Widespread economic transformations, such as increasing automation, tend to negatively affect some groups more than others in the Nordic countries, as elsewhere. Workers who risk losing their jobs to machines or other means are a societal concern; it is, after all, not their fault that society is changing. Importantly, not only are these workers at risk of unemployment, but there appears to be a correlation between employment vulnerability due to automation and voting habits. A recent study of Denmark, Finland, Norway and Sweden and other western European countries has shown that workers whose jobs are vulnerable to automation are most likely to vote for radical right-wing parties. However, initiatives to help people into other types of work must be treated with caution as they are not always successful, and further research is required.
2020.06.11 |
A host of recent research suggests that economic vulnerability stokes fears of status decline which leads people to vote for more right-wing parties. Firstly, a recent paper where I was one of the authors looked at 11 Western European countries, including Denmark, Finland, Norway and Sweden, which were chosen because they all have radical right parties with significant electoral success and they were included in a useful index on the risk of automation (formulated in the paper Arntz et al. (2016)). The study found that there is a link between automation and electoral behaviour in that workers whose jobs were vulnerable to automation were most likely to vote for radical right-wing parties. This is mainly because they were primarily concerned about whether they could manage economically. This can be interpreted as a fear of tumbling down the social ladder which they hope to alleviate by voting for these parties.
These findings tie in with results shown in other studies of other advanced capitalist economies, and highlight how economic anxiety is related to status anxiety, which then translates to specific patterns of party choice. Economically-vulnerable workers, who fear tumbling down the social ladder, may then find radical right-wing parties appealing, especially because such parties stress a nostalgic return to a “better,” earlier time, perhaps where widespread socio-economic changes including automation had not yet taken place. It seems clear, then, that widespread economic transformations tend to negatively affect some groups disproportionately more than others. As a result, these groups in our societies may feel left behind and resentful towards others, thus fuelling support for radical right-wing parties and their policy proposals.
From a social policy perspective, it is important to consider ways of providing assistance to workers who lose their income as a result of automation. Potential initiatives could include:
PICTURE: Inside of the Swedish car manufacturer Volvo manufacturing plant. Photo: Media.volvocars.com
Evidence on the impact of re-training workers is mixed, at best. Recent evidence from Germany and Denmark shows that training does have a positive outcome on employment and wages, but only in the long-run and for specific groups of workers. Even if training does indeed have positive outcomes for workers susceptible to automation, training access, at times, has been found to be biased against such workers, which can of course weaken its remedying effects. Although there has been little research on the issue to date, a few recent studies have identified that case-workers, who are obliged to meet their own targets, have a tendency to pick workers with better economic prospects for training courses. In such an event, economically-disadvantaged workers, who need such training the most, would remain worse-off relative to more advantaged workers. Training access biases may therefore entrench or magnify differences in economic outcomes, rather than correct them. However, this situation appears better in Nordic countries than elsewhere.
Since economic transformations, such as automation, are only likely to continue in the near future, social policies are important tools for policymakers in order to minimise the adverse the effects of such transformations. Social policies, including training, should however be well-designed and better-targeted. If not, such policies could worsen economic divides.
Two avenues for future research appear to be especially significant: Firstly, a better understanding is needed of which social policies are more effective in improving vulnerable workers’ economic outcomes, and, secondly, how access to such policies may be biased against the exact groups of workers these policies are designed to help, in order to avoid such bias in the future.