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Projecting impacts of carbon dioxide emission reductions in the US electric power sector: evidence from a data-rich approach

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  • Kyle E. Binder

    () (Federal Reserve Bank of Chicago)

  • James W. Mjelde

    () (Texas A&M University)

Abstract

Abstract Conditional forecasts of US economic and energy sector activity are developed using information from a dynamic, data-rich environment. The forecasts are conditional on a path for carbon dioxide emissions outlined in the US Environmental Protection Agency’s Clean Power Plan (CPP) and are estimated based on a factor-augmented autoregressive framework. Results suggest that overall growth will be slower under the CPP than it would otherwise; however, economic growth and CO2 reductions can be achieved simultaneously. There are little differences between unconditional (business-as-usual) and conditional forecasts of the variables in the early part of the forecast period; the impacts of the CPP are small while the constraints on carbon dioxide are less stringent. The results serve as a data-driven complement to structural analyses of policy change in the energy sector.

Suggested Citation

  • Kyle E. Binder & James W. Mjelde, 2018. "Projecting impacts of carbon dioxide emission reductions in the US electric power sector: evidence from a data-rich approach," Climatic Change, Springer, vol. 151(2), pages 143-155, November.
  • Handle: RePEc:spr:climat:v:151:y:2018:i:2:d:10.1007_s10584-018-2297-9
    DOI: 10.1007/s10584-018-2297-9
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    References listed on IDEAS

    as
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