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Application of computable general equilibrium (CGE) to climate change mitigation policy: A systematic review

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  • Babatunde, Kazeem Alasinrin
  • Begum, Rawshan Ara
  • Said, Fathin Faizah

Abstract

With the growing literature related to climate change mitigation measures and policy interventions, a systematic review of the application of computable general equilibrium (CGE) model is inevitable. Therefore, this article aims to characterise the relevant studies, define a comparative framework to identify the current state-of-the-art and the gaps in applied general equilibrium models. Firstly, the systematic review found a total of 301 research articles from Scopus and Web of Science databases and finally analysed 154 articles based on inclusion and exclusion criteria from 67 refereed journals. The review analysis found that application of CGE model is very vital in addressing climate change mitigation issues at the national, regional and global levels. However, China attracted the most substantial research interests followed by the USA, India and Australia, among others, which are in line with their share of greenhouse gas emissions in the world. Most of the research themes focus on the carbon tax, emission reduction target, emission trading, renewable energy, energy efficiency, and carbon capture and storage as primary drivers of low carbon economy. Nevertheless, there is a trend of employing more static CGE model compared to the dynamic CGE, although application of the latter has a limitation of providing right inputs to the macroeconomic policy. Finally, research directions and gaps envision other complementary models such as dynamic stochastic general equilibrium (DSGE) and agent-based model (ABM) for proper policy interventions.

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  • Babatunde, Kazeem Alasinrin & Begum, Rawshan Ara & Said, Fathin Faizah, 2017. "Application of computable general equilibrium (CGE) to climate change mitigation policy: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 61-71.
    • Handle: RePEc:eee:rensus:v:78:y:2017:i:c:p:61-71
    DOI: 10.1016/j.rser.2017.04.064
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