By Institute for Energy Research ——Bio and Archives--May 19, 2015
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…I would argue that calling these models “close to useless” is generous: IAM-based analyses of climate policy create a perception of knowledge and precision that is illusory, and can fool policy-makers into thinking that the forecasts the models generate have some kind of scientific legitimacy. IAMs can be misleading – and are inappropriate – as guides for policy, and yet they have been used by the government to estimate the social cost of carbon (SCC) and evaluate tax and abatement policies. [Pindyck 2015, bold added.]
One of the most important parts of an IAM is the damage function, i.e., the relationship between an increase in temperature and GDP (or the growth rate of GDP). When assessing [the climate’s sensitivity to emissions], we can at least draw on the underlying physical science and argue coherently about the relevant probability distributions. But when it comes to the damage function, we know virtually nothing – there is no theory and no data that we can draw from. As a result, developers of IAMs simply make up arbitrary functional forms and corresponding parameter values. [Pindyck 2015, bold added, footnotes removed.]Thus we see that all of the fancy computer models—including the three that the Obama Administration Working Group selected to estimate the “social cost of carbon”—rest on quicksand.(i] Most policymakers, let alone the general public, have no idea how flimsy and arbitrary is the foundation upon which these computer simulations stand. This is what leads Pindyck to write: “I will argue that the use of IAMs to estimate the SCC [social cost of carbon] or evaluate alternative policies is in some ways dishonest, in that it creates a veneer of scientific legitimacy that is misleading.” Later in his paper Pindyck further writes that “the developers and users of IAMs have tended to oversell their validity, and have failed to be clear about their inadequacies.” Because of this overselling of the power of these models, Pindyck believes “[t]he result is that policy makers who rely on the projections of IAMs are being misled.”
This does not mean we have to throw up our hands and give up on the estimation of the SCC and the analysis of climate change policy more generally. I have argued that the problem is somewhat simplified by the fact that what matters for policy is the possibility of a catastrophic climate outcome. How probable is such an outcome (or set of outcomes), and how bad would they be? And by how much would emissions have to be reduced to avoid these outcomes? I have argued that the best we can do at this point is come up with plausible answers to these questions… [Pindyck 2015, bold added.]We have already left the (utterly arbitrary and misleading) world of smooth functions which calculate the marginal impact of a further ton of emissions, allowing policymakers to set the “optimal” carbon tax. Pindyck spends most of his paper explaining why that is a delusion. Instead, as the block quotation above indicates, Pindyck simply wants experts to pick a few catastrophic scenarios, giving estimates of their severity and the associated levels of emissions making them more or less likely. This would give policymakers a rough idea of what they would need to do, in order to achieve reductions in the likelihood of such catastrophes. To understand the enormity of the chasm between the current approach and what Pindyck is suggesting, we should follow up on the phrase I bolded in the quotation above. Specifically, why did Pindyck write that “what matters for policy” are just the catastrophic scenarios? Earlier in his paper he had explained:
How do we know that the possibility of a catastrophic outcome is what matters for the SCC? Because unless we are ready to accept a discount rate that is very small, the “most likely” scenarios for climate change simply don’t generate enough damages – in present value terms – to matter. [Pindyck 2015, bold added.]At this point, I want the reader to pause, take a breath, and grasp the bombshell that Pindyck just lobbed. He is confirming what I have been telling IER readers for years: Using the very computer models and estimates from the IPCC’s own reports, I can show that the standard UN climate targets (such as limiting warming to 2 degrees Celsius) do not pass a standard cost/benefit test. Notwithstanding all of the rhetoric about the “science is settled” and how we are (supposedly) seeing the awful consequences of human-caused climate change before our very eyes, the IPCC’s own reports show that the popular “solutions” to the problem of climate change don’t make any sense. Once we realize this awkward fact, everything else falls into place. It’s why climate activists are trying to discredit the use of GDP as a criterion for policy evaluation, and it’s why the IPCC itself is switching its rhetoric to risk management and a focus on “co-benefits.” They have to do these things, because they know their own reports better than the outside world, and they know full well that when using standard economic tools, even mildly aggressive climate policy targets cannot be justified.
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