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6. Appendix

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Key features
Main challenges/ opportunities
DREAM gruppen
CGE model
Dynamic CGE model that enables the analyses on short and long run effects. It has 59 sectors plus 27 types of energy and 14 emissions in physical quantities. It has several fully integrated submodules for specific sectors and features that can be turned on/off as needed and can be used independently of one another.
Model is scalable, requiring consistent data. It is modular by design, meaning that the CGE-model is fully functional on its own as well as each of the sub- components.
Limitation concerning data availability and its integration in the model (it depends on access to detailed national statistics)
Challenges still exist concerning the modeling of future technological change (how to support a bottom-up approach with sufficiently detailed and updated data on costs and potentials of future technology?). Important to ensure that assumptions are documented in a transparent way.
Challenges underlined also on how to model carbon-intensive and export-oriented industries like cement, oil refineries etc.
(Dahl and Kirk, 2022)
(Danmarks Statistik, 2023)
(Dreamgro up, 2023)
Collaboration between the Centre of Policy Studies in Melbourne and Finnish researchers
Dynamic AGE model
FINAGE is a dynamic AGE model based on Monash/VU models influenced by models developed in the Centre of Policy Studies in Australia, with adaptations to the Finnish institutional setting.
FINAGE is very detailed, covering the economy at a level of some 100 industries and 150 commodities, especially focusing on energy data.
The model has a regional extension (at NUTS 3 level), and it covers households by age, income decile and by socioeconomic group.
FINAGE enables anticipation more than forecasting, as the methodology here is more based on sectoral expert opinions on what the technological landscape will be in 10 years.
Challenges concerning institutional setup: Complex institutional settings (like the one in Finland) and the widening of the policy scope point to the need to much more specific sectoral analyses.
Challenges in sectoral modelling: sometimes sectoral modelling implicitly assumes that policies necessary for reaching sectoral targets are in fact in place.
Challenges in modeling innovation and technological change: As models cannot predict new technologies, it is important to have expert insight to help in those decisions, e.g. engaging with business and engineering communities and their predictions to input those insights in the models.
(Honkatuki a et al., 2019)
(Koljonen et al., 2021)
Statistics Norway
The SNOW-NO model is a recursive dynamic computable CGE model developed for the Norwegian economy. The model finds equilibrium prices and quantities by simultaneously solving the set of equations that satisfy the profit- maximisation and utility-maximisation conditions.
The solution determines production, consumption, export and import levels for all goods, input use in each industry, relative prices of all goods and input factors (labour, capital and energy resources), as well as greenhouse gas emissions.
The model is calibrated to the Norwegian national accounts and environmental accounts from Statistics Norway, with base year 2018.
Norway is modelled as a small, open economy, while the rest of the world is reduced to imports and exports. The model represents the Norwegian economy, with 46 producing sectors and various household and public consumption sectors.
The SNOW-NO model incorporates the complexities found in the real-world for the Norwegian economy (e.g., the existing policies including various types of taxes and subsidies). It allows the identification of sectorial and macroeconomic impacts of emissions targets and introduction of climate related taxes.
Recursive models provide greater flexibility in details of the modelling and policies that can be analysed, compared to forward-looking models.
Challenges when modelling technological change: as technology changes rapidly, and technology choices and developments are important for costs of policies, it is important to include more knowledge on technologies under development or adoption.
Limitation linked with learning effects, technology spillovers and network externalities that are not modelled.
(Fæhn et al., 2010)
(Martinsen, 2011)
(Bjertnæs et al., 2013)
(Fæhn et al., 2013)
(Kiuila and Rutherford, 2013)
(Fæhn and Isaksen, 2016)
(Bye et al., 2018)
(Fæhn et al., 2020)
(Bye et al., 2021)
(Kaushal and Yonezawa, 2022)
National Institute of Economic Research (NIER) Konjunkturinsti tutet
EMEC (Environmental Medium Term Economic Model) is a standard single country CGE model based on the Swedish National and Environmental Accounts. The model is currently in its fourth version.
It specifies firms in 35 production sectors, together producing around 43 different products (this can vary year to year). In the current version the model disaggregated the road transport sector substantially (specification of 6+ vehicles and 5+ fuels). It also specifies 6 household types differentiated by income (low/high) and residential area (rural/small, urban/large) to study income distribution effects.
The model has been used to study interactions between the economy, energy use and emissions of several pollutants in Sweden to support policymaking.
The model allows for analysis of the long- run impacts of several energy and environmental policies on the economy and emissions of several pollutants and about how these policies can be designed in effective, cost efficient and equitable ways.
One of EMEC ́s main advantages is that it is a micro-economically consistent and comprehensive representation of price- dependent interactions between the different product markets, production factor markets and the public and private sector in the Swedish economy. Concerning limitations, EMEC is not suited to make forecasts for the short run but only to study the plausible ways in scenarios for the long run
(Krook- Riekkola et al., 2017)
(Östblom and Berg, 2006)
(Otto and Below, 2023)
Initiated by The Energy Agreement and embedded in the Danish Energy Agency
The IntERACT model setup integrates a general equilibrium model with a technical energy system model: it is a hybrid model, which provides a comprehensive description of the Danish economy and the Danish energy system, with keen attention to the interactions between the two.
The IntERACT setup consists of a top- down macroeconomic model and a bottom-up energy system model (TIMES- DK). The top-down model describes the macroeconomic relationships, i.e. economic flows between firms, households, the public sector and international trade. TIMES-DK describes the Danish energy system using a detailed technical modelling of both production and use of energy.
The TIMES energy system modelling framework is used in more than 60 countries, including Norway, Sweden and Finland, and the TIMES modelling framework model is developed and maintained within the IEA-ETSAP community.
One strength of the IntERACT model is the combination of consistent macroeconomic modeling with a detailed and technical description of the energy system, allowing it to provide insights on both economy and energy system wide effects of Danish climate and energy policy.
The hybrid modelling methodology is ideally suited for ex-ante calculations of the effects of policies set to meet the EU energy efficiency directive obligation. It keeps track of issues related to additionality, energy efficiency gap and rebound effects.
It captures overlapping policies related to emissions, renewable energy, energy efficiency, biodiversity, environment and competition.
Challenge: using large numerical models for policy decisions requires a strong commitment from policymakers and a continuous supply of resources for both model development and maintenance.
(Termanse n et al., 2019)
(Kristoffer Steen Andersen et al., 2019)
(Balyk et al., 2019)
(Kristoffer S. Andersen et al., 2019)
(Fortes et al., 2014)
Pan Nordic
Nordic Council of Ministers (Nordregio)
TERM stands for “The Enormous Regional Model”. The TERM-NORD model identifies:
-  53 industries
-  5 Nordic countries plus the rest of Europe (RoE)
-  26 regions within the Nordic countries (NUTS2 regions)
-  39 occupations
-  8 wage-bands
-  30 household types in each of DK, FI and SE (no data on Iceland and Norway)
Model developed for a Nordregio project- Ensuring inclusive economic growth in the transition to a green economy (EnIGG) -to study the distributional effects of climate policies in the Nordic countries. The Nordic- TERM model is the first model which covers almost the entire Nordic Region, consisting of the five Nordic countries Denmark, Finland, Iceland, Norway, and Sweden as well as the autonomous territory of Åland. Greenland and the Faroe Islands, which also form part of the Nordic Region, could not be considered in the model due to data limitations.
(Rimmer et al., 2023)