Developing a baseline scenario by soft-linking three models
Stress-testing the Norwegian economy: The effects of the 1.5°C scenario on global energy markets and the Norwegian economy
In this project we soft-link three models; GRACE, FRISBEE and KVARTS to study the effects on the Norwegian economy of reaching the 1.5°C target of global warming.
We develop a strategy on how to construct a consistent baseline scenario until 2050 for all three models. GRACE is a general equilibrium model of the world economy, FRISBEE is a partial equilibrium model of the global energy markets, while KVARTS is a model of the Norwegian economy. For FRISBEE and GRACE, we will align with the regional energy development of the baseline scenario in IEAʼs World Energy Outlook from 2019, but do not strive for a perfect hit. If the simulated demand of the various energy goods in the different regions is far off targets according to IEA, we will adjust relevant parameters values. Further, due to lack of data we perform various estimations regarding GDP growth rates and CO2-prices in various regions.
This report depicts a strategy to study the effects on the economy in Norway in a baseline scenario. The most important variables to be implemented from FRISBEE and GRACE in the KVARTS model are oil and gas prices, as well as investment and production profiles of oil and gas. Even if the baseline scenario is the focus in this report, we also describe the flow of variables between the models in the policy scenarios.
About the publication
Stress-testing the Norwegian economy: The effects of the 1.5°C scenario on global energy markets and the Norwegian economy. Developing a baseline scenario by soft-linking three models
Ådne Cappelen, Solveig Glomsrød, Lars Lindholt, Knut Einar Rosendahl and Taoyuan Wei
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Methods and documentation, Methods and documentation
- ISBN (online)
- ISBN (printed)
- About Reports
Analyses and annotated statistical results from various surveys are published in the series Reports. Surveys include sample surveys, censuses and register-based surveys.