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1. Understanding the Improbable: A Survey of Fat Tails in Environmental Economics

   https://doi.org/10.1146/annurev-resource-102020-094143  

   Conte, Marc N. ; Kelly, David L. ( October 2021 , Annual Review of Resource Economics)

   null (Ed.)

   We survey the growing literature on fat-tailed distributions in environmental economics. We then examine the theoretical and statistical properties of such distributions, focusing especially on when these properties are likely to arise in environmental problems. We find that a number of variables are fat tailed in environmental economics, including the climate sensitivity, natural disaster impacts, spread of infectious diseases, and stated willingness to pay. We argue that different fat-tailed distributions arise from common pathways. Finally, we review the literature on the policy implications of fat-tailed distributions and controversies over their interpretation. We conclude that the literature has made great strides in demonstrating when fat tails matter for optimal environmental policy. Yet, much is less well understood, including how alternative policies affect fat-tailed distributions, the optimal policy in a computational economy with many fat-tailed problems, and how to account for imprecision in empirical tests for fat tails. Expected final online publication date for the Annual Review of Resource Economics, Volume 13 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

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2. Agricultural Trade and Environmental Sustainability

   https://doi.org/10.1146/annurev-resource-101420-090453  

   Baylis, Kathy ; Heckelei, Thomas ; Hertel, Thomas W. ( October 2021 , Annual Review of Resource Economics)

   null (Ed.)

   Global agriculture consumes substantial resources and produces significant pollution. By shifting its production to new locations, and inducing changes in technology and input use, trade has a substantial impact on environmental sustainability of the world's food systems, but due to suboptimal environmental policy, the exact nature of these impacts is in dispute. We review the literature on agricultural trade and environmental sustainability, highlighting the different approaches taken in ecology versus economics. While useful in identifying environmental costs, much of the ecological literature does not compare these costs to a trade-free counterfactual and can therefore be misleading. Further, by moving production to places with more resources and increasing production efficiency, trade can reduce the environmental impact of food production. On the other hand, trade can also limit the effectiveness of domestic environmental policy because production can be shifted to countries with less stringent regulations. However, recently, consumers are leveraging trade policy to induce exporters to improve environmental sustainability. While such policies are gaining traction in wealthy countries, evidence suggests that such measures will not reach their potential without buy-in from decision makers in the countries where the environmental damages are occurring. Expected final online publication date for the Annual Review of Resource Economics, Volume 13 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

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3. Earth stewardship: Shaping a sustainable future through interacting policy and norm shifts

   https://doi.org/10.1007/s13280-022-01721-3  

   Chapin, F. Stuart ; Weber, Elke U. ; Bennett, Elena M. ; Biggs, Reinette ; van den Bergh, Jeroen ; Adger, W. Neil ; Crépin, Anne-Sophie ; Polasky, Stephen ; Folke, Carl ; Scheffer, Marten ; et al ( September 2022 , Ambio)

   Abstract Transformation toward a sustainable future requires an earth stewardship approach to shift society from its current goal of increasing material wealth to a vision of sustaining built, natural, human, and social capital—equitably distributed across society, within and among nations. Widespread concern about earth’s current trajectory and support for actions that would foster more sustainable pathways suggests potential social tipping points in public demand for an earth stewardship vision. Here, we draw on empirical studies and theory to show that movement toward a stewardship vision can be facilitated by changes in either policy incentives or social norms. Our novel contribution is to point out that both norms and incentives must change and can do so interactively. This can be facilitated through leverage points and complementarities across policy areas, based on values, system design, and agency. Potential catalysts include novel democratic institutions and engagement of non-governmental actors, such as businesses, civic leaders, and social movements as agents for redistribution of power. Because no single intervention will transform the world, a key challenge is to align actions to be synergistic, persistent, and scalable. 

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4. Becoming FEW Conscious: A Conceptual Typology of Household Behavior Change Interventions Targeting the Food-Energy-Water (FEW) Nexus

   https://doi.org/10.3390/su11185034  

   Berman, Holly ; Shwom, Rachael ; Cuite, Cara ( September 2019 , Sustainability)

   The food-energy-water (FEW) nexus presents an opportunity to rethink predominant approaches to household behavior change science. We linked emerging FEW nexus research with existing literature examining household consumption and pro-environmental behaviors. While a large body of work examines the environmental impacts of household life and explores pathways to behavior change for sustainability, the literature lacks studies that test interventions in multiple FEW resource categories, leaving researchers unable to identify tensions and tradeoffs in the household system. To guide this developing field and accumulate findings on household behavior across disciplines, we proposed a conceptual typology that synthesizes interdisciplinary analytic traditions to classify behavioral interventions targeting the household FEW nexus. The typology synthesizes behavioral interventions as active, passive, or structural, and household-specific or non-specific, illustrating six distinct categories: information, tailored information, action, gamification, policy/price change, and material/technology provision. A review of 40 studies that guided the typology identifies four significant lessons for future intervention research: household non-specific information and tailored information work better together, feedback is more effective when it is persistent, price-based interventions (information or incentives) are often ineffective, and material/technology provision is very effective but utilized in few household studies. To push forward household resource consumption science, we advocated for a holistic nexus focus that is rooted in interdisciplinarity, coalition building with stakeholders, and data reporting that facilitates knowledge accumulation. 

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5. Measuring the Uncertainty of Environmental Good Preferences with Bayesian Deep Learning

   https://doi.org/10.1145/3524458.3547250  

   Flores, Ricardo ; Tlachac, ML ; Rundensteiner, Elke A. ( September 2022 , 2022 ACM Conference on Information Technology for Social Good)

   Due to climate change and resulting natural disasters, there has been a growing interest in measuring the value of social goods to our society, like environmental conservation. Traditionally, the stated preference, such as contingent valuation, captures an economics-perspective on the value of environmental goods through the willingness to pay (WTP) paradigm. Where the economics theory to estimate the WTP using machine learning is the random utility model. However, the estimation of WTP depends on rather simple preference assumptions based on a linear functional form. These models are therefore unable to capture the complex uncertainty in the human decision-making process. Further, contingent valuation only uses the mean or median estimation of WTP. Yet it has been recognized that other quantiles of the WTP would be valuable to ensure the provision of social goods. In this work, we propose to leverage the Bayesian Deep Learning (BDL) models to capture the uncertainty in stated preference estimation. We focus on the probability of paying for an environmental good and the conditional distribution of WTP. The Bayesian deep learning model connects with the economics theory of the random utility model through the stochastic component on the individual preferences. For testing our proposed model, we work with both synthetic and real-world data. The results on synthetic data suggest the BDL can capture the uncertainty consistently with different distribution of WTP. For the real-world data, a forest conservation contingent valuation survey, we observed a high variability in the distribution of the WTP, suggesting high uncertainty in the individual preferences for social goods. Our research can be used to inform environmental policy, including the preservation of natural resources and other social good. 

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