In this article, we summarize the individual demand-level factors explaining the radical right-wing vote in European countries. To do so, we first review 46 quantitative peer-reviewed articles featuring the individual vote choice in favour of a radical right-wing party as the dependent variable. To identify relevant articles, we use Kai Arzheimer’s bibliography on the radical right and employ the following inclusion criterion: the articles must be written in English, they must use the individual vote for a radical right-wing party as the dependent variable, they must use a quantitative methodology and they must include some type of regression analysis. Using this strategy, we conduct a meta-analysis of 329 relevant models and find that over 20 individual variables are tested. Because many variables such as attitudes towards immigration, employment, age, education and gender only show moderate success rates in attempting to explain an individual’s propensity to vote for the radical right, we complement the review of quantitative studies with an analysis of 14 qualitative publications. The review of these qualitative works shows that the processes through which somebody becomes a voter, supporter or activist of the radical right are often more complex than the commonly used surveys can portray them. Frequently, feelings of relative economic deprivation and dissatisfaction with the political regime trigger an awakening that makes individuals seek engagement. However, the processes behind this awakening are complex and can only be partially captured by quantitative studies.

Do researchers share their quantitative data and are the quantitative results that are published in political science journals replicable? We attempt to answer these questions by analyzing all articles published in the 2015 issues of three political behaviorist journals (i.e., Electoral Studies, Party Politics, and Journal of Elections, Public Opinion & Parties)—all of which did not have a binding data-sharing and replication policy as of 2015. We found that authors are still reluctant to share their data; only slightly more than half of the authors in these journals do so. For those who share their data, we mainly confirmed the initial results reported in the respective articles in roughly 70% of the times. Only roughly 5% of the articles yielded significantly different results from those reported in the publication. However, we also found that roughly 25% of the articles organized the data and/or code so poorly that replication was impossible.

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