The “losers of automation”: A reservoir of votes for the radical right?

Zhen Jie Im, Nonna Mayer, Bruno Palier, Jan Rovny

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This paper studies the association between the risk of automation and vote choice in 11 West European countries. We extend upon labour economics literature on the effects of automation on the labour market by focusing on the political consequences of automation. We also build on existing work relating labour market risks to support for radical right parties. We argue that automation threat is most likely to increase support for radical right parties. We demonstrate that those more inclined to vote for the radical right rather than the average voters are those who are both threatened by automation and are still “just about managing” economically. They are more receptive to the narrative of the radical right, which simultaneously highlights the risk, and proposes protection. Using cross-sectional individual level data drawn from the European Social Survey (rounds 6, 7 and 8), we find that individuals who perceive themselves as “coping on present income” are significantly more likely to vote for radical right parties as risk of automation increases. They are also less likely to vote for major right parties.
Original languageEnglish
Article number2053168018822395
JournalResearch & Politics
Volume6
Issue number1
Number of pages7
ISSN2053-1680
DOIs
Publication statusPublished - 28 Mar 2019
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 517 Political science
  • automation
  • labour markets
  • electoral behaviour
  • radical right

Cite this

Im, Zhen Jie ; Mayer, Nonna ; Palier, Bruno ; Rovny, Jan. / The “losers of automation” : A reservoir of votes for the radical right? . In: Research & Politics. 2019 ; Vol. 6, No. 1.
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The “losers of automation” : A reservoir of votes for the radical right? . / Im, Zhen Jie; Mayer, Nonna; Palier, Bruno; Rovny, Jan.

In: Research & Politics, Vol. 6, No. 1, 2053168018822395, 28.03.2019.

Research output: Contribution to journalArticleScientificpeer-review

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