(John Kemp is a Reuters market analyst. The views expressed are his own)
By John Kemp
LONDON May 2 Uncertainty about the commitment of politicians and the public to "stay the course" risks derailing Britain's plan to cut greenhouse emissions by at least 80 percent by 2050.
"Recent statements from government ministers show that energy policy is once again in flux," according to the UK Energy Research Centre (UKERC).
"Climate change mitigation is subject to increasing trade-offs with other objectives within government," the researchers wrote in a report published on Wednesday.
Political uncertainty is just one of the risks that could discourage the massive investment needed in the next 30 years as Britain attempts to transform all aspects of its energy economy.
There are also major uncertainties about whether the technologies needed can be scaled up to the required size and whether enough capital can be raised from utilities, pension funds and other investors to pay for it all ("UK energy strategies under uncertainty" April 30).
But underlying all these other uncertainties is the question about whether voters and their political representatives can be convinced to foot the bill.
"Within the political debate, some have argued the UK should downgrade its commitment to reducing emissions because this is perceived to be too costly. But placing less emphasis on emissions reduction is not a cost or risk-free option," UKERC wrote.
The report's language, with its repeated references to objectives, trade-offs, preferences and constraints, suggests the best way to analyse energy policy and climate change is as a constrained optimisation problem.
Voters and policymakers want to maximise a number of goals related to affordable, reliable and sustainable energy, subject to a number of constraints imposed by physical laws, resource endowments and the state of technology.
Once energy and climate policy is characterised in this way, many of the aspects that are most controversial and perplexing become readily understandable.
Constrained optimisation problems are familiar to first-year economics students from the use of indifference curves to solve consumer choice and cost minimisation problems.
But the most commonly used and tractable form of constrained optimisation is linear programming, a mathematical technique for solving logistics problems developed by Leonid Kantorovich for the Soviet Red Army and George Danzig for the U.S. Air Force during World War Two to solve military problems.
Kantorovich used it to calculate the optimal distance between supply trucks crossing the frozen Lake Ladoga during the siege of Leningrad in the winter of 1941/42 to ensure they would not sink.
Danzig employed it to show how personnel could best be assigned to jobs, but it soon came to be used in many aspects of military training, manpower and logistics.
The resource optimisation made possible by linear programming was so powerful that the technique was considered a state secret in both countries because of its vital role in the war effort. Only in 1947 did the techniques become widely known when Danzig published them.
In the post-war world, linear programming has come to be employed in a huge range of industries.
Crude oil refiners use linear programming to determine which crudes to buy and what fuels to produce to maximise their margins. Airlines use it to plan their route networks to maximise revenue and minimise fuel bills. Logistics firms use it to find the best way to schedule parcel deliveries.
Even more complicated optimisations are now possible, including systems that allow preferences and constraints to take non-linear forms. But the basic idea (maximising or minimising an objective function subject to a number of constraints) is the same in each case.
In the case of energy and climate policy, most voters and policymakers say they want energy to be clean, affordable and reliable/secure. Unfortunately, there tend to be trade-offs among these three goals, and different members of the public express a preference for different combinations.
Environmental campaigners give overwhelming priority to meeting emissions goals. Only after emissions are curbed do they worry about considerations of cost and reliability. Environmentalists will cheerfully pay more (in some cases quite a lot more) and accept some reduction in convenience to achieve energy with few or zero emissions.
At the other pole, some voters doubt that the climate is changing at all or assign a very low priority to taking steps to deal with it. Voters and politicians in this group assign absolute priority to affordability and reliability. Only once those goals have been satisfied do they worry about cutting emissions.
Most voters and politicians have a mix of preferences somewhere between these two extremes. They want energy to be clean and affordable and reliable. Even so, there is quite a lot of variability in the weights that individual voters and politicians assign to these goals.
Much of the debate about climate and energy policy is framed in terms of the "science," as if there were a scientific basis for determining the right answer or the most efficient solution to the optimisation problem. In fact, most of the differences are not really about the science or evidence about costs but rooted in different preferences about outcomes.
Environmentalists and climate sceptics disagree for much the same reason that conservatives and liberals disagree on questions about income distribution and inequality.
CHANGING PUBLIC GOALS
For the most part, societies deal with this sort of collective choice problem through the political process. Political leaders aggregate the different preferences of individual voters to try to reach some sort of compromise.
The response to climate change is more about political choice than scientific modelling. Models can illustrate the consequences of various different course of action (and inaction), but they cannot make the choice itself. That decision is inherently political.
But politicians find that the problem with trying to aggregate voters' preferences over affordability, security and sustainability is that the preferences are themselves quite unstable over time.
In the late 1990s and early 2000s, there appeared to be strong support for ambitious policies to curb greenhouse emissions even if the transition to a low-carbon economy proved quite expensive. Recently, voters and policymakers have appeared far more worried about the costs.
Unfortunately, many investments in the energy sector are very capital intensive and have payback periods stretching for years or even decades. Making such long-term commitments in the face of unstable voter and political preferences is inherently difficult.
The other side of the optimisation problem is the constraints including physical laws, the current state of technology, and a country's natural endowments of resources such as coal, oil, gas, wind, solar and wave energy.
In theory, the constraints should be more stable than voters' preferences. Obviously the laws of physics don't change. But other constraints turn out to be surprisingly flexible and changeable. Technology obviously changes, sometimes quite dramatically. Resource endowments also turn out to be quite variable.
The shale revolution showed that a shift in technology could fundamentally alter the understanding of how much oil and gas might be technically and economically recoverable.
So climate change and energy policy turn out to be a constrained optimisation problem in which both preferences and constraints shift significantly over time.
Moreover, there is some evidence that the preferences and constraints are not independent but influence one another.
When oil and gas resources appeared to be running out, it was much easier to build support for ambitious policies to tackle climate change.
But the shale revolution seems to have changed the balance by holding out the prospect that fossil energy can remain much cheaper.
Finally, as the authors of the UKERC report acknowledge, both preferences and constraints are surrounded by enormous amounts of uncertainty. Since there is so much uncertainty about future preferences and constraints, the optimum solution is not well specified but embraces a wide range of possible policy choices and may be quite fuzzy.
The constantly shifting nature of both the preferences and the constraints, together with the tremendous amount of uncertainty surrounding both, explains why policymakers find it impossible to sustain a durable consensus around energy and climate policies. (editing by Jane Baird)