1932

Abstract

We describe the factors researchers should consider in deciding when and how to use computational general equilibrium (CGE) models for environmental policy analysis instead of partial equilibrium or engineering models. Special attention is given to modeling the social costs and benefits of regulations and the role played by labor markets. CGE models excel at quantifying interactions across different sectors of the economy, factor-market outcomes, and the distributional consequences of policy, all using a comprehensive set of the resource constraints faced by agents. The ceteris paribus nature of these experiments allows a skilled modeler to develop a systematic understanding of the connection between model assumptions and policy outcomes. Using CGE models to address environmental policy questions involves challenges, including the representation of narrow and technology-specific regulatory designs, data and aggregation issues, and the development of methods to improve model transparency and validity.

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2022-10-05
2024-06-13
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Literature Cited

  1. Antimiani A, Costantini V, Paglialunga E. 2015. The sensitivity of climate-economy CGE models to energy-related elasticity parameters: implications for climate policy design. Econ. Model. 51:38–52
    [Google Scholar]
  2. Aubert D, Chiroleu-Assouline M. 2019. Environmental tax reform and income distribution with imperfect heterogeneous labour markets. Eur. Econ. Rev. 116:60–82
    [Google Scholar]
  3. Baylis K, Fullerton D, Karney DH. 2014. Negative leakage. J. Assoc. Environ. Resour. Econ. 1:151–73
    [Google Scholar]
  4. Beckman J, Hertel TW, Tyner WE. 2011. Validating energy-oriented CGE models. Energy Econ 33:799–806
    [Google Scholar]
  5. Belgodere A, Vellutini C. 2011. Identifying key elasticities in a CGE model: a Monte Carlo approach. Appl. Econ. Lett. 18:1619–22
    [Google Scholar]
  6. Berman E, Bui LTM. 2001. Environmental regulation and productivity: evidence from oil refineries. Rev. Econ. Stat. 83:3498–510
    [Google Scholar]
  7. Boeters S, Savard L. 2013. The labor market in computable general equilibrium models. Handbook of Computable General Equilibrium Modeling P Dixon, D Jorgenson 1645–718 North Holland, Neth: Elsevier
    [Google Scholar]
  8. Böhringer C, Rutherford T. 2009. Integrated assessment of energy policies: decomposing top-down and bottom-up. J. Econ. Dyn. Control 33:1648–61
    [Google Scholar]
  9. Carbone JC, Rivers N. 2017. The impacts of unilateral climate policy on competitiveness: evidence from computable general equilibrium models. Rev. Environ. Econ. Policy 11:124–42
    [Google Scholar]
  10. Carbone JC, Rivers N, Yamazaki A, Yonezawa H. 2020. Comparing applied general equilibrium and econometric estimates of the effect of an environmental policy shock. J. Assoc. Environ. Resour. Econ. 7:4687–719
    [Google Scholar]
  11. Carbone JC, Shen Y. 2020. Assessing the benefits of air-quality improvements in general equilibrium: a review. Int. Rev. Environ. Resour. Econ. 14:11–36
    [Google Scholar]
  12. Carbone JC, Smith VK. 2008. Evaluating policy interventions with general equilibrium externalities. J. Public Econ. 92:5–61254–74
    [Google Scholar]
  13. Carbone JC, Smith VK. 2013. Valuing nature in a general equilibrium. J. Environ. Econ. Manag. 66:172–89
    [Google Scholar]
  14. Castellanos K, Heutel G. 2021. Unemployment, labor mobility, and climate policy NBER Work. Pap. 25797
    [Google Scholar]
  15. Chang T, Graff Zivin J, Gross T, Neidell M. 2016. Particulate pollution and the productivity of pear packers. Am. Econ. J. Econ. Policy 8:3141–69
    [Google Scholar]
  16. Chatzivasileiadis T. 2018. Quasi-Monte Carlo application in CGE systematic sensitivity analysis. Appl. Econ. Lett. 25:1521–26
    [Google Scholar]
  17. Chen H, Paltsev S, Reilly J, Morris J, Babiker M. 2016. Long-term economic modeling for climate change assessment. Econ. Model. 52:Part B867–83
    [Google Scholar]
  18. Fernández Intriago LA 2020. Carbon taxation, green jobs, and sectoral human capital Work. Pap., Resour. Fut. Washington, DC: https://ethz.ch/content/dam/ethz/special-interest/mtec/cer-eth/resource-econ-dam/documents/research/sured/sured-2020/Carbon%20Taxation,%20Green%20Jobs,%20and%20Sectoral%20Human%20Capital.pdf
    [Google Scholar]
  19. Fullerton D, Heutel G. 2010. The general equilibrium incidence of environmental mandates. Am. Econ. J. Econ. Policy 2:363–89
    [Google Scholar]
  20. Fullerton D, Ta CL. 2020. Costs of energy efficiency mandates can reverse the sign of rebound. J. Public Econ. 188:104225
    [Google Scholar]
  21. Ghandi A, Paltsev S. 2020. Global CO2 impacts of light-duty electric vehicles. Transp. Res. D Transp. Environ. 87:102524
    [Google Scholar]
  22. Goulder LH, Hafstead MAC, Williams RC 3rd 2016. General equilibrium impacts of a federal clean energy standard. Am. Econ. J. Econ. Policy 8:2186–218
    [Google Scholar]
  23. Graff Zivin J, Neidell M. 2012. The impact of pollution on worker productivity. Am. Econ. Rev. 102:73652–73
    [Google Scholar]
  24. Hafstead MAC, Williams RC 3rd 2018. Unemployment and environmental regulation in general equilibrium. J. Public Econ. 160:50–65
    [Google Scholar]
  25. Hafstead MAC, Williams RC 3rd 2019. Distributional effects of environmental policy across workers: a general-equilibrium analysis Work. Pap., Resour. Fut./Univ. Md. Washington, DC/College Park:
    [Google Scholar]
  26. Hafstead MAC, Williams RC 3rd, Chen Y 2022. Environmental policy, full-employment models, and employment: a critical analysis. J. Assoc. Environ. Resour. Econ. 9:2199234
    [Google Scholar]
  27. Harberger AC. 1962. The incidence of the corporation income tax. J. Political Econ. 70:3215–40
    [Google Scholar]
  28. Harberger AC. 1964. The measurement of waste. Am. Econ. Rev. 54:58–76
    [Google Scholar]
  29. Hermeling C, Löschel A, Mennel T. 2013. A new robustness analysis for climate policy evaluations: a CGE application for the EU 2020 targets. Energy Policy 55:27–35
    [Google Scholar]
  30. Kambourov G, Manovskii I. 2008. Rising occupational and industry mobility in the United States: 1968–97. Int. Econ. Rev. 49:41–79
    [Google Scholar]
  31. Karkatsoulis P, Siskos P, Paroussos L, Capros P. 2017. Simulating deep CO2 emission reduction in transport in a general equilibrium framework: the GEM-E3T model. Transp. Res. D Transp. Environ. 55:343–58
    [Google Scholar]
  32. Kehoe TJ 2005. An evaluation of the performance of applied general equilibrium models on the impact of NAFTA. Frontiers of Applied General Equilibrium Modelling: Essays in Honor of Herbert Scarf TJ Kehoe, TN Srinivasan, J Whalley 341–77 Cambridge, UK: Cambridge Univ. Press
    [Google Scholar]
  33. Kiuila O, Rutherford TF. 2013a. Piecewise smooth approximation of bottom–up abatement cost curves. Energy Econ. 40:734–42
    [Google Scholar]
  34. Kiuila O, Rutherford TF. 2013b. The cost of reducing CO2 emissions: integrating abatement technologies into economic modeling. Ecol. Econ. 87:62–71
    [Google Scholar]
  35. Lise J, Robin JM. 2017. The macro-dynamics of sorting between workers and firms. Am. Econ. Rev. 107:1104–35
    [Google Scholar]
  36. Magnani E. 2009. How does technological innovation and diffusion affect inter-industry workers’ mobility?. Struct. Change Econ. D 20:16–37
    [Google Scholar]
  37. Marten AL, Garbaccio R, Wolverton A. 2019. Exploring the general equilibrium costs of sector-specific environmental regulations. J. Assoc. Environ. Resour. Econ. 6:61065–104
    [Google Scholar]
  38. Marten AL, Newbold SC. 2017. Economy-wide effects of mortality risk reductions from environmental policies NCEE Work. Pap. 17-03, US Environ. Prot. Agency/Natl. Cent. Environ. Econ. Washington, DC:
    [Google Scholar]
  39. Marten AL, Schreiber A, Wolverton A. 2021. SAGE model documentation, version 2.0.1 US Environ. Prot. Agency Washington, DC: https://www.epa.gov/environmental-economics/sage-model-documentation-version-201
    [Google Scholar]
  40. Matus K, Nam KM, Selin NE, Lamsal LN, Reilly JM, Paltsev S. 2012. Health damages from air pollution in China. Glob. Environ. Change 22:155–66
    [Google Scholar]
  41. Miess M, Schmelzer S, Šcasný M, Kopecná V. 2022. Abatement technologies and their social costs in a hybrid general equilibrium framework. Energy J. 43:2153–79
    [Google Scholar]
  42. Morris J, Reilly J, Paltsev S, Sokolov A, Cox K. 2022. Representing socio-economic uncertainty in human system models. Earth's Fut 10:4E2021EF002239
    [Google Scholar]
  43. Morris MD. 1991. Factorial sampling plans for preliminary computational experiments. Technometrics 33:161–74
    [Google Scholar]
  44. Moscarini G, Postel-Vinay F. 2013. Stochastic search equilibrium. Rev. Econ. Stud. 80:1545–81
    [Google Scholar]
  45. Moscarini G, Postel-Vinay F. 2016. Wage posting and business cycles. Am. Econ. Rev. 106:5208–13
    [Google Scholar]
  46. Murphy KM, Topel RH. 2006. The value of health and longevity. J. Political Econ. 114:5871–904
    [Google Scholar]
  47. Neffke F, Otto A, Weyh A. 2017. Inter-industry labor flows. J. Econ. Behav. Organ. 142:275–92
    [Google Scholar]
  48. Nestor D, Pasurka C. 1995. CGE model of pollution abatement processes for assessing the economic effects of environmental policy. Econ. Model. 12:53–59
    [Google Scholar]
  49. Nordhaus WD. 1993. Optimal greenhouse-gas reductions and tax policy in the “DICE” model. Am. Econ. Rev. 83:2313–17
    [Google Scholar]
  50. Parrado E, Caner A, Wolff E. 2007. Occupational and industrial mobility in the United States. Labour Econ. 14:435–55
    [Google Scholar]
  51. Pizer W, Burtraw D, Harrington W, Newell R, Sanchirico J. 2006. Modeling economy-wide versus sectoral climate policies using combined aggregate-sectoral models. Energy J 27:135–68
    [Google Scholar]
  52. Saari RK, Selin NE, Rausch S, Thompson TM. 2015. A self-consistent method to assess air quality co-benefits from US climate policies. J. Air Waste Manag. Assoc. 65:174–89
    [Google Scholar]
  53. Schaal E. 2017. Uncertainty and unemployment. Econometrica 85:1675–721
    [Google Scholar]
  54. Shoven JB, Whalley J. 1984. Applied general-equilibrium models of taxation and international trade: an introduction and survey. J. Econ. Lit. 22:31007–51
    [Google Scholar]
  55. Smith VK, Zhao MQ. 2020. Economy-wide modeling, environmental macroeconomics, and benefit-cost analysis. Land Econ 93:3305–32
    [Google Scholar]
  56. Sue Wing I 2006. The synthesis of bottom-up and top-down approaches to climate policy modeling: electric power technologies and the cost of limiting U.S. CO2 emissions. Energy Policy 34:3847–69
    [Google Scholar]
  57. Sue Wing I 2008. The synthesis of bottom-up and top-down approaches to climate policy modeling: electric power technology detail in a social accounting framework. Energy Econ 30:547–73
    [Google Scholar]
  58. Taheripour F, Hertel TW, Tyner WE. 2011. Implications of biofuels mandates for the global livestock industry: a computable general equilibrium analysis. Agric. Econ. 42:3325–42
    [Google Scholar]
  59. US EPA (US Environ. Prot. Agency) 2011. The benefits and costs of the Clean Air Act from 1990 to 2020 Final Rep. Rev. A, Off. Air Radiat., US Environ. Prot. Agency Washington, DC: https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=P100GFL8.txt
    [Google Scholar]
  60. US EPA (US Environ. Prot. Agency) 2015. Economy-wide modeling: social cost and welfare White Pap., US Environ. Prot. Agency Sci. Advis. Board Panel Economy-Wide Model. Washington, DC:
    [Google Scholar]
  61. US EPA (US Environ. Prot. Agency) 2017. SAB advice on the use of economy-wide models in evaluating the social costs, benefits, and economic impacts of air regulations Rep. EPA-SAB-17–012, US Environ. Prot. Agency Sci. Advis. Board Panel Economy-Wide Model. Washington, DC:
    [Google Scholar]
  62. Valenzuela E, Hertel TW, Keeney R, Reimer JJ. 2007. Assessing global computable general equilibrium model validity using agricultural price volatility. Am. J. Agric. Econ. 89:2383–97
    [Google Scholar]
  63. Vennemo H. 1997. A dynamic applied general equilibrium model with environmental feedbacks. Econ. Model. 14:199–154
    [Google Scholar]
  64. Webster M, Fisher-Vanden K, Lammers R, Kumar V, Perla J 2022. Integrated hydrological, power system and economic modeling of climate impacts on electricity demand and cost. Nat. Energy 7:163–69
    [Google Scholar]
  65. Yuan M, Barron A, Selin N, Picciano P, Metz L, Reilly J, Jacoby H 2021a. Meeting potential new U.S. climate goals Joint Prog. Rep. Ser. 351, MIT Joint Prog. Sci. Policy Glob. Change Cambridge, MA:
    [Google Scholar]
  66. Yuan M, Tapia-Ahumada K, Reilly J 2021b. The role of cross-border electricity trade in transition to a low-carbon economy in the Northeastern U.S.. Energy Policy 154:112261
    [Google Scholar]
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