We develop a model of international agreements to price a transboundry externality and provide a new heuristic to aid in interpreting negotiation behavior. Under conservative assumptions, a country’s net benefits will be positive under an efficient pollution price if its share of global damages is less than half its share of worldwide abatement costs. We solve for a permit allocation scheme consistent with that heuristic such that every region will have positive net benefits in an agreement to price the pollution externality at the globally efficient level. We then apply this framework to climate change using regional data from Integrated Assessment Models and test the feasibility of a global climate change treaty. The results indicate that several regions have positive net benefits from a globally efficient price on carbon, including Western Europe, South Asia (including India), and Latin America. We then solve for a permit allocation scheme that should produce worldwide agreement on a climate treaty. Using the same model, we show that differential carbon taxes aimed at producing universal agreement would produce tax rate differences of an order of magnitude. We also argue that shares of global GDP might be an appropriate proxy for exposure to climate damages and find that a global climate treaty would be cost-benefit justified for all countries without transfers when that assumption is used.

This article presents findings from a cost-benefit analysis of the Tulsa Individual Development Account (IDA) program, a demonstration program that was initiated in the late 1990s and is being evaluated through random assignment. The program put particular emphasis on using savings subsidies to help participants accumulate housing assets. The key follow-up data used in the evaluation was collected around 10 years after random assignment, about 6 years after the program ended. The results imply that, during this 10-year observation period, program participants gained from the program and that the program resulted in net costs to the government and private donors, and that society as a whole was probably worse off as a consequence of the program. The article examines in some detail whether these findings are robust to a number of different considerations, including the assumptions upon which the results depend, uncertainly reflected by the standard errors of the impact estimates used to derive the benefits and costs, and omitted benefits and costs, and concludes that they are essentially robust. For example, a Monte Carlo analysis suggests that the probability that the societal net benefits of the Tulsa program were negative during the observation period is over 90% and that the probability that the loss to society exceeded $1000 is 80%. Further analysis considered benefits and costs that might occur beyond the observation period. Based on this analysis, it appeared plausible, although far from certain, that the societal net benefits of the Tulsa program could eventually become positive. This would occur if the program’s apparent positive net impact on educational attainment generates substantial positive effects on the earnings of program participants after the observation period ended. However, there was no evidence that the educational impacts had yet begun to produce positive effects on earnings by the end of the observation period.

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%.

Following the prototype of Mexico’s Progresa program, a number of countries in Latin America and the Caribbean have initiated conditional cash transfer (CCT) programs. More recently, countries in Sub-Saharan Africa (SSA) have followed suit. However, no comprehensive framework to carry out a cost-benefit analysis (CBA) exists. This paper presents such a CBA framework for CCTs which enables design features such as targeting and conditionality to be separately evaluated. The framework is applied to an evaluation of a CCT program for orphans and vulnerable children in Kenya. The role of conditionality in SSA and the need for distribution weights is discussed.

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 literature on Congressional control of the bureaucracy has examined how members of Congress pursue strategies such as oversight, the limitation of discretion in legislation [Moe, T. (1989). The politics of bureaucratic structure. In J. E. Chubb & P. E. Peterson (Eds.), Can the Government Govern? Washington, DC: Brookings Institution); Huber, J. D., & Shipan, C. R. (2002). Deliberate discretion: The institutional foundations of bureaucratic autonomy. New York: Cambridge University Press], and the use of tools such as administrative procedures [McCubbins, M., & Schwartz, T. (1984). Congressional oversight overlooked: police patrols vs. fire alarms. American Journal of Political Science, 21(1), 165–179; McCubbins, M., Noll, R., & Weingast, B. (1987). Administrative procedures as instruments of political control. Journal of Law, Economics, and Organization, 3, 243–277] and limitation riders [MacDonald, J. A. (2010). Limitation riders and congressional influence over bureaucratic policy decisions. American Political Science Review, 104 (November), 766–782] to exert influence over executive agency decision making. One area where Congress has attempted to exert control over agency decision-making is through the legislative modification of one of the most common bureaucratic decision-making tools: benefit-cost analysis (BCA). While scholars have examined political influence in agency regulatory impact analysis BCAs for proposed rules [Shapiro, S., & Morrall III, J. F. (2012). The triumph of regulatory politics. Benefit-cost analysis and political salience. Regulation and Governance, 6(2), 189–206], there has been a lack of examination of Congressional modification of agency BCA processes to justify and protect particularized [Mayhew, D. (1974). Congress: The electoral connection. New Haven, CT: Yale University Press] infrastructure projects in their districts. This paper will examine the effect of Congressional control over agency BCA processes to secure particularized benefits by developing an in-depth case study of the Federal Contact Tower Program (FCTP) operated by the Federal Aviation Administration (FAA) that examines the political and public management implications of Congress’s limitation of the FAA’s autonomy to operate the FCTP under current benefit-cost guidance. Building upon the literature on particularized benefits and Congressional delegation, the results of this study indicate that members of Congress use BCA processes to insulate infrastructure projects in their districts by restricting the ability of agencies to optimize program effectiveness.

Hong Kong’s franchised buses contribute significantly to its high pollution levels, which in turn result in excess mortality and hospitalizations. I show that replacing all of Hong Kong’s pre-Euro IV buses with cleaner Euro V buses would save 1260 statistical lives, among other benefits. The expected net benefit of such a project is HK$26.4 billion under a discount rate of 3.5%. This result is robust to a discount rate of 10% and a mortality decrease of half of what is expected. This is one of the first studies to estimate the public health impact of air pollution from franchised buses in Hong Kong. The city can therefore consider conducting accelerated replacement of its franchised bus fleet. Given the strongly positive result, other Asian cities with ageing bus fleets could also conduct similar benefit-cost analyses.

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.

Five states and Puerto Rico currently provide disability insurance to persons unable to work due to temporary disability. No states have adopted such policies since 1969. Labor unions and other advocacy groups have advanced bills in Washington and Oregon that would establish a public disability insurance plan to provide partial wage replacement for serious illness, accident and pregnancy. This paper estimates annual costs and benefits for a temporary disability insurance program in Washington State under the assumption that it would mirror the disability provisions in California without paid family leave.

The risk of dying in fires in nursing homes is six times the risk of dying in fires at home in Sweden. One way to reduce this risk is to install fire sprinklers. This study measures the benefits using value of full lives, life years and quality adjusted life years (QALYs) for deaths and injuries. The results show that sprinklers are cost-effective in newly built nursing homes no matter what value of life is used. However, if sprinklers are installed in already existing buildings, they are cost-effective only if the value of a statistical life is used.

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.

Circular A-94 specifies how analysts should discount costs and benefits of government projects, and thus how to account for risk. In this paper, we argue that the methods mandated by A-94 properly account for non-systematic and term risk, but not for systematic risk. A numerical example illustrates how improper accounting for systematic risk produces misleading results and social welfare loss. We conclude by proposing a simple modification of A-94’s procedures that would allow analysts to at least partially account for systematic risk.

We provide a theoretical and empirical comparison of two historic production quota buyouts: the 2002 US Peanut Quota Buyout and the 2004 US Tobacco Quota Buyout. Producer compensation under the US Peanut Quota Buyout came from the treasury while the US Tobacco Buyout was paid for by a consumer tax (i.e., tobacco tax). Given these two buyouts, an important question arises: How does the method of compensation affect distribution and efficiency? Producers, consumers, and society favor a treasury buyout (TB) for several reasons. Producers are compensated considerably more under a TB, consumers are not burdened with the charge of funding the buyout, and society does not face additional efficiency losses due to the buyout.

Many people have wondered why the US government conducts cost-benefit analysis with close reference to the value of a statistical life (VSL). It is helpful to answer that question by reference to the “Easy Cases,” in which those who benefit from regulatory protection must pay for it. In such cases, WTP is usually the right foundation for VSL, because beneficiaries are hardly helped by being forced to pay for regulatory protection that they believe not to be in their interests. In the Easy Cases, arguments from both welfare and autonomy support the use of WTP and VSL (with potentially important qualifications involving imperfect information and behavioral market failures). The analysis is less straightforward in harder cases, in which beneficiaries do not pay for all of the cost of what they receive (and may pay little of that cost). In such cases, arguments from welfare and autonomy might not lead in any clear direction. In the harder cases, regulation might be justified on welfare grounds even if the cost-benefit analysis (based on VSL) suggests that it is not. In principle, a direct inquiry into welfare (the master concept) would be preferable to use of cost-benefit analysis. In the harder cases, distributional considerations might also count in favor of proceeding (as prioritarianism suggests). But at the current time, direct inquiries into welfare consequences and into distributional effects are challenging in practice, and hence regulators should generally rely on cost-benefit analysis, making welfarist adjustments, or adjustments based on distributional considerations, only in compelling cases.

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.

The social opportunity cost of capital discount rate is the appropriate discount rate to use when evaluating government projects. It satisfies the fundamental rule that no project should be accepted that has a rate of return less than alternative available projects, and it ensures that worthy projects satisfy the potential Pareto test. The social time preference approach advocated by Moore et al. fails to satisfy either of these criteria even in the unlikely case that the private sector behaves myopically with respect to a project’s future benefits and costs.

The decades-old literature on the correct method for choosing and estimating a social discount rate (SDR) has resulted in two, largely opposing viewpoints. This note seeks to clarify the key sources of disagreement between these two camps. One view advocates that the choice should be based chiefly on the social opportunity cost of the return to foregone private capital investment (SOC), and suggests a SDR of around 7%. The other viewpoint, expressed by the authors, argues that the choice should be based on the social rate of time preference (STP), the rate at which society is willing to trade present for future consumption, suggesting a SDR of around 3.5%. Because of the fundamentally normative basis of the SDR choice, neither approach generates testable hypotheses that would allow falsification. For government project evaluation, the choice ultimately depends on the opportunity cost of public funds, which in turn depends on how fiscal policy actually operates. The STP approach contends that governments set targets for deficits and public debt, so that a marginal government project will be tax-financed, largely crowding out current consumption. The SOC belief is that governments set revenue targets, so that any government project will be deficit-financed on the margin, which will largely crowd out private investment. The authors also argue that a SDR based on the STP approach is appropriate for: benefit-cost analysis of government regulations, self-financing government projects, and government cost-effectiveness studies.