephen V., Potapov, Peter V. 2010. Quantification of global gross forest cover loss. Proceedings of the National Academy of Sciences of the United States of America 107(19): 8650-55.

Högberg, Mona N.; Maria J. I. Briones, Sonja G. Keel, Daniel B. Metcalfe, Catherine Campbell, Andrew J. Midwood, Barry Thornton, Vaughan Hurry, Sune Linder, Torgny Näsholm, Peter Högberg. 2010. uantification of effects of season and nitrogen supply on tree below-ground carbon transfer to ectomycorrhizal fungi and other soil organisms in a boreal pine forest. New Phytologist 187(2): 485-93. DOI: 10.1111/j.1469-8137.2010.03274.x.

International Association of Machinists and Aerospace Workers. 2011. Boeing’s High Stakes Strategy to Flee Collective Bargaining with the IAM. IAM. http://www.iam751.org/nlrb/Gemini.pdf

Jackson, Jerry. 2010. Promoting energy efficiency investments with risk management decision tools. Energy Policy 38(8):3865-73.

Johnson, H.J. 1994. Prospect Theory in the Commercial Banking Industry. Journal Of Financial And Strategic Decisions 7(1):73-89.

Kahneman, D.,Tversky, A. 1984. Choices, Values, and Frames. American Psychologist 39(4):341–350.

Kliger, D., Levy, O. 2009. Theories of choice under risk: Insights from financial markets. Journal of Economic Behavior & Organization 71(2): 330–46.

Kühberger, A. 1998. The Influence of Framing on Risky Decisions: A Meta-Analysis. Organizational Behavior and Human Decision Processes, 75(1):23-55.

Lipow, Gar. 2012. Solving the Climate Crisis through Social Change: Public Investment in Social Prosperity to Cool a Fevered Planet. Santa Barbara: Praeger Press.

Miller, Scott; Steven C. Wofsy, Anna M. Michalak, Eric A. Kort, Arlyn E. Andrews, Sebastien C. Biraud, Edward J. Dlugokencky, Janusz Eluszkiewicz, Marc L. Fischer, Greet Janssens-Maenhout, Ben R. Miller, John B. Miller, Stephen A. Montzka, Thomas Nehrkorn, and Colm Sweeney. 2013. Anthropogenic emissions of methane in the United States. Proceedings of the National Academy of Sciences of the United States of America 25-Nov. doi: 10.1073/pnas.1314392110

Muthulingam, Surash, Charles J Corbett, Shlomo Benartzi, Bohdan Oppenheim 2009. Managerial Biases and Energy Savings: An Empirical Analysis of the Adoption of Process Improvement Recommendations. Los Angeles: Anderson School of Management – University of California Los Angeles.

Pearce, F. 2010. Carbon Trading Tempts Firms to Make Greenhouse Gas. New Scientist Dec-16. http://www.newscientist.com/article/dn19878-carbon-trading-tempts-firms-to-make-greenhouse-gas.html.. Accessed 16/Jan/2013.

Quick, Jeffery C. 2013. Carbon Dioxide Emission Tallies for 210 U.S. Coal-fired Power Plants: A Comparison of Two Accounting Methods. Journal of the Air & Waste Management Association 29-Aug. http://dx.doi.org/10.1080/10962247.2013.833146

Reklev, Stian and Michael Szabo. 2013. U.N. talks on new carbon markets break down. Reuters: Nov-17. http://www.reuters.com/article/2013/11/17/us-carbon-talks-markets-idUSBRE9AG0ER20131117

Roht-Arriaza, N. 2010. “First, Do No Harm”: Human Rights and Efforts to Combat Climate Change. Georgia Journal of International & Comparative Law: Symposium: International Human Rights and Climate Change 38(3): 593-610.

Ruthner, L., Johnson, M., Chatterjee,B., Lazarus, M., Fujiwara, N., Egenhofer, C., Monceau T. du. and Brohe, A. 2011. Study on the Integrity of the Clean Development Mechanism (CDM). Brussels: European Commission, DG Clima. http://ec.europa.eu/clima/policies/ets/linking/docs/final_report_en.pdf

Saleska, Scott R.; Scott D. Miller, Daniel M. Matross, Michael L. Goulden, Steven C. Wofsy, Humberto R. da Rocha, Plinio B. de Camargo, Patrick Crill, Bruce C. Daube, Helber C. de Freitas, Lucy Hutyra, Michael Keller, Volker Kirchhoff, Mary Menton, J. William Munger, Elizabeth Hammond Pyle, Amy H. Rice, Hudson Silva. 2003. Carbon in Amazon Forests: Unexpected Seasonal Fluxes and Disturbance-Induced Losses. Science 302(5650): 1554-7. DOI:10.1126/science.1091165.

Schneider, L. 2011. Perverse incentives under the CDM: an evaluation of HFC-23 destruction projects. Climate Policy 11(2): 851-864.

Straw,Will and Reg Platt and Esther Cowdrey and Jimmy Aldridge. 2013. Up in smoke: How the EU’s faltering climate policy is undermining the City of London. London: Institute for Public Policy Research. http://m.ippr.org/images/media/files/publication/2013/11/up-in-smoke_Nov2013_11509.pdf

Stocker, Thomas and Qin Dahe and Gian-Kasper Plattner. 2013. Climate Change 2013: The Physical Science Basis:Technical Summary. Intergovernmental Panel on Climate Change. http://www.climatechange2013.org/images/uploads/WGIAR5_WGI-12Doc2b_FinalDraft_All.pdf

Szabo, Michael, Twidale, Susanna. 2013. Zombie CO2 projects on the rise as CDM hits 7,000. Point Carbon. http://www.pointcarbon.com/news/1.2453540?date=20130709&sdtc=1. Accessed July 12, 2013.

UNEP. 2013. UNEP Risoe CDM/JI Pipeline Analysis and Database: CDM Project Types. United Nations Environment Programme RIS0 Centre. http://www.cdmpipeline.org/cdm-projects-type.htm.. (Accessed Jan-13-2013).

United States Consulate – Mumbai. 2008. CARBON CREDITS SUFFICIENT BUT NOT NECESSARY FOR SUSTAINING CLEAN ENERGY PROJECTS OF MAJOR INDIAN BUSINESS GROUPS.. Mumbai, India: United States Consulate. http://wikileaks.org/cable/2008/07/08MUMBAI340.html.

United States Department of Agriculture, Forest Service. 2012. Future of America’s Forest and Rangelands: Forest Service 2010 Resources Planning Act Assessment. DC:USDA.

Valentini1, R.; G. Matteucci1, A. J. Dolman, E.-D. Schulze,4, C. Rebmann, E. J. Moors, A. Granier, P. Gross, N. O. Jensen, K. Pilegaard, A. Lindroth, A. Grelle, C. Bernhofer, T. Grünwald, M. Aubinet, R. Ceulemans, A. S. Kowalski, T. Vesala, Ü. Rannik, P. Berbigier, D. Loustau, J. Guethmundsson, H. Thorgeirsson, A. Ibrom16, K. Morgenstern, R. Clement, J. Moncrieff, L. Montagnani, S. Minerbi & P. G. Jarvis. 2000. Respiration as the main determinant of carbon balance in European forests. Letters to Nature. Nature 404: 861-865. doi:10.1038/35009084.

Wara, Michael. 2006. Measuring the Clean Development Mechanism’s Performance and Potential PESD Working Paper #56. http://iis-db.stanford.edu/pubs/21211/Wara_CDM.pdf

Wara, Michael., and David Victor. 2008. A realistic policy on international carbon offsets. PESD Working Paper #74. http://iis-db.stanford.edu/pubs/22157/WP74_final_final.pdf

Whyte, G. 1993. Escalating Commitment in Individual and Group Decision Making: A Prospect Theory Approach. Organizational Behavior and Human Decision Processes 4(3):430-55.

World Bank. 2013. World Development Indicators: GHG net emissions/removals by LUCF(Mt of CO2 equivalent). World Databank. Washington, DC: The World Bank. http://databank.worldbank.org/data/views/reports/tableview.aspx. Accessed July10 2013.

Zhang, Li; Bruce K. Wylie, Lei Ji, Tagir G. Gilmanov, Larry L. Tieszen, Daniel M. Howard. 2011. Upscaling carbon fluxes over the Great Plains grasslands: Sinks and sources. Journal of Geophysical Research: Biogeosciences 116(G3). DOI: 10.1029/2010JG001504.

[i] Example: utilities can afford to spend more to generate a unit of electricity than homeowners or small businesses can spend to save that same electricity unit.

[ii] Example: tenants seldom insulate rented units; they might move before recovering costs. Landlords seldom invest in insulation that benefits tenants, but not themselves.

[iii] Example: a contractor who installs a less expensive and less efficient furnace in a new custom home probably costs the home buyer money. The contractor chooses lowering the bid over offering the best deal.

[iv] Example: the contractor from footnote iii whose construction bid includes a cheap furnace does not offer the option of a higher cost, more efficient furnace that can provide long-term savings, for fear of confusing the buyer and losing the sale.

[v] This may be, in part, a case of principle/agent conflict. If decision-makers’ performance in institutions are below standard, taking risks to catch up can make sense. Success saves their jobs. Failure probably leaves them no more fired than they were going to be in any case. The added risk may be a poor decision for the institution, but not necessarily for the decision maker.

[vi] Not just deniers, but businesses that support token or symbolic remedies, while opposing effective action against climate change.

[vii] One serious exception: coal fires within closed mines can burn for decades. Fortunately mine fires that last this long are rare compared to the number of mines.

[1] Straw,Will and Reg Platt and Esther Cowdrey and Jimmy Aldridge. 2013. Up in smoke: How the EU’s faltering climate policy is undermining the City of London. London: Institute for Public Policy Research. http://m.ippr.org/images/media/files/publication/2013/11/up-in-smoke_Nov2013_11509.pdf

[2] Hahnel, R. 2012a. Left Clouds Over Climate Change Policy. Review of Radical Political Economics 44(2): 141-159.

Hahnel, R. 2012b. Desperately Seeking Left Unity on Climate Change Policy. Capitalism, Nature, Socialism (23, 4).

Hahnel, R. 2013a. An Open Letter to the Climate Justice Movement. New Politics:4-Nov. http://newpol.org/content/open-letter-climate-justice-movement

[3] Roht-Arriaza, N. 2010. “First, Do No Harm”: Human Rights and Efforts to Combat Climate Change. Georgia Journal of International & Comparative Law: Symposium: International Human Rights and Climate Change 38(3): 593-610.

[4] According to the sources cited above, it is not that managerial decision making always or even usually explicitly sets out to tip the scales. But energy savings is not taken seriously; heuristics are used in evaluating energy saving investments that are not used for evaluating labor. Simple payback and size of investment overwhelmingly determines whether an energy saving investment is made, usually without even considering net present value(NPV) or internal rate of return(IRR), which are almost always used in evaluating labor saving investments. Even when NPV and IRR are considered for energy investments, they are seldom risk adjusted, unlike labor cost reductions. Thus, in practice, firms demand many times the rate of return for energy saving investments they demand for investments that reduce labor cost, especially if risk-adjusted rate of return is considered.

Jackson, Jerry. 2010. Promoting energy efficiency investments with risk management decision tools. Energy Policy 38(8):3865-73.

Cooremans, Catherine. 2012. Investment in energy efficiency: do the characteristics of investments matter? Energy Efficiency 5(4): 497-518.

Abadie, Ramon Luis Maria and Arigoni Ortiz and Ibon Galarraga. 2012. The Determinants of Energy Efficiency Investments in the U.S. Energy Policy 45(Jun):551-56.

Anderson, Soren T. and Richard G. Newell. 2004. Information programs for technology adoption: the case of energy-efficiency audits. Resource and Energy Economics 26(1):27-50

Managers take energy efficiency so lightly that when they choose to invest in energy savings, order of presentation significantly affects which efficiency projects they choose

Muthulingam, Surash, Charles J Corbett, Shlomo Benartzi, Bohdan Oppenheim 2009. Managerial Biases and Energy Savings: An Empirical Analysis of the Adoption of Process Improvement Recommendations. Los Angeles: Anderson School of Management – University of California Los Angeles.

[5] International Association of Machinists and Aerospace Workers. 2011. Boeing’s High Stakes Strategy to Flee Collective Bargaining with the IAM. IAM. http://www.iam751.org/nlrb/Gemini.pdf

[6] Lipow, Gar. 2012. Solving the Climate Crisis through Social Change: Public Investment in Social Prosperity to Cool a Fevered Planet:11-30. Santa Barbara: Praeger Press.

[7] The most optimistic estimate of how precisely we could measure single source tailpipe CO2 emissions from United States coal electricity plants is Jeffrey Quick’s calculation of ±.65% to ±3.6%. (Estimates for all plants combined would be much more precise, but errors from multiple plants canceling out does us no good when a carbon price is levied at a plant by plant or a mine by mine basis.) Quick also notes that by measuring the carbon content of the coal delivered to power plants we could further improve the precision of the CO2 tailpipe emissions measurement from coal generated electricity by 50%”

Please note: this estimate is only for CO2 from coal generated electricity, and does not include other gases, and also is only for tailpipe emissions at the plant itself, and does not include lifecycle emissions from extracting, processing and transporting coal. (It is also worth remembering that in practice we have to focus on the high end of that error range, because we can’t know in any one year which measurements are at the high and low end of that error range. If a carbon pricing mechanism is to be effective at all, it must be effective on the assumption that the error for every lifecycle single source measure is at the high end, in this case ±3.6%. This parenthetical note is my own observation, and does not reflect anything in the Quick paper cited below.)

Quick, Jeffery C. 2013. Carbon Dioxide Emission Tallies for 210 U.S. Coal-fired Power Plants: A Comparison of Two Accounting Methods. Journal of the Air & Waste Management Association 29-Aug. http://dx.doi.org/10.1080/10962247.2013.833146

So what is the difference between precision for lifecycle and tailpipe emissions? Sticking with coal for the moment, coal mining is often associated with methane releases. Methane is 28 to 34 times as powerful a global warming gas per ton as carbon dioxide, depending on whether feedback effects are considered.

Stocker, Thomas and Qin Dahe and Gian-Kasper Plattner. 2013. Climate Change 2013: The Physical Science Basis:Technical Summary: Page 8-58. Intergovernmental Panel on Climate Change. http://www.climatechange2013.org/images/uploads/WGIAR5_WGI-12Doc2b_FinalDraft_All.pdf

Methane represents about 9% of total United States greenhouse gas emissions, and that is using an older, lower calculation for methane global warming potential. A recent National Academy of Sciences study shows aggregate United States EPA national estimates for methane emissions, based on bottom up reports, are 50% too low, again not taking into consideration the recalculation of methane’s power as a greenhouse gas. (I would note that if aggregate error is 50%, than single source error almost certainly is worse, since multiple errors usually cancel each other out to some extent during the aggregation process. Again, this parenthetical note is my observation and not to be attributed to Miller et. al cited immediately below.)

Miller, Scott; Steven C. Wofsy, Anna M. Michalak, Eric A. Kort, Arlyn E. Andrews, Sebastien C. Biraud, Edward J. Dlugokencky, Janusz Eluszkiewicz, Marc L. Fischer, Greet Janssens-Maenhout, Ben R. Miller, John B. Miller, Stephen A. Montzka, Thomas Nehrkorn, and Colm Sweeney. 2013. Anthropogenic emissions of methane in the United States. Proceedings of the National Academy of Sciences of the United States of America 25-Nov. doi: 10.1073/pnas.1314392110

Thus, methane underestimates alone would represent a 4.5% downward bias for all fossil fuel. Combined with  1.8% imprecision in tailpipe estimates (if we doubled current precision thought the means that Quick suggests), that gives U.S. fossil fuel emission estimates a best case imprecision of around 6.3%. Also, there is no reason to assume that we allocate the 4.5% of methane emissions that are measured correctly. That misallocation would imply that total imprecision for fossil fuel, even measuring carbon content of fuels as Quick suggests, would represent errors greater than 10%

In fairness to coal emissions measurement, greater methane leakage is associated with oil and gas than with coal in the USA. However, the most common means of transporting coal in the United States is by uncovered rail car. Uncovered rail cars carrying coal release significant amounts of coal dust. A large component of coal dust is black carbon. Black carbon is 700 times as powerful a contributor to global warming per ton as CO2.

Significant black carbon is associated with oil to a much greater degree. About 27% of fuel derived from oil is heavy distillates, such as diesel, kerosene, jet fuel, bunker fuel, and heating oil. Heavy distillates produce black carbon when burned. How much black carbon is produced depends in part on how cleanly the fuel is burned. Also, black carbon released at high altitudes has much higher impact than black carbon released on the ground level. So black carbon in the form of jet fuel burned in airplanes at high altitudes has much greater global warming impact per ton than the 700 times CO2 impact of heavy distillates burned for heating and in other transport.

Burning coal also emits black carbon, though in rich nations such as the United States, pollution control measures ensure that coal burning is not a significant black carbon source compared to oil.

Although we can greatly improve the measurement of overall methane and black carbon emissions, assigning those emissions to particular mines, oil or gas fields, or particular power plants or buildings or vehicles will not be easy. There are other greenhouse gases associated with fossil fuel burning as well. Thus it is unlikely that we can calculate lifecycle single source fossil-fuel emissions with a precision greater than 5%, and it seems probable that we can’t even reach that precision. Coal, ironically given that it produces more emissions per ton than other fossil fuels, may be the emission source we can measure most precisely.

Non fossil fuel sources such as high global warming potential (GWP) industrial gases, deforestation, and landfill methane are even harder to measure precisely on a granular level, especially since the latter are non-point sources.

[8] Roht-Arriaza, N. 2010. “First, Do No Harm”: Human Rights and Efforts to Combat Climate Change. Georgia Journal of International & Comparative Law: Symposium: International Human Rights and Climate Change 38(3): 593-610.

[9] Carbon Retirement. 2009. The Efficiency of Carbon Offsetting Through the CDM. London: Carbon Retirement. http://www.carbonretirement.com/sites/default/files/The%20efficiency%20of%20offsetting%20with%20CDM%20credits.pdf.. Accessed 16/Feb/2012

[10] Schneider, L. 2011. Perverse incentives under the CDM: an evaluation of HFC-23 destruction projects. Climate Policy 11(2): 851-864.

Wara, Michael. 2006. Measuring the Clean Development Mechanism’s Performance and Potential PESD Working Paper #56. http://iis-db.stanford.edu/pubs/21211/Wara_CDM.pdf

Wara, Michael., and David Victor. 2008. A realistic policy on international carbon offsets. PESD Working Paper #74. http://iis-db.stanford.edu/pubs/22157/WP74_final_final.pdf

Hahnel criticizes opponents of CDM for citing the work of Michael Wara to show non-additionality.(Hahnel, 2012a, 148). Hahnel’s point is that Wara’s main concern was overpricing of credits rather than non-additionality. However even though additionality was never Wara’s main concern, it was a concern. In the first of the papers Hahnel cites Wara says “The CDM provides perverse economic incentives to HCFC-22 producers that have led to a large fraction of the CER supply being produced by HFC-23 abatement. Even if some fraction of these reductions are “real and additional,” (emphasis mine) they still may not be the best use of Annex I party resources for addressing non-Annex I GHG emissions. “ (Wara, 2006, 31). Note the use of terms “fraction” and “even if”. Clearly Wara conveys in that paper that most, perhaps all, of the HFC-23 projects are NOT real and additional.

(In case you are using Hahnel’s reference list to check this source, let me point out that the actual title of the Wara paper is “Measuring the Clean Development Mechanism’s Performance and Potential”. In the version Hahnel sent me, Hahnel’s reference list describes the title of Wara’s paper as “The performance and potential of the clean development mechanism”. I mention this only for the purpose of making checking sources easy. Standard citation styles seem designed to encourage errors in title, author and journal name, and to make such errors difficult to catch. Unfortunately most refereed papers contain errors of this kind, probably including my own.)

The second paper Hahnel cites contains a similar statement: “At root, the CDM and other offset schemes are unable to determine reliably whether credits are issued for activities that would have happened anyway while also keeping transaction costs under control and assuring investor certainty.” (Victor and Wara, 2008, 8). Victor and Wara are suggesting that, with an extremely small number of exceptions, offsets cannot be both additional AND cost effective, that one excludes the other. Remember that cost effectiveness is the means by which offset schemes claim to transfer capital from rich to poor nations without undermining gains for the climate. If offset climate neutrality and offset cost effectiveness are mutually exclusive, then all arguments for offsets vanish.

It is perfectly valid to cite a paper for any fact or analysis it contains, even if that analysis is not its primary concern. Making use of people’s research in ways they did not anticipate is an integral part of scholarly discourse, as long as that use does not distort the content of paper cited, and is not unfair in other ways.

Both working papers cited are pdfs without embedded page numbers. Thus, your reader may show the quotes on slightly different pages. If so, your reader’s search function is your friend.

[11] European Commission. 2011. Europa Press Release: Emissions Trading: Commission welcomes vote to ban certain industrial gas credits. Brussels:European Union. http://europa.eu/rapid/press-release_IP-11-56_en.htm.. Accessed 16/Feb/2013

[12] Alexeew, J., Bergset, L., Meyer, K., Petersen, J., Schneider,L. And Unger, C. 2010. An analysis of the relationship between the additionality of CDM projects and their contribution to sustainable development. International Environmental Agreements 10(3):233-248

[13] “…In many cases, carbon revenues are the icing on the cake, but are not decisive for the investment decision…,” and “…Many projects would also be implemented without registration under the CDM…”

Cames, M., Anger, N., Böhringer, C., Harthan, R. and Schneider, L. 2007. Long-term prospects of CDM and JI:98. Dessau, Germany: The Federal Ministry Of the Environment, Nature Conservation and Nuclear Safety. http://www.umweltdaten.de/publikationen/fpdf-l/3294.pdf

“…verifications, particularly of additionality and baselines, are widely critiqued in terms of: inadequate rigour and transparency, conflicts of interest…”

Ruthner, L., Johnson, M., Chatterjee,B., Lazarus, M., Fujiwara, N., Egenhofer, C., Monceau T. du. and Brohe, A. 2011. Study on the Integrity of the Clean Development Mechanism (CDM):15-T2. Brussels: European Commission, DG Clima. http://ec.europa.eu/clima/policies/ets/linking/docs/final_report_en.pdf

Alexandre Kossoy, senior financial specialist at the World Bank’s Carbon Finance Unit, in a July 2013 interview said projects dropping out from CDM “will survive without it… For most, getting (credits) is the cherry on top of the cake.”

Szabo, Michael, Twidale, Susanna. 2013. Zombie CO2 projects on the rise as CDM hits 7,000. Point Carbon.

[14] Chomitz, K., Akhmetova,D., Hutton, S., Demberel,U., Pinglo, M.E., Shaliz, Z., Gray, C., Taylor-Dormond, M.,Wallich, C., Tenev, S., Thomas, V., Chikkatur, A, Kelly, L., Salvemini, D., Liebenthal, A., Ligot, J., Mason, C., Meisner, C., Nelson, A., Ozen, A., Rossi, F., Schenck, R., Schneider, R., Shalizi, Z., Fall, C.M.,Wolf, J., Fan Zhang and Fuqiu Zhou. 2010. Phase II: The Challenge of Low-Carbon Development—Climate Change and the World Bank Group. Washington, DC: The World Bank:72. http://siteresources.worldbank.org/EXTCCPHASEII/Resources/cc2_full_eval.pdf

[15] United States Consulate – Mumbai. 2008. CARBON CREDITS SUFFICIENT BUT NOT NECESSARY FOR SUSTAINING CLEAN ENERGY PROJECTS OF MAJOR INDIAN BUSINESS GROUPS.. Mumbai, India: United States Consulate. http://wikileaks.org/cable/2008/07/08MUMBAI340.html

[16] Abdellaoui, Mohammed, Bleichrodt, Han, Kammoun, Hilda. 2013. Do financial professionals behave according to prospect theory? An experimental study. Theory & Decision 74(3): 411-429.

Alam, Nafis, Tang, Kin Boon. 2012. Risk-taking behaviour of Islamic banks: application of prospect theory. Qualitative Research in Financial Markets 4(2/3): 156 – 64.

Bone, J., Hey, J., Suckling, J. (1999). Are Groups More (or Less) Consistent than Individuals? Journal of Risk and Uncertainty 18(1):63-81.

Chih, Hsiang-Lin, Shen, Chung-Hua. 2005. Investor protection, prospect theory, and earnings management: An international comparison of the banking industry. Journal of Banking & Finance 29(10): 2675-697

Gill, D. Prowse V. 2012. A structural analysis of disappointment aversion in a real effort competition. American Economic Review 102 (1): 469–503.

Gurevich, G., Kliger, D.,Levy, O. 2009. Decision-making under uncertainty: A field study of cumulative prospect theory. Journal of Banking and Finance 33(7) 1221–229.

Fiegenbaum, Avi.1990. Prospect theory and the risk-return association: An empirical examination in 85 industries. Journal of Economic Behavior & Organization 14(2): 187-203.

Gill, D. Prowse V. 2012. A structural analysis of disappointment aversion in a real effort competition. American Economic Review 102 (1): 469–503.

Gurevich, G., Kliger, D.,Levy, O. 2009. Decision-making under uncertainty: A field study of cumulative prospect theory. Journal of Banking and Finance 33(7) 1221–229.

Johnson, H.J. 1994. Prospect Theory in the Commercial Banking Industry. Journal Of Financial And Strategic Decisions 7(1):73-89.

Kahneman, D.,Tversky, A. 1984. Choices, Values, and Frames. American Psychologist 39(4):341–350.

Kliger, D., Levy, O. 2009. Theories of choice under risk: Insights from financial markets. Journal of Economic Behavior & Organization 71(2): 330–46.

Kühberger, A. 1998. The Influence of Framing on Risky Decisions: A Meta-Analysis. Organizational Behavior and Human Decision Processes 75(1):23-55.

[17] Fielding, R. 2010. Chinese renewable firms vent anger at UN over CDM rejections. Business Green 6-Aug. http://www.businessgreen.com/bg/news/1804572/chinese-renewable-firms-vent-anger-un-cdm-rejections.. Accessed 16/Jan/2012.

[18] Pearce, F. 2010. Carbon Trading Tempts Firms to Make Greenhouse Gas. New Scientist Dec-16. http://www.newscientist.com/article/dn19878-carbon-trading-tempts-firms-to-make-greenhouse-gas.html.. Accessed 16/Jan/2013.

[19] European Commission. 2011. Europa Press Release: Emissions Trading: Commission welcomes vote to ban certain industrial gas credits. Brussels:European Union. http://europa.eu/rapid/press-release_IP-11-56_en.htm.. Accessed 16/Feb/2013

[20] Hahnel, R. 2012a. Left Clouds Over Climate Change Policy. Review of Radical Political Economics 44(2): 151.

[21] World Bank. 2013. World Development Indicators: GHG net emissions/removals by LUCF(Mt of CO2 equivalent). World Databank. Washington, DC: The World Bank. http://databank.worldbank.org/data/views/reports/tableview.aspx. Accessed July10 2013.

[22] The first two citations incorporate natural fluxes as subsidiary points. The Ekblad and Högberg and Högberg et. al articles focuses on natural fluxes.

Valentini1, R.; G. Matteucci1, A. J. Dolman, E.-D. Schulze,4, C. Rebmann, E. J. Moors, A. Granier, P. Gross, N. O. Jensen, K. Pilegaard, A. Lindroth, A. Grelle, C. Bernhofer, T. Grünwald, M. Aubinet, R. Ceulemans, A. S. Kowalski, T. Vesala, Ü. Rannik, P. Berbigier, D. Loustau, J. Guethmundsson, H. Thorgeirsson, A. Ibrom16, K. Morgenstern, R. Clement, J. Moncrieff, L. Montagnani, S. Minerbi & P. G. Jarvis. 2000. Respiration as the main determinant of carbon balance in European forests. Letters to Nature. Nature 404: 861-865. doi:10.1038/35009084.

Saleska, Scott R.; Scott D. Miller, Daniel M. Matross, Michael L. Goulden, Steven C. Wofsy, Humberto R. da Rocha, Plinio B. de Camargo, Patrick Crill, Bruce C. Daube, Helber C. de Freitas, Lucy Hutyra, Michael Keller, Volker Kirchhoff, Mary Menton, J. William Munger, Elizabeth Hammond Pyle, Amy H. Rice, Hudson Silva. 2003. Carbon in Amazon Forests: Unexpected Seasonal Fluxes and Disturbance-Induced Losses. Science 302(5650): 1554-7. DOI:10.1126/science.1091165.

Ekblad, A. and P. Högberg. 2001. Natural abundance of 13C in CO2 respired from forest soils reveals speed of link between tree photosynthesis and root respiration. Oecologia 127(3): 304-8. DOI 10.1007/s004420100667.

Högberg, Mona N.; Maria J. I. Briones, Sonja G. Keel, Daniel B. Metcalfe, Catherine Campbell, Andrew J. Midwood, Barry Thornton, Vaughan Hurry, Sune Linder, Torgny Näsholm, Peter Högberg. 2010. uantification of effects of season and nitrogen supply on tree below-ground carbon transfer to ectomycorrhizal fungi and other soil organisms in a boreal pine forest. New Phytologist 187(2): 485-93. DOI: 10.1111/j.1469-8137.2010.03274.x.

Zhang, Li; Bruce K. Wylie, Lei Ji, Tagir G. Gilmanov, Larry L. Tieszen, Daniel M. Howard. 2011. Upscaling carbon fluxes over the Great Plains grasslands: Sinks and sources. Journal of Geophysical Research: Biogeosciences 116(G3). DOI: 10.1029/2010JG001504.

[23] World Bank. 2013. World Development Indicators: GHG net emissions/removals by LUCF(Mt of CO2 equivalent). World Databank. Washington, DC: The World Bank. http://databank.worldbank.org/data/views/reports/tableview.aspx. Accessed July10 2013.

Hansen, Matthew C.,Stehman, Stephen V., Potapov, Peter V. 2010. Quantification of global gross forest cover loss. Proceedings of the National Academy of Sciences of the United States of America 107(19): 8650-55.

United States Department of Agriculture, Forest Service. 2012. Future of America’s Forest and Rangelands: Forest Service 2010 Resources Planning Act Assessment. DC:USDA.

Although the United States has net sequestration from Land Use Change and Forestry ( LUCF) (World Bank, first source in this endnote). and even increased net forest cover, it faces high gross loss of forest from logging, fire, and pests (Hansen and Stehman and Potapov, second source in this endnote, pages 8650-55). Logging may well have worse consequences than fire. New growth replacing older growth results in less healthy, more fragmented forests.

The formal definition of “fragmentation” is wilderness too near human activity, especially 98 feet or fewer. 28% of forests, 30% of all shrubland, and 40% of grasslands is considered fragmented in the United States (United States Department of Agriculture, Forest Service, third source in this end note, page 38). The following quote casts light on where business as usual has taken the United States: “Considering the forest types that are not naturally fragmented and that are usually found in accessible locations, typically less than one-half of the total area of those forest types qualified as intact forest.” (ibid, page 40) Further, in the long run, forest cover, total tree canopy, forest carbon stocks, biodiversity, resilience, other services are expected to decrease (ibid, page xiii)