While DHS sought a monetized benefit-cost analysis based on case studies, early scoping of the project left the way open for multi-criteria decision analysis, cost-effectiveness, and qualitative analysis. Our team developed new ways to modify and implement standard models and, somewhat to our surprise, found that benefit-cost analyses were possible in almost all cases. Along the way, we learned a lot about the power of basic benefit-cost analysis, but also learned lessons about baselines, context, and using sparse data with sensitivity and uncertainty analysis.

Professor Martin Weitzman passed away unexpectedly at the end of August 2019. A substantial number of accounts of his many contributions to economics in general and environmental economics in particular are available, and collectively provide a good overview of his contributions and influence on the profession (see links at the end of this post). In this short note, I want to highlight some aspects of his works that are relevant for applied welfare economics in general and cost-benefit analysis in particular. I single out two stellar contributions that opened up new vistas for research and enriched the literature on welfare measurement.

Perhaps the most direct application of his celebrated “dismal theorem” (Weitzman 2009) is that cost-benefit analysis has little to offer when it comes to global climate policy. Indeed, given the assumptions of his model, comparing benefits and costs provides no useful information to decision-makers in this particular context.

The National Center for Children in Poverty reports that 21% of American children are living in poverty, including 46% of African American and 40% of Latino children. Compared to non-poor children, on average impoverished children are 15.6% less likely to graduate high school and 37% more likely to be unemployed as adults.

Research has documented that high-quality early childhood education boosts the skills of disadvantaged children in the short-term. However, a recent series of articles finds that comprehensive early childhood education programs have positive long-term impacts on earnings, criminal activity, and health. Such programs remediate socioeconomic inequality by improving the economic prospects of their participants. While the boost in cognitive skills eventually fades away, the boost in non-cognitive skills persists over the life cycle.

The Carolina Abecedarian Project (ABC) and the Carolina Approach to Responsive Education (CARE)—the continuation of ABC—are early childhood education programs that promote skills (such as language) and cognitive development, providing treatment until age 5 for 50 weeks per year. García et al. (2018a) conducted a benefit cost analysis of these programs by monetizing the benefits of treatment for the participants over their lives, and comparing benefits to programmatic costs.

ABC/CARE improves the language and development skills of children and, subsequently, their years of education completed. Figure 1, which is reproduced from Garcia et al. (2018a), displays the average life-cycle net present values per program participant of the main components of the ABC/CARE programs. Benefits were measured from birth to forecasted death, discounted to birth at a rate of 3%. Programmatic costs are adjusted to reflect the welfare cost of taxation to fund the programs. Both benefit and cost estimates are statistically significant at standard levels, and account for forecasting and estimation error, and are adjusted for. As indicated in the figure, higher future earnings and the avoided cost of crime (to society) are significant components of the benefit of the program.

Over four decades ago I struggled through my first year of graduate school in economics, a struggle made palatable by the extraordinary professor who taught my first economics course. Deirdre McCloskey was (and is) smart, fun, and eccentric, and she enthusiastically led us through our first pass at economics. Part of that passage included learning to write, for McCloskey held – a notion considered eccentric – that economists should write well. Although good writing remains suspect among economists, Deirdre McCloskey taught me long ago that good writing makes for good economics.

In class, McCloskey stressed the value of writing well, passing out class notes on writing. I kept the notes for many years and hopefully studied them as I attempted to become a passable writer. I finally discarded the notes when they and much else appeared in McCloskey’s 1985 article, “Economical Writing.” The article soon became a short book of the same title; a second edition followed thirteen years later. We now are rewarded with a third edition of Economical Writing, with a new subtitle: Thirty-Five Rules for Clear and Persuasive Prose (University of Chicago Press, 2019). McCloskey’s personality pervades her little book, which is fun to read and humbling to those of us who would write better.

In the following interview I asked Richard Zeckhauser to recount what it was like to be part of the “Whiz Kids,” the name given to a group of experts with which Robert McNamara (then Secretary of Defense and later President of the World Bank) surrounded himself in order to turn around the management of the United States Department of Defense in the 1960s. The group sought to shape government decision making by bringing in economic analysis, operations research, game theory, and computing, as well as by implementing new methods, such as Planning Programming Budgeting System (PPBS). Their efforts did a lot to extend and solidify the influence of the principles of benefit cost analysis in U.S. Federal government decisions.

The interview with Richard is a complement to Alain Enthoven’s new article, “How Systems Analysis, Cost-Effectiveness Analysis or Benefit-Cost Analysis First Became Influential in Federal Government Program Decision-Making," appearing in the upcoming Summer 2019 Journal of Benefit Cost Analysis (Volume 10, No. 2). There Alain recounts in detail his experience as a Whiz Kid and the origins of the cost-benefit analysis movement in government as a tool for planning and budgeting.

The field of benefit-cost analysis is replete with guidance on theoretical and empirical valuation of impacts. Many fewer resources, however, are available for analysts to consult when determining the set of policy impacts to value in the first place. This post describes a new article published with co-authors Joseph Ripberger, Wesley Wehde, Hank Jenkins-Smith, Carol Silva, Kuhika Gupta, Benjamin Jones, and Robert Berrens, in the Spring 2019 Issue of the Journal of Benefit-Cost Analysis. The article, entitled, ‘Benefit-Cost Analysis, Policy Impacts, and Congressional Hearings,’ proposes a method for identifying policy impacts that contributes a degree of systematism, transparency, and replicability to the process.

Academic researchers and government institutions have both encouraged retrospective analysis of the costs and benefits of regulation to facilitate evidence-based review and possibly revision of the design and stringency of existing regulations (White House 2012; Morgenstern 2015). However, rigorous examples of these types of ex post analyses are relatively rare. This post describes a study comparing the retrospective costs (evaluated ex post) of a U.S. Environmental Protection Agency (EPA) regulation to the cost estimates reported during the regulatory process (calculated ex ante). These findings are reported in more detail in a recent article, “Retrospective Evaluation of the Costs of Complying with Light-Duty Vehicle Surface Coating Requirements,” published in the Spring Issue of the Journal of Benefit Cost Analysis, with co-authors Nathalie Simon and Ann E. Ferris.

In recent years, the EPA has attempted to conduct retrospective cost analysis systematically by developing a framework that identifies the main cost components and key questions analysts should ask when evaluating them ex post.  (The framework is described in detail in an article from a 2014 Special Issue of the Journal of Benefit Cost Analysis, Retrospective Cost Analyses of EPA Regulations: A Case Study Approach.)

Since Ronald Reagan’s 1981 Executive Order 12291 established benefit-cost analysis as standard practice for major rule changes, benefit-cost analysis has been commonly used to assess the efficiency of proposed federal regulations. Because of this and subsequent executive orders, all federal regulations that are projected to have a total economic impact of over $100 million are subject to a full benefit-cost analysis. Despite this prevalence at the federal level, benefit-cost analysis is much less common at the state level. In 2013, the Pew-MacArthur Results First Initiative released a study of the use of benefit-cost analysis in the states (study results were subsequently reported in the Journal of Benefit Cost Analysis in 2015). The study found that, over the four years from 2008 to 2011 states conducted only 36 full cost benefit analyses and 312 partial cost-benefit analyses. This averaged out to 9 full analyses and 78 partial analyses per year across all 50 states.

Administrative agencies, courts, and litigants are just coming off two years of intense debates over the legality of agency deregulation through delay. One fascinating development has been how significant cost-benefit analysis has been in these debates. Cost-benefit analysis has formed the basis for several important court losses suffered by the administration. (See Air Alliance 2018; California 2017.) Now agencies have proposed to repeal many big-ticket rules, including the Clean Power Plan, the Clean Water Rule, and vehicle emissions standards. A key question is what role cost-benefit analysis will play in the upcoming legal battles over repeals.

The 2019 Annual Conference and Meeting of the Society for Benefit-Cost Analysis took place March 13-15 at George Washington University’s Marvin Center. The conference was attended by 329 friends of benefit-cost analysis, the largest number of attendees since the first conference in 2008. The attendees were treated to a cornucopia of benefits and costs, eminent speakers, and good conversation.

Since the 1964 Surgeon General’s report linking smoking cigarettes to adverse health outcomes, numerous federal, state, and local governments have passed regulations designed to reduce the prevalence of smoking and related externalities. Examples of such regulations include cigarette taxes, public health campaigns, minimum purchasing ages for tobacco, and – the focus of this post – smoking bans in bars and restaurants. While the links between smoking and health are clear, the effects of these bans on social welfare, which includes other types of risky behavior as well as smoking, are less well understood. This post describes work-in-progress to address some of the gaps. Preliminary results will be presented at the Annual Conference and Meeting of the Society for Benefit-Cost Analysis in March 2019.

There is growing skepticism among both academics and government officials about the benefits of large-scale sport and cultural events. Although Input-Output (IO) has long been the dominant approach to estimating the impacts of these events, the method faces criticism for both its lack of realism and the incompleteness of its results. Consequently, economists have begun to turn to two alternative approaches: computable general equilibrium (CGE) and cost-benefit analysis. These approaches can take into account effects not captured within an IO framework. They also often produce strikingly different results than those obtained using an IO model. This post reports some preliminary results from ongoing research evaluating nearly 60 studies that use cost-benefit methods to evaluate events. More complete results will be presented at the Society for Benefit-Cost Analysis Conference in March 2019.

An IO approach is fundamentally a multiplier approach, converting expenditures (on infrastructure, for example) into gross production in the host city. One limitation is that IO treats expenditures, such as those for infrastructure or by the local population, as fully additional; since this approach does not take account of substitution (i.e., that these resources have been diverted from other uses), it may overstate the favorable economic impact of an event. Another concern is IO’s focus only on gross domestic product and other related impacts, rather than on welfare, which also recognizes externalities and opportunity costs (Massiani 2018).

The earliest examples of the use of cost-benefit analysis and CGE to evaluate mega-events appeared in the 1980s and 1990s, respectively. Since then, almost 60 cost-benefit analyses of mega events of different sizes have been conducted. (For an examination of the use of CGE in evaluating mega-events, see Massiani (2018a).)

Fomenting revolution brings to mind crowds storming the barricades, not analysts struggling to debug a spreadsheet or craft a clear sentence. Yet in his book, The Cost-Benefit Revolution, Cass Sunstein (Robert Walmsley University Professor, Harvard Law School) argues that benefit-cost analysts are doing exactly that. The barricades we surmount are decision-making errors resulting from overreliance on intuition and emotion, our weapons are science and economics, and our achievements are better policies.