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on Resource Economics |
Issue of 2014‒12‒19
five papers chosen by |
By: | Williams III, Roerton C. (Resources for the Future); Gordon, Hal (Resources for the Future); Burtraw, Dallas (Resources for the Future); Jared C. Carbone; Morgenstern, Richard D. (Resources for the Future) |
Abstract: | Carbon taxes efficiently reduce greenhouse gas emissions but are criticized as regressive. This paper links dynamic overlapping-generation and microsimulation models of the United States to estimate the initial incidence. We find that while carbon taxes are regressive, the incidence depends much more on how carbon tax revenue is used. Recycling revenues to cut capital taxes is efficient but exacerbates regressivity. Lump-sum rebates are less efficient but much more progressive, benefiting the three lower income quintiles even when ignoring environmental benefits. A labor tax swap represents an intermediate option, more progressive than a capital tax swap and more efficient than a rebate. |
Keywords: | carbon tax, distribution, incidence, tax swap, income quintiles, climate change |
JEL: | H22 H23 Q52 |
Date: | 2014–08–07 |
URL: | http://d.repec.org/n?u=RePEc:rff:dpaper:dp-14-24&r=res |
By: | Li, Shanjun; Kyul Yoo, Han; Shih, Jhih-Shyang (Resources for the Future); Palmer, Karen (Resources for the Future); Macauley, Molly K. (Resources for the Future) |
Abstract: | Methane is the second most prevalent greenhouse gas and has a global warming potential at least 28 times as high as carbon dioxide. Municipal solid waste landfills are reported to be the third-largest source of anthropogenic methane emissions in the United States, responsible for 18 percent of emissions in 2011. Capturing landfill gas for use as an energy source for electricity or heat produces alternative energy as well as environmental benefits. A host of federal and state policies encourage the development of landfill-gas-to-energy projects. Our research provides the first systematic economic assessment of the role these policies play in adoption decisions. Results suggest that renewable portfolio standards and investment tax credits have contributed to the development of these projects, accounting for 13 of 277 projects during our data period from 1991 to 2010. These policy-induced projects have led to 12.5 million metric tons of carbon dioxide–equivalent reductions in greenhouse gas emissions and a net benefit of $52.59 million. |
Keywords: | renewable energy, landfill methane, renewable portfolio standards, investment tax credit |
JEL: | Q48 Q53 |
Date: | 2014–07–08 |
URL: | http://d.repec.org/n?u=RePEc:rff:dpaper:dp-14-17&r=res |
By: | Ranganathan, Shyam (Department of Mathematics); Bali Swain, Ranjula (Department of Economics) |
Abstract: | Global emissions beyond 44 gigatonnes of carbondioxide equivalent (GtCO2e) in 2020 can potentially lead the world to an irreversible climate change. Employing a novel dynamical system modeling approach, we predict that in a business-asusual scenario, it will reach 61 GtCO2e by 2020. Testing estimated parameters, we nd that limiting the burden of emission reduction to the top 25 global emitters, does not increase their encumbrance. In absence of emission cuts, technology and preferences for environmental quality have to improve by at least 2.6 percent and 3.5 percent if the emission target has to be met by 2020. |
Keywords: | Sustainable Development Goals; dynamical systems; Bayesian; greenhouse gases |
JEL: | C51 C52 C53 C61 Q01 Q50 |
Date: | 2014–10–31 |
URL: | http://d.repec.org/n?u=RePEc:hhs:uunewp:2014_010&r=res |
By: | Shrader, Jeffrey |
Abstract: | For many environmental problems, economics adaptation will likely be the primary means by which potential damages are avoided. How and by how much humans adapt to environmental risks, therefore, is a question of paramount importance. This paper uses a novel dataset documenting the introduction of forecasts of an important, global driver of climate variation—El Nino/Southern Oscillation (ENSO)—to derive the first well identified estimates of total adaptation in a climate exposed industry. The primary results indicate that for the setting under consideration, risks from ENSO events can be almost entirely mitigated given 3 months of advance warning. This adaptation comes from a combination of daily and annual actions. In sum, the results point both to the ability for individuals in some settings to mitigate their own environmental risks given high quality information. |
Keywords: | Adaptation, Climate, Fisheries, Forecasts, Environmental Economics and Policy, Research and Development/Tech Change/Emerging Technologies, Research Methods/ Statistical Methods, Risk and Uncertainty, D8, Q22, Q54, |
Date: | 2014 |
URL: | http://d.repec.org/n?u=RePEc:ags:aaea14:170626&r=res |
By: | Wang, Sun Ling; Ball, Eldon; Nehring, Richard; Williams, Ryan; Chau, Truong |
Abstract: | We employ state panel data for the period 1961-2004 to identify the role of climate change on U.S. agricultural productivity growth using a stochastic production frontier method. We examine the patterns of productivity changes and weather variations across regions and over time. Climate variables are measured using temperature humidity index (THI) load and Oury index at both their means and the degree of deviation from their historical norm (shocks). We also incorporate irrigation ratio and local public goods—R&D, extension, and road infrastructure—to capture the effects of specific state characteristics and to check for the robustness of the estimates of climate variables’ impacts. Results indicate that higher THI load can drive farm production from its best performance using given inputs and best technology. On the other hand, a higher Oury index, irrigation ratio, local R&D, Extension, and road density can drive state overall farm production closer to the production frontier. In addition, weather “shock” variables seem to have more consistent and robust impacts in explaining technical inefficiency than do level variables. |
Keywords: | U.S. agricultural productivity, technical inefficiency, stochastic frontier, climate change, THI load, Oury index, Environmental Economics and Policy, Productivity Analysis, |
Date: | 2014–07 |
URL: | http://d.repec.org/n?u=RePEc:ags:aaea14:177170&r=res |