generated: 2026-02-03 08:37:19

All times in US Eastern Time

Program at a Glance

Thursday March 12, 2026

9:00 AM - 9:30 AM

Registration and Continental Breakfast

Plenary

9:30 AM - 11:15 AM

Opening Remarks and Keynote by Amitabh Chandra

Plenary

11:30 AM - 12:30 PM

Awards Luncheon

Plenary

1:00 PM - 2:30 PM

Quantifying Trade-Offs: Frontiers in Measuring Efficiency, Productivity, and Sustainability

Full Panel of Research Presentations

Preferences: From Surveys to AI: Improving the Credibility of Valuation Evidence

Full Panel of Research Presentations

Pharmaceuticals: When Price Caps Meet Innovation and Patient Outcomes

Full Panel of Research Presentations

Community Readiness and Public Engagement in Climate–Health Decision Making

Roundtable/Panel

Innovative Financing for Climate-Resilient Food Systems: A Benefit-Cost Analysis Clinic

Innovative Session

2:45 PM - 4:15 PM

Water and Land Quality Valuation

Full Panel of Research Presentations

Health Risk Valuation over the Lifetime

Full Panel of Research Presentations

Preferences: Designing Better Stated-Preference Evidence for Benefit–Cost Decisions

Full Panel of Research Presentations

Preferences: New Approaches to Preference Measurement in Applied Policy

Full Panel of Research Presentations

Designing a National Benefit Cost Analysis System - and how Generative AI can help

Roundtable/Panel

4:30 PM - 6:00 PM

Ecosystems, Wildlife, and Environmental Policy

Full Panel of Research Presentations

Risk: Valuing Health and Environmental Risks Under Nonlinear Responses

Full Panel of Research Presentations

Valuation: Extending Benefit–Cost Analysis: Behavior, Capitalization, and Distribution

Full Panel of Research Presentations

Preferences: What We Measure When We Elicit Value and Willingness to Pay

Full Panel of Research Presentations

The UK’s experience of using CBA to shape regulatory policy

Roundtable/Panel

6:00 PM - 7:30 PM

Reception

Plenary

Friday March 13, 2026

8:30 AM - 9:00 AM

Registration and Continental Breakfast

Plenary

9:00 AM - 10:30 AM

Valuing the Environment: Modeling Trade-Offs in Regulation, Ecosystems, and Global Sustainability

Full Panel of Research Presentations

Housing: Sorting, Prices, and Welfare Under Building Regulations

Full Panel of Research Presentations

Preferences: Evidence on stated-preference valuation and elicitation design in Policy Appraisal

Full Panel of Research Presentations

Water: Water Quality, Pricing, and Welfare in Practice

Full Panel of Research Presentations

OECD Mortality Risk Valuation Report

Roundtable/Panel

10:45 AM - 12:15 PM

Public Programs: Evidence from Applied Benefit–Cost Analysis

Full Panel of Research Presentations

Governance: Evaluating Complex Regulatory Interventions

Full Panel of Research Presentations

Valuation: New Empirical Tools for Applied Benefit–Cost Work

Full Panel of Research Presentations

Reframing Regulatory Budgeting: Integrating Retrospective Review and Evidence-Based Governance

Roundtable/Panel

Benefit–Cost Analysis and the Courts

Roundtable/Panel

12:30 PM - 2:00 PM

Luncheon Keynote With Solomon Hsiang

Plenary

2:15 PM - 3:45 PM

Valuing Health and Environmental Risk Reductions

Full Panel of Research Presentations

Climate Policy: Climate Benefits Beyond the Headlines: Evidence and Methods

Full Panel of Research Presentations

Equity: Equity, Ranking, and Welfare in Policy Appraisal

Full Panel of Research Presentations

Practical considerations in conducting benefit cost analysis

Roundtable/Panel

4:00 PM - 5:30 PM

The Year in Review and the Year Ahead: Perspectives on U.S. Regulation

Roundtable/Panel

SBCA Program

1. Registration and Continental Breakfast [Plenary]
Thursday | 9:00 am-9:30 am | Grand Ballroom

2. Opening Remarks and Keynote by Amitabh Chandra [Plenary]
Thursday | 9:30 am-11:15 am | Grand Ballroom

3. Awards Luncheon [Plenary]
Thursday | 11:30 am-12:30 pm | Grand Ballroom

4. Quantifying Trade-Offs: Frontiers in Measuring Efficiency, Productivity, and Sustainability [Full Panel of Research Presentations]
Thursday | 1:00 pm-2:30 pm | Amphitheater

Organizer: Carl Pasurka, Unaffiliated

From Rhetoric to Reform: Civil Service Employment Structures and the Measurement of Government Efficiency Deborah Aiken, unaffiliated; and Carl Pasurka, Unaffiliated show abstract

Improving government efficiency has long been a central policy objective. Reducing inefficiency enables governments to expand services without increasing expenditures, lower the costs of current service levels, or achieve both simultaneously. While the goal is broadly shared, the effectiveness of specific policy interventions varies. This study applies production efficiency metrics—technical, allocative, and scale efficiency—to evaluate whether employment structure (at-will vs. merit-based) correlates with government performance. Drawing on state-level data across core functions including transportation, infrastructure, public safety, welfare, and health, we find no meaningful differences in efficiency between employment systems. We argue that policymakers should shift focus toward empirically grounded interventions targeting input composition, labor quality, and organizational design. Measures to promote good management practices in the government and civil servant competence are more likely to improve government efficiency. Tools grounded in the economic theory of production offer tractable methods for diagnosing inefficiency and guiding reform.
Sustainable Productivity Indicators: Private or Societal Perspective? Moriah Bostian, Lewis&Clark College show abstract

Given limited resources on this planet, multiple environmental threats, and a severe climate crisis, many policies, programs, and initiatives (e.g., UN’s Sustainable Development Goals) aim at pro-moting so-called ‘sustainable productivity growth’ to ensure a sufficient supply of food and other goods for a growing population with minimal environmental damage. In order to assess whether a farm or firm, a sector, a country or a region, or the planet as a whole has sustainable productivity growth and to assess the efficacy of policies and programmes that aim at promoting sustainable productivity growth, it is imperative to have reliable ways of measuring sustainable productivity. Although traditional productivity is unequivocally defined as outputs divided by inputs, perhaps somewhat surprisingly, neither a clear definition of sustainable productivity (growth) nor a well-suited method for measuring it exists. This paper briefly reviews current approaches for measuring ‘environmentally adjusted’ productivity, that take into account environmental effects of production, i.e., the ‘environmental pillar’ of sustainability. By extending these approaches to also include the ‘social pillar’ of sustainability, we derive measures of ‘sustainable productivity’. While most existing studies for measuring environmentally adjusted productivity take the perspective of the producer, we point out that it is important to also take into account the society’s perspective when measuring sustainable productivity. We suggest how one can take into account the society’s perspective when measuring sustainable productivity and we compare sustainable productivity measures from the producer’s and the society’s perspective.
Shadow Pricing Ecosystem Services in Boreal Forests Moriah Bostian, Lewis&Clark College show abstract

Boreal forests are multifunctional landscapes that simultaneously supply market goods, such as timber and bioenergy, and crucial non-market ecosystem services, including biodiversity and carbon sequestration. Managing these outputs inevitably involves trade-offs. To quantify them, we estimate shadow prices using a multiple-output directional distance function (DDF) that accounts for both desirable and undesirable outputs. We extend the standard model by endogenizing the directional vector and correcting for sampling variation via boot-strap methods. Applying this framework to a county-by-year panel of Swedish forests (2008–2014), we find that shadow prices vary across space and time but remain generally low. This suggests that enhancing biodiversity and carbon sequestration could be achieved with limited opportunity costs for timber production. Further, we explore substitution patterns through Morishima elasticities, offering guidance on least-cost strategies for improving environmental outcomes. Our results reveal underexploited potential for conservation policy to capitalize on the relatively low costs of ecosystem service provision in boreal forest systems.

5. Preferences: From Surveys to AI: Improving the Credibility of Valuation Evidence [Full Panel of Research Presentations]
Thursday | 1:00 pm-2:30 pm | Room 308

The value of wetlands in reducing flood losses Jesse Gourevitch, Environmental Defense Fund; Adam Gold, Environmental Defense Fund; and Helena Garcia, University of North Carolina - Chapel Hill show abstract

Wetlands provide a range of ecosystem services that support human well-being. However, a lack of actionable information about the economic value of these services has contributed to policies that have failed to protect these ecosystems. We address this challenge by quantifying the value of wetlands in reducing riverine flood damages across the entire U.S. Our approach leverages flood insurance claims data and annually observed changes in wetland area between 1985 and 2023, allowing us to compare multiple claims for single properties before and after they experience changes in upstream wetland area over time. We find that claim amounts for individual properties increase by 0.01% – 0.03% per hectare of upstream wetland loss. Based on these effects, we estimate that wetland loss since 1985 has increased flood insurance claims payments by a total of $9.4 billion or 8.3%. These historical losses have disproportionately affected low-income households and people of color, contributing to disparities in exposure to flood risk. We also calculate the marginal value of wetlands in reducing flood losses for each sub-watershed in the U.S. The distribution of marginal values is highly right-skewed, where the median is $88 per hectare and the 90th percentile is $17,000 per hectare. In 13% of sub-watersheds, marginal benefits of flood mitigation alone outweigh costs of land conservation. Policymakers and government agencies can use this information for conducting benefit-cost analyses on proposed regulations and spending, designing land use policies, and pricing flood insurance.
Total Economic Valuation of Great Lakes Recreational Fisheries: Estimating Willigness to Pay with Stated and Inferred Attribute Non-attendance Models and Data from Two Opt-In Panels Andrew Earle, East Carolina University; Gregory Howard, East Carolina University; Ash Morgan, Appalachian State University; and John Whitehead, Appalachian State University show abstract

Whitehead, Howard, and Cornicelli (Land Economics, 2025) use stated preference methods to estimate willingness to pay (WTP) to avoid reductions in recreational catch in Great Lakes fisheries using 2021 data from the Dynata opt-in panel. One persistent issue in stated preference research is insensitivity to scope, which occurs when WTP does not increase proportionally with the size of the environmental improvement. The authors estimate an inferred attribute non-attendance (ANA) model that incorporates scope effects and find that the scope elasticity is significantly underestimated in naïve models that ignore ANA. In 2025, we re-fielded the survey using both Dynata and Qualtrics opt-in panels to compare model performance and data quality across samples. We find no difference in the frequency of hypothetical referendum votes across tax amounts but observe differences in scope sensitivity in naïve logit models. In the Dynata data, both scope attributes are statistically significant, while in the Qualtrics data, only one is significant. In a stated ANA model, marginal WTP estimates increase by roughly 300% and are all statistically significant. The Dynata results show equivalent marginal WTP across scope variables, whereas the Qualtrics results diverge. In an inferred ANA model, marginal WTP estimates are statistically equivalent across both panels and scope attributes. These results demonstrate that accounting for attribute non-attendance substantially improves the sensitivity of WTP estimates to policy scope, addressing a key validity concern in stated preference research. The comparison of online panels reveals no significant differences in objective measures of data quality, despite substantial variation in survey costs. However, differences in estimated WTP across panels suggest that panel choice can affect value estimates and, ultimately, policy conclusions. These findings provide practical guidance for the design and implementation of stated preference surveys using commercial opt-in panels for environmental valuation.
Repeated Binary-Choice Preference Elicitation Daniel Petrolia, Mississippi State University; and John Whitehead, Appalachian State University show abstract

We compared estimated willingness to pay (WTP) and attribute non-attendance (ANA) derived from responses to a contingent-valuation survey using two different repeated binary-choice (RBC) elicitation formats to the standard single binary-choice (SBC) elicitation format. We find that elicitation format can affect mean WTP with a predictable pattern – asking more questions reduces WTP -- but for the most part, the differences are not statistically significant. When adjusted for vote confidence, there are no discernible patterns and no significant differences. Regarding ANA, the results are mixed, indicating no obvious advantages for any elicitation format. The results do indicate that using confidence-adjusted vote data can have an impact on the type of non-attendance inferred, and that for the two RBC elicitation formats tested, using confidence-adjusted vote data can increase the share of full attendance. These results support the notion that repeated binary-choice preference elicitation can yield preference information consistent with the standard single-choice preference elicitation method, but at substantially lower cost to the researcher.
Estimating Willingness-to-Pay With LLMs: Bridging the Data Availability Gap with Synthetic Contingent Valuation Bob Fischer, Texas State University show abstract

Willingness-to-pay (WTP) estimates are central to benefit-cost analysis (BCA) and regulatory decision-making. Given the importance of incorporating non-use values into BCA, contingent valuation (CV) remains a significant methodology for capturing people’s WTP. However, CV surveys remain expensive and slow relative to the budgets and timelines of BCA practitioners. As a result, many non-use values are frequently absent in BCAs to which they are arguably relevant—or, instead, are merely described qualitatively, making explicit tradeoffs less transparent than would be optimal. We argue that this problem can be mitigated, at least to degree, by relying on synthetic data. We use an AI-enabled research workbench (Alethic-ISM), which enables the computational execution of structured analytic graphs incorporating large language models (LLMs), to conduct synthetic contingent valuation experiments. The research workbench is encoded with CV protocols as a pipeline of demographic profile generation, scenario presentation, decision elicitation, and structured output parsing. In this configuration, LLMs act as parameterized “synthetic respondents,” producing synthetic (simulated) data that can represent people’s WTP. This option is inexpensive and quick relative to traditional CV studies. This framework supports three modes of synthetic experimentation: replication, in which existing CV studies are run synthetically to assess consistency with known findings; extension, in which new variables or demographic conditions are introduced to simulate unaddressed concerns; and original design, in which novel contingent valuation experiments are developed and refined synthetically toward protocol finalization and ultimate field deployment. We also explore the possibilities, as well as limitations, of using synthetic results to directly inform regulatory impact analyses.

6. Pharmaceuticals: When Price Caps Meet Innovation and Patient Outcomes [Full Panel of Research Presentations]
Thursday | 1:00 pm-2:30 pm | Room 310

Evaluating MFN Drug Pricing Caps: A Benefit-Cost Modeling Comparison Lawrence Hsu, University of Toronto show abstract

Following Executive Order 14273, the White House announced a Most-Favored Nation (MFN) drug pricing policy aimed at lowering U.S. prescription drug prices and curbing what it called “global freeloading” on American research and development (R&D). I pose two questions: What are the net social benefits of MFN price caps once reduced revenues, R&D pipeline effects, and downstream health and labor outcomes are quantified? Do conclusions shift when welfare is valued using traditional metrics, including quality-adjusted life year (QALY), compared to an equity-sensitive metric, Generalized Risk-Adjusted Cost-Effectiveness (GRACE)? I map MFN price-cut scenarios (an aggregate U.S. price level of 54% markdown) to revenue shocks by therapeutic area, embed those shocks in a block-recursive R&D pipeline with 2 discovery blocks and 4 clinical/approval blocks with stage-specific transition probabilities by GBD level-2 disease group, and translate revenue shocks into both fewer projects and longer time-to-approval via “sticky” stages with constant dropout hazards. Health is valued using QALY-style willingness-to-pay benchmarks and GRACE-style severity weighting, and I decompose health gains into pharmaceuticals versus non-clinical drivers using a balanced attribution. My key contributions include: (i) a quantitative, structural link from price caps to revenues, pipeline dynamics, and population health/labor; (ii) a welfare comparison under QALY and GRACE; and (iii) an upper-bound estimation that holds foreign pricing fixed, alongside a steady-state counterfactual in which U.S. and E.U. prices jointly adjust. In the calibrated MFN case, a 20% decline in R&D spending implies roughly a 40% reduction in steady-state approvals and an additional 0.6 years in expected time-to-approval, conditional on success. Under QALY-style valuation, price savings exceed innovation losses (about $8,000 present value per capita over 30 years), while GRACE-style weighting can drive net benefits toward zero or below. This invites discussion on when value-based pricing outperforms uniform caps on benefit-cost grounds.
Benefit-cost analysis in low- and middle-income countries Lisa Robinson, Harvard University; and Brad Wong, Mettalytics show abstract

Benefit-cost analysis is increasingly used to assess interventions outside the health care system in low- and middle-income countries. However, there is no easily accessible source of previously completed analyses. We describe the development of a database of these studies focused on interventions that improve public health. These interventions may address, for example, environmental, transportation, occupational, nutritional, behavioral, and other risks, including climate change. They may involve implementing regulations, developing targeted taxes, fees, or subsidies, or directly funding goods and services. We then summarize the results and implications of these studies. Our overall goal is to develop a publicly available, easily accessible database that can be used by others interested in these issues. Our hope is that this database will be used to inform near-term policy decisions as well as to identify research gaps and provide a starting point for future work. This database was developed as part of the Disease Control Priorities project, see: https://dcp4.w.uib.no/volumes/volume-3-interventions-outside-the-health-care-system/.
Evaluating Benefits (and costs) of Music Therapy Pierre Vilain, KPMG; and Paul Kim, KPMG show abstract

Music therapy (MT) has been used for decades as a treatment for patients facing a variety of conditions. For patients with autism, MT has been seen as a means to enable communication and expression, addressing some of the core issues of many autistic people. Likewise with people with schizophrenia or schizophrenia-like conditions MT is seen as improving emotional and relational competencies. Several other conditions have also been described as impacted positively by MT, a discipline that requires specialized academic and clinical training to tailor interventions to specific individual needs. While there is enormous anecdotal evidence of MT benefits, we review research based on accepted evaluation techniques such as randomized controlled trials (RTCs). Our review concludes that MT is found to yield various benefits, including reducing symptom severity and general quality of life improvements. We then explore how these benefits can be incorporated into a general benefits-cost analysis (BCA) framework, specifically measuring outcomes relative to various resource costs. We apply the framework to validate current public expenditures on MT for New York City’s principal provider of MT.
Benefit-Cost Analysis of CareCast: A Climate-Health AI System for Baltimore City Sandya Venugopal, University of Maryland, Baltimore County show abstract

Synopsis: Extreme weather events are an escalating public health concern in U.S. cities, disproportionately affecting populations with preexisting vulnerabilities. CareCast (created by the author's award-winning team at Cornell Tech Inaugural Climate Health Hackathon) is an AI-driven climate health communication platform that delivers wrap-around personalized SMS alerts to mitigate weather-related health risks. This study presents a localized benefit-cost analysis (BCA) assessing the implementation of CareCast in Baltimore City, Maryland, over a six-year horizon (2026–2031). Problem: Baltimore experiences recurrent extreme heat and humidity events that worsen chronic illness outcomes and strain emergency healthcare systems. Approximately one in five Baltimore residents is older or medically vulnerable, amplifying the city’s exposure to weather-related morbidity and mortality. Methodology: The analysis evaluates CareCast’s economic feasibility using city-specific healthcare utilization rates, cost benchmarks from Maryland hospital data, and demographic risk profiles. Benefits were quantified as avoided emergency department visits, reduced hospitalizations, productivity gains, caregiver time savings, and monetized quality-adjusted life years (QALYs). Net present value (NPV) and benefit-cost ratios (BCR) were calculated at 4% and 7% discount rates following U.S. Office of Management and Budget guidance. Results: Under conservative assumptions, total discounted benefits over six years equal approximately $7.2 million (4%) and $6.6 million (7%) against project costs of $1.8 million. The resulting BCRs (5.45 at 4% and 5.20 at 7%) indicate strong economic justification. The analysis suggests CareCast can prevent over 550 emergency visits and 40 hospitalizations annually, yielding measurable equity and resilience co-benefits for low-income neighborhoods. Conclusions: This paper contributes new urban-scale evidence on AI-enabled climate adaptation in public health. The findings suggest that targeted, low-cost digital interventions like CareCast provide scalable pathways for reducing heat-related emergency burdens and enhancing climate resilience. The methodology can inform future municipal investment decisions across comparable mid-sized U.S. cities. Keywords: Climate Resilience, Health Equity, AI-driven Principled Social Policy Intervention

7. Community Readiness and Public Engagement in Climate–Health Decision Making [Roundtable/Panel]
Thursday | 1:00 pm-2:30 pm | Room 307

Organizer: Alice Karanja, African Population and Health Research Center (APHRC)
Chair: Esther Anono, African Population and Health Research Center (APHRC))

Open Dialogue: Embedding Public Engagement and Equity in Decision Frameworks Esther Anono, African Population and Health Research Center (APHRC)) show abstract

Addressing the climate–health crisis requires policies that are not only economically sound but also socially feasible and equitable. Yet traditional benefit–cost analysis rarely accounts for the readiness of communities and institutions to implement change. This roundtable examines how Community Readiness Assessment (CRA) and Public Engagement can be integrated into Benefit–Cost Analysis (BCA) to reveal the hidden economic value of trust, participation, and social capacity. The discussion draws on experience from African settings, including Kenya’s arid and semi-arid lands, where climate variability threatens nutrition, health, and livelihoods. It explores how readiness indicators including community leadership, awareness, institutional collaboration, and resource access, can be translated into quantifiable benefits and used to inform investment prioritization. Panelists will share methods for valuing engagement through participatory modeling, systems mapping, and qualitative–quantitative integration. The session will demonstrate how readiness metrics expose the costs of policy inaction and strengthen the case for locally anchored adaptation programs. By reframing readiness as both a diagnostic and an investment lens, this roundtable highlights public engagement as a measurable driver of effectiveness and equity. The conversation contributes to evolving approaches that make benefit–cost analysis more participatory, inclusive, and responsive to real-world implementation challenges in climate–health systems.

8. Innovative Financing for Climate-Resilient Food Systems: A Benefit-Cost Analysis Clinic [Innovative Session]
Thursday | 1:00 pm-2:30 pm | Room 302

Organizer: Claire Nyapucha, Prosperbridge Initiative for Empowerment
Chair: Claire Nyapucha, Prosperbridge Initiative for Empowerment

9. Water and Land Quality Valuation [Full Panel of Research Presentations]
Thursday | 2:45 pm-4:15 pm | Amphitheater

Organizer: John Whitehead, Appalachian State University
Chair: Rob Moore, Scioto Analysis

The public benefits of mitigating harmful algal blooms in US lakes Matt A. Weber, Independent Consultant; Lisa A. Wainger, University of Maryland Center for Environmental Science; Kehinde Ojo, Morgan State University; Eva Bailey, University of Maryland Center for Environmental Science; Scott Knoche, Morgan State University; Anjali Gulati, Morgan State University; Emily Sommerfeld, Morgan State University; and Elizabeth Price, University of Maryland Center for Environmental Science show abstract

Harmful algal blooms (HABs) are a widespread issue across lakes and other freshwater resources, affecting every US state. Lake HABs are typically associated with the rapid growth of cyanobacteria, also known as blue-green algae. The toxins produced by the bacteria cause a variety of adverse health effects in humans, dogs, and other organisms. As a result, numerous ecosystem services are impacted by HABs, such as lake recreation, conservation of fish and wildlife, livestock production, and water supply. Currently, methods to verify HABs, and treatments to control them, are expensive and limited to select locations, such as popular recreation sites and drinking water reservoirs. Research investments by numerous entities, including the US Army Corps of Engineers, aim to broaden HAB mitigation options by improving methods of characterizing the timing and location of HAB events, and developing a wider range of treatments to reduce HAB intensity, with lower ancillary harms than algaecides. We will describe the development of a national stated preference survey designed to estimate the public benefits of HAB mitigation in US lakes, including focus group insights and pilot survey results. We divide the contiguous US into nine multistate climate regions with respondents voting on hypothetical improvement programs for their home region. Survey attributes focus on lake surface area that is unsuitable for water contact recreation due to HABs, lake aquatic life conditions as influenced by HABs, and the availability of real-time public information on HAB conditions for all US lakes. Final survey results are expected in late 2026. The research is intended to inform public management of HABs and similar water quality issues.
Coal Mining, Drinking Water Quality, and the Value of Remediation Daniel Kraynak, National Center for Environmental Economics, USEPA; and Wes Austin, Environmental Protection Agency show abstract

Coal mining activity is well known to impact nearby surface waters, and these impacts can translate to lower finished drinking water quality (Hendryx et al., 2012). Contamination of surface waters and disruption of drinking water can occur even after mines are closed if not properly sealed or remediated. These impacts to drinking water have significant and under-studied public health consequences. Prior research has struggled with several issues in estimating the relationship between coal mining and drinking water quality, including lack of data availability, limited credible identifying variation, and an inability to separate impacts of mining on water quality from impacts on air quality changes (Mueller, 2022). This paper attempts to fill this research gap using two decades of information on coal mining activity combined with drinking water quality samples across the continental US. Mining data comes from the Mine Safety and Health Administration (MSHA), which has information on the location, operational status, and production levels of coal mines nationally since 2000. We use drinking water data from an author-compiled database of drinking water quality samples covering 45 states. We combine these two rich data sources to investigate differences in water quality trends across public water systems with varying degrees of exposure to coal mining. Our preliminary estimates suggest that despite substantial regulation, coal mines continue elevate concentrations of inorganic chemicals in drinking water above standards enforced by the EPA. Prior to the conference we plan to add remediations data from the Office of Surface Mining Reclamation and Enforcement’s Abandoned Mine Land Inventory System. We hope the project will eventually culminate in a benefit- cost evaluation of federally funded mine remediation projects.
Lead Contamination and Home Prices, a Hedonic Analysis of an Omaha, NE Superfund Site Patrick Walsh, US EPA NCEE; Heather Klemick, National Center for Environmental Economics, USEPA; Adam Thiesing, US EPA NCEE; and Karen Sullivan, US EPA, Office of Land and Emergency Management show abstract

Past studies of the effects of Superfund remediations on residential property values have found heterogeneous effects that depend on distance from the contamination and whether cleanup activities are in-progress or complete. Studies have typically used site-level data on cleanup timeline and location as a proxy for remediation status. Because contamination and remedial activities vary within a site and cleanups can take many years, site-level data are often too coarse to reflect whether an individual residential property was contaminated or remediated at a particular time. There may also be a mismatch between property-level and site-level risk perceptions. If home buyers are most concerned with property-level contamination and cleanup, this potential measurement error in defining contamination and cleanup could lead to attenuated estimates of remediation price effects. This study estimates the effects of a Superfund site on home values using a rich dataset with property-level information. The Omaha, NE lead site was superfund listed in 2009 but has had soil sampling and cleanup activities ongoing since 1999, resulting in over 40,000 properties tested and 13,000 remediated to date. Previous research has shown that soil excavations at the Omaha Lead Site yielded a statistically significant drop in children’s lead exposure (Ye et al. 2022). However, the extent of homebuyer awareness of and response to individual property contamination and cleanups is unknown. Since our unique dataset has property level information on levels and types (soil, paint, dust) of lead contamination, we can test hypotheses about whether home buyers are more responsive to property-, neighborhood-, or site-level information about contamination and cleanup status, and whether site-level “stigma” depresses prices at properties where cleanup has already occurred or where contamination never exceeded the level of concern. Preliminary results suggest the property-level indicators yield a larger and more consistent impact on home values than traditional measures.
Coastal Hazards, Property Sales, and Tradeoffs between Natural and Man-Made Coastal Protection Amila Hadziomerspahic, Environmental Protection Agency; Patrick Walsh, US EPA NCEE; and Rachel Strow, APPRISE show abstract

Sea level rise (SLR) is an increasing threat to coastal communities and poses a complex challenge for homeowners, governments, and other local stakeholders. The Chesapeake Bay area has experienced the most rapid SLR on the Atlantic Coast of the U.S. Local and regional coastal adaptation policies in the Bay aim to preserve historic communities and employment while promoting more natural solutions like “living shorelines.” When local priorities conflict with regional goals, however, policies should be informed by the range of their potential impacts on public and private interests. This study estimates the impacts of different shoreline protection methods on housing prices. We use several comprehensive datasets to describe the shoreline of the Bay and its main tributaries, providing an expansive view of coastal features. To characterize natural coastal factors, we incorporate data on geomorphology, exposure to coastal hazards (e.g., erosion and SLR), and the presence of natural habitats that may mitigate those risks. To capture the extent of gray and green shoreline protective infrastructure, we use a dataset of coastal adaptation structures from the VA Institute of Marine Sciences and a dataset of living shoreline installations from the Maryland Department of the Environment. Our analytic approach combines coastal adaptation data with housing transactions from Maryland’s coastal counties in a hedonic pricing model that we use to test hypotheses about the property price impacts of different adaptation methods. We use variation in coastal factors to identify the price effects of amenities and disamenities associated with coastal protection practices. Preliminary results suggest that property markets are accounting for several forms of shoreline protection, with older “harder” structures commanding higher values than more natural approaches. Homes with living shorelines installed do not see a significant price impact, however, even though their construction is costly and requires regular maintenance.

10. Health Risk Valuation over the Lifetime [Full Panel of Research Presentations]
Thursday | 2:45 pm-4:15 pm | Room 302

Organizer: W. Kip Viscusi, Vanderbilt University
Chair: Thomas J. Kniesner, Claremont Graduate University

The Ramifications of Promotional Material on Informed Consent Elissa Philip Gentry, Arizona State University show abstract

In many self-pay medical markets, such as fertility treatments, the decision to begin treatment—or the expectation for how long to remain in treatment—depends on a patients’ personal willingness to pay and their assessment of risks. With no other informational intermediary (such as a third-party payer), patients’ ability to parse this information becomes paramount. The doctrine of informed consent is generally relied upon to bridge this gap; however, the relationship between promotional materials and the extent of disclosure required is understudied. This study examines text from websites of fertility clinics to assess the strength of promotional materials and reviews. It then uses an experimental context to measure beliefs regarding success rates after exposure to comparable promotional materials. The experiment assesses the type of disclosure necessary to update beliefs to be more in line with empirical success rates.
Danger Pay Thomas J. Kniesner, Claremont Graduate University; Ryan Sullivan, Naval Postgraduate School; and W. Kip Viscusi, Vanderbilt University show abstract

This paper examines optimal danger pay policy for the Department of Defense (DOD). Current DOD policy provides military personnel a stipend of $225 per month and tax-exempt status on any income earned while in a combat zone. In contrast, civilian DOD personnel receive a pay increase of 5-35% (not tax exempt) depending upon which country they are deployed into in addition to their regular pay. DOD danger pay policy does not appear to appropriately compensate fatality risk for deployed personnel. In order to provide precise estimates for optimal danger pay, we utilize restricted data from the Defense Manpower Data Center (DMDC) on all DOD military and civilian personnel for the years 2001-2025. The data are documented at the monthly level and include detailed individual information on gender, race, education, age, rank, marital status, job type, service, deployment status, location, and fatality date. A variety of models including fixed effects and LASSO regressions are used to estimate fatality rate changes as a function of deployment status across all countries in the DMDC database. These estimates are combined with value of statistical life (VSL) estimates from the economics literature to provide specific values on danger pay for use by the DOD.
The Value of a Statistical Life Year W. Kip Viscusi, Vanderbilt University show abstract

Embedded in the value of a statistical life (VSL) is a stream of valuations of each expected year of life. The value of a statistical life year (VSLY) has a function analogous to the VSL, except that it values short periods of life extension. This article reviews previous studies and reports new labor market estimates of the average VSLY and the variation of these values with age using two approaches—inferring the average VSLY based on estimates of the VSL and a new estimation approach that provides direct empirical estimates of the valuation of a discounted life year. The discount rate used in assessing the VSLY has a pivotal effect on the estimated VSLY. The average VSLY is $600,000 to $800,000 based on a 3 percent interest rate. The VSLY is substantially lower in the absence of discounting and more than doubled at a discount rate of 10 percent.

Discussant:

Glenn Blomquist, University of Kentucky;

11. Preferences: Designing Better Stated-Preference Evidence for Benefit–Cost Decisions [Full Panel of Research Presentations]
Thursday | 2:45 pm-4:15 pm | Room 308

Household Preferences for School Bus Transportation: Survey Evidence Caroline Tompson, Wake Forest University show abstract

Despite widespread recognition and availability, school bus use across the United States is declining. Starting in 2022, the majority of public schoolchildren do not travel to and from school by bus, but rather by private vehicle. This transition generates private and social costs, such as increasing traffic congestion and additional travel time for parents and guardians. Together, this suggests a disconnect between current school bus service and potential users. To investigate preferences for school transportation, I designed and fielded a survey investigating household preferences for school bus transportation in the Wake County Public School System, the largest school district in North Carolina. By collecting both revealed and stated preference data, I identify trade-offs respondents are willing to make between travel time and delays or cancellations of school bus service. On average, respondents would trade more than one hour of weekly student travel time to avoid a delay or cancellation of service. Leveraging dichotomous choice information, I find survey respondents value their students' travel time at a rate of about $23 per hour per week. Additionally, respondents would be willing to pay $20 to avoid a delay or cancellation of school bus service. To my knowledge, these are the first willingness to pay estimates related to school transportation.
Estimating the economic benefits of better winter forecasts on transportation Lou Nadeau, Eastern Research Group, Inc. show abstract

The National Weather Service (NWS) is tasked with saving lives and property from weather-related risks. In addition to the forecasts provided regularly by NWS, the agency also provides more detailed information to local authorities called Impact-Based Decision Support Services (IDSS). A key question is how to estimate the economic benefit of these services. Eastern Research Group, Inc. (ERG) used Agent-Based Modeling (ABM), a simulation approach, to develop a systematic and repeatable process for valuing IDSS and potentially other NWS products and services. The IDSS process involves providing services to decision-makers who use that information to influence the public decisions. The public uses the information it receives (directly and indirectly) from NWS, the media, emergency managers, and other members of the public, as well as their own perceptions of the event. Modeling techniques such as ABM are well-suited to handle analysis of complex systems such as this. The model ERG developed focuses on estimating the economic value of reducing crashes and weather-related travel delays based on better information provided by NWS through the IDSS process. The base set of simulations in the model varies a number of factors that can affect these outcomes including storm intensity, storm duration, frequency of information provided by NWS, the time of day the storm arrives, and the extent to which IDSS influences decisions, among other aspects. Using the variation in model parameters, we are able provide insights into how those parameters (e.g., storm intensity, storm arrival time) affect the economic value of NWS’s IDSS. In this presentation we will describe the model and its settings and outputs and discuss findings and insights from the model.
Commercial Rent Premia from Transportation Investments: Transfer or Net Benefits? Pierre Vilain, KPMG; and Jung Bae, KPMG show abstract

It has been widely observed that inter-city rail service improvements are associated with higher commercial rents in station areas. If these higher rents are due to the service improvements, how should these rent premia be treated in a benefit-cost analysis (BCA)? For residential rents it is common practice to treat the observed premia observed in station areas as transfers and omitted from a BCA. A classic paper by Jennifer Roback (1982) illustrates how such residential real estate premia are capitalizations of travel time benefits for households enjoying proximity to the station. Including both travel time savings and real estate `benefits is therefore double counting. However, we argue that commercial rent premia are not so clearly transfers. We develop a simple model and discussion drawing on urban economics (Fujita et. al. (1999) or Gleaser (2008)). We suggest that agglomeration benefits from increased connectivity are additional to static user benefits and propose that these observed premia should not be thought of as transfers. We discuss implications for inter-city rail service, and report findings from previous research related to commercial real estate impacts of new high speed rail service, including the Amtrak Acela service. We conclude with a discussion of the possibility for integrating these benefits into standard BCA for inter-city rail or transit.
Investigating depth-damage relationship using U.S. National Flood Insurance Program (NFIP) Data- A case study approach Kshama Harpankar, ABT Associates show abstract

State and federal regulatory agencies utilize benefit-cost analysis to determine economic feasibility of flood risk mitigation projects. By translating physical flood characteristics such as depth and duration of flooding in economic terms, depth-damage curves play a crucial role in benefit estimation for such projects. Use of generalized depth-damage curves has been documented as an important source of uncertainty and bias in flood damage estimates. The objective of this paper is to investigate the empirical depth-damage relationship using the National Flood Insurance Program (NFIP) claims data for two states (Pennsylvania and Texas) to understand regional damage variability. The analysis will present empirical depth-damage relationships for the two states and assess the relative fit of probability distribution of damage at various depths. Analysis will also apply generic U.S. Army Corps of Engineers (USACE) depth-damage curves to the NFIP damage data for each state to calculate predicted damage and assess sensitivity of benefit estimates generated by each depth-damage curve. Findings of the study can be helpful to practitioners aiming to improve accuracy of benefit estimates for flood risk mitigation projects.

12. Preferences: New Approaches to Preference Measurement in Applied Policy [Full Panel of Research Presentations]
Thursday | 2:45 pm-4:15 pm | Room 310

An Accounting of the False Claims Act Mackenzi Barrett, Vanderbilt University; Benjamin McMichael, ; and W. Kip Viscusi, Vanderbilt University show abstract

For several years, the Department of Justice has touted the use of the False Claims Act (FCA) to protect the public fisc. Since its reinvigoration in the 1980s, recoveries under the FCA total nearly $80 billion. The majority of these recoveries stem from the healthcare sector, and although the FCA is a general fraud-enforcement mechanism, healthcare fraud is by far its largest target. Despite these substantial recoveries, the FCA has come under recent fire for being unconstitutional due to its unique structure, which allows private persons to bring lawsuits in the name of the United States. For the first time in its 162-year history, a federal district court held the FCA unconstitutional. In its opinion, the court described the FCA as “a strain on federal resources,” because the government must monitor FCA lawsuits. Given the possibility of the elimination of the FCA, it is crucial to determine whether it is worth saving, whether in its current form or in an alternative form. Prior research demonstrates that the FCA has substantial deterrent effects that dwarf its monetary recoveries. Building on this prior literature and exploiting the FCA’s unique structure, we consider whether there are heterogeneous benefits between nonintervened cases and intervened cases. Our empirical analysis of nearly seven thousand qui tam lawsuits reveals a striking inefficiency: The government declines to intervene in approximately 62% of cases, yet these declined cases contribute only about 10% of total recoveries. The 90th percentile of recovery in declined cases is zero dollars, meaning the vast majority produce nothing for the treasury while consuming disproportionate judicial resources. We propose a reformed False Claims Act that eliminates the ability of relators to proceed when the government declines to intervene. The result would be a fraud-enforcement mechanism that is both constitutionally sound and economically efficient.
“Take care!” Investigation of Preferences for Elderly Care in Poland. The role of altruism in a Discrete Choice Experiment. Anna Bartczak, University of Warsaw; Wiktor Budziński, University of Warsaw; and Małgorzata Kalbarczyk, University of Warsaw show abstract

We investigate preferences for elderly care provided in their homes through a DCE approach. Our primary focus was to determine whether individuals are willing to pay for 10 years of insurance that covers medical care, assistance with hygiene, help with housework, and transportation, all while allowing them to remain in their own homes. The study was conducted in Poland among adults under 65 years. Each of the approximately 2,000 respondents was assigned to one of two treatments. The scenarios and questionnaires in each treatment were nearly identical; however, they differed in terms of the payment mechanism. In one survey, the payment mechanism was voluntary insurance (a private good), while in the other survey, it was mandatory (a public good). By comparing the results from these two treatments, we aimed to examine the potential presence of altruism within the DCE framework. Some previous studies suggest that public valuation may include a positive value associated with altruistic preferences, which could explain why public valuation tends to be higher than private valuation. However, these findings may be influenced by varying attitudes toward different methods of providing public and private risk reduction. In our study, we aimed to minimise this effect by using the same method of provision for the good, specifically an insurance mechanism, which differed only in terms of whether it was mandatory or not. Our preliminary results indicate that respondents are willing to pay for medical care, assistance with hygiene, and help with housework. When comparing the two treatments, we did not find any significant differences in respondents’ preferences, suggesting a lack of altruism in the DCE when a coercive uniform payment is used. Furthermore, we aim to explore respondents’ perspectives on the health and income levels of others and investigate how altruism, as measured on a psychometric scale, affects valuation.
Estimating the Value of a Statistical Life in Iran: A Revealed Preference Approach Mohammad Amin Eshghi Nezami, Amirkabir University of Technology; Amir Mohammad Sahebzadeh, Sharif university of Technology; and Hamed Kashani, sharif university of technology show abstract

This study aims to estimate the Value of a Statistical Life (VSL) in Iran using a revealed preference approach, representing one of the first investigations of this topic in the country. By leveraging real-world data, the research infers individuals' valuation of life-saving measures, which is critical for effective policymaking in health, safety regulations, and environmental risk management within Iran's unique socio-economic and cultural context. A comprehensive dataset, including mortality risk data, economic indicators, and demographic variables, is analyzed to examine how individuals' choices reflect their willingness to pay for reduced risk. The findings indicate that the estimated VSL in Iran significantly differs from values reported in other countries, highlighting local economic conditions and cultural attitudes toward risk. This pioneering research contributes to the emerging literature on VSL estimation in Iran and provides valuable insights for policymakers aiming to enhance public safety and health initiatives. The results underscore the importance of context-specific valuations in developing effective risk management strategies.
The Value of the U.S. Poison Center Network David Metz, RAND; Elizabeth Marsolais, RAND; Anthony Yu, RAND; Elena Younossi, RAND; and Benjamin Miller, RAND Corporation show abstract

The U.S. Poison Center Network (PCN), composed of regional Poison Centers and their national accrediting organization, America’s Poison Centers, delivers confidential guidance on poisoning prevention and management. In 2023, via the Poison Help Line, Poison Centers managed over two million human poison exposure cases from individuals and healthcare providers. RAND was commissioned by America’s Poison Centers to evaluate the current and evolving role of the PCN. The project had three goals. First, RAND conducted a survey of individual Poison Centers from March to May 2025 to collect information on the scope and scale of services provided, operational costs, and sources of funding. Second, RAND conducted 12 interviews and focus groups to understand how individuals interact with the PCN. Finally, RAND conducted a benefit-cost analysis of the PCN by monetizing benefits. The primary benefits included reduced health care utilization, shorter length of stay, and lower mortality risk. Despite reductions in real-dollar funding from state, local, and private sources, the PCN generates around $3 billion in annual benefits, primarily driven by avoided health care expenditures. Our study estimated a benefit-cost ratio of around 16, though this estimate can be sensitive to parameter choices, such as health care prices and the social discount rate.

13. Designing a National Benefit Cost Analysis System - and how Generative AI can help [Roundtable/Panel]
Thursday | 2:45 pm-4:15 pm | Room 307

Organizer: Dale Whittington, University of North Carolina at Chapel Hill
Chair: Vic Adamowicz, University of Alberta

14. Ecosystems, Wildlife, and Environmental Policy [Full Panel of Research Presentations]
Thursday | 4:30 pm-6:00 pm | Amphitheater

Organizer: John Whitehead, Appalachian State University
Chair: Patrick Walsh, US EPA NCEE

Measuring the Demand for a Wildlife Vaccine Vic Adamowicz, University of Alberta; Qin Xu, Department of Resource Economics and Environmental Sociology, University of Alberta; Marty Luckert, Department of Resource Economics and Environmental Sociology, University of Alberta; Margo Pybus, University of Alberta; Scott Napper, University of Saskatchewan; Hermann Schaetzl, University of Calgary; and Sabine Gilch, University of Calgary show abstract

Wildlife health is typically the responsibility of state and provincial government agencies as wildlife are public resources and provide benefits to diverse groups in society. When wildlife diseases arise, these agencies consider various actions, including vaccines. But the use of vaccines in wildlife is controversial, and vaccine designers have little information on the acceptability of, or demand for, specific designs of vaccines. Information on the desired attributes of vaccines and the willingness to purchase vaccines can inform research on vaccines and provide information on the potential for the development of a market. We examine the acceptability of, and demand for, a vaccine for Chronic Wasting Disease (CWD). CWD is a fatal prion disease that affects deer, elk, moose and other cervids. CWD is present in 36 U.S. states and five Canadian provinces and is rapidly increasing in prevalence and extent. Vaccines may be the only effective means of addressing CWD. Informed by research on CWD vaccine development, we conduct a survey of wildlife agencies, affiliated wildlife organizations, and tribal organizations across North America and several countries in Europe. We employ a choice experiment to identify the demand for vaccines and the trade-offs between vaccine effectiveness, delivery mechanism, persistence of response, and cost. Our data include over 50 responses from U.S. states and Canadian Provinces. Only 13% of respondents would not deploy any vaccine. Respondents strongly prefer high levels of effectiveness in infection prevention compared to vaccines that prolong life. There are also strong preferences for dry powder delivery systems (relative to liquid packets). With the best attribute combinations and modest prices, the probability of purchasing a vaccine is high (>80%). A latent class model reveals two classes of agencies; one (33% probability) that is price sensitive and likely to purchase only the most effective vaccine, while the other class (67% probability) is less price sensitive and more willing to accept vaccines that are less effective.
On Animal Status: The Value of a Statistical Life Versus the Value of a Statistical Animal Life (For a Pig) Shi-Ling Hsu, Florida State University; and Jacob P. Byl, Western Kentucky University show abstract

Public concern for animal welfare has exploded in recent decades. Research and scholarship have followed, producing increasingly sophisticated estimates of how much monetary value people place on the humane treatment of animals. Studies have examined willingness to pay for welfare for a variety of food animals, including beef cows, dairy cows, pigs, chickens, laying hens, and even salmon. A focus on animal welfare, however, is incomplete. Cruelty is morally repellant, but harms are imposed upon animals in a very wide variety of contexts, such as habitat destruction and deaths or harm incidental to industrial or agricultural activity. A prohibition of cruelty still leaves in place these less obvious harms that occur far more frequently. Cost-benefit analysis can lend some perspective on these broader harms to animals. Cost-benefit analyses commonly take account of the impact on human lives, but very rarely on animal lives, an omission that we argue (along with many others) is indefensible. As an initial step towards developing some framework for comparing human lives with the lives of animals, we estimate the value of a statistical animal life – in our study, a farm pig – alongside an estimate of the value of a statistical human life – in our study, a farmworker. While a developed literature exists for estimation of the latter, there has been no effort to estimate the former, and certainly no effort to compare the two. We make these estimates to: (i) provide a very early step in providing some empirical foundation for the ethical status of animals vis-à-vis human beings, and (ii) establish a numerical comparison for purposes of conducting cost-benefit analyses for actions affecting animals. In that sense, this study is an effort to derive an analogy to the value of a statistical [human] life.
Exploring the Drivers of Water Rate Changes in the United States Elizabeth Spink, Environmental Protection Agency; and Wes Austin, Environmental Protection Agency show abstract

Water rates have been increasing at twice the rate of inflation in recent decades and are expected to continue to rise. This paper takes a step forward in understanding the factors affecting increases in water rates over time. Using a multi-state panel of water and wastew- ater rate data, we first present observational analyses of how water rates and the speed of rate increases vary by water system size, source water category, lead service line prevalence, treated water quality, and region. Next, we conduct an event-study analysis of changes in water rates following changes in state-level water quality standards, Safe Drinking Water Act violations, and receipt of State Revolving Fund grants and loans. Preliminary findings suggest that health-based violations and lead action level exceedances are associated with higher water rates in the years following a violation. We also find that utilities that re- ceive Drinking Water State Revolving Fund assistance have higher water rates in subsequent years. We explore the heterogeneity of impacts across grant and loan characteristics includ- ing repayment requirements and funded project type. We then show the extent to which increases in utility operational and capital expenditures accompany rate increases using de- tailed water utility financial data from the Wisconsin Public Service Commission and discuss the implications using a theoretical model of regulatory rate approval decisions. We further investigate the interactions and feedbacks between previous violation history, the probability of State Revolving Fund assistance, and the probability of future violations as well as the role of increases in utility operational and capital expenditures in these dynamics. Finally, by matching utilities geographically to Census block group income and demographic data, we investigate the water affordability implications of water rate changes and how the incidence of water provision costs is distributed across high- and low-volume users.
The impact of population density on PM2.5 concentration Pengfei Liu, University of Rhode Island; Kaijun Nong, Beihang University; and Lei Zhu, Beihang University show abstract

As urbanization and societal aging accelerate, air pollution, particularly PM2.5, poses significant environmental and public health challenges, with human activities as the primary emission source. Using data on population density and PM2.5 concentrations in China from 2000 to 2022, we analyze over 130 million spatial units to explore the population-pollution exposure relationship. Employing geological features as instruments for density, we find that population density significantly increases PM2.5 concentrations, with an estimated elasticity of 5.1%. This effect is more pronounced in less developed regions, highlighting the interplay between economic development and environmental protection. Additionally, we assess the cost-benefit implications of PM2.5 mitigation strategies. Implementing stricter emission controls in high-density areas could reduce healthcare costs associated with PM2.5-related illnesses, estimated at $50 billion annually in China, while improving productivity and quality of life. However, initial investments in pollution control technologies, averaging $10 billion per region, pose challenges for less developed areas. Our findings suggest that targeted interventions in densely populated, less developed regions could yield significant health and economic benefits, reinforcing the urgency of integrating environmental strategies with urban planning.

15. Risk: Valuing Health and Environmental Risks Under Nonlinear Responses [Full Panel of Research Presentations]
Thursday | 4:30 pm-6:00 pm | Room 307

International Cost-Benefit Analysis Applications for Climate Adaptation: A Systematic Review Nir Becker, Tel Hai College; and Gur Angel, Hebrew University of Jerusalem show abstract

This paper systematically reviews international applications of cost-benefit analysis (CBA) in climate change adaptation, addressing persistent gaps in methodological practice, geographical and sectoral coverage, and policy relevance. The central research questions guide a global synthesis of adaptation CBAs published from 2000 to 2025: What are the prevailing methodological approaches and valuation techniques? Which adaptation measures are most frequently analyzed, and what do their economic efficiency results reveal? What challenges and limitations complicate the use of CBA in adaptation contexts, especially concerning uncertainty, data scarcity, non-market valuation, and equity? The review draws on 127 studies spanning 62 countries and multiple sectors, using a standardized template for data extraction and rigorous inclusion/exclusion criteria. It analyzes frameworks, discount rates, non-market value integration, treatment of uncertainty, and baseline scenario development across infrastructural, nature-based, policy, behavioral, and hybrid adaptation measures. Benefit-cost ratios and net present values are compared across regions and sectors to identify geographic disparities, sectoral trends, and context-dependent patterns in economic efficiency. Novel contributions of this study include a comprehensive mapping of international practices, equity-sensitive evaluation of distributional impacts, and a synthesis of emerging approaches such as real options analysis and multi-criteria decision tools integrated with CBA. Results highlight both economically efficient adaptation investments and persistently understudied regions and sectors. The discussion details practical, ethical, and methodological constraints - including intergenerational discounting and the valuation of non-market benefits - and recommends avenues for robust data collection, methodological standardization, and policy integration. This review offers actionable insights for policymakers, researchers, and practitioners seeking to advance the use of CBA in climate adaptation, with implications for strategic investment, cross-regional learning, and the evolution of benefit-cost analysis in environmental decision-making.
“From Vulnerability to Value: Integrating Climate Justice, Heritage, and Clean Energy into Global Benefit–Cost Analysis” Aamir Ashfaq Khan, ABT Associates show abstract

As the world faces accelerating climate and energy crises, countries in the Global South stand at the frontlines of vulnerability yet also at the frontier of innovation. This paper redefines the application of Benefit Cost Analysis (BCA) through an integrated lens of climate justice, heritage conservation, and clean energy transition, using empirical insights from Pakistan’s Climate Hub Forum (CHF) initiatives. The study evaluates three interlinked domains that shape sustainable and regenerative policy outcomes: Clean Energy Transition: Applying BCA to decentralized renewable energy systems, assessing their fiscal viability, social inclusivity, and long-term resilience across rural and peri urban regions. Climate and Circular Economy Models: Quantifying the ecological and economic returns of CHF’s One Million Trees and Towards Zero Waste programs, offering scalable frameworks for low-carbon community transformation. Heritage-Led Regeneration: A pioneering analysis of heritage eco-tourism in the Gandhara Civilization (Taxila)the world’s first university revealing how cultural assets can drive economic diversification, identity preservation, and green growth. By embedding social equity and intergenerational justice within BCA, this research challenges conventional efficiency-based evaluation, presenting a more human-centered economic narrative. The analysis demonstrates how climate-vulnerable nations can transform risks into regenerative value systems by linking policy, culture, and innovation. Ultimately, the paper positions the Global South not as a passive recipient of aid, but as an active architect of new economic paradigms where benefit–cost frameworks advance both efficiency and empathy. These insights provide actionable guidance for international agencies, governments, and development institutions seeking inclusive, evidence-based pathways toward a resilient and equitable global economy.
Probabilistic dose-response methods for non-cancer health benefits analysis Anna Belova, ICF Incorporated; Greg Paoli, Risk Sciences International; Kate Munson, ICF Incorporated; Emma Hartnett, Risk Sciences International; and Franco Momoli, Risk Sciences International show abstract

Toxicological studies provide data on the effects of exposure to environmental chemicals on non-cancer health endpoints that are used for reference dose/concentration development. However, epidemiological evidence for non-cancer endpoints, particularly dose-response relationships necessary for quantitative risk analysis, is frequently lacking. Consequently, non-cancer health impacts are often described qualitatively in benefit-cost analyses (BCAs) of environmental regulations, leading to underestimation of the monetized health benefits. The probabilistic dose-response methodology was developed and explored as a means to estimate a probabilistic version of a reference dose based on toxicological data, where there is explicit application of the desired level of confidence and an explicit incidence goal for the health effect in question. This methodology can be extended to applications in formal quantitative risk analysis and human health benefit analysis. Building on this methodology, we develop risk and benefits analysis case studies for three chemicals (1,4-dioxane, 1,3-butadiene, and vinyl chloride) and three non-cancer health outcomes (chronic kidney disease, cirrhosis, and birth weight). In that, we combine exposure assessment and dose-response assessment via Monte Carlo simulation to estimate the incidence of toxicological health endpoints (kidney necrosis, liver polymorphism, and 5% mean increase in fetal weight). The endpoint incidence is evaluated under a baseline scenario and under a hypothetical exposure reduction scenario. These results are then translated into non-cancer health outcomes and used in an integrated health impact model to estimate the societal benefits of the hypothetical policy action. Sensitivity analysis and uncertainty analysis demonstrate which model inputs drive the benefit estimates. We demonstrate the extension of the probabilistic dose-response methodology to the characterization of non-cancer health risks in exposed populations and estimation of monetized health benefits associated with policy changes. The key challenge of this analysis lies in the translation of the toxicological endpoints to the human health outcomes that can be valued.
Reducing PFAS in Drinking Water and Perinatal Health Wes Austin, Environmental Protection Agency show abstract

Per- and polyfluoroalkyl substances (PFAS), often dubbed "forever chemicals" due to their resistance to degradation, are frequently found in drinking water sources, and exposure to PFAS has been linked to a litany of health effects. PFAS exposure can impact fertility, cross the placental barrier, and lead to adverse developmental outcomes like increased risk of gestational diabetes, gestational hypertension, preeclampsia, fetal loss, low birthweight, and infant mortality. We study the connection between PFAS exposure in drinking water and fetal health using a two-stage least squares instrumental variables approach. In the first stage, we predict changes in PFAS concentrations using the roll-out of state policies that set limits to PFAS in drinking water across nine states from 2018-2021. In the second stage, we use these policy-induced reductions in PFAS concentrations to predict changes in perinatal health in communities served by drinking water systems with PFAS detections. Identification relies on state policy-induced reductions in PFAS at systems that were previously above maximum contaminant level thresholds. Using data on water system treatment practices, we show reductions in PFAS resulting from state policies can be partially explained by adoption of improved water treatment technologies. We use the CDC's national individual-level birth certificates data to investigate a wide range of perinatal health outcomes including birthweight, likelihood of low birthweight, gestation length, likelihood of preterm gestation, gestational hypertension, gestational diabetes and presence of congenital anomalies. We find that a one part-per-trillion reduction in PFOA or PFOS in drinking water leads to a 3.5 - 7.2 gram increase in birthweight for affected newborns. We also explore heterogeneity in our primary outcomes across areas with greater likelihood of relying on private domestic wells and propensity to purchase bottled water.

16. Valuation: Extending Benefit–Cost Analysis: Behavior, Capitalization, and Distribution [Full Panel of Research Presentations]
Thursday | 4:30 pm-6:00 pm | Room 308

Capitalization of Climate Mitigation in Housing Markets: Evidence from California’s Residential Construction Requirements Finn Dobkin, George Washington University show abstract

Wildfires are increasing across California, destabilizing insurance markets and worsening the state’s housing crisis. In response, the state adopted Chapter 7A of the California Building Code in 2008, which requires fire-resistant materials and design features for new construction in designated Fire Hazard Severity Zones. These mandates represent one of the first large-scale policy experiments in integrating climate mitigation into the housing stock. Yet, it remains unclear whether such state-led interventions effectively stabilize insurance markets or housing values in high-risk regions. This study takes place in two parts. First, it examines the capitalization of wildfire-resilient building codes into housing markets and insurance outcomes. Specifically, it evaluates whether the share of Chapter 7A-compliant homes within a ZIP code reduces insurance nonrenewals and dependence on the California FAIR Plan, and whether the 2008 regulatory cutoff generated measurable price premiums and greater liquidity for compliant homes, as well as whether there are spillovers to neighboring homes. Second, we implement a benefit-cost framework to evaluate whether the gains from wildfire-resilient construction, measured through reduced insurance instability, avoided losses, and positive home capitalization, outweigh the additional construction costs imposed by Chapter 7A. Evidence of positive capitalization and positive welfare effects would suggest that climate-resilient building codes meaningfully reduce financial risk exposure and suggest that Chapter 7A could be a useful tool for other states to replicate.
Behavioral Extensions of BCA in Water and Environmental Policy: Evidence from the Ganges River Anjali Yadav, Indian Institute of Technology Kanpur show abstract

This paper explores three questions: which behavioral factors drive individual willingness to act on water pollution, how those determinants can be translated into uptake scenarios for benefit–cost analysis, and how community aspirations for an ideal river condition map onto benefit categories used in policy evaluation. The paper presents new primary data from a structured survey of 300 respondents in two districts of Uttar Pradesh, India, collected using a clustered sampling design that captures both industrial point-source and diffuse non-point-source pollution contexts. The novelty of the research lies in formally integrating non-monetary behavioral drivers, such as social norms, attitudes, knowledge, and risk perception, into a benefit–cost analysis framework and in using an aspiration gap measure of the ideal Ganga as a practical proxy for community-defined benefits. Logistic regression and mediation analysis are used to identify how these behavioral factors shape willingness to act, while scenario simulations translate predicted probabilities into low-, medium-, and high-uptake projections. The results show that social norms and pro-environmental attitudes are the strongest predictors of willingness to act, while knowledge influences behavior indirectly through heightened risk perception. Respondents with larger gaps between current and ideal river conditions show greater readiness to engage. Scenario simulations indicate baseline willingness at about 35 percent, rising to 65 percent under norm-based interventions and exceeding 70 percent among high-aspiration respondents. These findings demonstrate that embedding empirically grounded behavioral parameters and aspiration measures into benefit–cost analysis improves the realism and policy relevance of benefit projections for river restoration and water governance, contributing to more credible and socially informed environmental decision-making.
Adaptation versus Mitigation in Coastal Recreation: Evidence from a Polish Bathing Water DCE Mikołaj Czajkowski, University of Warsaw; and Wojciech Zawadzki, University of Warsaw show abstract

Climate change is intensifying bathing water risks in temperate seas through heavier downpours, runoff, and thermal conditions favoring microbial contamination. Policy makers face a practical adaptation–mitigation choice set. Mitigation reduces the hazard itself (e.g., investments and standards that lower expected infections), while adaptation manages exposure (e.g., more frequent monitoring and timely communication so that people can avoid risky days). Although environmental economics has documented willingness to pay (WTP) for climate mitigation and for local environmental improvements, much less is known about the relative valuation of mitigation versus adaptation in recreational water policy – and how these valuations differ between active users and the general public (Berrens et al. 2004; Viscusi and Zeckhauser 2006; Brouwer et al. 2016). We report on a discrete choice experiment designed to quantify preferences for bathing water risk management on Poland’s Baltic coast. The experiment varies (i) water quality (infection risk), expressed as expected infections per 1,000 bathers (a mitigation outcome); (ii) frequency of water quality monitoring (every d days; an adaptation lever); and (iii) annual household cost (payment vehicle). We compare coastal users (n≈1,500) with a general population sample (n≈1,000) using the same instrument. For a subset of users, we can additionally test whether prior exposure to bathing water information scripts in earlier fieldwork shifts preferences – an information to valuation linkage that remains underexplored in the bathing water context (cf. Adamowicz and DeShazo 2006). The paper’s policy focus is twofold: (1) quantify WTP for reducing infection risk (mitigation) versus increasing monitoring frequency (adaptation), and (2) identify whether users and non users prioritize different policy mixes, with implications for efficient and publicly supported coastal management.
Extending the range of distributional weighting with microdata Dan Acland, University of California at Berkeley show abstract

The application of distributional weights to Benefit Cost Analysis poses significant practical challenges, largely because of the need for data on the distribution of income, and the distribution of costs and benefits, in affected populations. The range of feasible applications can be expanded by the use of microdata rather than binned data. The methodology involves identifying "synthetic populations" in microdata, that are plausibly representative of the populations affected by a policy, and then identifying or constructing "proxy indicators" based on observables, that are plausibly correlated with actual costs or benefits. In addition to expanding the range of feasible applications of distributional weighting, the use of microdata eliminates several sources of bias that arise when using binned data. In this presentation I present the basic methodology and illustrate it using a number of real-world examples, and argue that the feasibility and plausibility of the methodology is, in many cases, on par with unweighted Benefit Cost Analysis itself. Other keywords: regulation.

17. Preferences: What We Measure When We Elicit Value and Willingness to Pay [Full Panel of Research Presentations]
Thursday | 4:30 pm-6:00 pm | Room 310

Gospel Water Experiment: Campaign Impact on Water Bills and Conservation in Ghana Anthony Amoah, University of Environment and Sustainable Development show abstract

The study investigates the impact of public education campaigns by Ghana Water Limited (GWL) on water consumption and arrears (non-payment) among urban households in the Accra East Region of Ghana. Using a randomised difference-in-differences framework and administrative data from 2018 to 2024 covering over 7 million anonymised meters, two interventions are evaluated: Treatment 1 (GWL-only community engagement) and Treatment 2 (GWL with religious leaders, dubbed “gospel water”). The results show that while Treatment 1 reduces arrears by 1.9 percentage points, water consumption is also reduced by 3.9 percentage change. Similarly, while Treatment 2 reduces arrears by 3.4 percentage points, water consumption is also reduced by 13 percentage change. Higher water rates and active billable status significantly increased both arrears and consumption, underscoring affordability barriers. These findings shed light on the fact that, for a religiously dominated country like Ghana, there is evidence of the superior efficacy of religious collaboration in promoting water conservation and reducing arrears. This provides proof for culturally specific approaches in managing public utilities.
Sparing Cropland for Solar Energy or Sharing through Agrivoltaics? Paul Mwebaze, University of Illinois Urbana Champaign show abstract

Utility-scale solar expansion on cropland in the US Midwest is sparking opposition and interest in agrivoltaics — integrating solar panels with crop production. This approach raises key questions about trade-offs between land-sparing (monofunctional) and land-sharing (agrivoltaics) strategies. We explore the opportunities and challenges for farmers and solar developers, assess impacts on land conservation and the costs of meeting food and energy demands, and outline policy and market changes needed for adoption. Agrivoltaics could enhance social acceptance of solar on cropland, easing land-use conflicts while supporting renewable energy goals.
Valuing Agrivoltaics: Farmer Preferences and Policy Implications for Dual Land Use in the U.S. Midwest Paul Mwebaze, University of Illinois Urbana Champaign show abstract

Utility-scale solar is expanding across U.S. croplands, intensifying food–energy land-use conflicts. Agrivoltaics (AV)—co-locating photovoltaics with crops—offers a compromise, but farmer adoption is uncertain. We conducted a discrete choice experiment with 200 producers in 12 Midwestern states to quantify how technology design and contract terms shape willingness to adopt AV versus crop-only or solar-only options. The design varies five attributes: need for new equipment, need to switch crops, income variability relative to status quo (0% vs. 50% lower), share of the field under solar, and total lease payment. Across 708 choices, 84% prefer the crop-only status quo; only 16% choose an alternative. Among partial land-use scenarios, AV attracts 15% of choices versus 1% for solar-only, indicating stronger receptivity to dual use when farming continues. Higher lease payments significantly increase adoption, while “50% lower income variability” is less preferred than zero variability, underscoring a premium on stable payments. Land share under panels and requirements for new equipment or crop switching are not statistically significant. Adopters report lower baseline income per acre than non-adopters, suggesting AV is relatively more attractive on lower-return parcels. Taken together, three implications emerge. First, dual-use framing matters: farmers are far more receptive to AV than to displacing agriculture with solar-only, especially when farming continues on part of the field. Second, contract design is pivotal: sufficiently high lease payments can overcome inertia, but contracts must also guarantee stable annual income, not merely reduce variability. Third, targeting and design should prioritize lower-return parcels and minimize disruptive requirements (e.g., equipment or crop switching) to ease operational fit. These results provide empirical guidance for developers and policymakers seeking to scale AV in row-crop landscapes: pair competitive leases with revenue-stability provisions and farmer-centric designs that keep agriculture at the core of the land-use bundle.
Valuing the Benefits of Avoided Oil Spills in the Maritime Environment Jennifer Baxter, Industrial Economics, Inc.; Robert Paterson, Industrial Economics, Inc.; and Christopher Lauer, U.S. Coast Guard show abstract

The U.S. Coast Guard promulgates regulations aimed at reducing the risk of maritime incidents occurring in navigable waters and involving vessels and offshore and onshore facilities. To estimate the value of the resulting risk reductions, it applies standard values for avoided consequences, including fatalities, nonfatal injuries, and damages from oil spills. The values applied to human health effects are updated regularly by the U.S. Department of Transportation. In contrast, Coast Guard’s standard value for avoided oil spills has not been updated in nearly 20 years. While high-quality estimates of WTP to avoid oil spills exist, these studies focus on the largest spills on record, where millions of gallons of oil were spilled in a single incident. In contrast, review of 14 years of Coast Guard incident data show that typical spills are much smaller and more frequent. The challenge for analysts is whether and how to apply existing WTP studies, and how to construct avoided cost estimates where benefit transfer would be unsuitable. We propose a new set of standard values for use in Coast Guard regulatory analyses that vary based on spill characteristics and rely on a combination of historical data from actual claims submitted for reimbursement pursuant to the Oil Pollution Act of 1990, settlement agreements between RPs and Trustees to compensate for damages to natural resources, and existing WTP studies. A key challenge addressed by our work is an approach for extracting and applying data from negotiated settlements. Our approach is informed by structured expert elicitation involving natural resource damage assessment experts.

18. The UK’s experience of using CBA to shape regulatory policy [Roundtable/Panel]
Thursday | 4:30 pm-6:00 pm | Room 302

19. Reception [Plenary]
Thursday | 6:00 pm-7:30 pm | Continental Ballroom

20. Registration and Continental Breakfast [Plenary]
Friday | 8:30 am-9:00 am | Grand Ballroom

21. Valuing the Environment: Modeling Trade-Offs in Regulation, Ecosystems, and Global Sustainability [Full Panel of Research Presentations]
Friday | 9:00 am-10:30 am | Room 302

Organizer: Deborah Aiken, unaffiliated

Shadow Pricing Ecosystem Services in Boreal Forests Moriah Bostian, Lewis&Clark College; Tommy Lundgren, Swedish University of Agricultural Sciences, Sweden; and Shuyi Wang, Swedish University of Agricultural Sciences, Sweden show abstract

Boreal forests are multifunctional landscapes that simultaneously supply market goods, such as timber and bioenergy, and crucial non-market ecosystem services, including biodiversity and carbon sequestration. Managing these outputs inevitably involves trade-offs. To quantify them, we estimate shadow prices using a multiple-output directional distance function (DDF) that accounts for both desirable and undesirable outputs. We extend the standard model by endogenizing the directional vector and correcting for sampling variation via bootstrap methods. Applying this framework to a county-by-year panel of Swedish forests (2008–2014), we find that shadow prices vary across space and time but remain generally low. This suggests that enhancing biodiversity and carbon sequestration could be achieved with limited opportunity costs for timber production. Further, we explore substitution patterns through Morishima elasticities.
Pathways for food and land-use systems in Ethiopia Yirgalem Nigussie, Addis Ababa University, Ethiopia show abstract

This study addresses Ethiopia’s urgent need to transform its food and land-use systems to meet Sustainable Development Goals, particularly in food security, environmental sustainability, and climate resilience. Using the FABLE Calculator, the authors model three scenarios—Current Trends, National Commitments, and Global Sustainability—projecting outcomes from 2020 to 2050. The National Commitments pathway, which emphasizes irrigation expansion and productivity growth, shows promise for achieving food self-sufficiency by 2030. In contrast, the Current Trends scenario leads to ongoing deforestation and poor dietary diversity, while the Global Sustainability pathway supports biodiversity and lower greenhouse gas emissions through international cooperation. The study’s novelty lies in integrating local knowledge with scientific modeling to develop actionable strategies. It concludes that Ethiopia must adopt a hybrid approach, blending traditional agricultural practices with modern innovations. Key recommendations include promoting agroecological methods and expanding protected areas to mitigate environmental harm and support long-term sustainability. The research offers new modeling insights to guide policy decisions.
Balancing Growth and Green: Analyzing the Economic-Environmental Trade-offs Through Chinese Secondary Industry Linge Yang, University of Connecticut show abstract

This paper examines the economic effects of environmental regulation in China’s secondary industry by combining neoclassical economic theory with a quasi-experimental approach. It identifies two key findings: (1) strict environmental regulations can cause significant economic losses, underscoring the tradeoff between environmental protection and economic growth; and (2) there is an inverted U-shaped relationship between regulation and output, indicating an optimal level of regulation that maximizes both environmental and economic benefits. To enhance traditional benefit-cost analysis (BCA), which integrates health, environmental, and economic factors using general equilibrium models, the study employs a production function approach within a partial equilibrium framework. This method focuses on direct economic impacts, including compliance costs and technical feasibility, offering a practical complement to BCA. The paper concludes that well-designed regulatory policies can strike a balance between environmental sustainability and economic performance, providing insights for policymakers aiming to optimize industrial regulation without compromising growth.
Cross-Media Mercury Releases from Coal-fired Electric Power Plants Rolf Färe, Oregon State University; Shawna Grosskopf, Oregon State University; Cynthia Morgan, Independent Researcher; Carl Pasurka, Independent Researcher; and Ron Shadbegian, Appalachian State University show abstract

While previous investigations of cross-media pollutants have focused on the risk / damage implications of transferring releases from one media to another, our paper implements a production perspective on cross-media pollutants. To assess the cost of reducing toxic emissions produced by electric power plants, this study uses data from the toxics release inventory (TRI) to estimate a quadratic directional distance function, which allows us to calculate elasticities of transformation and shadow prices of bad outputs released into different media. In addition to marginal abatement costs, we can also examine whether releases into different media are substitutes (i.e., reduction in releases in one media leads to increased releases in another media) or complements (i.e., reduction in releases in one media leads to increased releases in another media). We will operationalize our model using data from 2000 to 2005 for coal-fired power plants with releases of mercury into the air, land, and surface waters.

22. Housing: Sorting, Prices, and Welfare Under Building Regulations [Full Panel of Research Presentations]
Friday | 9:00 am-10:30 am | Room 307

Exploring the effect of cooking energy on subjective wellbeing in seven developing countries Franklin Amuakwa-Mensah, Luleå University of Technology; Anthony Amoah, University of Environment and Sustainable Development; and George Marbuah, African Development Bank show abstract

The study examines the impact of cooking energy type on subjective wellbeing, measured in the form of life satisfaction and making ends meet, in seven low- and middle-income countries (LMIC) in Africa, Asia, and Latin America. A sample of 1,200 respondents were interviewed in each country, amounting to a total of 8,400 observations. We classified primary cooking fuel of households into clean and unclean and design a quasi-experiment where households with clean energy type are the treated group whereas unclean energy type households are the controlled. Given that treatment is not randomly assigned, and we are using observational data, it is difficult to have a counterfactual outcome. As a result, we employ the Inverse Probability-Weighted Regression-Adjustment (IPWRA) estimator, which allows us to estimate the effectiveness of treatment using observational data where treatment status, in this case clean cooking energy, is not randomized. Our results show that clean cooking fuel have positive effect on both measure of subjective wellbeing (life satisfaction and making ends meet) if we do not account for country fixed effect in our model. However, accounting for country fixed effect, we find negative effect of clean cooking fuel on life satisfaction, with no significant effect on making ends meet. The continental analysis show that clean cooking fuel have negative effect on life satisfaction in both African and Asian countries with the effect being more pronounced in Asia. Moreover, clean cooking fuel have negative effect on making ends meet, only in Asia. Given the differences in gender roles in developing countries, we carried out a gender analysis to investigate whether there is disparity in the impact of clean cooking fuel use on subjective wellbeing. We find negative effect of clean cooking fuel use on life satisfaction for both males and females, however, the effect is relatively high for females.
Potential Trip Value: Methodology for Economic Evaluation of Unmet Travel Demand Thomas Redstone, STV Inc; Patricia Macchi, STV Inc; Hana Shuck, STV Inc; and Bronwyn Horgan, STV Inc show abstract

This research explores the economic benefits of realizing unmet transportation demand and specifically, for trips that are suppressed due to existing transportation barriers. Transportation barriers might include insufficient or limited transportation supply, coverage, cost and affordability constraints, or lack reliability. This research focuses on the economic value that journeys to work, healthcare visits, education, and recreation opportunities generate when transportation barriers are lowered, inducing new trips in society. The objective is to present a methodology to quantify the potential trip value associated with improving access to mobility and transportation for trips that are not taken at present but made following transportation investments that reduce barriers and improve access. This involves identifying induced demand, defined as new trips not previously made and derived from travel demand models, travel surveys, and literature reviews. This methodology assigns different monetized values to those induced trips based on trip purpose and duration. Practitioners could apply this methodology to capture the economic benefits more fully or to better understand the return on investment for a proposed transportation investment by accounting for the transportation users for which demand exists but who are excluded due to systemic limitations to transportation access. This approach provides a more comprehensive basis for decision-making for transportation investments, emphasizing the economic benefits of an accessible transportation network. This research includes a case study that applied the methodology to make the business case for a transit agency to invest in service improvements.
The effect of phasing-out energy inefficient dwellings from the housing market: a sorting demand model approach Anna Creti, University Paris-Dauphine; Gabrielle Fack, Universite Paris-Dauphine; Edouard Civel, Chaire Economie du Climat; and Daniel Herrera, Mines Paris - PSL show abstract

We estimate an equilibrium sorting model of housing demand to evaluate the French phase-out of energy-inefficient dwellings from the rental market. Using nationwide transaction, land use, and Energy Performance Certificate (EPC) data, we recover heterogeneous preferences over energy efficiency and other dwelling attributes. The policy announcement reduced rental-oriented purchases of EPC~G units, with compensating effects for owner-occupiers and second-home owners. Embedding these responses in a structural framework, we show that the phase-out induces significant buyer sorting and modest price adjustments. The results underscore how the market impacts of energy-efficiency regulation hinge on endogenous reallocation across buyer types and housing quality.
Fiscally Regressive Subsidies and the Spatial Diffusion of Electric Vehicles in French Cities Marco Percoco, Università Bocconi show abstract

This paper investigates the equity implications of the 2018 policy change regarding France’s electric vehicle (EV) subsidies, focusing on its differential impact across French municipalities (i.e., communes) with varying income levels. Using a synthetic event study and a synthetic difference-in-differences approach, a significant and disproportionately lower rate of EV adoption is identified in communes with a higher share of non-taxable (i.e., lower-income) households. Although the nominal subsidy reduction for new EV purchases was the same (€1,500), the proportional financial burden was larger for lower-income households, thus inhibiting EV uptake compared with higher-income households. Robustness checks—including placebo tests, alternative treatment definitions, and the exclusion of outlier years and regions—support the validity of the causal inference. Additionally, the results show that the €1,000 additional benefit for non-taxable households on secondhand vehicles did not sufficiently offset the impact of the reduction in new EVs. These findings underscore the regressive effects of uniform subsidy cuts across income levels, which may hinder lower-income households from participating equally in the clean energy transition. This work contributes to the literature on environmental equity and offers policy-relevant insights for designing socially inclusive decarbonization strategies amid declining public subsidies across Europe.

23. Preferences: Evidence on stated-preference valuation and elicitation design in Policy Appraisal [Full Panel of Research Presentations]
Friday | 9:00 am-10:30 am | Room 308

The Psychological Toll of Heat: The Effects of Temperature on Mental Health in Mexico Yumin Hong, University of Texas at Austi; and Antonia Vazquez, University of Texas at Austi show abstract

While extreme heat events are becoming more frequent, evidence on their mental-health consequences in middle-income settings remains limited and focused on mortality. We examine how short-run heat relates to mental health in Mexico using weekly data, combining administrative outcomes on suicides and emergency department visits for mental illness (2008–2019) with survey measures of mental well-being (2013–2019). Comparing hotter and cooler weeks within locations in the same calendar week of the year, we find that one additional day above 30°C in a week increased suicides by 3.2% and emergency department visits for mental illness by 2.4%, relative to weekly means. These magnitudes are larger than comparable U.S. benchmarks, about 5.5 times for suicides and 1.3 times for mental illness emergency department visits. Although both genders show declines in mental well-being on hotter weeks in the survey data, manifestation patterns differ by gender: emergency department visit increases are larger among women, while suicide increases are concentrated among men. Emergency department visit increases are smaller where psychiatrists are available, and we find no clear differences by state air-conditioning prevalence or by urban versus rural status. This paper shows that the burden of heat on mental health in Mexico spans subclinical distress, clinical demand, and mortality, highlighting the need to incorporate mental-health costs into climate policy and economic assessment frameworks, especially for low- and middle-income countries, where most people with mental disorders reside and who are more vulnerable to climate risks.
Willingness to Pay for Reducing Multiple Health Risks: A Cross-Country Study Muriel TRAVERS, Nantes University; Gildas Appéré, University of Angers; Ståle Navrud, Norwegian University of Life Sciences; Henrik Lindhjem, Menon Economics; Daniel Herrera, Mines Paris - PSL; and Maria Kostopoulou, MINES ParisTech show abstract

This paper examines how the simultaneous valuation of multiple health risks may affect Willingness to Pay (WTP) for risk reductions related to air pollution and chemical exposure. It addresses a key question in Benefit–Cost Analysis: Can the total WTP for reducing several health risks be reasonably calculated as the sum of their separate valuations? Is there an empirically significant bias leading to an overestimation or underestimation of the overall WTP? Indeed, there may be ‘synergies’ between reductions in different health risks in terms of individual preferences. Therefore, the methodological objective of this paper is to test the robustness of the Individual Valuation and Summation (IVS) assumption, which underlies most multi-risk valuation exercises. Currently, most health-endpoint risks are assessed separately through independent surveys, implicitly assuming that total WTP for several health endpoint risks could be obtained by summing separate valuations. This paper questions the validity of that additive approach by examining whether accounting for potential interactions between risks significantly alters estimated welfare measures. To explore this issue, new primary data were collected between June and August 2025 through a Discrete Choice Experiment (DCE) conducted in six European countries (France, Italy, Poland, Serbia, Sweden, and the United Kingdom) selected for their diversity in living standards and health profiles. The survey focuses on three health endpoints (Asthma, Type 2 Diabetes, and Chronic Kidney Disease) whose risks are associated in part with air pollution or chemical exposure. At the time of submission, econometric estimates are ongoing. Nevertheless, initial findings appear to indicate various results concerning interactions between health risks.
Willingness to Pay for Environmental Health: A QALY-Based Study Across Europe Maria Kostopoulou, MINES ParisTech; Daniel Herrera, Mines Paris - PSL; Henrik Lindhjem, Menon Economics; Ståle Navrud, Norwegian University of Life Sciences; Gildas Appéré, University of Angers; and Muriel TRAVERS, Nantes University show abstract

This study uses a survey-based contingent scenario to investigate how much individuals across six European countries—France, Italy, Spain, Greece, Poland, and Sweden—are willing to pay (WTP) for improvements in environmental health. It aims to quantify the value individuals place on reducing adverse health outcomes linked to environmental factors and to provide policy-relevant estimates for economic evaluations. The survey adopts a Quality-Adjusted Life Year (QALY)-based framework and presents illnesses that differ in severity and duration. This approach allows us to disentangle individuals’ preferences for more severe, shorter illnesses versus less severe, longer-lasting ones. Valuations are further compared under probabilistic risk reductions and certain health outcomes to assess WTP for preventive versus treatment-oriented interventions. Respondents are randomly assigned to a probability module or a certainty module, with those failing probability training redirected to the certainty module. The probability module uses a discrete choice experiment (DCE) to elicit WTP for reducing fatal and non-fatal illness risks, while the certainty module applies a double-bounded dichotomous choice (DBDC) format to measure WTP for faster recovery from an existing illness. Some respondents are also randomly presented with disease-specific labels (e.g., lung cancer, stroke, heart disease) to examine potential disease-related premiums. The pilot phase is currently underway, with full-scale data collection scheduled to begin in November 2025. We expect respondents will differentiate between illness severity and duration, with no linear relationship between these two QALY attributes. Some valuations may also reflect a disease-specific premium due to connotation or bias. Additionally, we anticipate that the certainty module will produce different WTP estimates than the probability module, though the exact direction and magnitude of any certainty bias remain to be investigated.
The Crowding Out Effect of Tobacco Spending: An Answer in Search of a Question? Don Kenkel, Cornell University show abstract

A line of public health research estimates the extent to which spending on tobacco crowds out consumer expenditure on other goods and services. Studies have estimated the crowding out effect of tobacco spending for a range of low- and middle-income countries; studies are also applying the methodology to estimate crowding out effects of spending on other health-related goods including alcohol, e-cigarettes, and sugar-sweetened beverages. The studies interpret the crowding out effects as measuring household well-being, especially in the context of poorer households where tobacco spending might crowd out expenditures on goods like food and clothing. In this paper, I argue that the research on the crowding out effect of tobacco spending is technically sophisticated but poorly motivated. The typical study uses cross-sectional data from a household expenditure survey to estimate a system of Engel curves that model the budget shares allocated across categories of goods. The Engel curves are derived from the quadratic almost ideal demand system (QAIDS) and are estimated by three-stage least squares. The Engel curves are estimated conditional on tobacco spending, which is treated as pre-determined. The key parameter of interest provides a simple test of whether the household utility function is weakly separable in tobacco and other goods. However, neoclassical economic theory does not provide a priori motivation to treat tobacco spending as pre-determined or to test for weak separability. The methodology could equally be applied to estimate whether spending on clothing crowds out tobacco expenditures. Even more fundamentally, the QAIDS and the Engel curves are based on the assumption that the household has chosen the utility-maximizing allocation of its budget across goods, including tobacco. To interpret the crowding effect as a relevant measure of household well-being requires additional strong assumptions, such as paternalistic value judgements about the goods in question.

24. Water: Water Quality, Pricing, and Welfare in Practice [Full Panel of Research Presentations]
Friday | 9:00 am-10:30 am | Room 310

A cost-benefit analysis of using wastewater data to guide typhoid vaccination Aparna Keshaviah, Mathematica Policy Research; Agha Akram, Independent researcher; Dheeya Rizmie, Mathematica, Inc; Ian Raxter, Michigan Value Collaborative; Afroza Jannat Suchana, International Centre for Diarrhoeal Disease Research, Bangladesh; Afroza Jannat Suchana, International Centre for Diarrhoeal Disease Research, Bangladesh; Rezaul Hasan, International Centre for Diarrhoeal Disease Research, Bangladesh; Ziaur Rahman, International Centre for Diarrhoeal Disease Research, Bangladesh; Mahbubur Rahman, International Centre for Diarrhoeal Disease Research; Megan Diamond, World Health Organization; and Anthony D'Agostino, Mathematica, Inc. show abstract

Problem statement Enteric diseases are a leading cause of mortality in developing countries, yet are highly preventable. Typhoid vaccines remain underutilized, and diagnostic capacity constraints impede treatment and prevention. Wastewater monitoring can potentially provide a more accurate picture of disease burden if detection and quantification of Salmonella Typhi in wastewater are advanced. To motivate why countries should invest in improving wastewater testing methods, we conducted a cost-benefit analysis. Methods We estimated benefits that could accrue if wastewater data informed the early launch of a theoretical typhoid vaccine campaign in Cox’s Bazar, Bangladesh. After empirically estimating the lead-time advantage of localized wastewater data over existing clinical data to flag case upticks, we simulated changes in case counts from a 1- to 14-day early campaign launch, using ordinary differential equation modeling. We quantified benefits resulting from averted cases (from preserved caregiver time, school days, and wages), hospitalizations (from savings to public funds), and deaths (using the value of statistical life). We then calculated how cumulative benefits, costs, and the ratio of the two varied by campaign launch timing scenario over a five-year period. Results Cumulative benefits varied by campaign launch timing. With a 13-day early launch, every $100 spent on wastewater monitoring could yield $295 in societal benefits by year 5. Cumulative benefits equaled cumulative costs with a 5-day early launch and outweighed costs when the campaign was launched even earlier. Conclusion Our findings suggest that governments could reap benefits from advancing wastewater surveillance to provide early warnings of new typhoid outbreaks. The framework we developed for our analysis lays the groundwork for similar analyses in other LMICs that, like Bangladesh, routinely experience enteric disease outbreaks. Our analysis is especially relevant as Bangladesh launches its first typhoid vaccination campaign (Fall 2025), and as other resource-constrained LMICs consider campaigns to counter enteric disease.
The Evolving Role of Regulatory Impact Analysis in Litigation Christopher Carrigan, George Washington University; and Scott Walster, Peregrine Economics show abstract

While the requirement that agencies perform regulatory impact analyses to support their significant proposed rules has a long history dating back to at least to the 1980s, these analyses have traditionally been less of a focus in challenges to those rules by aggrieved parties through judicial review. However, Supreme Court decisions over the past several years (e.g., Michigan v. EPA, West Virginia v. EPA, Loper Bright Enterprises v. Raimondo, etc.) have changed the landscape of how courts decide on the legality of agency regulations, including the degree to which an agency’s analysis is an important consideration and scrutinized during the review process. This project examines judicial review decisions, with a particular focus on the role that supporting analysis has played in those decisions. Specifically, the research will investigate how court decisions on rulemaking challenges have considered analysis in those decisions, how that has changed over time, and how the characteristics of both the rules and litigants affect the role supporting analysis plays in judicial review. An additional goal of the project is to further link these court decisions to the features of the comment letters that form the foundation of these challenges. Ultimately, the research will present an extensive empirical examination of the evolving importance of agency analysis to judicial review, a topic of growing interest in the regulatory scholarship.
Economic Benefit Analysis for NOAA Space Weather Next Elisa Turner, MITRE Corporation; Joseph Conran, National Oceanic and Atmospheric Administratio; Erin Lynch, NOAA; Michael Cook, The MITRE Corporation; Cecilia Wei, The MITRE Corporation; Luke Shaffer, The MITRE Corporation; and Jess Grana, The MITRE Corporation show abstract

Space weather (SWx) describes variations in the space environment between the Sun and the Earth. These solar variations can disrupt critical technology including the electric power grid, satellite communications and aviation operations. NOAA’s mission to build a weather ready nation includes observing, studying, and advising citizens and industry stakeholders of SWx conditions. MITRE and NOAA are finalizing an economic benefits study of the Next Generation space weather program and its satellite-based observations. The effort began with an extensive literature review to identify benefit mechanisms and understand how observations inform forecasts and alerts. Value of Information (VOI) theory was applied to link observations to benefits via value chains, emphasizing the decisions and actions industries can take, based on NOAA information, to mitigate economic impact. These valuations were incorporated into an event-driven model applying the probability of different magnitude events via Monte Carlo simulations.
Health Benefits From Cycling and Their Role in Benefit-Cost Analysis Henrik Andersson, Swedish National Road and Transport Research Institute

25. OECD Mortality Risk Valuation Report [Roundtable/Panel]
Friday | 9:00 am-10:30 am | Amphitheater

Organizer: W. Kip Viscusi, Vanderbilt University
Chair: Thomas J. Kniesner, Claremont Graduate University

Panelists:

Lisa Robinson, Harvard University;
Glenn Blomquist, University of Kentucky;
Al McGartland, Institute for Policy Integrity;
W. Kip Viscusi, Vanderbilt University;
Clayton Masterman, University at Buffalo School of Law;

26. Public Programs: Evidence from Applied Benefit–Cost Analysis [Full Panel of Research Presentations]
Friday | 10:45 am-12:15 pm | Room 307

Taxation Made Easy: A Cost-Benefit Analysis of Prefilled Sales Tax Returns Foroogh Chamaki, Queen's University; Glenn Jenkins, Queens University; and Mikhail Miklyaev, Cambridge Resources International Inc show abstract

Small and medium-sized enterprises incur disproportionately high compliance costs under the current Goods and Services Tax/Harmonized Sales Tax (GST/HST) reporting system. To reduce these costs, some EU and Latin American countries have successfully adopted prefilled tax return systems supported by national e-invoicing infrastructures. Canada has not yet adopted this innovation. This study estimates the economic welfare improvement that would result if Canada were to implement a system of prefilled GST/HST returns. An integrated financial, economic, and stakeholder cost-benefit analysis is used. Implementation of a prefilled GST/HST return system in Canada is estimated to generate a present value of compliance cost savings over 10 years for GST-/HST-registered businesses of CAD 14.3 billion. Over 99% of these savings would accrue to over 3.7 million medium, small, and self-employed businesses. After netting out the costs of implementing this intervention, the economic welfare improvement for the economy would be CAD 13.6 billion. The additional income taxes collected due to the reduction in business costs have a positive budgetary impact on both the federal and provincial governments. Hence, after deducting estimated costs, the government’s net gain would be CAD 2.6 billion. The net after-tax gain by Canadian businesses would be approximately CAD 11 billion.
New Mexico Economic Development Tax Expenditure Assessment Brendon Gray, New Mexico Legislative Finance Committee; and Drew Weaver, New Mexico Legislative Finance Committee show abstract

Each year, the state of New Mexico forgoes about $600 million—4.5 percent of total state revenues—for economic development tax incentives, yet the state previously had little insight on the impact of these investments. Because of this gap, policymakers are unable to make evidence-based decisions on whether to continue, modify, or stop the investments once they are implemented. This report addresses this gap and examines the return on investment (ROI) of New Mexico’s economic development tax incentives. The report uses a region-specific economic model and estimates the impacts of the incentives using publicly available administrative data. The analysis measures both economic ROI—the growth in New Mexico’s economy that results from state investments—and fiscal ROI, or the increase in state revenues attributable to those investments. Expanding on traditional incentive ROI analyses, the report focused on communicating insights to policymakers through concise, visually oriented “one-pagers” presented on an ongoing basis to develop shared interest and understanding of the results. This approach was intended not only to present findings but to equip policymakers with timely, accessible evidence to guide resource-allocation decisions. The report also evaluated incentive design elements for alignment with best practices to identify ways to enhance efficiency and transparency in future incentive programs. In general, the report found that New Mexico’s economic development tax incentives have minor effects on economic activity and are revenue negative, especially for the state’s flagship tax incentives focusing on the film and manufacturing industries. The findings underscore the importance of using evidence-based assessments to steward limited state resources and ensure economic incentives deliver measurable public value.
Benefit-Cost Analysis of the Federal Government’s Return to In-Person Work Jeffrey Horn, US Coast Guard; Dominik Mockus, US Coast Guard; David Nowak-Laird, US Coast Guard; and Jeremy Petosa, U.S. Coast Guard show abstract

The COVID-19 pandemic disrupted our nation and the world. One of the results of the pandemic was remote or hybrid work. Estimates suggest 61% of paid days in the US in May 2020 were work-from-home days. During Calendar Year 2024. less than one-fifth of work by Department of War civilian employees was not conducted in person. However, as time goes on, more companies are requiring employees to return to the office. Examples of private sector companies that have implemented return to office are Amazon, AT&T, Meta's Instagram, Dell Technologies, and Boeing. Only about 27% of paid days in the US in September 2025 were work-from-home days. On January 20, 2025, President Trump issued a Presidential Memorandum requiring federal employees to return to work in-person on a full-time basis. This presentation explores the benefits and costs of this policy. While many articles exist about remote or hybrid work versus full-time in-person work in general, we are the first to take a deeper dive into the benefit-cost analysis for federal government employees in the DC Metro area. This presentation will investigate the costs and benefits from this policy to the federal government. This includes the costs to the Office of Personnel Management (OPM) for drafting and publishing guidance, the cost to human resources offices to process paperwork changes, and the cost of maintaining real estate. The presentation will also address the impacts to the States of Virginia and Maryland as well as the District of Columbia; the impacts to WMATA and other significant commuter operations; and the impacts to federal government employees. We explore multiple qualitative benefits and, to the extent possible, try to quantify what we can. These benefits include the improved ability for collaboration, building stronger relationships with peers, and creating a more robust office culture. Keyword: Other (Policy)
Cost Benefit Analysis of Food Donation Drives Using Monte Carlo Simulation Anvesha Bhagat, Academy for Math, Science, and Engineering, New Jersey; and Richard Bruns, Johns Hopkins University show abstract

Everyone deserves healthy food to live a full, healthy life. Yet millions of hardworking families still face hunger and when people don’t have enough to eat, it impacts their health, education, and future opportunities. 47 million people face hunger in the U.S. Over 13 million kids don’t have enough food to grow up strong. These numbers reveal a crisis that threatens us all, but together, we can end it. Today, food banks serve as critical lifelines for communities, addressing the urgent needs of hunger and food insecurity. These organizations rely on the goodwill of donors, that provide cash or in-kind food donations, to help them meet their objectives. Studies have found that food pantries provide millions of dollars in value to recipients and their communities annually. I conduct cost-benefit analyses of food donation programs using Monte Carlo simulations to evaluate the economic impact of local food investments. By gathering data from various food pantries in New Jersey including resource costs, food procurements, transportations, logistics, marketings, and facility expenses. I run multiple simulations to estimate the cost per meal. The results indicate that the most influential factors affecting meal costs are whether the pantry is operated by volunteers or full-time staff, and whether the food is donated or prepared from scratch. My findings show that food pantries staffed primarily by volunteers, with minimal full-time employees and a reliance on donated food, are the most cost-efficient and provide the greatest benefits to low-income families. It is also indicating that an investment of $1 in food donation delivers $8.5 of social value. Beyond the measurement of cost effectiveness, the methodology helps in understanding how food pantries could improve their cost effectiveness. It generates significant and wide-ranging benefits that can be categorized into social, environmental, and economic impacts.

27. Governance: Evaluating Complex Regulatory Interventions [Full Panel of Research Presentations]
Friday | 10:45 am-12:15 pm | Room 308

In a League [Table] of Their Own: The Cost-Effectiveness of Federal Regulation Keith Belton, American Chemistry Council; and John Graham, Indiana University show abstract

Used extensively in sports to compare the performance of teams, league tables have also been used to compare the cost effectiveness of regulations intended to save lives, an application developed and first promoted by the Office of Management and Budget in the late 1980s and early 1990s. Using a methodology developed and employed by Morrall, we construct a league table based on dozens of recent federal regulations intended to prevent premature mortality and morbidity. We test our hypothesis that the use of benefit-cost analysis in regulatory impact analysis has led to improvement in the cost effectiveness of life-saving regulations over time.
The Challenges of Assessing AI Regulation Stephen Gibson, UK Government Regulatory Policy Committee show abstract

The recent surge in Generative Artificial Intelligence has introduced both opportunities and risks to society. This talk discusses the challenges of assessing the impacts of regulation of AI. It identifies a range of different concerns that might give rise to AI regulation and sets out approaches that may inform the design of AI regulation as well as principles for a robust AI regulatory framework. The talk focuses on the methodologies and challenges involved in evaluating the impacts of AI regulation particularly where there is both significant uncertainty around the costs and benefits of the proposed regulation and the potential for near-existential risk, meaning that AI regulatory proposals are not easily susceptible to standard cost benefit analysis approaches. It outlines and considers the use of a range of quantitative and qualitative approaches to the assessment of AI regulatory proposals including breakeven analysis, using real options and applying the precautionary principle. The talk draws on this background paper. https://dash.harvard.edu/server/api/core/bitstreams/942665e9-90e9-42e7-a2f1-34afc8f3b4ce/content
The Socio-Economic Benefits of Earth Observation by Satellites Massimo Florio, CSIL show abstract

Earth Observation (EO) has become a strategic component of the space economy, offering essential data and services with wide-ranging socio-economic and environmental implications. Despite the growing availability of EO data and rapid technological advances, a comprehensive quantification of its potential economic impact across sectors is still lacking. This paper addresses two main research questions: which economic sectors could benefit most from EO advancements, and what is the potential contribution of fully exploiting EO services and applications to value added and, ultimately, national GDP. We develop a novel multi-method approach that combines (a) a machine learning text analysis of EO-related scientific literature with (b) a quantitative assessment based on user surveys, expert elicitation, and Monte Carlo simulations. The first method maps scientific publications to economic sectors to infer the prospective potential of EO applications, while the second estimates their potential economic impact using data for Italy. The analysis draws on a survey of 106 end users, a Delphi study with 13 EO experts, and complementary national statistics. Results identify six sectors—agriculture, mining, electricity, water and waste, construction, and transport—as those with the greatest EO-related opportunities, with agriculture showing the highest potential. The simulated economic effects suggest that the diffusion of EO services and applications could generate a potential annual direct impact on Italian GDP of around 5%, underlining the transformative potential of EO technologies for the national economy. The study makes both substantive and methodological contributions. Substantively, it provides one of the first comprehensive estimates of EO’s cross-sectoral economic impact. Methodologically, it introduces a replicable, data-driven framework that integrates text mining, expert judgment, and probabilistic modeling. This approach can be applied to other countries or adapted to assess the socio-economic impact of emerging technologies beyond Earth Observation. Keywords: Earth Observation, space industry, machine learning, Monte Carlo simulation, Delphi method

28. Valuation: New Empirical Tools for Applied Benefit–Cost Work [Full Panel of Research Presentations]
Friday | 10:45 am-12:15 pm | Room 310

Pricing Suffering in Animals Natalie Jacewicz, University of San Diego School of Law; Bob Fischer, Texas State University; and Victor Crespo, Duke University show abstract

Large majorities of Americans care about animal welfare, and many federal regulations affect the welfare of billions of domesticated animals. Agencies promulgate rules affecting whether show horses endure sores, whether cows contract diseases, and whether chickens have access to the outdoors. The manner in which agencies consider animal welfare in decision-making thus has consequences for millions of Americans’ preferences for greater animal welfare. This Article investigates how animal welfare informs agency decision-making through the first systematic analysis of cost-benefit analysis (CBA) in regulatory impact analyses published by the U.S. Department of Agriculture over roughly the past 20 years. The survey reveals a widespread neglect of animal welfare. Most CBAs ignore effects to animal welfare altogether. To the extent CBAs contain qualitative discussions of impacts to animal welfare, such discussions are thin. Only a handful of CBAs monetize animal welfare effects. Taken together, these findings suggest a systematic neglect of animal welfare that undermines rational decision-making. This Article argues that animal welfare should be incorporated into agencies’ CBAs to reflect Americans’ concern for animals’ well-being. CBAs’ current approach to animal welfare falls short of executive guidance and risks being found arbitrary and capricious by courts. To improve agencies’ decision-making and compliance with law, the Article suggests a variety of technical and procedural tools agencies could use to account for the value that Americans place on animal welfare.
Climate-Resilient Food Systems: A Benefit-Cost Analysis of Financing Models for Nutrition and Agricultural Adaptation in East Africa Claire Nyapucha, Prosperbridge Initiative for Empowerment show abstract

Climate change is intensifying food and nutrition insecurity across Sub-Saharan Africa, particularly among vulnerable rural households reliant on rain-fed agriculture. Rising temperatures, erratic rainfall, and recurrent droughts have disrupted food supply chains, worsened malnutrition, and increased the economic vulnerability of farming communities. While adaptation strategies exist—including drought-resistant crops, drip irrigation, and post-harvest technologies—scaling them requires robust financial models and evidence of economic viability. This study employs benefit-cost analysis (BCA) to assess the relative efficiency of different financing models—such as climate adaptation funds, green bonds, concessional loans, and community-based savings and credit schemes—in supporting nutrition-sensitive and climate-smart food system interventions. Data sources include agribusiness pilot projects in Kenya and Ethiopia, climate adaptation investment portfolios, and regional health and nutrition datasets. The analysis quantifies both direct costs (capital mobilization, adaptation technologies, and program implementation) and benefits (improved yields, reduced post-harvest losses, enhanced dietary diversity, reduced malnutrition-related morbidity, and climate risk mitigation). Preliminary results demonstrate that investments in drip irrigation and cold-chain storage, when supported by blended finance and climate funds, generate a benefit-cost ratio ranging from 3.5 to 6.2, with the highest returns accruing in nutrition outcomes for children under five and women of reproductive age. Beyond efficiency, distributional analysis shows that community-managed savings groups improve access to finance for smallholder farmers, especially women and youth, amplifying equity and resilience. These findings underscore the importance of integrating financial innovation with climate adaptation strategies to secure both economic and nutritional outcomes. By linking finance, food systems, and climate resilience through rigorous BCA, this paper contributes actionable insights for policymakers, donors, and investors seeking to align agricultural adaptation with equitable nutrition security in East Africa.
Economic Valuation of Climate-Smart Farming Preferences in Kenya’s Drylands Alice Karanja, African Population and Health Research Center (APHRC); Boscow Okumu, African Population and Health Research Center (APHRC); Esther Anono, African Population and Health Research Center (APHRC)); Stepha McMullin, World Agroforestry; Bonventure Mwangi, APHRC; and Elizabeth Kimani, APHRC show abstract

Understanding farmer preferences and willingness to pay for climate-smart practices is vital for designing efficient and equitable adaptation policies in Africa’s drylands. This study applies a discrete choice experiment (DCE) using 5,652 observations from households in Laikipia County, an arid and semi-arid landscape in Kenya, to quantify the perceived economic value of key agroecological interventions. Respondents evaluated alternative land-management packages that varied by agroforestry, water conservation, crop diversification, tillage method, farm nutrient input, and program cost. A multinomial logit model revealed strong and significant preferences for agroforestry (β = 0.48, p < 0.001), water conservation (β = 0.26, p < 0.001), and organic farming (β = 0.27, p < 0.001). Cost carried a negative sign (β = –0.00013, p = 0.013), confirming price sensitivity. Using the cost coefficient to derive marginal willingness to pay, households valued agroforestry at roughly four times the monetary equivalent of other practices, about KSh 3,700 (≈USD 30) in relative terms. Findings demonstrate clear economic incentives for policies that expand access to trees on farms, improve soil-water conservation, and promote affordable nutrient inputs. Integrating these preferences into benefit–cost analysis yields positive social returns, with estimated benefit–cost ratios above 3:1 when scaled through county extension programs. Companion qualitative data reveal gender-linked patterns, with women preferring lower-cost, time-saving options such as water harvesting and mixed cropping. Overall, the analysis provides evidence that investing in community-driven, climate-smart agriculture in Kenya’s drylands is not only environmentally sustainable but also economically efficient and socially equitable.

29. Reframing Regulatory Budgeting: Integrating Retrospective Review and Evidence-Based Governance [Roundtable/Panel]
Friday | 10:45 am-12:15 pm | Amphitheater

Organizers: Deborah Aiken, unaffiliated; Eliane Catilina, U.S. Dept of Transportation;
Chair: Darren Timothy, US Department of Transportation

Panelists:

Deborah Aiken, unaffiliated;
Eliane Catilina, U.S. Dept of Transportation;
Joseph Cordes, George Washington University;
Susan Dudley, George Washington University;
Paul Mwebaze, University of Illinois Urbana Champaign;

30. Benefit–Cost Analysis and the Courts [Roundtable/Panel]
Friday | 10:45 am-12:15 pm | Room 302

Organizer: Caroline Cecot, George Washington University
Chair: Caroline Cecot, George Washington University

Panelists:

Elissa Philip Gentry, Arizona State University;
Jack Lienke, University of Connecticut;
Caroline Cecot, George Washington University;

31. Luncheon Keynote With Solomon Hsiang [Plenary]
Friday | 12:30 pm-2:00 pm | Grand Ballroom

32. Valuing Health and Environmental Risk Reductions [Full Panel of Research Presentations]
Friday | 2:15 pm-3:45 pm | Amphitheater

Organizer: John Whitehead, Appalachian State University
Chair: Vic Adamowicz, University of Alberta

Using Stated Preference to Estimate WTP to Reduce Risk of Non-financial Impacts of Chronic Morbidity from Infectious Illnesses Sandra Hoffman, USDA Economic Research Service; Alan Krupnick, Resources for the Future; Daniel Rigby, U. of Manchester; and Michael Burton, U. of Western Australia show abstract

In BCA morbidity is typically valued using avoided medical costs plus lost wages, which underestimates WTP. Stated preference surveys could be used to estimate these benefits, but the sheer number of such outcomes has been a barrier to their development. We developed a suite of surveys using 3 approaches to address this challenge of high dimensionality. We present results on one approach, use of a single survey to develop estimates for multiple outcomes. Instream water, drinking water, and food safety policy reduce exposure to food and waterborne pathogens. The infectious illnesses they cause can lead directly to serious complications and long-term adverse health outcomes. This discrete choice experiment survey elicits WTP to reduce risk of developing eleven such outcomes, including hospitalized dehydration, sepsis, reactive arthritis, Guillan Barre syndrome, end-stage kidney disease, vision impairment, meningitis, and irritable bowel syndrome. The survey uses conventional disease outcome descriptions, a well validated risk tutorial, and a generalized delivery mechanism successfully used in other surveys. Disease prognoses are described as they would be by a physician at disease onset. The major innovation explored here is the feasibility of including multiple illnesses in a single survey as a way to overcome “high dimensionality.” Around 1000 respondents each faced 5 choices (5 different diseases). We found appropriate sensitivity to cost and risk change, but not to income. However, employment status was significant with those unemployed or looking for work willing to pay less, and retired respondents willing to pay more than employed respondents. African American WTP exceeded that of whites. We show that a single survey can produce credible WTP estimates for multiple chronic disease outcomes.
The effect of low-level childhood lead exposure on earnings: a comparison of different approaches Heather Klemick, National Center for Environmental Economics, USEPA; Dennis Guignet, Appalachian State University; Ron Shadbegian, Appalachian State University; and Linda Bui, Brandeis University show abstract

Lead is a toxin that damages children’s neurodevelopment. Numerous studies have found a significant association between higher blood lead levels (BLL) and lower intelligence quotients (IQ) and academic performance (EPA 2024a). Many analyses of policies to reduce lead exposure have monetized benefits by applying estimates linking BLL to IQ, and IQ to adult earnings (e.g., EPA 2024b; Larsen and Sánchez-Triana 2023; Pew Charitable Trusts 2017). A limitation of this approach is that the most commonly used BLL-IQ studies rely on data from the 1980s and 1990s, when BLLs were much higher than they are today (Lanphear et al. 2005, 2019; Crump et al. 2013). In addition, newer studies have estimated the effects of BLL on children’s school performance (e.g., Aizer et al. 2018, Evens et al. 2015, Shadbegian et al. 2019). While academic performance has been linked to adult earnings (Chetty et al. 2014), the relationship between BLL and academic performance has not been used to estimate the benefits of policies to reduce lead exposure. Following a 2022 protocol, Axelrad et al. have identified 37 studies that estimate the BLL-IQ relationship in populations with relatively low BLLs (mean BLL < 5 µg/dL). We will present the meta-analytic average of these estimates, as well as estimates from key subsets of studies, such as those with mean BLL < 3.5 µg/dL, which is more reflective of the current population. We will also conduct a review and meta-analysis of studies estimating the relationship between BLL and academic performance, building on recent reviews (EPA 2024a; Crawfurd et al. 2024). We will apply both approaches in an illustrative benefits analysis to estimate the change in earnings from reducing lead exposure. The results will provide a better understanding of the benefits of further reducing BLLs from current levels and allowing a comparison across multiple methodologies.
Wildlife Crossings: A Cost-Benefit Analysis Rob Moore, Scioto Analysis; and Jacob Strang, Scioto Analysis show abstract

Each year, one to two million crashes occur between vehicles and animals in the United States. These social costs pose a threat to safety, causing an estimated 200 passenger fatalities, 26,000 injuries, and more than $8 billion in economic costs including vehicle damage and medical expenses. One reason so many collisions happen is because wildlife migrate at key points of high traffic along public highways. By strategically building crossing infrastructure following animal migratory patterns, some public projects have been able to reduce wildlife collisions in high-traffic areas by more than 90%. In moderate collision areas, this can prevent 20 or more collisions per year. In high-collision areas, more than 100 collisions can be prevented per year. In this analysis, we estimate the net social benefits of building a wildlife crossing in an area with a moderate to high number of wildlife vehicle collisions. We find that building a wildlife crossing will lead to a wide range of social impacts, from lives saved to healthier wildlife ecosystems. We estimate that a wildlife crossing with a lifespan of 70 years will lead to 1,400 fewer collisions, an average of more than one fewer passenger fatality, 60 fewer injuries, $2.5 million lower medical expenses, $1.6 million lower vehicle damage, $65 thousand lower roadkill disposal and towing costs, 1,200 fewer animal lives lost, and $2.1 million in ecosystem services. In total, the net present value of building a wildlife crossing in an area with a moderate to high number of wildlife vehicle collisions is $13.8 million over the course of a 70-year lifespan. This implies a benefit-cost ratio of $10 in social benefits for every $1 in social costs and an average annual benefit of $200,000. Under our model, the benefits of a wildlife crossing exceed costs within seven years of crossing construction. Across a variety of different inputs and trials, we found that in the best case scenario, as many as 7,100 collisions can be prevented, 20 passenger fatalities can be avoided, and 6,700 animal deaths can be prevented from one wildlife crossing structure. We estimate that a wildlife crossing can lead to between $11 and $147 million of net social benefits over 70-80 years. In 99.7% of the trials we performed, the net present value of wildlife crossings was positive. Even under the most expensive wildlife crossing proposals, the net present value of building a wildlife crossing structure remains positive if it is built in a location with at least 26 collisions per year within a ten-mile radius.
Preferences for Reducing Air Pollution Health Risks Increase after Substantial Air Quality Improvement Yanying Wang, South China Normal University show abstract

Across the globe, air quality has improved in many cities over recent decades due to tighter environmental governance. Standard theory predicts that, as air quality gets better, willingness to pay (WTP) for a marginal health-risk reduction should decline as baseline health risk falls. Contrary to this prediction, we document a puzzle: using two waves of discrete choice experiments (DCE) fielded in 2016 and 2024 in Beijing, China, we find that WTP for reducing mortality and morbidity risks rose by more than 60% even as ambient PM₂.₅ concentrations fell by about 58% over the same period. We propose and test several mechanisms that can account for this pattern. First, perceived credibility of the government’s air quality policy increased markedly from 2016 to 2024, amplifying the valuation of health-risk reductions. Second, income growth exhibits a non-linear pass-through to WTP, with marginal effects rising at higher income levels. Third, WTP for reducing mortality risks rises with contemporaneous PM₂.₅ within a given year, but this relationship does not hold in cross-year comparisons. We rule out lower cost sensitivity, different protest patterns or COVID-related salience as primary explanations. These findings indicate that valuations in settings with both experience good and public good features are not invariant. It is especially important to regularly update health risk valuation metrics in a fast-developing context and consider perceived credibility in the providing institution when applying stated preference methods.

33. Climate Policy: Climate Benefits Beyond the Headlines: Evidence and Methods [Full Panel of Research Presentations]
Friday | 2:15 pm-3:45 pm | Room 307

Standalone Solar Energy Powered System For Sustainable Poultry Production Wilfred Okonkwo, ABT Associates show abstract

Poultry farming is an important unit of the livestock industry that contributes significantly to animal protein production, job creation, and food safety. Poultry production in the developing countries is fraught with many challenges, in particular, inadequate energy supply, which often times leads to a high mortality rate and low profit margin. Solar energy has the potential key role to play for sustainable energy supply in poultry production and the food security industry. However, the undocumented concerns expressed by poultry consumers about chicken meat and eggs produced under solar radiation influence may lead to disease and some illnesses on consumption formed the major aim of this study. An experimental study using 300 pullet birds in a standalone solar-powered poultry system was conducted for a period of six weeks session in 3 replicates. The results of the experiment were compared with grid-electric and fossil fuel-powered systems. The proximate composition of the chickens bred under the 3 heating sources was experimentally conducted in a laboratory. The meat parts investigated were the liver, heart, kidney, wings, breast, thigh, and gizzard, while the proximate parameters examined were protein, Fat, ash, fibre, moisture, and carbohydrate. The laboratory investigation and the proximate contents analysis of the various parts of the chickens under the different methods were characterized and presented in this paper. Solar has a higher comparative advantage over conventional chickens, probably due to the sustainable and efficient energy utilization it offers. Use of solar results to the production of healthy chickens and high-quality meat. Indications showed that solar has no harmful effect on poultry meat qualities. The results of the study could be the starting point for modern poultry evolution and a useful tool for policymakers towards improved poultry production systems.
The Effect of Remote Job Opportunities on Internal Migration Aghairza Mammadov, University of South Florida show abstract

This paper examines how remote job opportunities (RJOs) influence internal migration patterns in the United States. Motivated by migration theory, which emphasizes job search costs as a major factor behind relocation, the paper considers two opposing effects. RJOs can make migration easier for individuals who were previously discouraged by the risk of not finding a job in a new location. At the same time, they may reduce the need for moves that are solely motivated by the search for better career opportunities. Leveraging a nationally representative dataset of 11.5 million individuals, the study applies a shift-share IV and recursive bivariate probit model to ensure credible identification. Results show that RJOs lower interstate migration by 36.9 percent while raising moves between local labor markets by 23.6 percent and within local labor markets by 50.2 percent. These findings suggest that remote work reduces long-distance migration but encourages medium and short distance moves, reshaping the geography of labor market adjustment.
Wealth Accumulation in College Savings Accounts and Educational Opportunities Alexey Vasilenko, Vanderbilt University show abstract

529 college savings plans have become more prevalent than student loans among undergraduates, yet their educational impacts remain largely unexplored. This paper examines how wealth gains in 529 plans shape educational opportunities using a shift-share IV approach that exploits variation in target-date fund designs within these plans. Contrary to existing literature suggesting minimal effects of household wealth on college attendance, I find that 529 wealth gains are remarkably effective at increasing four-year college attendance, matching the impact of targeted grant aid per $1,000. These wealth gains also reduce student loan borrowing and boost private K-12 school enrollment. However, 529 wealth gains accrue disproportionately to upper-income households, exacerbating the four-year college attendance gap between students from the top and bottom income quartiles by 16% in 2023.

34. Equity: Equity, Ranking, and Welfare in Policy Appraisal [Full Panel of Research Presentations]
Friday | 2:15 pm-3:45 pm | Room 308

Why a Properly Conducted Benefit-Cost Analysis Requires the Consideration of Distributional Impacts Richard Revesz, New York University; Burçin Ünel, Institute for Policy Integrity at New York University School of Law; and Sarah Wheaton, New York University show abstract

The consideration of the distributional impacts of government policies has traditionally been viewed as an inquiry that proceeds alongside a benefit-cost analysis but that is not part of the assessment of a policy’s benefits and costs. That view is analytically wrongheaded. Generally, benefit-cost analyses are conducted based on impacts on an average member of the population. Often, however, the populations affected by government policies vary from the average in significant ways. Heterogeneity by age, race, income, and other factors is relevant to the assessment of the benefits and costs of particular policies for three principal reasons. On the benefits side, certain groups face higher levels of exposure to environmental harms and, where the dose-response functions are non-linear or where exposure to different pollutants results in negative synergistic effects, these groups face higher harms from exposure to an additional unit of pollution. Also, certain groups have higher vulnerability to particular exposures. And, on the cost side, certain groups bear higher burdens because of differences in geography, spending patterns, and other behaviors. This article provides a robust review of the scientific, epidemiological, and economic literature for each of these mechanisms, surveys what agencies have already done, and sets forth an agenda for future research. The consideration of the distributional impacts of policies can lead to large differences in the assessment of benefits and costs. For example, one study found that the top 5% of the population in terms of susceptibility to cancer may be subject to 25 times more risk of cancer than the average person and the top 1% may face more risk. As a result, a benefit-cost analysis based on impact to the average member of the population would significantly underestimate the benefits of regulatory protections, leading to a biased analysis and economically inefficient regulations.
Toxic Tradeoffs: Impact of Environmental Regulations on Workplace Safety Sanjukta Mitra, Iowa State university show abstract

Environmental regulations reduce ambient pollution exposure, which may benefit workers at regulated firms; on the other hand, new compliance costs may crowd out safety investments at firms, increasing the risk of worker injuries. This paper uses a Difference-in-Differences design to estimate the short-run net effects of the 1990s Clean Air Act (CAA) PM10 standards on workplace injuries in the mining sector, us- ing a panel linking Mine Safety and Health Administration (MSHA) mine-year injury records to novel sub-county PM10 nonattainment boundaries for 1983–1997. Serious nonattainment designation increased workplace injuries by 3.7 per 100 full-time workers, and the total number of severe injuries by 0.776 per mine, imposing an economic cost on workers of roughly $0.20 billion (1990 dollars) per year. These effects persist across specifications and are driven by reduced safety compliance, increased work hours and overexertion among retained staff. The findings reveal thorny distributional tradeoffs: health benefits of the 1990 CAA Amendments are large but diffuse, while safety costs are small and concentrated among workers.
Life Years Saved from Tobacco Harm Reduction Products: A Dynamic Population Simulation Model for Nepal Trilochan Pokharel, Nepal Administrative Staff College show abstract

Tobacco use remains a major cause of preventable death, making smoking cessation a key public health priority. Evidence suggests that e-cigarettes or vaping products may reduce smoking initiation and increase cessation, potentially contributing to tobacco harm reduction despite their associated health risks. This study evaluates the possible population-level impact of vaping in Nepal. A dynamic population simulation model is applied using 210 scenarios projected over 80 years. The baseline year is 2019, with data from the UN Population Division, Nepal STEPS Survey 2019, and Global Burden of Disease 2019. Baseline smoking prevalence was 32.83% for males and 11.42% for females. Initiation rates were estimated at 29.41% for males and 1.38% for females, while cessation rates varied by age and sex. Scenarios combine hypothetical changes in smoking initiation (−20% to +20%), cessation (5% to 200%), and vaping health risks (0% to 20%). Across all scenarios, life years saved relative to life years lost due to smoking ranged from −10.04% to 57.62% for males and from 0.07% to 21.52% for females. Four scenarios were considered plausible, assuming a 10% reduction in initiation, a 25% or 50% increase in cessation, and vaping health risks of 5% or 10%. After 50 years, males experienced life years saved of 13–14% with a 25% increase in cessation and 21–22% with a 50% increase, while smoking prevalence declined to around 16–17%. For females, life years saved ranged from 2% to 4.5%, and smoking prevalence fell below 0.5%. The share of e-quitters among all quitters was consistently higher for females. In summary, under plausible assumptions, vaping could meaningfully reduce smoking prevalence and increase life years saved in Nepal. Although based on hypothetical scenarios, the results indicate a potentially beneficial role for tobacco harm reduction strategies.

35. Practical considerations in conducting benefit cost analysis [Roundtable/Panel]
Friday | 2:15 pm-3:45 pm | Room 302

Organizer: Joe Devlin,

Panelists:

Joe Devlin, ;
Deborah Aiken, unaffiliated;

36. The Year in Review and the Year Ahead: Perspectives on U.S. Regulation [Roundtable/Panel]
Friday | 4:00 pm-5:30 pm | Amphitheater

Organizer: Craig Thornton, Mathematica
Chair: Lisa Robinson, Harvard University

Panelists:

Susan Dudley, George Washington University;
Jason Schwartz, Institute for Policy Integrity;
Stuart Shapiro, Rutgers University;
Heidi King, Heidi King Consulting;

Index to Participants

Acland, Dan: 16
Adamowicz, Vic: 13 , 14 , 32
Aiken, Deborah: 21 , 29 , 35 , 4
Akram, Agha: 24
Amoah, Anthony: 17
Amoah, Anthony: 22
Amuakwa-Mensah, Franklin: 22
Andersson, Henrik: 24
Angel, Gur: 15
Anono, Esther: 28 , 7
Appéré, Gildas: 23
Austin, Wes: 14 , 15 , 9
Bae, Jung: 11
Bailey, Eva: 9
Barrett, Mackenzi: 12
Bartczak, Anna: 12
Baxter, Jennifer: 17
Becker, Nir: 15
Belova, Anna: 15
Belton, Keith: 27
Bhagat, Anvesha: 26
Blomquist, Glenn: 10 , 25
Bostian, Moriah: 21 , 4
Bruns, Richard: 26
Budziński, Wiktor: 12
Bui, Linda: 32
Burton, Michael: 32
Byl, Jacob P.: 14
Carrigan, Christopher: 24
Catilina, Eliane: 29
Cecot, Caroline: 30
Chamaki, Foroogh: 26
Civel, Edouard: 22
Conran, Joseph: 24
Cook, Michael: 24
Cordes, Joseph: 29
Crespo, Victor: 28
Creti, Anna: 22
Czajkowski, Mikołaj: 16
D'Agostino, Anthony: 24
Devlin, Joe: 35
Diamond, Megan: 24
Dobkin, Finn: 16
Dudley, Susan: 29 , 36
Earle, Andrew: 5
Eshghi Nezami, Mohammad Amin: 12
Fack, Gabrielle: 22
Färe, Rolf: 21
Fischer, Bob: 28 , 5
Florio, Massimo: 27
Garcia, Helena: 5
Gibson, Stephen: 27
Gilch, Sabine: 14
Gold, Adam: 5
Gourevitch, Jesse: 5
Graham, John: 27
Grana, Jess: 24
Gray, Brendon: 26
Grosskopf, Shawna: 21
Guignet, Dennis: 32
Gulati, Anjali: 9
Hadziomerspahic, Amila: 9
Harpankar, Kshama: 11
Hartnett, Emma: 15
Hasan, Rezaul: 24
Herrera, Daniel: 22 , 23
Hoffman, Sandra: 32
Hong, Yumin: 23
Horgan, Bronwyn: 22
Horn, Jeffrey: 26
Howard, Gregory: 5
Hsu, Lawrence: 6
Hsu, Shi-Ling: 14
Jacewicz, Natalie: 28
Jenkins, Glenn: 26
Kalbarczyk, Małgorzata: 12
Karanja, Alice: 28 , 7
Kashani, Hamed: 12
Kenkel, Don: 23
Keshaviah, Aparna: 24
Khan, Aamir Ashfaq: 15
Kim, Paul: 6
Kimani, Elizabeth: 28
King, Heidi: 36
Klemick, Heather: 32 , 9
Kniesner, Thomas J.: 10 , 25
Knoche, Scott: 9
Kostopoulou, Maria: 23
Kraynak, Daniel: 9
Krupnick, Alan: 32
Lauer, Christopher: 17
Lienke, Jack: 30
Lindhjem, Henrik: 23
Liu, Pengfei: 14
Luckert, Marty: 14
Lundgren, Tommy: 21
Lynch, Erin: 24
Macchi, Patricia: 22
Mammadov, Aghairza: 33
Marbuah, George: 22
Marsolais, Elizabeth: 12
Masterman, Clayton: 25
McGartland, Al: 25
McMichael, Benjamin: 12
McMullin, Stepha: 28
Metz, David: 12
Miklyaev, Mikhail: 26
Miller, Benjamin: 12
Mitra, Sanjukta: 34
Mockus, Dominik: 26
Momoli, Franco: 15
Moore, Rob: 32 , 9
Morgan, Ash: 5
Morgan, Cynthia: 21
Munson, Kate: 15
Mwangi, Bonventure: 28
Mwebaze, Paul: 17 , 29
Nadeau, Lou: 11
Napper, Scott: 14
Navrud, Ståle: 23
Nigussie, Yirgalem: 21
Nong, Kaijun: 14
Nowak-Laird, David: 26
Nyapucha, Claire: 28 , 8
Ojo, Kehinde: 9
Okonkwo, Wilfred: 33
Okumu, Boscow: 28
Paoli, Greg: 15
Pasurka, Carl: 21
Pasurka, Carl: 4
Paterson, Robert: 17
Percoco, Marco: 22
Petosa, Jeremy: 26
Petrolia, Daniel: 5
Philip Gentry, Elissa: 10 , 30
Pokharel, Trilochan: 34
Price, Elizabeth: 9
Pybus, Margo: 14
Rahman, Mahbubur: 24
Rahman, Ziaur: 24
Raxter, Ian: 24
Redstone, Thomas: 22
Revesz, Richard: 34
Rigby, Daniel: 32
Rizmie, Dheeya: 24
Robinson, Lisa: 25 , 36 , 6
Sahebzadeh, Amir Mohammad: 12
Schaetzl, Hermann: 14
Schwartz, Jason: 36
Shadbegian, Ron: 21 , 32
Shaffer, Luke: 24
Shapiro, Stuart: 36
Shuck, Hana: 22
Sommerfeld, Emily: 9
Spink, Elizabeth: 14
Strang, Jacob: 32
Strow, Rachel: 9
Suchana, Afroza Jannat: 24
Suchana, Afroza Jannat: 24
Sullivan, Karen: 9
Sullivan, Ryan: 10
Thiesing, Adam: 9
Thornton, Craig: 36
Timothy, Darren: 29
Tompson, Caroline: 11
TRAVERS, Muriel: 23
Turner, Elisa: 24
Ünel, Burçin: 34
Vasilenko, Alexey: 33
Vazquez, Antonia: 23
Venugopal, Sandya: 6
Vilain, Pierre: 11 , 6
Viscusi, W. Kip: 10 , 12 , 25
Wainger, Lisa A.: 9
Walsh, Patrick: 14 , 9
Walster, Scott: 24
Wang, Shuyi: 21
Wang, Yanying: 32
Weaver, Drew: 26
Weber, Matt A.: 9
Wei, Cecilia: 24
Wheaton, Sarah: 34
Whitehead, John: 14 , 32 , 5 , 9
Whittington, Dale: 13
Wong, Brad: 6
Xu, Qin: 14
Yadav, Anjali: 16
Yang, Linge: 21
Younossi, Elena: 12
Yu, Anthony: 12
Zawadzki, Wojciech: 16
Zhu, Lei: 14