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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
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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.
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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
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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.
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Preferences for Reducing Air Pollution Health Risks Increase after Substantial Air Quality Improvement
Yanying Wang, South China Normal University
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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.
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Wildlife Crossings: A Cost-Benefit Analysis
Rob Moore, Scioto Analysis; and Jacob Strang, Scioto Analysis
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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.