Recently, a number of authors, including Burgess and Zerbe, have recommended the use of a real social discount rate (SDR) in the range of 6–8% in benefit-cost analysis (BCA) of public projects. They derive this rate based on the social opportunity cost of capital (SOC) method. In contrast, this article argues that the correct method is to discount future impacts based on the rate of social time preference (STP). Flows in or out of private investment should be multiplied by the shadow price of capital (SPC). Using this method and employing recent United States data, we obtain an estimate of the rate of STP of 3.5% and an SPC of 2.2. We also re-estimate the SDR using the SOC method and conclude that, even if analysts continue to use this method, they should use a considerably lower rate of about 5%.

Given that President Obama’s Executive Orders on regulation have emphasized the importance of retrospective analysis and review of existing federal rules, I survey the state of retrospective analysis and review of federal regulations. I first ask how much is known about the economic merit of past federal regulatory decisions, based on retrospective economic analyses of their effects. I review reports of the Office of Management and Budget and related literature, but unlike those reports I find only five rules, issued by the National Highway Traffic Safety Administration (NHTSA), for which retrospective analyses provide estimates of both costs and reasonably good proxies for benefits (e.g., adverse health effects avoided). Other retrospective studies of federal rules estimate are incomplete, estimating only the compliance costs, or only the benefits, or only costs and measures of effectiveness, like emissions reductions, which do not closely relate to people’s welfare.

I also seek to explain differences in the practice of retrospective analysis and review between NHTSA, which appears to have the best record of retrospective analyses among federal agencies, and the Environmental Protection Agency (EPA), an important regulatory agency. I find that NHTSA regularly conducts such analyses and reviews, while EPA rarely does retrospective analysis and presents rulemakings that look like business as usual as being the result of a retrospective review. I analyze the role of data limitations, statutory authority, and institutional incentives in influencing the different behaviors of these two agencies. I conclude that differences in data availability and in particular the lack of relevant control groups, are an important barrier to retrospective analysis at EPA. This data deficiency, combined with important restrictions on EPA’s ability to consider information on net benefits or cost-effectiveness in its rule-making, are together the biggest hindrance to generating better information about the effects of its rules. I conclude with recommendations intended to generate more measurement of the actual effects of regulations.

The Census of Fatal Occupational Injury (CFOI) provides data for creating objective measures of workplace risk used in estimations of wage-risk premia for value of statistical life (VSL) calculations. This relatively new data set enables a more theoretically defensible measure for use in hedonic wage equations. However, constructing these rates from the CFOI data necessarily involves creating an industry-occupation matrix defining the “jobs,” deciding whether or not to include the self-employed, and selecting a denominator. These choices in the construction of the risk measure alone, as shown here, result in variations of VSL estimates ranging from $8 million to $18 million. Further, risk measures based on the CFOI data, regardless of construction, are sensitive to simple changes in the specification for the hedonic wage equation. In particular, fixed effects describing the industry in which a worker is employed, as well as the worker’s occupation, are primary influences on the magnitude of the VSL estimates.

The water quality index (WQI) has emerged as a central way to convey water quality information to policy makers and the general public and is regularly used in US EPA regulatory impact analysis. It is a compound indicator that aggregates information from several water quality parameters. Several recent studies have criticized the aggregation function of the EPA WQI, arguing that it suffers from “eclipsing” and other problems. Although past papers have compared various aggregation functions in the WQI (usually looking at correlation), this is the first paper to examine these functions in the context of benefit-cost analysis. Using data from the 2003 EPA CAFO rule, the present paper examines four aggregation functions and their impact on estimated benefits. Results indicate that the aggregation method can have a profound effect on benefits, with total benefit estimates varying from $82 million to $504 million dollars. The net benefits of the rule vary from negative to positive over this range of estimates. Furthermore, a sensitivity analysis does not find convincing evidence to substitute the current aggregation function, although several changes to the underlying WQI methodology may be warranted.

Many public policies and private actions affect the risk of injury, illness, or death, yet changes in these risks are not easily valued using market prices. We discuss how to value these risk reductions in the context of benefit-cost analysis. We begin with a pragmatic focus, describing the analytic framework and the approaches currently used for valuation, including estimates of willingness to pay, cost of illness, and monetized quality-adjusted life years. We then turn to some conceptual issues that illustrate areas in need of further exploration.