4 The Mitigation Policy Curve – Part 2 – Counter-Examples

In the first part on the mitigation policy curve I looked at

  • The Small Country Problem. How one small country acting unilaterally will make an insignificant impacts of global climate change.
  • How it is very likely to be against the economic interests of any country to join the small group of countries already with climate mitigation policies.

In this section I will look at two examples that go completely against logical thinking. There can be instances (like in Britain) where bold policies increase global warming at great cost to that economy, but the shale gas, which constrains global warming at net benefit to the gas-producing country?

To see the effect of policy, there is a need for analysis both at the front-end (prior to implementation), during and after. The question is about the gradient of the policy cost curve, at the point

Policy increasing global emissions?

We know that policy countries are in a minority of countries. With the structure of global growth this amount will fall.

Look at the long-term. Implementing a policy, you are saying to businesses that, ceteris paribus, your energy costs are going to rise year-on-year relative to those in non-policy countries. There will be a bigger incentive to make technological efficiency gains in these countries, but those gains can be transplanted to non-policy countries. In this global emissions may decrease more rapidly than they would have done, but the policy countries bear well over 100% of the costs and it becomes a policy benefit to the non-policy countries. By implication they will achieve around 200% of the global decline in emissions.

Question is, will it be more or less than 200% of the decline? Could it be that the policy countries energy-efficient factories are replaced by less energy-efficient factories in the non-policy countries?
There is some economic theory needed here. The Solow growth model shows a technological growth curve. Developing countries can achieve rapid growth by adapting to higher-productivity by adapting existing technologies. Their lower-unit labour costs will enable to undercut the more advanced economies, but the growth in these economies will grow the global economy as well. Most of this is unit labour costs. But by adapting previous generation technologies and exploiting labour costs less than a tenth those of the rich countries, they can under-cut the rich world. Greater technological advance is mostly in unit labour costs, but it can also mean lower unit energy costs. The portion of global output transferred from the rich countries to the poorer developing countries could result in higher total energy use, and ceteris paribus, higher CO2 emissions.

What is clear is that policy countries will increase unit energy costs. There is a two-pronged approach in Britain. The European-wide carbon-trading scheme will restrict supply of energy, bidding up the price. But also renewables cost more than fossil fuels. So the two-pronged approach doubly increases unit energy costs. Increasing unit energy costs accelerates the switching of manufacturing to developing countries, mostly China. The blue bit above postulates that energy per unit of output is globally could increase. But that is part of the problem. China has much higher CO2 emissions per unit of output as Britain. If Britain’s aggressive rush to renewables is successful, then this gap will increase, as much of Chinese energy output is from coal. A de-carbonised British economy will also be a de-industrialised one. But overall global emissions will have increased through switching of output to China.

The biggest cost of the policy for Britain is nothing to do with switching low-CO2 emitting production to high CO2 emitting countries. It is the restriction on economic growth. Loss of jobs from manufacturing, and pushing up higher energy costs elsewhere constrains growth. Due to the long-term consequences of that pushes policy costs through the roof. In the sectors where jobs are lost overseas, the policy curve is positive. If British Climate Change Act 2008 is massively unsuccessful in meeting the carbon targets, it could be a very expensive policy to increase global CO2 emissions.

The Shale-Gas Counter Example

In the USA, a consequence of the shale gas revolution has been to drastically reduce unit energy costs to industry. But also there has been a switch away from coal. As CO2 emissions of gas are around half that of coal, US CO2 emissions have been falling with electricity prices. The US is enjoying both cheaper and cleaner energy. Consequently, some chemical factories that relocated to China have returned to the USA. China has a greater proportion in its electricity production than USA, and the gap is widening. So the switching of a factory from USA reduces global CO2 emissions, even though the total energy usage remains the same.

Let me show this graphically.

Suppose (as is likely at present), the Climate Change Act 2008 falls a long way short of its target but unintentionally moves a substantial part of manufacturing to China through higher costs. For Britain this will be a large cost relative to British, but may be a net contributor to global warming. The policy curve points gets a positive slope! Conversely, “free market” shale gas in the USA has constrained global carbon emissions doubly by reducing US carbon emissions per unit of output, and switching production from China, where carbon emissions per unit of output are higher. It is having positive benefits on the US economy as well (hence negative costs), whilst constraining (slightly) the top-end of global warming.

5 The Climate Cost Curve

This is a draft proposal in which to frame our thinking about the climatic impacts of global warming, without getting lost in trivial details, or questioning motives. It is an updated version of a draft posted on 26/10/2012.

The continual rise in greenhouse gases due to human emissions is predicted to cause a substantial rise in average global temperatures. This in turn is predicted to lead severe disruption of the global climate. Scientists project that the costs (both to humankind and other life forms) will be nothing short of globally catastrophic.

That is

CGW= f {K}                 (1)

The costs of global warming, CGW are a function of the change in the global average surface temperatures K. This is not a linear function, but of increasing costs per unit of temperature rise. That is

CGW= f {Kx} where x>1            (2)

Graphically

The curve is largely unknown, with large variations in the estimate of the slope. Furthermore, the function may be discontinuous as, there may be tipping points, beyond which the costly impacts of warming become magnified many times. Being unknown, the cost curve is an expectation derived from computer models. The equation thus becomes

E(CGW)= f {Kx}                (3)

The cost curve can be considered as having a number of interrelated elements of magnitude M, time t and likelihood L. There are also the adaptation costs/benefits (which should lead to a planned credit) along with the costs involved in taking actions based on false expectations. Over a time period, costs are normally discounted by r. Then there are two subjective factors – The collective risk factor R, and, when considering a policy response, a weighting W should be given to the scientific evidence. That is

E(CGW)=f {M,1/t,L,A,│Pr-E()│,r,R,W}    (4)

Magnitude M is the both severity and extent of the impacts on humankind or the planet in general in a physical sense.

Time t is highly relevant to the severity of the problem. Rapid changes in conditions are far more costly than gradual changes. Also impacts in the near future are more costly than those in the more distant future due to the shorter time horizon to put in place measures to lessen those costs.

Likelihood L is also relevant to the issue. Discounting a possible cost that is not certain to happen by the expected likelihood of that occurrence enables due unlikely but catastrophic events to be considered alongside near certain events.

Adaptation A is for a project to adapt to the changed climate, to lessen or null the costs. It is the difference between the actual costs spent and the climate impacts saved. Upon completion, a project should have a net credit value.

│Pr-E()│ is the difference between the predicted outcome, based on the best analysis of current data at the local level, and the expected outcome, that forms the basis of adaptive responses. It can create a cost in two ways. If there is a failure to predict and adapt to changing conditions then there is a cost. If there is adaptation to an anticipated future condition that does not emerge, or is less severe than forecast, there is also a cost. │Pr-E()│= 0 when the outturn is exactly as forecast in every case. Given the uncertainty of future outcomes, there will always be costs incurred if the climate cost savings from adaptation is a unitary value. If there are a range of possible scenarios, then this value could be a credit.

Discount rate r is a device that recognizes that people prioritize according to time horizons. Discounting future costs or revenue enables us to evaluate the discount future alongside the near future.

Collective risk factor R, is the risk preference weighting. If policy-makers assume a collective risk-neutral position, then this weighting will be 1. Risk lovers – the gamblers and many self-made billionaires – have a weighting of less than one. Those who take out insurance are risk averse. Insurance gives a certain premium to compensate if a much greater probabilistic loss occurs. For instance, the probability of a £200,000 house being completely destroyed in a year is around 1 in 10,000. So the expected loss is just £20 in any year. Most people are risk averse when it comes to their most valuable asset, so would pay a premium of far greater than £20 compensate for this unlikely loss. With respect to potential catastrophes, we usually expect governments to take a risk-averse approach. That is to potentially spend more on certain costs (like flood defences) than the total expected losses from letting catastrophes from happening. For any problem on a vast scale, we need to articulate the risk preference weighting. The “precautionary principle”, used in arguing for tough and immediate mitigation policies, effectively creates a collective risk factor many times greater than 1. NB, as the costs of climate change will increase with time, a risk averse weighting is the equivalent of a negative discount rate r. That is, you could assume R = f {-r}.

Finally the Weighting (W) is concerned with the strength of the evidence. How much credence do you give to projections about the future? Here is where value judgements come into play. I believe that we should not completely ignore alarming projections about the future for which there is highly circumstantial evidence, but neither should we accept such evidence as the only possible future scenario. In fact, by its very nature the “evidence” will be highly circumstantial. Consider the costs of climate change graph again. The data we have (which needs to converted into evidence) is for a very short section, and for miniscule fluctuations in costs, compared to the predicted catastrophe.

This leads to a vast area of evidence quality as

  • Small errors or biases in temperature measurement will have huge impacts on future projections. (Impacts on historical climate sensitivity)
  • Small errors or biases in distinguishing between natural and human-caused extreme weather events or short-run climatic changes will have huge impacts on projected costs.

If we assume that some sort of climate catastrophe is going to happen, convincing an independent third-party could include

  • Science building a clear track record of short-run predictive successes, both on warming trends and damage impacts.
  • Learning from the errors and exaggerations.
  • Be very clear as to the quality and relevance of the evidence.
  • Corroborating evidence. Show the coherence of one part of the picture with another. For instance, trying to reconcile with estimates of polar ice cap rate of melt with the rate of sea level rise reveals some very interesting questions.
  • Corroboration of between different techniques and evaluation methods.
  • For a junior science, show the underlying methodology draws upon the best of the mature sciences and philosophies of science.

The prediction of catastrophe is highly emotive. There are comparisons here with the justice system in has Britain failed where there are highly emotive crimes, for instance the IRA bringing their bombing campaign to the British mainland in the early 1970s.

  • Clear separation of the understandable emotion, from the evidence gathering.
  • Developing, and continually improving, quality standards for evidence gathering
  • A dim view taken for tampering with, or suppression of evidence.
  • A dim view taken on influencing the jury.
  • Allowing the accused a strong defence. The lack of any credible defence argument, despite a strong defence team, will remove any “reasonable doubt” in the minds of the jury, where the accused is in denial of the overwhelming evidence of their guilt.

6 A halving of climate sensitivity

Lord Lawson, in a spirited attack on the Energy Bill passing through parliament, said in the House of Lords on 18th June 2013

There is an emerging consensus among scientists that the climate sensitivity of carbon is probably less than they thought. That means, importantly, that any dangers from warming, if they occur, are postponed well into the next century. It means that there is no urgency to go ahead in this way, not only because the uncertainties are in the distant future but because we have no idea what technologies will develop over the next 100 years.

The analysis I have developed shows Lord Lawson understates how significant the climate sensitivity issue to the problem of catastrophic warming and mitigation policy.

In my analysis, the maximum warming would be 7oC. There can be a case for warming topping out at some level, as

  • There are diminishing returns to increases in greenhouse gas on temperature.
  • There are diminishing returns at some point for unit rises in emissions on levels of GHGs. That is, higher levels of GHGs in the atmosphere will lead to higher levels of absorption.

I will assume that climate sensitivity is halved, but will assume that temperatures eventually reach 5oC above pre-industrial levels.

The simple curve to work out the consequences is the policy curve. Any constraint of greenhouse gas levels will only have half the impact on temperature. The policy curve will shift to the right to PC1.

The climate costs curve is somewhat more difficult. The elements to consider in the curve are

E(CGW)=f {M,1/t,L,A,│Pr-E()│,r,R,W}

I have highlighted the elements to consider.

Time t will be doubled. Warming rates will therefore be halved. Some of the harmful consequences of warming are from unprecedented rapid change. For many animals and plants, it is speculated sudden change is much more damaging than a slower change. More importantly, sudden changes in average temperature could jolt climate systems into different patterns. Savannahs could become deserts, or the monsoon could shift. Another aspect to consider is that rapid warming of the tundra could release massive amounts of CH4 into the atmosphere, further accelerating warming. Or rapid warming could lead to rapid disintegration and breakup of the polar ice caps, leading to rapid acceleration of sea level rise. The slower warming will make us much less likely to cross these climate tipping points.

Adaptations A
can be phased in more gradually. For instance, with sea level rise, the Thames Barrier will no longer be adequate. A replacement to last 50 years will need to be much less extensive. If warming causes crop yields to fall by increased drought there is more time to adjust.

With changes happening more slowly, (and less chaotically), the adaptation cost errors, │Pr-E()│, are likely to be less.

For any positive rate of discount r, then the current net present value will be lower for the much extended warming period. However, as Stern had a discount value of not much different to zero, allowing for a discount rate would totally cover the other issues.

For all of these reasons, the climate cost curve will move down to CC1 and total cost curve to TC1. The point where policy costs equals climate change costs moves from A to B. That is at a significantly higher temperature, and for a much lower level of policy cost.

I have steered away from the weighting W issues. But given that sensitivity is a core issue that the climate models have got consistently wrong, then any weighting given to other predictions should be viewed with greater scepticism.

7 Appendix – Deriving the Policy and Forecast Graph

In the introduction, the derivation of the graph to replicate the claim that the costs of catastrophic global warming will be many times greater than mitigation policy costs was logically incomplete. This is a derivation of the two cost functions from a series of PowerPoint slides, which I find somewhat more satisfactory.

Slide 1

First draw two axis’s – for temperature and relative cost.

Slide 2

Next, add in five points.

A. If there had been no rise in human greenhouse gases, there would be no rise in temperatures and thus no consequential costly climate impacts.

B. With “business as usual”, there will be a huge amount of warming, with hugely costly consequential climate impacts.

C. Globally, policy could be used to stop any further rise in greenhouse gases, but with huge global cost.

D. No policy and no policy costs.

E. Intersection of two curves, which in Stern’s view is at the point of constraining warming to about 3 degrees above pre-twentieth century levels.

Slide 3

Connecting up the points AB (climate costs) and CD (Policy costs) with straight lines (linear functions), creates an intersection at point F.

To replicate Stern, we need cost functions that intersect at point E. That is the climate cost curve connects AEB and the policy costs curve connects CED.

Slide 4

Drawing curves within PowerPoint is beyond my current skills. Simple curves have symmetrical properties. The required cost curves do not have such properties.

Slide 5

Above is the actual graph used.

Slide 6

On my graphs the cost curves are unstable functions

For climate costs

RC = f(T4)

For policy costs

RC = f((10-T)5)

To justify policy

  1. Must have reliable consequences of warming beyond human experience. Climate models must be robust for the high temperature rise forecast and have a phenomenal degree of precision on the shorter-term cost impact forecasts.
  2. Must be sure that got achievable high-impact low-cost policies, with a highly results-driven approach to policy implementation.

Stephan Lewandowsky on Hurricane Sandy

Jo Nova posts on Stephan Lewandowsky’s analysis of Hurricane Sandy. Below is my comment, with the relevant links.

Lewandowsky has a lot to say about the overwhelming evidence for smoking causing lung cancer, but in substance has just this to say about the impending catastrophic global warming.

Trends such as the tripling of the number of weather-related natural disasters during the last 30 years or the inexorable rise in sea levels. Climate scientists predicted those trends long ago. And they are virtually certain that those trends would not have occurred without us pumping billions of tons of CO2 into the atmosphere.

There are 3 parts to this.

First, the economic analysis of natural disasters is Lewandowsky’s own. He ignores completely the opinions of Roger Pielke Jr, an expert in the field, with many peer reviewed studies on the subject. Pielke Jnr has shown there is nothing exceptional in the normalised cost of Hurricane Sandy. Furthermore, a 2009 report showed that New York is vulnerable to hurricanes, and the shape of the coastline makes it particularly vulnerable to storm surges.

Second, the sea level rise is a trivial issue. From the University of Colorado graph, it is clear that sea levels are rising at a steady rate of 31cm a century.

Third, he claims the predictions of unnamed “experts” have been fulfilled. A balanced analysis would point out that the CO2 levels have risen faster than predicted, but temperatures have not.

Last week I posted a proposal for analysing the costly impacts of global warming. Using the “equation”, I would suggest Lewandowsky overstates both the Magnitude and Likelihood that Sandy was caused by global warming. He misperceives the change in frequency (1/t). Furthermore, given than he has a track record in the highly biased use of statistics in his own field, and his deliberate lack of balance, the Weighting attached to anything he says should be negative. That is, like to newspapers of the Soviet Union, if Lewandowsky claims something, we should read between the lines to see what he does not say. However, unlike the Soviet Union we are still able to look for alternative opinions.


Normalized US Hurricane damage impacts


2012_rel4: Global Mean Sea Level Time Series (seasonal signals removed)