Resource and Energy Economics最新文献

As countries reduce greenhouse gas emissions to fight the potential impacts of climate change, increasing attention is being paid to methane, which is roughly 34 times more potent than CO₂ over a 100-year time span. Governments in many jurisdictions aim to reduce methane by 45–75% in oil and gas sectors by 2030. Methane reductions are often achieved by implementing new technologies and operational techniques, but jurisdictions have discussed the implementation of a methane tax. While several studies have focused on the financial costs of reducing methane emissions through adopting new technologies, little information exists on the economy-wide impacts of these initiatives and the effectiveness of different policy tools. We develop a dynamic computable general equilibrium model for British Columbia, Canada, to evaluate the economy wide impacts of methane technology standards versus taxes. Findings indicate that methane can be reduced by 75% by 2030 using technology standards at a loss of 0.0089% of GDP in 2030. Impacts associated with a methane tax will range from a loss of 0.0071–0.18% in 2030, depending on whether new technologies are assumed to be adopted. If a sufficiently high methane tax incentivizes adoption of new technology, the negative impacts of a tax are lower than that of a standard once the policy is fully implemented. While the overall economy-wide impact of a technology standard is relatively low, we find that it is as much as 65% higher than the direct costs.

This study estimates the relationships between green and blue nature and the life satisfaction (LS) of residents in the six largest cities in the Netherlands to monetize the value of urban nature. The analysis uses both survey and geographic information system (GIS) data on the availability of nature to examine the influence of this methodological choice on the valuation outcomes. The main findings are that different indicators of the availability of nature consistently reveal positive relationships with reported LS, which implies substantial marginal willingness-to-pay (MWTP) values for urban nature. Valuation results based on the survey data indicate higher MWTPs compared to GIS data on nature availability, which may be explained by the more disaggregated data from surveys on the availability and use of nature.

Persistent air-pollution problems have led authorities in many cities around the world to impose limits on car use by means of vintage-specific restrictions or low-emission zones. Any vintage restriction must establish not only the cars that face a restriction but also its geographic area of application. As a result of the restriction, a fraction of restricted cars are exported outside the restricted area. Because restricted cars become cheaper, emissions in the restricted area could increase if exported cars remain too close to it. The extent to which such emissions leakage can occur crucially depends on transaction costs in the car market. We study this possibility with a model of the car market that allows for transaction costs and data from Santiago’s 2017 vintage restriction. We fail to find emissions leakage, at least severe enough to undo the 2017 policy effects. Interestingly, transaction costs are shown to have a non-monotonic impact on emissions, and hence, on welfare.

Energy policies for promoting investment in renewable energy sources have become crucial for deploying green energy technologies worldwide. Conventional incentive systems assign risk to either policymakers or investors. In this paper, we combine option theory and game theory to obtain optimal parameters for incentive schemes with different degrees of risk-sharing. We present an empirical application to the Spanish electricity market for 2013, when the Feed-in Tariff scheme was still in force, and for 2019, when Feed-in Tariffs had been completely phased out but before the demand shock caused by COVID-19, the restructuring of market price limits, and the recent energy price crisis in Europe. Our results indicate that there are more flexible systems based on Fixed Tariffs and Premiums that can outperform conventional designs, since they may enable the same investment level to be reached at a lower regulatory cost. In addition, these hybrid schemes permit risk-sharing between both parties. Our results may also be useful for designing incentives awarded through competitive auctions.

Despite a 30-year long history, Renewable Portfolio Standards (RPS) remain controversial and debates continue to surround their efficacy in leading the low-carbon transition in the electricity sector. Contributing to the ongoing debates is the lack of definitive causal evidence on their impact on investments in renewable capacity and generation. This paper provides the most detailed analysis to date of the impact of RPSs on renewable electricity capacity investments and on generation. We use state-level data from 1990–2019 and recent econometric methods designed to address dynamic and heterogeneous treatment effects in a staggered adoption panel data design. We find that, on average, RPS policies increase wind generation capacity by 600–1200 MW, a 44% increase, but have no significant effect on investments in solar capacity. Additionally, we demonstrate that RPSs have slow dynamic effects: most of the capacity additions occur 5 years after RPS implementation. Estimates for wind and solar electricity generation mimic those for capacity investments. We also find similar results using an alternate treatment definition that allows states to meet their RPS requirements with pre-existing renewable generation and renewable generation from nearby states.

This paper explores the effect of gasoline prices on traffic congestion and carbon emissions. The international crude oil price is used as an instrumental variable for the gasoline price in Chinese cities. Empirical results show that a ten percent increase in gasoline prices significantly decreases traffic congestion in rush hours by 0.87%. In addition to reducing vehicle kilometers traveled, higher gasoline prices also decrease carbon emissions by increasing travel speed and fuel efficiency. A ten percent increase in gasoline prices is found to decrease CO₂ emissions by 40.6 million metric tons, accounting for 2.3% of the total CO₂ emissions in the transport sector of China in 2016. This paper's estimates offer guidance for gasoline pricing policies, fuel taxes, traffic congestion, and the Dual-Carbon Target.

The intersection of mining activities and the preservation of fragile ecosystems presents a challenge, exemplified by the coexistence of lithium resources and the pristine High-Andean wetlands. In this study, we demonstrate the transformative potential of accounting for the intrinsic non-use values associated with these vital wetlands. By incorporating these values, we not only reshape optimal mining patterns but also forge a path towards enhanced environmental conservation. To quantify the value of affected biodiversity and ecosystems, we employ a meta-analytic benefit transfer function. Subsequently, we integrate these values into a competitive land use model that treats ecosystem services as valuable assets and incorporates the opportunity costs associated with mining activities. The results of our study reveal a compelling narrative: when the value of wetland ecosystems is considered, the pace of lithium extraction is markedly affected. The extent of this impact varies depending on factors such as wetland size, ecosystem service value, damage levels, and resource rents. By quantifying the ecological impacts of mining in economic terms, our findings present an avenue for policymakers to design a mineral extraction tax that complements a mitigation hierarchy to conserve these precious ecosystems.

Time preferences are considered a leading cause of the energy efficiency gap. We test two cognition-based mechanisms (concentration bias and underestimation bias) which are distinct from time preferences but can produce identical behaviour when costs are paid upfront and benefits are spread over time. We use an experiment that measures willingness-to-pay for an improvement in fuel economy to test the explanatory power of these mechanisms. The sample is large, nationally representative and comprised only of car buyers (n = 2368). The experiment varies between-subjects (i) the payment schedule for the fuel economy improvement, and (ii) the temporal framing of its monetary benefit. We combine the payment schedules and the benefit frames so that the pattern of results predicted by time preferences differs from the pattern predicted by cognitive mechanisms. Results support the preregistered hypotheses: willingness-to-pay increases as the payment schedule becomes more dispersed across time and decreases when the benefit is presented as more disaggregated (i.e. a monthly saving instead of annual or multi-year saving). The findings are consistent with the predictions of the two cognitive mechanisms, which may explain part of the energy-efficiency gap currently attributed to pure time preference.

We analyze the data of 689 Chinese listed firms between 1999 and 2010 to study the relationship between firms’ political connections and their pollution emissions. We find that, ceteris paribus, a polluting firm with politically connected top managers discharges about 25% more chemical oxygen demand (COD) per 10,000 RMB (about 1,500 USD) worth of total output. The impact of political connections on COD emissions gradually fades out with the departure of politically connected top managers. However, political connections do not affect firms’ emissions of unregulated water pollutants or air pollutants that receive high levels of public attention. In addition, we find evidence that polluting firms may leave wastewater treatment units idle, which lessens treatment costs and thus raises pollution emissions. The findings of this study would help advance discussion about managing water pollution and designing effective environmental regulations under a command-and-control policy schema in developing countries.

Proponents of Bitcoin argue that demand for electricity from Bitcoin miners can lead to an increase in renewable electricity capacity. We rigorously evaluate this claim by estimating a Bitcoin electricity demand curve and include this demand curve in a long-run model of the Texas electricity market. We find that while Bitcoin mining can indeed increase renewable capacity, it also increases carbon emissions. When Bitcoin miners provide grid management services in the form of demand response, their emissions impact is largely mitigated.