A dynamic CGE modelling approach for analyzing trade-offs in climate change policy options: the case of Green Climate Fund

The research evaluates policy options to reach a 450 PPM CO2 concentration target by 2050, focusing on the period up to 2035. Using the GDynE model, the authors compare domestic carbon taxes and international emission trading (IET) against scenarios where the Green Climate Fund (GCF) is used for welfare redistribution, energy efficiency, or renewable energy. The findings indicate that while abatement costs are generally detrimental to the growth of developing countries, a GCF financed by an 8% levy on developed countries' carbon tax revenues can mitigate these losses. Specifically, investing GCF resources into energy efficiency in developing countries provides the most significant global benefit, potentially resulting in a net gain for developing economies and reducing the overall cost of meeting climate targets for all parties.

• Abatement costs required to meet a 450 PPM target are projected to be significantly detrimental to the economic growth of developing countries, which may hinder their political willingness to accept binding emission constraints.
• A global carbon market (International Emission Trading) is more cost-effective than separate domestic carbon taxes, reducing global GDP losses by approximately 0.7%.
• The implementation of a global carbon market can create regional losers; for example, Energy Exporters are projected to be 17% worse off than the baseline by 2035 under IET, compared to only 7% worse off under domestic taxes.
• Financing the Green Climate Fund (GCF) through an 8% levy on carbon tax revenues from developed countries can lower the global price of carbon permits.
• Among GCF allocation strategies, investing in energy efficiency (GCF-EE) is the most effective at reducing global abatement costs and can lead to positive economic benefits for developing countries as an aggregate.
• A mixed GCF strategy combining energy efficiency and renewable energy (GCF-MIX) reduces welfare losses for both developed and developing countries, partly due to synergistic effects where efficiency gains lower the cost of renewables.
• The use of GCF for technical change (energy efficiency or renewables) reduces the total amount of revenue collected by the fund over time because the resulting lower carbon prices reduce the tax base.
• The model predicts that without further measures, global CO2 emissions will increase by 56% by 2035 compared to 2010 levels, with India seeing the highest projected increase at 196%.

APA

Antimiani, A., Costantini, V., Markandya, A., Martini, C., Palma, A., & Tommasino, M. C. (2014). A dynamic CGE modelling approach for analyzing trade-offs in climate change policy options: the case of Green Climate Fund. Basque Centre for Climate Change. https://www.bc3research.org/h6T8Uy8Nm4gFs0O/201409080854521662835982.pdf

Chicago

Antimiani, Alessandro, Valeria Costantini, Anil Markandya, Chiara Martini, Alessandro Palma, and Maria Cristina Tommasino. A dynamic CGE modelling approach for analyzing trade-offs in climate change policy options: the case of Green Climate Fund. Basque Centre for Climate Change, 2014. https://www.bc3research.org/h6T8Uy8Nm4gFs0O/201409080854521662835982.pdf.

Wikipedia

{{cite report |last1=Antimiani |first1=Alessandro |last2=Costantini |first2=Valeria |last3=Markandya |first3=Anil |last4=Martini |first4=Chiara |last5=Palma |first5=Alessandro |last6=Tommasino |first6=Maria Cristina |title=A dynamic CGE modelling approach for analyzing trade-offs in climate change policy options: the case of Green Climate Fund |publisher=Basque Centre for Climate Change |date=September 2014 |url=https://www.bc3research.org/h6T8Uy8Nm4gFs0O/201409080854521662835982.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{antimiani2014dynamic, author = {Antimiani, Alessandro and Costantini, Valeria and Markandya, Anil and Martini, Chiara and Palma, Alessandro and Tommasino, Maria Cristina}, title = {{A dynamic CGE modelling approach for analyzing trade-offs in climate change policy options: the case of Green Climate Fund}}, institution = {Basque Centre for Climate Change}, year = {2014}, month = sep, url = {https://www.bc3research.org/h6T8Uy8Nm4gFs0O/201409080854521662835982.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }