From Farsighted (Steven Johnson, 2018) p130-2
Regulatory impact analysis was, in practice, what we commonly call cost-benefit analysis. In deciding whether to implement a new regulation, agencies would have to calculate the potential costs and benefits of the regulation, in part by predicting the downstream consequences of implementing it. The executive order effectively compelled government agencies, eventually overseen by the Office of Information and Regulatory Affairs (OIRA), to walk through the key steps of decision-making that we have explored – mapping all the potential variables and predicting the long-term effects – and it even pushed them to explore other decision paths that might not have been initially visible when the proposed regulation was originally being drafted. If, at the end of the analysis, the regulation could be shown to “maximize net benefits” – in other words, not just do more good than harm, but do more good than any other comparable option on the table -the agency would be free to implement it. “Reagan’s ideas applied across a spectacularly wide range, covering regulations meant to protect the environment, increase food safety, reduce risks on the highways and in the air, promote health care, improve immigration, affect the energy supply, or increase homeland security,” writes Cass Sunstein, who ran OIRA for several years during the Obama administration.
When it was first proposed, regulatory impact analysis was seen as a conservative intervention, an attempt to rein in runaway government spending. But the basic framework has persevered, largely unmodified, through six administrations. It is one of the rarest of creatures in the Washington ecosystem: an institutional practice with bipartisan support that leads to better government. Cost-beneflt analysis turned out to have genuine potential as a tool for progressive values, and not just anti-Big Government cutbacks. Under the Obama administration, an interagency group formulated a monetary figure measuring “the social cost of carbon” – a cost that many environmentalists felt had been long overlooked in our decisions about energy policy. Experts were drawn from the Council on Environmental Quality, the National Economic Council, the Office of Energy and Climate Change, the Office of Science and Technology Policy, the EPA, and the Departments of Agriculture, Commerce, Energy, Transportation, and Treasury. Collectively, they mapped all the downstream effects of releasing carbon into the atmosphere, from agriculture disruptions triggered by climate changes to the economic cost of increasingly severe weather events to the geographic dislocation triggered by rising sea levels. In the end, they calculated the social cost of carbon to be $36 per ton released into the atmosphere.
The figure itself was only an estimate – a more recent Stanford study suggests it may be several times higher – but it provided a baseline cost for any government regulation that involved carbon-generating technology. The calculation, for instance, was an essential justification for the aggressive targets for fuel economy standards that the EPA mandated for automobiles and trucks during the Obama administration. In a sense, by assigning a dollar value to the cost of carbon, regulators were adding a predictive stage to decisions that involved fossil fuels, one that offered a longterm view. Their decision was no longer limited to the present tense benefit of using those fuels as a source of energy. That $36 per ton cost gave them a way of measuring the future impact of the decision as well. It was, at its core, a calculation: If we choose this option, how much carbon will that release into the atmosphere, and how much will it cost for us to deal with the consequences of those emissions in the years to come? But that calculation made the choice far more farsighted than it would have been without it.
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