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Energy Efficiency and Energy Governance: A Stochastic Frontier Analysis Approach

Author

Listed:
  • J. Barrera-Santana
  • G.A. Marrero
  • F.J. Ramos-Real

Abstract

This work analyzes the impact of energy governance on energy efficiency in a set of 29 OECD countries. A Stochastic Frontier Analysis (SFA) approach is conducted to estimate the energy efficiency levels in this sample of countries between 2000 and 2015. Energy governance is measured by an Energy Efficiency Governance Index (EEGI) constructed in Barrera-Santana et al. (2020). The results suggest that increasing the average quality of energy governance by 10% could raise energy efficiency levels by around 9.20%, according to the estimate of our preferred SFA model. To achieve this outcome there are two key requirements: set quantified and achievable targets, and carry out an extensive evaluation of the results of energy policies. Our results are robust to different econometric approaches and variations of the EEGI.

Suggested Citation

  • J. Barrera-Santana & G.A. Marrero & F.J. Ramos-Real, 2022. "Energy Efficiency and Energy Governance: A Stochastic Frontier Analysis Approach," The Energy Journal, , vol. 43(6), pages 243-284, November.
    • Handle: RePEc:sae:enejou:v:43:y:2022:i:6:p:243-284
    DOI: 10.5547/01956574.43.6.jbar
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    References listed on IDEAS

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    1. Sunjoo Park, 2015. "State Renewable Energy Governance: Policy Instruments, Markets, or Citizens," Review of Policy Research, Policy Studies Organization, vol. 32(3), pages 273-296, May.
    2. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    3. Gustavo A. Marrero & Francisco J. Ramos-Real, 2013. "Activity Sectors and Energy Intensity: Decomposition Analysis and Policy Implications for European Countries (1991–2005)," Energies, MDPI, vol. 6(5), pages 1-20, May.
    4. Lei Jiang & Henk Folmer & Minhe Ji & Jianjun Tang, 2017. "Energy efficiency in the Chinese provinces: a fixed effects stochastic frontier spatial Durbin error panel analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(2), pages 301-319, March.
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