Create a culture of experiments in environmental programs.

Organizations need a better "learning by doing" approach.

Physical distancing versus testing with self-isolation for controlling an emerging epidemic.

Two distinct strategies for controlling an emerging epidemic are physical distancing and regular testing with self-isolation. These strategies are especially important before effective vaccines or treatments become widely available. The testing strategy has been promoted frequently but used less often than physical distancing to mitigate COVID-19. We compared the performance of these strategies in an integrated epidemiological and economic model that includes a simple representation of transmission by "superspreading," wherein a relatively small fraction of infected individuals cause a large share of infections. We examined the economic benefits of distancing and testing over a wide range of conditions, including variations in the transmissibility and lethality of the disease meant to encompass the most prominent variants of COVID-19 encountered so far. In a head-to-head comparison using our primary parameter values, both with and without superspreading and a declining marginal value of mortality risk reductions, an optimized testing strategy outperformed an optimized distancing strategy. In a Monte Carlo uncertainty analysis, an optimized policy that combined the two strategies performed better than either one alone in more than 25% of random parameter draws. Insofar as diagnostic tests are sensitive to viral loads, and individuals with high viral loads are more likely to contribute to superspreading events, superspreading enhances the relative performance of testing over distancing in our model. Both strategies performed best at moderate levels of transmissibility, somewhat lower than the transmissibility of the ancestral strain of SARS-CoV-2.

Emphasize personal health benefits to boost COVID-19 vaccination rates.

The rapid development of COVID-19 vaccines is a tremendous scientific response to the current global pandemic. However, vaccines per se do not save lives and restart economies. Their success depends on the number of people getting vaccinated. We used a survey experiment to examine the impact on vaccine intentions of a variety of public health messages identified as particularly promising: three messages that emphasize different benefits from the vaccines (personal health, the health of others, and the recovery of local and national economies) and one message that emphasizes vaccine safety. Because people will likely be exposed to multiple messages in the real world, we also examined the effect of these messages in combination. Based on a nationally quota representative sample of 3,048 adults in the United States, our findings suggest that several forms of public messages can increase vaccine intentions, but messaging that emphasizes personal health benefits had the largest impact.

Hesitancy Toward a COVID-19 Vaccine.

The scientific community has come together in a mass mobilization to combat the public health risks of COVID-19, including efforts to develop a vaccine. However, the success of any vaccine depends on the share of the population that gets vaccinated. We designed a survey experiment in which a nationally representative sample of 3,133 adults in the USA stated their intentions to vaccinate themselves and their children for COVID-19. The factors that we varied across treatments were: the stated severity and infectiousness of COVID-19 and the stated source of the risk information (White House or the Centers for Disease Control). We find that 20% of people in the USA intend to decline the vaccine. We find no statistically significant effect on vaccine intentions from the severity of COVID-19. In contrast, we find that the degree of infectiousness of the coronavirus influences vaccine intentions and that inconsistent risk messages from public health experts and elected officials may reduce vaccine uptake. However, the most important determinants of COVID-19 vaccine hesitancy seem to be distrust of the vaccine safety (including uncertainty due to vaccine novelty), as well as general vaccine avoidance, as implied by not having had a flu shot in the last two years.

Protecting local water quality has global benefits.

Surface water is among Earth's most important resources. Yet, benefit-cost studies often report that the costs of water quality protection exceed its benefits. One possible reason for this seeming paradox is that often only a narrow range of local water quality benefits are considered. In particular, the climate damages from water pollution have rarely been quantified. Recent advances in global water science allow the computation of the global methane emission from lakes caused by human nutrient enrichment (eutrophication). Here, we estimate the present value of the global social cost of eutrophication-driven methane emissions from lakes between 2015 and 2050 to be $7.5-$81 trillion (2015 $US), and in a case-study for one well-studied lake (Lake Erie) we find the global value of avoiding eutrophication exceeds local values of either beach use or sport fishing by 10-fold.

Effects of Physical Distancing to Control COVID-19 on Public Health, the Economy, and the Environment.

Physical distancing measures are important tools to control disease spread, especially in the absence of treatments and vaccines. While distancing measures can safeguard public health, they also can profoundly impact the economy and may have important indirect effects on the environment. The extent to which physical distancing measures should be applied therefore depends on the trade-offs between their health benefits and their economic costs. We develop an epidemiological-economic model to examine the optimal duration and intensity of physical distancing measures aimed to control the spread of COVID-19. In an application to the United States, our model considers the trade-off between the lives saved by physical distancing-both directly from stemming the spread of the virus and indirectly from reductions in air pollution during the period of physical distancing-and the short- and long-run economic costs that ensue from such measures. We examine the effect of air pollution co-benefits on the optimal physical distancing policy and conduct sensitivity analyses to gauge the influence of several key parameters and uncertain model assumptions. Using recent estimates of the association between airborne particulate matter and the virulence of COVID-19, we find that accounting for air pollution co-benefits can significantly increase the intensity and duration of the optimal physical distancing policy. To conclude, we broaden our discussion to consider the possibility of durable changes in peoples' behavior that could alter local markets, the global economy, and our relationship to nature for years to come.

Policy Brief - What's in a Name? A Search for Alternatives to "VSL".

Benefit-cost analyses of environmental, health, and safety regulations often rely on an estimate of the value of statistical life (VSL) to calculate the aggregate benefits of reducing human mortality risk. The VSL represents the marginal rate of substitution between mortality risk and money. Although this concept is well-understood by economists, it is viewed by many non-economists as confusing technical jargon that borders on the immoral. Based on focus groups and a quantitative ranking exercise, this article describes a systematic approach for identifying and testing alternatives to the VSL terminology, with the goal of identifying an alternative term that more clearly communicates the VSL concept to a broad audience.

Using structural restrictions to achieve theoretical consistency in benefit transfers.

Analysts often extrapolate estimates of the value of environmental improvements reported in prior studies to evaluate new policy proposals, a practice sometimes referred to as "benefit transfer." Benefit transfer functions are frequently specified based on statistical considerations alone. However, such a purely statistical approach can lead to willingness-to-pay functions that fail to satisfy some aspects of theoretical consistency that may be especially important for policy evaluations. In this paper, we examine several previous meta-analyses of nonmarket valuation studies in light of the adding-up condition, which is one important aspect of theoretical validity. We then use meta-regression to estimate a new willingness-to-pay function for surface water quality improvements intended to be used for benefit transfers. We estimate the meta-regression model using summary results from 51 previously published stated preference studies. An important feature of our approach is that we develop the meta-regression estimating equation to ensure that the resulting benefit transfer function will necessarily comply with the adding-up condition. This is achieved by first specifying a marginal willingness-to-pay function and then deriving an expression for total willingness-to-pay. This leads to a non-linear estimating equation, so we estimate the parameters of the model using non-linear least squares. We discuss the advantages and disadvantages of our approach relative to other structural approaches, and we compare our empirical results to a more traditional nonstructural meta-regression model. Finally, we examine the quantitative importance of imposing the adding-up condition in our case study by performing some illustrative calculations of willingness-to-pay for hypothetical water quality improvements using both structural and non-structural models.

Potential biodiversity benefits from international programs to reduce carbon emissions from deforestation.

Deforestation is the second largest anthropogenic source of carbon dioxide emissions and options for its reduction are integral to climate policy. In addition to providing potentially low cost and near-term options for reducing global carbon emissions, reducing deforestation also could support biodiversity conservation. However, current understanding of the potential benefits to biodiversity from forest carbon offset programs is limited. We compile spatial data on global forest carbon, biodiversity, deforestation rates, and the opportunity cost of land to examine biodiversity conservation benefits from an international program to reduce carbon emissions from deforestation. Our results indicate limited geographic overlap between the least-cost areas for retaining forest carbon and protecting biodiversity. Therefore, carbon-focused policies will likely generate substantially lower benefits to biodiversity than a more biodiversity-focused policy could achieve. These results highlight the need to systematically consider co-benefits, such as biodiversity in the design and implementation of forest conservation programs to support international climate policy.

Prioritizing conservation activities using reserve site selection methods and population viability analysis.

In recent years a large literature on reserve site selection (RSS) has developed at the interface between ecology, operations research, and environmental economics. Reserve site selection models use numerical optimization techniques to select sites for a network of nature reserves for protecting biodiversity. In this paper, we develop a population viability analysis (PVA) model for salmon and incorporate it into an RSS framework for prioritizing conservation activities in upstream watersheds. We use spawner return data for three closely related salmon stocks in the upper Columbia River basin and estimates of the economic costs of watershed protection from NOAA to illustrate the framework. We compare the relative cost-effectiveness of five alternative watershed prioritization methods, based on various combinations of biological and economic information. Prioritization based on biological benefit-economic cost comparisons and accounting for spatial interdependencies among watersheds substantially outperforms other more heuristic methods. When using this best-performing prioritization method, spending 10% of the cost of protecting all upstream watersheds yields 79% of the biological benefits (increase in stock persistence) from protecting all watersheds, compared to between 20% and 64% for the alternative methods. We also find that prioritization based on either costs or benefits alone can lead to severe reductions in cost-effectiveness.

Ecological effects of density-independent mortality: application to cooling-water withdrawals.

A wide variety of environmental stresses can cause density-independent mortality in species populations. One example is cooling-water withdrawals, which kill or injure many aquatic organisms near power plants and other industrial facilities. In the United States alone, hundreds of facilities withdraw trillions of gallons from inland and coastal waters every year to cool turbines and other manufacturing equipment. A number of detailed, site-specific studies of the effects of such cooling-water withdrawals have been conducted over the last 30 years, but only a few generalizations have been proposed in the peer-reviewed literature. In this paper we use a series of basic theoretical models to investigate the potential effects of density-independent mortality on species populations and ecosystems, with particular focus on the effects of cooling-water withdrawals on fish populations, fisheries, and aquatic communities. Among other results, we show that the effects of cooling-water withdrawals on a species will depend on the magnitude of other co-occurring stressors, environmental variability, the nature of the management regime in the associated fisheries, and the position of the species in the food web. The general models in this paper can provide a starting point for further empirical case studies and some preliminary conceptual guidance for decision makers who must choose between alternative policy options for controlling cooling-water withdrawals.

Population level impacts of cooling water withdrawals on harvested fish stocks.

Trillions of gallons are withdrawn every year from U.S. rivers, estuaries, lakes, and coastal waters to cool the turbines of power plants and other equipment in manufacturing facilities. In the process, large numbers of aquatic organisms die from entrainment into the plant or impingement against the outer portion of the intake structure. In this paper, we develop a generalized age-structured population model with density dependent survival of sub-adult age classes, and we use the model to perform a screening analysis of the effects of entrainment and impingement for 15 harvested fish stocks off the California and Atlantic coasts. Stock sizes are estimated to be depressed by entrainment and impingement by less than 1% in 10 of the 15 cases considered, between 1 and 3% in two cases, and between 20 and 80% in three cases. A variety of sensitivity analyses are conducted to evaluate the influence of several sources of model and parameter uncertainties.