摘要
EconometricaVolume 82, Issue 1 p. 41-88 Optimal Taxes on Fossil Fuel in General Equilibrium Mikhail Golosov, Mikhail Golosov Dept. of Economics, Princeton University, 111 Fisher Hall, Princeton, NJ 08544, U.S.A.; [email protected]Search for more papers by this authorJohn Hassler, John Hassler IIES, Stockholm University, SE-106 91, Stockholm, Sweden; [email protected]Search for more papers by this authorPer Krusell, Per Krusell IIES, Stockholm University, SE-106 91, Stockholm, Sweden; [email protected]Search for more papers by this authorAleh Tsyvinski, Aleh Tsyvinski Dept. of Economics, Yale, 28 Hillhouse Avenue, New Haven, CT 06511, U.S.A.; [email protected] We thank Lint Barrage, Jiali Cheng, Bill Nordhaus, Jonas Nycander, Tony Smith, Sjak Smulders, and seminar participants at ESSIM, EIEF, EUI, IIES, Mistra-SWECIA, Yale, UCL, CREI, the Environmental Macro Conference at ASU, the EEA Annual Meeting (Glasgow), Fudan University (Shanghai), the Chinese University of Hong Kong, Beijing University, Bonn, Zurich, Carlos III, REDg DGEM (Barcelona), Oxford, Princeton, and Stanford. Golosov and Tsyvinski thank NSF for support and EIEF for their hospitality; Krusell thanks ERC and Mistra-SWECIA for support, and Hassler thanks Mistra-SWECIA and the Swedish Research Council for support.Search for more papers by this author Mikhail Golosov, Mikhail Golosov Dept. of Economics, Princeton University, 111 Fisher Hall, Princeton, NJ 08544, U.S.A.; [email protected]Search for more papers by this authorJohn Hassler, John Hassler IIES, Stockholm University, SE-106 91, Stockholm, Sweden; [email protected]Search for more papers by this authorPer Krusell, Per Krusell IIES, Stockholm University, SE-106 91, Stockholm, Sweden; [email protected]Search for more papers by this authorAleh Tsyvinski, Aleh Tsyvinski Dept. of Economics, Yale, 28 Hillhouse Avenue, New Haven, CT 06511, U.S.A.; [email protected] We thank Lint Barrage, Jiali Cheng, Bill Nordhaus, Jonas Nycander, Tony Smith, Sjak Smulders, and seminar participants at ESSIM, EIEF, EUI, IIES, Mistra-SWECIA, Yale, UCL, CREI, the Environmental Macro Conference at ASU, the EEA Annual Meeting (Glasgow), Fudan University (Shanghai), the Chinese University of Hong Kong, Beijing University, Bonn, Zurich, Carlos III, REDg DGEM (Barcelona), Oxford, Princeton, and Stanford. Golosov and Tsyvinski thank NSF for support and EIEF for their hospitality; Krusell thanks ERC and Mistra-SWECIA for support, and Hassler thanks Mistra-SWECIA and the Swedish Research Council for support.Search for more papers by this author First published: 05 February 2014 https://doi.org/10.3982/ECTA10217Citations: 382 AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Abstract We analyze a dynamic stochastic general-equilibrium (DSGE) model with an externality—through climate change—from using fossil energy. Our central result is a simple formula for the marginal externality damage of emissions (or, equivalently, for the optimal carbon tax). This formula, which holds under quite plausible assumptions, reveals that the damage is proportional to current GDP, with the proportion depending only on three factors: (i) discounting, (ii) the expected damage elasticity (how many percent of the output flow is lost from an extra unit of carbon in the atmosphere), and (iii) the structure of carbon depreciation in the atmosphere. Thus, the stochastic values of future output, consumption, and the atmospheric CO2 concentration, as well as the paths of technology (whether endogenous or exogenous) and population, and so on, all disappear from the formula. We find that the optimal tax should be a bit higher than the median, or most well-known, estimates in the literature. 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