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1. Reducing inefficiency in carbon auctions with imperfect competition.

   Goldner, K.; Immorlica, I.; Lucier, B (January 2020, 11th Innovations in Theoretical Computer Science Conference, ITCS 2020)

   Vidick, T. (Ed.)

   We study auctions for carbon licenses, a policy tool used to control the social cost of pollution. Each identical license grants the right to produce a unit of pollution. Each buyer (i.e., firm that pollutes during the manufacturing process) enjoys a decreasing marginal value for licenses, but society suffers an increasing marginal cost for each license distributed. The seller (i.e., the government) can choose a number of licenses to put up for auction, and wishes to maximize the societal welfare: the total economic value of the buyers minus the social cost. Motivated by emission license markets deployed in practice, we focus on uniform price auctions with a price floor and/or price ceiling. The seller has distributional information about the market, and their goal is to tune the auction parameters to maximize expected welfare. The target benchmark is the maximum expected welfare achievable by any such auction under truth-telling behavior. Unfortunately, the uniform price auction is not truthful, and strategic behavior can significantly reduce (even below zero) the welfare of a given auction configuration. We describe a subclass of “safe-price” auctions for which the welfare at any Bayes-Nash equilibrium will approximate the welfare under truth-telling behavior. We then show that the better of a safeprice auction, or a truthful auction that allocates licenses to only a single buyer, will approximate the target benchmark. In particular, we show how to choose a number of licenses and a price floor so that the worst-case welfare, at any equilibrium, is a constant approximation to the best achievable welfare under truth-telling after excluding the welfare contribution of a single buyer. 

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2. Explicitly Resolved Cloud Feedbacks in the Radiative‐Convective Equilibrium Model Intercomparison Project

   https://doi.org/10.1029/2023MS003738  

   Stauffer, Catherine L; Wing, Allison A (November 2023, Journal of Advances in Modeling Earth Systems)

   Abstract Radiative‐convective equilibrium (RCE) is particularly well suited for studying tropical deep‐convection, a regime of clouds that contributes some of the highest uncertainties to the estimates of total cloud feedback. In order to perform a comprehensive calculation and decomposition of cloud feedbacks in cloud‐permitting models, previously primarily done in global climate models, the configuration of a satellite simulator for use with offline data was successfully implemented. The resultant total cloud feedback is slightly positive, primarily driven by the longwave effects of increases in cloud altitude. The high‐cloud altitude feedback is robustly positive and has a central value and uncertainty well‐matched with prior estimates. Reductions in high cloud amount drive a tropical anvil cloud area feedback that is on average negative, consistent with prior estimates. However, a subset of models with finer horizontal grid spacing indicate that a positive tropical anvil cloud area feedback cannot be ruled out. Even though RCE is only applicable to tropical deep‐convective clouds, the RCE total cloud feedback is within the range of prior comprehensive estimates of the global total cloud feedback. This emphasizes that the tropics heavily influence the behavior of global cloud feedbacks and that RCE can be exploited to learn more about how processes related to deep convection control cloud feedbacks. 

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3. Simple, Credible, and Approximately-Optimal Auctions

   Daskalakis, C; Fishelson, M; Lucier, B; Syrgkanis, V; Velusamy, S (January 2020, 21st ACM Conference on Economics and Computation, EC 2020)

   null (Ed.)

   We identify the first static credible mechanism for multi-item additive auctions that achieves a constant factor of the optimal revenue. This is one instance of a more general framework for designing two-part tariff auctions, adapting the duality framework of Cai et al [CDW16]. Given a (not necessarily incentive compatible) auction format A satisfying certain technical conditions, our framework augments the auction with a personalized entry fee for each bidder, which must be paid before the auction can be accessed. These entry fees depend only on the prior distribution of bidder types, and in particular are independent of realized bids. Our framework can be used with many common auction formats, such as simultaneous first-price, simultaneous second-price, and simultaneous all-pay auctions. If all-pay auctions are used, we prove that the resulting mechanism is credible in the sense that the auctioneer cannot benefit by deviating from the stated mechanism after observing agent bids. If second-price auctions are used, we obtain a truthful O(1)-approximate mechanism with fixed entry fees that are amenable to tuning via online learning techniques. Our results for first price and all-pay are the first revenue guarantees of non-truthful mechanisms in multi-dimensional environments; an open question in the literature [RST17]. 

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4. How Does Organized Convection Impact Explicitly Resolved Cloud Feedbacks in the Radiative‐Convective Equilibrium Model Intercomparison Project?

   https://doi.org/10.1029/2023MS003924  

   Stauffer, Catherine L; Wing, Allison A (October 2024, Journal of Advances in Modeling Earth Systems)

   Abstract In simulations of radiative‐convective equilibrium (RCE), and with sufficiently large domains, organized convection enhances top of atmosphere outgoing longwave radiation due to the reduced cloud coverage and drying of the mean climate state. As a consequence, estimates of climate sensitivity and cloud feedbacks may be affected. Here, we use a multi‐model ensemble configured in RCE to study the dependence of explicitly calculated cloud feedbacks on the existence of organized convection, the degree to which convection within a domain organizes, and the change in organized convection with warming sea surface temperature. We find that, when RCE simulations with organized convection are compared to RCE simulations without organized convection, the propensity for convection to organize in RCE causes cloud feedbacks to have larger magnitudes due to the inclusion of low clouds, accompanied by a much larger inter‐model spread. While we find no dependence of the cloud feedback on changes in organization with warming, models that are, on average, more organized have less positive, or even negative, cloud feedbacks. This is primarily due to changes in cloud optical depth in the shortwave, specifically high clouds thickening with warming in strongly organized domains. The shortwave cloud optical depth feedback also plays an important role in causing the tropical anvil cloud area feedback to be positive which is directly opposed to the expected negative or near zero cloud feedback found in prior work. 

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5. Spatial dimensions of water quality value in New England river networks

   https://doi.org/10.1073/pnas.2120255119  

   Johnston, Robert J.; Moeltner, Klaus; Peery, Seth; Ndebele, Tom; Yao, Zhenyu; Crema, Stefano; Wollheim, Wilfred M.; Besedin, Elena (May 2023, Proceedings of the National Academy of Sciences)

   Households’ willingness to pay (WTP) for water quality improvements—representing their economic value—depends on where improvements occur. Households often hold higher values for improvements close to their homes or iconic areas. Are there other areas where improvements might hold high value to individual households, do effects on WTP vary by type of improvement, and can these areas be identified even if they are not anticipated by researchers? To answer these questions, we integrated a water quality model and map-based, interactive choice experiment to estimate households’ WTP for water quality improvements throughout a river network covering six New England states. The choice experiment was implemented using a push-to-web survey over a sample of New England households. Voting scenarios used to elicit WTP included interactive geographic information system (GIS) maps that illustrated three water quality measures at various zoom levels across the study domain. We captured data on how respondents maneuvered through these maps prior to answering the value-eliciting questions. Results show that WTP was influenced by regionwide quality improvements and improvements surrounding each respondent’s home, as anticipated, but also by improvements in individualized locations identifiable via each respondent’s map interactions. These spatial WTP variations only appear for low-quality rivers and are focused around particular areas of New England. The study shows that dynamic map interactions can convey salient information for WTP estimation and that predicting spatial WTP heterogeneity based primarily on home or iconic locations, as typically done, may overlook areas where water quality has high value. 

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