The second reason for an optimistic interpretation of the results is illustrated by the lower panel of Table 19. It implies that significant reductions in emissions can be achieved with very little structural disruption.
In Denmark, the percentage deviation in employment in 2030, in the worst-affected occupation out of the 39 in our model is -1.13 per cent. That is the result for Personal care workers in the bottom panel of Table 12. An adjustment of that size would not necessitate employed workers losing their jobs. It does not mean that 1.13 per cent of Denmark’s personal care workers will be put out of work in 2030. From the top two panels of Table 12, we can see that it means employment of Personal care workers will grow between 2019 and 2030 by 3.8 per cent according to the policy-based scenario as opposed to 4.9 per cent according to the baseline scenario.
In Norway, the worst affected occupation is Health professional, with negative deviations of 0.69 per cent. This occupation has strong baseline growth in Norway. Adoption of greenhouse policies means that their employment growth will be slightly lower than it otherwise would have been.
In Finland and Sweden, the worst-affected occupation is Handicraft and Printing, with negative deviations of 1.93 and 2.59 per cent, respectively. In both countries, employment in this occupation falls according to the baseline (top panel of Table 12). Greenhouse policies could therefore exacerbate a potential adjustment problem, particularly in Finland. However, even with the negative greenhouse contribution, it seems likely that the decline in employment opportunities for Printing workers over 11 years would be managed by natural attrition.
For Iceland, the narrative is similar to that in Finland and Sweden. The occupation worst affected by greenhouse policies is Agriculture, forestry and fishing, with a deviation of -1.31 per cent. This occupation has declining employment under the baseline scenario. Again, it seems likely that even with the negative greenhouse contribution the decline in employment opportunities for Iceland’s Agriculture, forestry, and fishing labourers would be managed by natural attrition.
Our estimates show that some of the contractions observed in specific sectors seem to affect industrial output (Table 10) more intensively than employment (Table 11). That is illustrated by the results for fuel-based electricity production (industry 31) in Finland and Sweden. These results suggest that, in many energy-intensive sectors, substantial reductions in greenhouse gas emissions can be achieved with minimal impacts on output and an overall increase in employment.
In any case, when analysing these results, it should be considered that the sectoral contractions observed in some industries have been calculated without taking processes of innovation and technological change into consideration. For instance, the modest contraction of the wood products industry expected in Finland, Sweden, and Norway is driven by the diversion of feedstock into motor fuels, which might undermine the competitiveness of these industries. However, this outcome is far from being inevitable if product innovation and diversification strategies are adopted in the affected sectors. In the wood industry this can be achieved, for example, by cascading the use of biomass (European Commission 2018a, b). Looking at the other dimensions of employment (wage band, age, education, and region), we can see in Table 19 that the policy-induced deviations for the worst-affected groups are negligible, amounting to less than one per cent in absolute terms.
Large policy-induced negative employment deviations can be found among our industry results (Table 11). However, 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 these policies are unlikely to cause skill-based or regional mismatches in Nordic labour markets.
The final row of results in Table 19 shows the policy-induced cost-of-living increases relative to the national average for the worst affected group of households in Denmark, Finland, and Sweden. In all cases, the worst affected households are rural households in upper income deciles. These households devote relatively high shares of their consumer spending to motor fuels. Nevertheless, even for these households, the relative cost-of-living effect of greenhouse policies is small.