Working Papers June 2016

Working Paper Series

We welcome papers submitted by SBCA members on topics in benefit-cost analysis for circulation as part of this working paper series. The Society shares these papers as a service to its members and the benefit-cost analysis community. The Society for Benefit-Cost Analysis does not edit the papers before sharing and inclusion of a working paper here does not constitute endorsement by the Society of any of its content.  

SBCA members interested in submitting their working papers for future issues may contact Erika Dowd, Executive Director, at

Unquantified Benefits and the Problem of Regulation Under Uncertainty

Authors: Jonathan S. Masur and Eric A. Posner (University of Chicago Law School)

Abstract: Regulatory agencies are required to perform cost-benefit analysis of major rules. However, in many cases regulators refuse to report a monetized value for the benefits of a rule that they issue. Sometimes, they report no monetized value; at other times, they report a monetized value but also state that not all benefits have been quantified. On occasion, regulators also refuse to monetize or fully monetize costs. These practices raise a puzzle. If a regulator chooses not to monetize all the benefits or all the costs, it is not doing cost-benefit analysis. If it is not doing cost-benefit analysis, what is it doing?  To investigate this question, we compiled a data set consisting of all major regulations issued by agencies from 2010 to 2013. We come to three conclusions. First, there are countless examples where agencies fail to fully monetize the benefits and costs of regulations. Second, in most cases, agencies could easily monetize or partially monetize those benefits and costs. Third, even where monetization would be difficult, the agencies could and should have made explicit the implicit valuations they relied on and supported those valuations as much as possible with empirical evidence. We then proceed to explain how agencies could engage in cost-benefit analysis even when they do not have a reliable basis for estimating valuations. Even where they lack complete data, agency regulators may be able to make reasonable guesses about the harms or benefits from regulations. In many cases, these guesses will be based on the experience and latent knowledge of the agency staff. These preliminary guesses constitute Bayesian prior probabilities. While agencies should be permitted to “guess”—that is, supply a subjective prior probability—they must also be required to update their estimates as they gain new information.


A Benefit-Cost Analysis of the Middle Fork Greenway Trail

Authors and affiliations: John C. Whitehead, John Lehman and Melissa Weddell, Appalachian State University

Abstract: The Town of Boone, NC Greenway Trail is a 3.84 mile long paved trail with additional unpaved sections that attract many types of users including walkers, joggers, and cyclists. The proposed Middle Fork New River extension would add 6.5 miles to the total paved mileage. In order to estimate recreation benefits of the extension we use revealed and stated preference data to estimate the change in value of current visits and change in visits with the additional mileage. The total opportunity cost of the project includes land acquisition, construction, operation and maintenance costs. Considering only recreation benefits the Middle Fork Greenway Trail passes a benefit-cost test. The net present value is estimated to be $2.78 million. This conclusion does not change after considering a number of partial sensitivity analyses.


Risk Beliefs and Preferences for E-Cigarettes

Author: W. Kip Viscusi (Vanderbilt University)

Abstract: Drawing on evidence from a new nationally representative survey, this article examines several measures of risk beliefs for e-cigarettes. For both lung cancer mortality risks and total smoking mortality risks, respondents believe that e-cigarettes pose risks that are lower than the risks of conventional tobacco cigarettes. However, people greatly overestimate the risk levels of e-cigarettes compared to the actual risk levels. Risk beliefs for conventional cigarettes receive at least a two-thirds informational weight in the formation of e-cigarette risk beliefs. Public perceptions of nicotine levels of e-cigarettes are closer to the beliefs for conventional cigarettes than are their health risk perceptions. Consumers’ desired uses of e-cigarettes are more strongly related to health risk perceptions than perceived e-cigarette nicotine levels. The overestimation of e-cigarette risks establishes a potential role for informational policies.​


Exploring Cost-Benefit Analysis of Research, Development and Innovation Infrastructures: An Evaluation Framework

Authors and affiliations: Massimo Florio (Department of Economics, Management and Quantitative Methods, University of Milan), Chiara Pancotti (CSIL Centre for Industrial Studies, Milan), Emanuela Sirtori (CSIL Centre for Industrial Studies, Milan), Silvia Vignetti (CSIL Centre for Industrial Studies, Milan), Stefano Forte (TIF Lab, Department of Physics, University of Milan and INFN Milan)

Abstract: Governments, funding agencies and policy makers have high expectations for research, development and innovation (RDI) infrastructures in the context of science and innovation policies aimed at sustaining economic growth in the long term. The stakes associated with their selection and evaluation are therefore high. Cost-benefit analysis of RDI infrastructures is a new field. The intangible nature of some benefits and the uncertainty associated to the achievement of research results have often discouraged the use of a proper CBA for RDI infrastructures. Recently, some attempts to develop a CBA theoretical framework for RDI infrastructures have been made in the context of the use of Structural Funds by the Czech government and JASPERS. Moreover, the new Guide for the CBA of investment projects in the context of Cohesion Policy, recently adopted by the European Commission (2014) provides guidelines to appraise RDI projects, but also admits that – due to lack of experience and best practices – further steps are needed to improve the evaluation framework.

This paper presents the results and the lessons learned on how to apply ex-ante CBA for major RDI infrastructures by a team of economists and scientists at the University of Milan and CSIL during a three-year research project supported by a EIBURS grant of the European Investment Bank Institute. Albeit the comprehensive conceptual framework presented in the paper builds on principles firmly rooted in CBA tradition, their application to the RDI sector is still in its infancy. So far, the model has been applied on two cases in physics involving particle accelerators (the Large Hadron Collider (LHC) at CERN and the National Centre for Oncological Treatment (CNAO) in Italy)). In a nutshell, the model presented breaks down benefits into two broad classes: i) use benefits, held by different categories of infrastructure’s users such as scientists, firms, students and general public visitors, and ii) non-use benefits, denoting the social value for the discovery potential of the RDI infrastructure regardless of its actual or future use. We argue that the social value of discovery can be estimated with contingent valuation techniques. Another significant feature of our approach is the stochastic nature of the CBA model, intended to deal with the uncertainty and risk of optimism bias in the estimates.


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Working Paper Series - Working Papers June 2016