This research presents a thorough evaluation of macroeconomic modelling tools in the context of analysing industrial transformation. It emphasizes the need to link macroeconomic models with energy system models to accurately depict industrial transformation. The study begins with a broad survey of macroeconomic modelling tools. A detailed database of 61 tools is then compiled, providing a critical analysis of the tools' structures and features. From this broad spectrum, the focus is narrowed to Computable General Equilibrium (CGE) models. The study develops a multi-criteria analysis framework, applied specifically to four CGE modelling tools, which encompasses 19 criteria categorized under four main pillars: Industrial/Sectoral representation, Technological change, Employment, and Environment. This framework critically evaluates these tools' suitability in analysing industrial transformation, highlighting the diversity of their capabilities and limitations. Although the GEM-E3 model demonstrates a high level of alignment with the framework's criteria, none of the four tools achieves a full score in any category, indicating potential areas for improvement. The broader analysis of the database's tools reveals issues such as limited accessibility, inadequate representation of social aspects, and insufficient geographical coverage. Additionally, the study notes a general lack of transparent information concerning the full features of macroeconomic modelling tools in public literature. Concluding with recommendations for further research, the study underscores the complexities in macroeconomic modelling and the need for comprehensive tools that effectively address the multifaceted aspects of industrial transformation. Such advancements will assist in making informed decisions towards a transformation that is both environmentally and economically sustainable.
ELBERRY Ahmed;
GARAFFA Rafael;
FAAIJ A.P.C.;
VAN DER ZWAAN Bob;
2024-06-07
PERGAMON-ELSEVIER SCIENCE LTD
JRC138153
1364-0321 (online),
https://www.sciencedirect.com/science/article/pii/S1364032124001850,
https://publications.jrc.ec.europa.eu/repository/handle/JRC138153,
10.1016/j.rser.2024.114462 (online),
| Name | Country | City | Type |
|---|
This document is only visible at the Commission level.
You are not authorized to publish or distribute it outside the European Commission.
This is a public document. You can share this publication.
Datasets
| ID | Title | Public URL |
|---|
Dataset collections
| ID | Acronym | Title | Public URL |
|---|
Scripts / source codes
| Description | Public URL |
|---|
Additional supporting files
| File name | Description | File type |
|---|