FEEM working papers "Note di lavoro" series
2016 .076

The Cost of Climate Stabilization in Southeast Asia, a Joint Assessment with Dynamic Optimization and CGE Models


Autori: Francesco Bosello, Giacomo Marangoni, Carlo Orecchia, David A. Raitzer, Massimo Tavoni
Serie: Mitigation, Innovation and Transformation Pathways
Editor: Massimo Tavoni
Parole chiave: Climate Change Mitigation, Asian Economies, Computable General Equilibrium Models
Numero JEL: Q54, Q58, C68

Abstract

Southeast Asia is at a time one of the most vulnerable region to the impacts of a changing climate, with millions of its inhabitants still trapped in extreme poverty without access to energy and employed in climate-sensitive sectors, and, potentially, one of the world’s biggest contributors to global warming in the future. Fortunately, major Southeast Asian countries are also implementing policies to improve their energy and carbon efficiency and are discussing if and how to extend these further. The present study aims to assess the implications for energy consumption, energy intensity and carbon intensity in the Southeast Asia region of a set of short-term and long-term de-carbonization policies characterized by different degrees of ambition and international cooperation. The analysis applies two energy-climate-economic models. The first, the fully dynamic Integrated Assessment model WITCH, is more aggregated in the sectoral and country representation, but provides a detailed technological description of the energy sector. The second, the ICES Computable General Equilibrium model, offers a richer sectoral breakdown of the economy and of international trade patterns, but is less refined in the representation of technology. The joint application of these two complementary models allows the capture of distinct and key aspects of low- carbon development paths in Southeast Asia.

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Suggested citation: Bosello, F., G. Marangoni, C. Orecchia, D. A. Raitzer, M. Tavoni, (2016), 'The Cost of Climate Stabilization in Southeast Asia, a Joint Assessment with Dynamic Optimization and CGE Models', Nota di Lavoro 76.2016, Milan, Italy: Fondazione Eni Enrico Mattei

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