“Job-killing regulation” has become a popular part of our political lexicon: but are jobs actually killed by regulation?
In his chapter in the new book Does Regulation Kill Jobs?, Adam Finkel, also one of the book’s co-editors, suggests that lessons learned over the past 25 years from improving the quantitative risk assessment (QRA) of environmental and health hazards can lead to better analyses of whether regulations indeed kill jobs, create them, both, or neither.
Government agencies engage in QRA when they study the harm arising out of particular health or environmental hazards and conclude, for example, that a particular pollutant will injure or kill an estimated number of people. Finkel argues that the controversies and lessons from such analyses are similar to, and can be directly applicable to, the assessment of the regulatory impact on jobs. He draws explicit connections between these two “spheres of analysis,” showing how the controversies faced by QRA may prove instructive for assessing the impacts of regulation on jobs.
To emphasize the parallels between these two forms of analysis, Finkel begins his discussion with a hypothetical proposal to reduce by ten parts per billion the ozone levels to which three hundred million Americans are exposed. Using these numbers, and his prior experience as a regulator, Finkel describes how QRA can estimate the number of lives saved and the total monetary equivalent of life-saving benefits. A jobs impact analysis of the same proposal might indicate that this regulation would result in a loss of a certain number of jobs at a certain cost. However, decision-makers and the public have come to expect the risk analysis to pay attention to various important phenomena, such as the uncertainty in the lives saved, the variation in risk across the population, and the possible ripple effects on other risks of reducing ozone—but don’t have similar expectations for job impact analyses.
According to Finkel, there are three major controversies that QRA has faced that have resulted in lessons that may prove instructive for job impact analysis. First, he points to the debate over whether QRA systematically exaggerates risk, which (if true) could lead to public fear and an incentive for agencies to become still more “conservative” in estimating risk. This debate, he maintains, has led to an over-reaction with agencies adjusting their methods of calculating risk so that they are less conservative, but in doing so also less accurate. Finkel suggests that this controversy may be instructive for jobs impact analysis, so that regulators do not over-react to critiques and seek similarly skewed analyses which lead to overly pessimistic estimates of job loss.
Another key debate that QRA has faced has been the precision with which to estimate risk. Finkel indicates that contemporary risk assessments embrace uncertainty and address the impact of individuals’ interaction with regulation by using other sophisticated methodologies. According to Finkel, risk assessors have abandoned false precision not only because it is scientifically unreliable, but also because “honest portrayals of uncertainty have helped to defuse and moderate controversy.” These lessons in accurately describing the uncertainty in analytical conclusions may also help those engaging in jobs impact analysis, especially as some of the techniques used in risk assessment are “tailor-made for expressing the uncertainty in employment impact.”
Finkel concludes by asserting that we should study the net effects, not merely the immediate impacts, of hazards and regulations to control them. He indicates that it is common for risk-reducing regulations to have multiple consequences and that QRA has in the past been myopic as to the secondary effects, which may either compound the benefit from the regulation or have it result in an overall negative outcome. Finkel suggests that job impact analysis may benefit from doing the same so that “indirect, but salient” effects are also taken into account and the overall outcome becomes the focus of the inquiry rather than merely immediate effects. He asserts that regulators engaged in jobs impact analysis should be free to consider the second-order effects in assessing the net impact of the regulation, while also considering counterfactual scenarios.
Although the debate of the impact of regulation on jobs continues, Finkel concludes by indicating that the history of QRA controversies may not only prove instructive, but also indicate that job impact analysis will continue to be refined and improved.
Finkel ultimately supports rigorous efforts to quantify both the number of net jobs lost or gained and the welfare toll of each job loss, and believes that the results should become part of the bottom-line, cost-benefit comparison of important regulations. He does so for one main reason: without careful quantification, he says, decision-makers lose the ability to give job impacts their proportionate attention. He fears that instead they may treat job impacts as essentially too trivial to change regulatory decisions or too important for anything else (like lives saved) to matter at all.
This post is part of RegBlog’s six-part series, Does Regulation Kill Jobs?