The multiregional global economy

Financial support: AIE, Chaire Modélisation Prospective…

Accounting for the feedback loops between national and global pathways is one of the research focuses of the International IMACLIM Network. The Network’s capacity to do so mainly rests on the IMACLIM-R global model of CIRED, a multi-sector multi-region dynamic recursive growth model.

Brazil, China and India are 9 of the 12 world regions disaggregated by IMACLIM-R. One of the challenges facing the Network will be the methodological investigation of what numerical dialogue could be organised between the detailed national models of these countries and the corresponding representations in IMACLIM-R.

In the course of a recent RISKERGY project, CIRED produced an additional global modelling tool: the KLEM-POLES architecture, which couples compact ‘KLEM’ macroeconomic models to 50 countries of the POLES energy system model (Ghersi, 2016). KLEM-POLES has the advantage to disaggregate all countries currently under focus of the Network—at the cost of a much more aggregated economic description. It may provide an alternative integrating framework to the Network’s country models. Picking up on the KLEM-POLES effort, a KLEM-TIAM collaborative started with the global TIAM model of the EPMRG of UCC, with its focus on producing consistent KLEM and TIAM mitigation pathways over the century, based on a methodology adapted from that used with POLES.


Hamid-Cherif M., Waisman, H.-D. (2016). Global carbon pricing and the “Common but differentiated responsibilities” – The case of China. International Environmental Agreements: Politics, Law and Economics 16: 671–689. 

Ghersi, F. (2016). Projet RISKERGY, Rapport final. Project report, CIRED, 84 p.
Bibas, R., Méjean, A., Hamdi-Cherif, M. (2015). Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. Technological Forecasting and Social Change vol. A: 137-152.

Waisman, H.-D., Guivarch, C., Grazi, F., Hourcade, J.-C (2012). The Imaclim-R model: Infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight. Climatic Change 114 (1).

Sassi, O., Crassous, R., Hourcade, J.-C., Gitz, V., Waisman, H.-D., Guivarch, C. (2010). IMACLIM-R: A modelling framework to simulate sustainable development pathways. International Journal of Global Environmental Issues 10 (1&2): 5-24.

Crassous, R., Hourcade, J.-C., Sassi, O. (2006). Endogenous structural change and climate targets: modeling experiments with Imaclim-R. The Energy Journal, Special Issue on the Innovation Modeling Comparison Project

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