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Executive Summary

In August 2019, the Nordic Prime Ministers adopted a new steering document for Nordic co-operation, entitled ‘Our Vision 2030’. The document states that the Nordic Region aims to become the most sustainable and integrated region in the world by 2030. Working towards a carbon-neutral society is one of the specific priorities of the strategy. 
A new generation of European and Nordic climate policies sets ambitious goals to reach carbon neutrality by or before 2050. The new policies place emphasis on sectors that have proven more challenging to de-carbonise in the past, including: (a) the process industry (e.g. steelmaking, cement, aluminium smelting, petrochemicals); (b) land, air, and maritime transport; and (c) agriculture and animal husbandry. The new climate policies may have both positive and negative impacts on Nordic economies and societies:
  • Economic impacts may arise from technology substitution processes steered by said climate policies. Some technologies, in particular those based on fuel combustion, will be phased out and replaced by cleaner alternatives. That will lead to mixed economic effects, depending on the ability of the various sectors to adapt to carbon-neutral production and consumption systems.
  • Distributive impacts of climate policies will depend on how household finances are affected in terms of income, i.e. quantity and quality of jobs, as well as spending, i.e. cost of living.
  • Regional impacts of climate policies may also be significant. Some regions may be impacted more than others due to their economic dependence on disrupted sectors or, conversely, their overall economic resilience.
This report contains a quantitative analysis of the possible effects of selected climate policies on the Nordic economies in terms of: (a) macroeconomic costs, i.e. impacts on GDP and other macroeconomic variables; (b) labour markets, i.e. employment effects by industry, occupation, wage band, required educational level, age, and subnational region; (c) cost of living, i.e. effects on various types of households, by degree of urbanisation (urban/intermediate/rural) and income decile.
The analysis focuses on a selection of greenhouse policies and their possible impacts for 2019
Our policy scenario looks at the 2020-2030 period. However, our simulations take 2019 as the base year because 2020 was an atypical period due to the global economic disruption caused by the COVID-19 pandemic. 
to 2030: 
  • attainment of targets for a higher biofuel share of motor fuels (see Table 3);
  • attainment of targets for a higher share of electric vehicles in passenger car fleets (see Table 4); and
  • phasing-out of remaining coal-fired electricity.
The analyses in this report are based on a newly developed, multi-regional, computable general equilibrium (CGE) model called Nordic-TERM. It is a model with a high level of regional and sectoral disaggregation that identifies: the five Nordic countries and Rest of Europe; 25 NUTS2 regions within the Nordic countries; 53 industries; 39 occupations together with several occupational characteristics, such as wage bands; and 30 types of households classified by income decile and urban, intermediate, and rural location. That level of detail makes Nordic-TERM an ideal tool for looking at the distributional and structural effects of policies in the Nordic Region. The Nordic-TERM model is the first CGE model to be developed for the Nordic Region and allows for analyses at the national and subnational level.
Using Nordic-TERM, we compute the effects of greenhouse policies by comparing baseline and policy runs of the model for 2019 to 2030. In the baseline run, we assumed no new greenhouse policies beyond those implemented by 2019. The baseline run incorporates macro forecasts and data from the OECD and the World Bank, as well as assumptions concerning productivity differences between broad sectors (agriculture, mining, manufacturing, and services). The policy run estimates the effects of the three greenhouse policies mentioned above. 
The shocks in the policy run take account of: 
  • increases in the cost of motor fuels for industries (mainly the road transport industry) in connection with the attainment of biofuel targets in diesel;
  • increases in the cost of motor fuels for households in connection with the attainment of biofuel targets;
  • changes in the composition of inputs in the production of motor fuels (substitution of oil with biomaterials);
  • increases in the use of electricity by households in connection with the attainment of targets for electric vehicles as a share of the passenger car fleet;
  • reductions in the use of motor fuels by households in connection with the reduction in internal combustion vehicles as a share of passenger cars;
  • increased expenditure by households on charging stations for electric vehicles; and
  • loss of physical capital through scrapping of remaining coal-fired electricity generation, and its replacement by other forms of generation.
The results of the simulation indicate that the attainment of targets for biofuels and electrification of car fleets, together with phasing-out of the remaining coal-fired electricity generation, will be sufficient to meet the 2030 emission reduction target in Sweden, but not in the other Nordic countries (Table 7).
Implementation of these greenhouse policies will have moderate macroeconomic costs. With the policies in place, simulated GDP in the least affected Nordic country, Iceland, is 0.18 per cent less in 2030 than according to the no-policy baseline. In the worst affected Nordic country, Sweden, the GDP cost of the policies in 2030 is a reduction of 1.31 per cent compared to baseline growth over the 11-year period, see Table 8.
The employment deviations in 2030 for the 25 NUTS2
The NUTS classification (Nomenclature of territorial units for statistics) is a hierarchical system for dividing up the economic territory of the EU and the UK. The nomenclature is produced by Eurostat for the purpose of the collection, development, and harmonisation of European regional statistics.
Nordic regions caused by the greenhouse policies are all less than one per cent in absolute terms (Table 16). Norra Mellansverige shows the largest positive deviation (0.37%) while Vestlandet shows the largest negative deviation (-0.49%). With regard to greenhouse policies, Norra Mellansverige has a favourable industry mix (namely a dependence on forestry activity) compared to other Swedish regions. By contrast, Vestlandet has an unfavourable industry mix (namely a particular focus on oil) compared to other Norwegian regions.
In all the Nordic countries, greenhouse policies have negative employment effects on occupations that are used intensively for the provision of private and public consumption services. Those include occupations such as Health professional and Personal care worker (see Table 12). The effects on employment in Scientific and engineering professional, Metal machine trade, and Electrical trade are uniformly positive. For other occupations there are mixed effects across countries. The biggest negative employment deviation across the 39 occupations in the Nordic countries is -2.6% (Handicraft and printing, in Sweden).
As was to be expected, due to a relatively high share of consumer spending on motor fuels, greenhouse policies increase living costs for rural households relative to those in urban and intermediate regions. There is no systematic pattern across deciles: high-income families are just as likely to suffer relative cost-of-living increases as low-income families. However, the relative effects for all family types are very small (Table 17). 
The results in this report allow an optimistic conclusion to be drawn. They suggest that significant reductions in greenhouse emissions can be achieved at moderate macroeconomic cost with almost no structural disruption (Table 19). In terms of adjustment, we consider the occupational and subnational regional results to be of prime relevance. It is reassuring that the greenhouse policies do not generate any large negative employment deviations in these two respects. It means that these policies are unlikely to cause skill-related or locational mismatches on the Nordic labour markets.