Title: Government Analysis Of The Benefits And Costs Of Regulation
Abstract: Expenditures incurred because of federal environmental, health, and safety regulation have grown dramatically in recent decades, and now total several hundred billion dollars annually. These costs appear likely to increase significantly in the next decade, as well. Yet the economic impacts of regulation receive much less scrutiny than direct, budgeted government spending. The potential gains of regulatory reform are substantial. Research suggests that more than half of the federal government's regulations would fail a strict benefit-cost test using the government's own numbers (Hahn, 1998). There is ample research suggesting that regulation could be significantly improved, so that we could save more lives with fewer resources (Morrall, 1986; Viscusi, 1996). One study found that a reallocation of mandated expenditures toward those regulations with the highest payoff to society could save as many as 60,000 more lives a year at no additional cost (Tengs and Graham, 1996). Recently, Congress has begun to show a greater interest in assessing the economic impact of regulation. In 1996, Senator Ted Stevens of Alaska added an amendment to the Omnibus Consolidated Appropriations Act of 1997 that required the director of the Office of Management and Budget (OMB) to provide Congress with estimates of the total annual benefits and costs of all federal regulatory programs and estimates of the benefits and costs of individual regulations. This statute was the first to mandate such an accounting. In September 1997, the OMB produced its first report on the benefits and costs of regulation in response to the Stevens amendment, and it recently completed a second report in the fall of 1998. At this point it is not clear whether Congress will require additional reports. This essay reviews the increasing use of economic analysis in regulatory decision-making, assesses the first OMB report, and considers how the use of economic analysis can help to inform regulatory decision-making.