Though estimating the vote share of radical right parties in advance of an election is politically important, it is always a challenge. This can be due to sampling bias in the polling, in which the sample may not represent the population of radical right party supporters, or critical events, such as scandals about radical right party candidates, may take place during the campaign period and voters who intended to support the radical right could then switch to other parties. But the most critical problem in estimating the vote share of radical right parties is social desirability bias.
Social desirability bias is hardly something new in the study of voting behavior. In terms of voter turnout, respondents tend to claim that they will go to the polling booth, despite the fact that they may not vote on election day. In the case of radical right party voting, the effect of social desirability bias is just the opposite. Instead, radical right party voters will not publicly report that they support the party, preferring to hide their true preference and say that they support other parties or have not yet decided. This phenomenon is what Kuran calls “preference falsification”, which is used to shield oneself from social pressure. Here, the “wisdom of crowds” method can address this issue.
The rationale of this design come from its name: the average belief of the vox populi (or crowd) can actually be quite accurate and may even be better than the conjecture of polling experts. This crowd estimate is actually based on the aggregate of different respondents’ individual estimates regarding the quantity of interest. In our case, the quantity of interest would be the percentage share of votes a radical right party will get in the upcoming election. The “wisdom” part refers to the errors of the individual estimates which tend to cancel out one another. Thus, the basic idea is that the more variable the individual estimates are, the more accurate is the crowd estimates in comparison to the true value (i.e. the actual vote share the radical right party can get).
However, the wisdom of crowds design does not exist all the time but only under specific conditions. First, the respondents must be diverse in opinions. By adding a number of perspectives, the crowd estimates will be less skewed. Second, the knowledge of the respondents has to be both specialized and local. Third, the independence of respondents needs to be guaranteed. If respondents within the crowd merely repeat the answers of others, this condition is the violated.
The application of a “wisdom of crowds” design was applied in a case study of the AfD’s vote share in the 2017 German federal election. They asked respondents to speculate the percentage share of second votes AfD would obtain in the 2017 Bundestag election. After comparing the findings of the “wisdom of crowds” design with other kinds of techniques, they found it to be the least biased and most efficient. Nevertheless, one shall bear in mind that the crowd estimate, no matter how accurate it is, only gives one an aggregate estimate. In other words, we never know whether the respondents support / would vote for AfD or not.
In general, “wisdom of crowds” design is more commonly employed in forecasting elections. It has already been used in forecasting the UK general election in 2015 and US presidential elections. However, for the studies of radical right parties’ electoral performance, “wisdom of crowds” design is still under-utilized. So, there may be great potential for using it in the future, especially due to its low cost.
In September and October, Portugal, Austria, and Switzerland are going to hold general elections. Perhaps one may try to make use of this design to forecast the electoral performances of radical right parties and compare these crowd estimates with the true electoral results. The comparison of results can be interesting, because the radical right parties in these three countries behave rather differently. While Portugal is still regarded as an exception to the success of a radical right party, the Swiss People’s Party and Freedom Party of Austria have already set foot in national parliament. Thus, it is worthwhile to investigate whether the accuracy of crowd estimates in these three countries differ from or concur with one another.
Mr Ka Ming Chan is a Doctoral Fellow at CARR and Doctoral candidate at Geschwister Scholl Institute of Political Science, Ludwig-Maximilians-Universität. See his profile here.
© Ka Ming Chan. Views expressed on this website are individual contributors and do not necessarily reflect that of the Centre for Analysis of the Radical Right (CARR). We are pleased to share previously unpublished materials with the community under creative commons license 4.0 (Attribution-NoDerivatives).
