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Dynamic Interactions between Carbon and Energy Prices in the U.S. Regional Greenhouse Gas Initiative

Author

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  • Man-Keun Kim

    (Department of Applied Economics, Utah State University, Logan, Utah 84322, USA,)

  • Kangil Lee

    (Department of Agricultural Economics, Oklahoma State University, Stillwater, Oklahoma 74078, USA.)

Abstract

Numerous studies have investigated the dynamic interrelationship between carbon emission trading market and energy markets. Previous studies focused on the European Union emissions trading scheme (EU-ETS) ascertain that carbon market and energy markets are closely attached, and find that electricity market is the main driver of the system. Our research on U.S. Regional Greenhouse Gas Initiative (RGGI) using lag augmented vector autoregression reveals that the RGGI market and electricity market in the region are tied but not strongly, unlike the EU-ETS. This loose relationship between the two markets might be explained by the recent weak carbon credit demand stemming from fuel switching and low electricity demand. Another finding is that natural gas is the main driver of the RGGI system, which is possibly due to from the recent shale gas boom.

Suggested Citation

  • Man-Keun Kim & Kangil Lee, 2015. "Dynamic Interactions between Carbon and Energy Prices in the U.S. Regional Greenhouse Gas Initiative," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 494-501.
  • Handle: RePEc:eco:journ2:2015-02-13
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    Cited by:

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    2. Chris Jeffords & Alexi Thompson & David Yerger, 2015. "Employment Booms and Busts Stemming from Nonrenewable Resource Extraction," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 809-815.
    3. Kim, Man-Keun & Kim, Taehoo, 2016. "Estimating impact of regional greenhouse gas initiative on coal to gas switching using synthetic control methods," Energy Economics, Elsevier, vol. 59(C), pages 328-335.

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    More about this item

    Keywords

    Carbon Emission Trading; Lag Augmented Vector Autoregression; Regional Greenhouse Gas Initiative;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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