No abstract

Objective Macro‐level studies have consistently found a connection between economic crises and support for far‐right parties. However, research on the micro foundations for this electoral support has generally found little or no correlation between an individual's economic environment and far‐right voting. We test one possible explanation for this seeming paradox, namely, that determinants of far‐right identification differ across time and particularly in times of crisis. Methods Utilizing traditional representative data from Eurobarometer surveys in a manner that strips away confounding issues generally found in the extant literature, we directly test whether individuals concerned about their personal economic situation, or that of their country, are more likely to identify with far‐right ideological beliefs during economic crises. Results Ultimately, we find little evidence to support the claim that the Great Recession of 2007–2009 and its aftermath shifted the determinants of support for far‐right ideology, though prospective pocketbook concerns do increase the likelihood of identifying with the far right. Conclusions We discuss the implications of these findings and offer additional avenues for future research.

The literature surrounding extreme right parties in Europe has developed dramatically over the past two decades. However, the analysis of electoral success for these parties has produced muddled results, and occasionally even conflicting findings. This article argues this confusion is partially due to a reliance on an inappropriate model choice. Through the use of simulations, a goodness-of-fit exercise, and a prediction exercise based on model cross-validation, I show that the traditional Tobit specification—adopted to deal with electoral results of fringe parties—is theoretically untenable, statistically inferior to alternative models, and practically prone to revealing effects that are unsupported by the underlying data. Rather, the results suggest that best practices should see researchers adopt Cragg or Heckman models for two-stage questions, or consider adopting an analysis applying multiple overimputation if the main question is focused on the determinants of electoral success.

Many large survey courses rely on multiple professors or teaching assistants to judge student responses to open-ended questions. Even following best practices, students with similar levels of conceptual understanding can receive widely varying assessments from different graders. We detail how this can occur and argue that it is an example of differential item functioning (or interpersonal incomparability), where graders interpret the same possible grading range differently. Using both actual assessment data from a large survey course in Comparative Politics and simulation methods, we show that the bias can be corrected by a small number of “bridging” observations across graders. We conclude by offering best practices for fair assessment in large survey courses.