Green rooftops, also known as vegetated roofs, will play a critical role in enhancing the resilience of urban areas in the face of climate change and other contemporary environmental and social challenges. To ensure the optimal design and implementation of these green technologies, it is vital to understand the public’s preferences, values, and attitudes toward the government support for green rooftops. This study employs contingent valuation methods, specifically utilizing a payment card and a choice experiment, to investigate these topics that have received inadequate exploration within the current body of literature. Our findings indicate that 45% of the public is aware of green rooftops, and the most desired features on an extensive green rooftop, ranked by importance, are: flowers, grass, trees, and walking paths. The majority (79%) of the public supports a federally proposed legislation currently under review (the Public School Green Rooftop Program) and has a mean willingness to pay of approximately $176 per household as a one-time payment. Additionally, the results show that individuals place a higher value on green rooftops that incorporate solar energy technology compared to those without. Furthermore, there is a perceived, loss of value when access to a green rooftop is limited, as opposed to having open access.

The effects of transgenic corn use and federal biofuel policies on state-level cropping patterns in the US Corn Belt region are investigated using state-level data from 2000 to 2019. During this time, producers moved away from diverse cropping patterns and toward simpler rotational practices. Empirical evidence indicates that the intensification of corn acres planted was positively impacted by the spread of genetically modified (GM) soybeans—used as a proxy for GM corn for biofuel usage—but the effects of biotech advancements on producer planting decisions vary across states. This suggests that future policy changes affecting corn production decisions at the farm level will also be heterogeneous across states.

In 1992, Congress passed The Elwha River Ecosystem and Fisheries Restoration Act with the goal of “full restoration of The Elwha River Ecosystem and native anadromous fisheries.” As part of that act, the federal government was required to produce a benefit-cost analysis on dam removal of the Elwha and Glines Canyon dams, which was published in 1994. This article revisits that initial 1994 benefit-cost analysis; background on its methods and assumptions is given, comparisons are made to current state-of-the-art techniques in benefit-cost analysis, and an ex post benefit-cost analysis of the project is conducted for comparison purposes. We find that the cost and scope of the project exceeded original expectations, the cost of the foregone electricity generation was less than expected, and that anticipated recreational and fisheries benefits were both delayed, and lower, than expected. Furthermore, issues such as the value of hatchery-spawned versus wild anadromous fish seem not to have been anticipated in the original analysis, highlighting the fact that in doing an ex ante analysis, researchers must expect that unexpected factors may influence the ex post results of any project.

Conversion of biomass to electricity is often not economically feasible as a result of large transportation costs and low output prices. We build a model of an adaptable biorefinery situated at an agri-processing facility that already has biomass on-site and consider the optimal scale of the plant to achieve a price premium by selling peaking power given uncertain biomass deliveries year over year as a result of climatic variability. We find that, for conservative electricity prices, a plant situated near cotton gins in Texas could operate with positive expected net revenue while converting on average only 38% of available biomass for peak electricity prices.

Despite extensive literature on contributing factors to the high commodityprices and volatility in the recent years, few have examined these causalfactors together in one analysis. We quantify empirically the relativeimportance of three factors: global demand, speculation, and energyprices/policy in explaining corn price volatility. A structural vectorauto-regression model is developed and variance decomposition is applied tomeasure the contribution of each factor in explaining corn price variation.We find that speculation is important, but only in the short run. However,in the long run, energy is the most important followed by global demand.

Unconventional resources of crude oil and natural gas – shale energy – increased significantly in the US in the early 2000s, triggered by the strong rise in the price of crude oil and technical advances in production. The US is a clear forerunner in the production of shale energy, due to its existing knowledge and infrastructure. The rest of the world is following, although negative environmental effects and other factors have obstructed the diffusion of new extraction methods. In Europe, Polish production is expected to start in the next few years, although environmental concerns are delaying the onset. The rise in the importance of shale energy will increase global oil and gas production markedly. The rising global supplies will improve global energy security in the long run and help to stabilise the large international price differences for natural gas.

This paper analyzes optimal nonlinear pricing for a monopoly supplying a bundle of a commodity and a related service, where the consumers' private information is captured by scalar variable. With constant marginal costs, we find the standard result where the good and the service in the bundle are lower than separately. However, under the increasing cost assumption, when the degree of the complementarity becomes sufficiently high, the marginal price of separate good is lower than the good price in the bundle. Contrary to Martimort (1992), when good and service are perfectly complementary, we can not conclude that it is costly for consumers to sign two contracts from different shops than to buy the bundle. Because of asymmetric properties in the utility function, profitability result of bundling strategy depends, on the one hand, on the degree of complementarity between commodity and related service and on the other hand, on the degree of the optional service.