4.8 Article

Enhancing the quality of climate policy analysis in China: Linking bottom-up and top-down models

Journal

RENEWABLE & SUSTAINABLE ENERGY REVIEWS
Volume 151, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2021.111551

Keywords

Top-down and bottom-up linkage; Climate change policies; Economic impacts; Computable general equilibrium modeling; Energy sector modeling; China

Funding

  1. World Bank's Research Support Grant (RSB)

Ask authors/readers for more resources

Macroeconomic models, when used alone, tend to overestimate economic impacts of climate change policies due to their inability to represent detailed technological characteristics. Integrating these models with bottom-up energy sector models can provide more accurate assessments. Results of this study show that the hybrid model can lead to economic impact assessments that are nearly three times smaller than those assessed by top-down models alone.
Macroeconomic models are the most common analytical tools to assess economy-wide impacts of climate change policies. These models are, however, not capable of representing detailed physical characteristics of energy production and combustion technologies and often lead to the overestimation of economic impacts. One solution to address this problem is to link top-down macroeconomic models with bottom-up energy sector models that can represent technological details. This study develops a hybrid model by linking a top-down computable general equilibrium model with a bottom-up energy sector model and implements it to assesses economic impacts of emission reduction targets in China set under the Paris Climate Agreement. Results show that economic impacts assessed by the hybrid model are nearly three times smaller than that assessed by the top-down model alone.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available