EPA “Anticipates” Expanding Agency Toolkit for Fashioning Statistical Lies

Comment Opportunity! Be heard!

That there are three kinds of lies—“lies, damned lies, and statistics”—is an apocryphal phrase of great relevance to the modern regulatory state. For it is with ease that regulators manipulate math in order to legitimate their otherwise unjustifiable actions.

Of course, these sorts of shenanigans wouldn’t be necessary if the system worked as intended. If federal agencies were full of disinterested civil servants toiling on behalf of the public interest, then there’d be no need for fuzzy math. But that’s not what exists, alas. Instead, federal agencies have become political chips to be doled out to special interests,* in exchange for their having helped elect a given President. Having thus captured federal agencies, these special interests employ the power of the state to advance their narrow causes. And this is why statistical lies are necessary: They obfuscate the unsavory quid pro quo politics that undergird the modern regulatory state.

Consider, for example, the extreme degree to which EPA now serves NRDC and Sierra Club, rather than the American people. Over the last five election cycles, such green groups have become an increasingly important cog in the progressive political campaign machinery. As a result, they’ve enjoyed unprecedented access at the EPA. They dominate the ranks of political appointees, and have had an inordinately heavy hand in reg writing. From the fact that no agency has been as thoroughly captured as EPA, it follows that the agency long has excelled in the black arts of engendering quantitative “benefits” from thin air.

Take EPA’s bedrock bull$h!t statistic: the value of a life “saved” by one of the agency’s air quality rules. Whenever you hear EPA administrator Gina McCarthy talk about the trillions of dollars in economic activity *created* by the Clean Air Act, her point is founded upon the value of a statistical life. There is no greater proffered justification for EPA’s existence than the statistical value of life. And how does the agency achieve this crucial figure? Here’s how EPA describes its calculation:

“Suppose each person in a sample of 100,000 people were asked how much he or she would be willing to pay for a reduction in their individual risk of dying of 1 in 100,000, or 0.001%, over the next year. Since this reduction in risk would mean that we would expect one fewer death among the sample of 100,000 people over the next year on average, this is sometimes described as “one statistical life saved.” Now suppose that the average response to this hypothetical question was $100. Then the total dollar amount that the group would be willing to pay to save one statistical life in a year would be $100 per person × 100,000 people, or $10 million. This is what is meant by the “value of a statistical life.”

So…The “value” of each “prevented death” is ascertained by asking people how much hypothetical money they’d be willing to spend in order to avoid a fraction of one percent chance of death. How could this possibly have meaning? The question doesn’t actually pertain to your money, after all. More importantly, there’s zero referent for estimating the value of reducing your mortality risk by a fraction of one percent. The “benefit” is a total abstraction. It is useless; nonetheless, it makes for a perfect talking point.

Another example of EPA’s numerical black magic occurred in 2012 when the agency undertook a “state-of-the-art value preference survey” to justify a controversial Clean Water Act rule for the Chesapeake Bay. The regulation would cost $27 billion; the direct economic benefits of the rule were far less. So the agency had to engineer “benefits.” EPA set about doing so by calculating the “value” of aesthetic improvement to the Bay for those who would never even visit its shores. This was described as an “ancillary benefit.”

These two bogus figures–the statistical value of a life and the value of improving a body of water you’ll never visit–are among many, all of which serve as the background to the point of this post: EPA this month indicated that it will expand significantly the agency’s bag of statistical *tricks.* In an early February notice, EPA announced:

Over the next three years, the Agency anticipates embarking on a number of survey development efforts associated with a variety of economics projects including those related to valuation of ecosystems, children’s health risks, mortality risk reductions, improvements to coastal waters including the Chesapeake Bay, to name a few.

Note the Orwellian language. EPA’s statistical lies are called “economic projects.” The specific “economic project” at issue in this announcement is the use of focus groups to lend a quantitative value to EPA’s rules and regulations. To the agency’s credit, it is taking comment on the wisdom of its proposal. I plan on submitting a comment, along the lines laid out by this bog post. If you’d like to submit a comment—which I highly recommend—you may do so at this link. If you have any difficulties doing so, email me at [email protected], and I will make sure your comment gets submitted.

*“Special interests” can be in either the private or non-profit sector; regulatory capture occurs whichever party holds the presidency. I fully understand that the Founding Fathers appreciated the necessity of special interests (‘air is to fire as faction is to democracy,’ or whatever the quote is). However, the role of factions is more properly limited to influencing the legislature, rather than effectuating policy through the executive.