As a pretext for expanding political control of the economy, redistributing wealth, and bilking consumers for the benefit of special interests, nothing beats the pseudo-science of social-cost-of-carbon estimation.
A new study by economists Laurie Johnson, Starla Yeh, and Chris Hope, The Social Cost of Carbon: Implications for Modernizing Our Electricity System, has the unintentional virtue of exposing what a menace SCC analysis has become.
Before examining the Johnson, Yeh, Hope (JYH) study, let’s review some preliminaries.
The “social cost of carbon” is an estimate of how much damage an incremental ton of carbon dioxide (CO2) emissions inflicts on society in a given year. Raise the SCC estimate high enough, and it can justify almost any CO2-reduction measure, no matter how costly.
Although recent science indicates that, far from being “worse than we thought,” the state of the climate is better than they told us, the Obama administration’s 2013 SCC estimate ($11-52/ton) is about 50% higher than its 2010 estimate ($4.70-35.10/ton). Cato Institute climatologist Chip Knappenberger lays bare the political calculus behind the revision:
In this way, all qualifying rules and regulations, including the EPA’s promised emissions limits on new and existing power plants, appear less costly — a critical asset, as costs are often the greatest barrier to approval.
Since the war on global warming is a high priority within the Obama administration, finding ways to make the social cost of carbon appear to be as high as possible is the ongoing objective.
Back in May, the administration increased its previous estimate by more than 50%, from $25 to $40, which means that all proposed carbon dioxide emissions cuts are now some 50% more valuable.
Despite their seeming rigor, SCC estimates are inherently subjective, as MIT Professor Robert Pindyck explains in a recent paper. Interestingly, Pindyck is not a climate skeptic. He believes CO2 emissions “will eventually result in unwanted climate change”; he even favors adoption of a carbon tax.
The computer programs used to estimate the SCC are called “integrated assessment models” (IAMs) because they integrate a model of how CO2 emissions supposedly change the climate with a model of how climate change supposedly damages the economy. Finding the IAMs “so deeply flawed as to be close to useless as tools for policy analysis,” Pindyck cautions that “their use suggests a level of knowledge and precision that is simply illusory, and can be highly misleading.” He explains:
The modeler has a great deal of freedom in choosing functional forms, parameter values, and other inputs, and different choices can give wildly different estimates of the SCC and the optimal amount of abatement. You might think that some input choices are more reasonable or defensible than others, but no, “reasonable” is very much in the eye of the beholder. Thus these models can be used to obtain almost any result one desires.
Two speculative inputs in particular determine the outcomes of SCC analyses: climate sensitivity, which “translates increases in CO2e [carbon dioxide-equivalent] concentration to increases in temperature,” and the damage function, which “translates higher temperatures into reductions in GDP and consumption.”
Far from settled science, climate sensitivity remains a focus of ongoing research and debate. “Here is the problem,” writes Pindyck: “the physical mechanisms that determine climate sensitivity involve crucial feedback loops, and the parameter values that determine the strength (and even the sign) of those feedback loops are largely unknown, and for the foreseeable future may even be unknowable.”
The damage function is almost pure guesswork:
When assessing climate sensitivity, we at least have scientific results [e.g. temperature data] to rely on, and can argue coherently about the probability distribution that is most consistent with those results. When it comes to the damage function, however, we know almost nothing, so developers of IAMs can do little more than make up functional forms and corresponding parameter values. And that is pretty much what they have done.
None of the loss functions modelers select is “based on any economic (or other) theory,” Pindyck adds. “They are just arbitrary functions, made up to describe how GDP goes down when T [temperature] goes up.”
One reason damage functions are speculative is that it is highly uncertain how adaptive capabilities will develop. Since technology is what enables humans to adapt to their environment, SCC analysts must make assumptions about technological change over the next 50-100 years. Good luck with that!
Economist Indur Goklany finds that modelers often fail to account for reasonably anticipated changes in future adaptive capabilities, and thus “substantially overestimate future net damages from global warming.”
Societies will adapt more easily to climate change if CO2 emissions have benefits as well as costs. As discussed last week on this blog, in a recent study based on thousands of laboratory and field experiments, climate researcher Craig Idso estimates that rising CO2 concentrations boosted global agricultural output by $3.2 trillion during the past 50 years and will increase yields by another $9.8 trillion between now and 2050. Incorporating CO2 fertilization benefits of that magnitude in IAMs would significantly reduce most SCC estimates.
Of the three IAMs the Obama Inter-Agency Group used to estimate the SCC, the DICE and PAGE models have no CO2 fertilization benefit. Since the CO2 fertilization effect has substantial science behind it, leaving it out of DICE and PAGE seems quite arbitrary. Somehow I’m not surprised that JYH co-author Chris Hope is also creator of the PAGE model.
Another arbitrary choice that can have “huge effects on SCC estimates,” according to Pindyck, is the selection of discount rates. Modelers use discount rates to determine the present value of future costs and benefits. Discounting reflects the fact that people tend to attach less value to costs and benefits in the future, especially the remote future, than they do to costs and benefits in the present. Other things being equal, the lower the discount rate, the larger the present value of future CO2-related damages, and the larger the estimated SCC.
Although Office of Management and Budget (OMB) Circular A-4 instructs agencies to use a 7% discount rate as the base case in regulatory analysis, because 7% is the “average before-tax rate of return to private capital” in the U.S. economy, the Obama Inter-Agency Working Group used only discount rates of 2.5%, 3%, and 5%. The discrepancy may look like small potatoes, but through the miracle of compounding, small differences in the annual discount rate add up to big bottom-line differences.
For example, in the Inter-Agency Group’s May 2013 technical paper, the SCC for 2010 is $11 per ton at a 5% discount rate but $52 per ton at a 2.5% discount rate. “In other words,” notes Institute for Energy Research economist Robert Murphy, “cutting the discount rate in half caused the reported SCC to more than quadruple.”
JYH compute carbon’s social cost using discount rates even lower than the low-end of the Inter-Agency Group’s range. The Inter-Agency Group, using 2.5%, 3%, and 5% discount rates, produced year-2010 SCC estimates of $52, $33, and $11 per ton. JYH, using discount rates of 1%, 1.5%, and 2%, produce SCC estimates of $266, $122, and $62 per ton. JYH’s lowest SCC estimate is bigger than the Inter-Agency Group’s highest SCC estimate. Those big numbers leverage a lot of mischief.
JYH translate their SCC numbers into cents-per-kilowatt estimates, and then “compare the total social cost (generation plus environmental costs) of building new generation from traditional fossil fuels versus cleaner technologies.” They also “examine the cost of replacing existing coal generation with cleaner options, ranging from conventional natural gas to solar photovoltaic.” Their results are exactly what climate campaigners want to hear:
- In a full accounting that incorporates environmental damages, renewables are always more “efficient” than new coal generation, and usually more efficient than new gas generation.
- If the SCC is $266/ton or even $122/ton, switching from coal to solar or installing carbon capture and sequestration (CCS) is more efficient than maintaining an existing coal power plant.
In the authors’ words:
We find that for most SCC values, it is more economically efficient (from a social cost–benefit perspective) for the new generation to come from any of these cleaner sources rather than conventional coal, and in several instances, the cleanest sources are preferable to conventional natural gas. For existing generation, for five of the six SCC estimates we examined, replacing the average existing coal plant with conventional natural gas, natural gas with carbon capture and storage, or wind increases economic efficiency. At the two highest SCCs, solar photovoltaic and coal with carbon capture and storage are also more efficient than maintaining a typical coal plant.
An obvious objection is that the average cost of generating electric power from today’s existing coal fleet is 3.0 cents/kWh, as JYH acknowledge. To all relevant economic actors — power producers, consumers, and shareholders — that seems pretty darn efficient. At 3.0 cents/kWh, society is getting a whole lot of bang for very little electricity buck.
But, argue JYH, a $266/ton SCC makes the “real” cost of electric power from existing coal plants 10 times greater:
Specifically, at $266/ton CO2, the average coal plant costs 34.5 cents/kWh (more than ten times its direct generation costs) versus 15.1 and 13.3 cents/kWh, respectively, for new coal with CCS and solar. At $122/ton CO2, the average coal plant costs 18.7 cents/kWh versus 13.8 and 13.3 cents/kWh, respectively.
So here is the madness to their method. Having selected very low discount rates to produce very high SCC estimates, JYH compare their make-believe price of coal- or gas-fired electricity with the actual market price of wind- or solar-generated electricity. They then pretend to demonstrate that wind and solar are cheaper than new gas, and that replacing existing coal power plants with renewables will make the overall economy more efficient. That is just plain loopy.
Any serious attempt to repower America with renewables would cause electric rates to skyrocket. The premature retirement of the existing U.S. coal fleet, which supplies 40% of U.S. electric power, would destroy hundreds of billions of dollars in shareholder value. Regulating or taxing natural gas generation based on SCC estimates of $122-266/ton would trigger massive capital flight from the gas industry. And if SCC estimates demand corrective taxes for coal and gas, why not for oil, too? Such measures would snuff out the shale revolution — arguably the most important source of new jobs, investment, tax revenue, and competitive advantage of the past 20 years.
Even if those “transitional” costs could somehow be avoided, wind and solar energy are simply too intermittent, unreliable, and inefficient to power a modern economy. In 2012, wind and solar technologies provided 3.46% and 0.11% of U.S. electric generation, respectively. Wind and solar power would not make even those meager contributions but for mandatory production quota and other policy privileges.
Swapping out existing coal with renewables and installing renewables instead of new gas would compel America to spend lots more for a much smaller, much less reliable electricity supply. How can that possibly be economically efficient?
JYH try to finesse renewable electricity’s well-known deficiencies: “An ideal comparison of costs would be one that adjusted for the intermittency of renewable sources, which is not captured in a levelized cost comparison. Adjusting for this factor is beyond the scope of this analysis, so the estimates here should be viewed as a first approximation.”
In other words, JYH place “beyond the scope” of their analysis the very thing that: (1) makes kilowatts from wind and solar power less valuable than kilowatts from coal, gas, or nuclear energy; (2) renders wind and solar energy unfit to provide base load electricity (power you can depend on 24/7); and (3) makes wind worthless as a source of peaking power on summer days when the heat is intense precisely because the wind isn’t blowing.
In a study of three interconnection regions that account for more than half of U.S. installed wind capacity, economist Jonathan Lesser found that during 2009-2012, over 84% of the installed wind generation failed to produce electricity when demand was greatest. During peak hours on high demand days, only 1.8% to 7.6% of wind infrastructure generated power in the Midwest ISO region, only 6.0% to 15.9% of installed wind generated power in the Texas (ERCOT) region, and only 8.2% to 14.6% of installed wind produced power in the PJM region.
An electric power station that fails to produce during a heat wave is like metro service that’s available except when you need to get to work. Neither is of much value, regardless of how ‘competitive’ the rates may seem to some social cost of carbon analysts.
As Lesser put it, forcing taxpayers and ratepayers to subsidize wind “is like asking someone to pay for a taxi that does not show up when it’s raining.” But armed with their SCC estimates, JYH can pretend that the no-show taxi is a bargain at any price!
We should, however, be grateful to JYH for clarifying the nature and purpose of SCC analysis. SCC analysts manipulate speculative numbers to create the illusion that uneconomic energy is actually cheaper than economic energy. They do so for the purpose of advancing an agenda that, if seriously implemented, would put most of us in the poor house.