This paper develops a framework for analysing intergovernmental relationships around greenhouse gas (GHG) mitigation policies along a cooperation-conflict spectrum that affects the probability of their enactment. Cooperative policies, such as federal fiscal transfers to sub-national governments, facilitate enactment. Coordination policies, including enabling and funding mechanisms, promote interdependence between jurisdictions. Competitive policies, such as federal performance standards and price mechanisms, increase political conflict over authority. We categorise 23 policies developed by over 1,500 state stakeholders into the cooperation/coordination/conflict taxonomy. If scaled to the national level, these policies could reduce GHG emissions by over 3 billion tonnes by 2020 and generate nearly 2.2 million jobs (1.19 per cent above baseline projections). Nearly two-thirds of the job gains are from coordinated and cooperative policy options that are unlikely to occur under the status quo policy process. We recommend a national climate action planning process to reduce GHG emissions while increasing aggregate economic efficiency.
An overview is given of the growing number of regional associations in which states have entered into voluntary arrangements to limit greenhouse gas (GHG) emissions. In particular, in the Regional Greenhouse Gas Initiative (RGGI), a number of northeastern states have joined to create a regional GHG cap and trade program, beginning with the utility industry. Analysis is made of the five key issues relating to these current and potential climate action associations: the extent of the total and individual state mitigation cost-savings across all sectors from potential emission permit trading coalitions; the size of permit markets associated with the various coalitions; the relative advantages of joining various coalitions for swing states such as Pennsylvania; the implications of the exercise of market power in the permit market; and the total and individual state/country cost-savings from extending the coalition beyond US borders. It is shown that overall efficiency gains from trading with a system of flexible state caps, with greater overall cost savings increasing with increasing geographic scope.
When deciding how long to keep waiting for delayed rewards that will arrive at an uncertain time, different distributions of reward times dictate different optimal strategies for maximizing reward. For example, when reward timing distributions are heavy-tailed (e.g., waiting on hold with customer service) there is a point in time at which waiting is no longer advantageous because the opportunity cost of waiting is too high. Alternatively, when reward timing distributions have a more predictable time scale (uniform or Gaussian), it can be advantageous to wait as long as necessary for the reward to arrive. Although people learn to approximate optimal strategies, little is known about how this learning occurs. One possibility is that people form a general cognitive representation of the probability distribution that governs reward timing and then infer a strategy from that model of the environment. Another possibility is that they learn an action policy more directly, without explicitly representing the reward timing distribution. Here, in a series of studies in which participants decided how long to persist for delayed rewards before quitting, we provided participants with general information about the reward timing distribution in several ways. Whether the information was provided through counterfactual feedback (Study 1), previous exposure (Study 2), or description (Study 3), it did not obviate the need for direct, feedback-driven learning in the decision context. These results suggest that learning when to quit waiting for delayed rewards might depend on task-specific experience, not solely on general probabilistic reasoning.
Recent US data indicate a clear and progressive decoupling of carbon emissions and energy intensity from economic growth. This is primarily a consequence of state and national environmental and energy policy actions, and secondarily a result of shifts in economic structure and increases in natural gas supplies. To assess future opportunities of proactive approaches to policy and investment, we analyze 20 sector-based actions at the national and subnational levels in the US that can narrow remaining national carbon emissions gaps by 2020 and beyond, while improving economic and energy efficiency in every sector. These actions are found to provide favorable returns on investment for job creation, energy and cost savings, and multiple measures of energy security. Selection and design of these new actions are based on evaluation of hundreds of policy options derived from facilitated, stakeholder and consensus-based development of comprehensive climate action planning in 20 states. They represent top issues of focus for policymakers, and serve as key drivers for new investment, collaboration, and governance approaches that are needed to integrate economic, energy, and environmental security in the US. This same general approach to planning and analysis is of value to other nations seeking similar benefits. Techniques for comprehensive, multi-objective, fully integrated, and collaborative systems of planning and analysis are important as a means for comprehensive security solutions. This also requires leadership at all levels of government, and a broadened view of national security. P. Delaquil et al.28
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.