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Centrist by Comparison: Extremism and the Expansion of the Political Spectrum

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You win policy debates by crafting arguments for extreme

positions—and then shifting the entire window of debate.

Daily Kos, 2006

Abstract

While it is well understood that policy suggestions outside the range of mainstream debate are prevalent in various policy domains of American politics, their effects remain unexplored. In this paper, we suggest that proposing policies far from the political mainstream can re-structure voter perceptions of where alternatives lie in the ideological space. We provide support for this hypothesis using results from six survey experiments. We find that the introduction of extreme alternatives into the public discourse makes mainstream policies on the same side of the spectrum look more centrist in the public eye, thus increasing support for these moderate alternatives.

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Notes

  1. Political pundits, on the other hand have suggested that the introduction of extreme policy alternatives into the political discourse is strategic, serving the purpose of shifting the scope of the political debate. This idea is usually attributed to Joseph Overton, who argued that the range of policies or opinions deemed acceptable by the public (the Overton-window) is in a constant flux and can be shifted by introducing and defending ideas not yet “on the table”.

  2. To our knowledge, Herne (1997) is the only study reporting on the analysis of context dependent preferences over policies. While that study provides evidence on preference reversals in the context of choices between highly stylized multi-dimensional government programs, represented by numerical values it is unclear how much those results generalize to “simpler” and more salient issues.

  3. We illustrate this logic with a simple formal and graphical analysis in Online Appendix A.

  4. In the last study we added a further condition with both extreme policies.

  5. We conducted multiple smaller studies instead of one large, but better powered experiment in order to increase our confidence that results are not driven by particular features of a particular set of issues or sample.

  6. MTurk is now widely used to conduct survey experiments in political behavior (e.g. Huber et al. 2012; Healy and Gabriel 2014). See Berinsky, Huber, and Lenz (2009) for an assessment of MTurk as a data collection platform.

  7. Descriptive statistics of the samples in each studies are reported in Table 5 in the Appendix.

  8. We also used slightly different survey instruments for measurement in this study as it was programmed using YouGov’s own survey software (the questionnaires for the first and third studies were programmed with Qualtrics).

  9. Note that since all subjects were shown these alternatives, we can recover each respondent’s preference with respect to these alternatives. For our analyses we discard information about the absolute rankings because they are not comparable across different choice sets (the distribution of the top-ranked choices across experiments is reported in Fig. S3 in the SI).

  10. As Table 6 in the Appendix shows, the randomization was successful in the sense that in each study treatment group assignment was unrelated to measured pre-treatment covariates.

  11. We replicated each regression with binary outcomes (such as preference for the moderate liberal policy) using logit models that yielded similar results. We chose to report estimates from the linear model for an ease of interpretation and because the specifications are saturated.

  12. In Studies 1 and 2 these indicators are orthogonal to each other (i.e. either a liberal or a conservative extreme policy is introduced). In Study 3, some respondents saw both extreme alternatives, so in this case the estimated effects of these indicators capture the marginal effect of adding a given alternative.

  13. We use medians to guard against the effect of outliers which are likely to be due to measurement error (e.g. respondents confusing the endpoint of scales). The results look essentially the same with means as summary statistics.

  14. For instance, liberals are overrepresented in the MTurk samples. However, it is also possible that effect sizes differ because the MTurk respondents are more attentive to the survey. Unfortunately it is impossible to disentangle these two explanations (differences in political beliefs vs. survey taking strategies) with our data.

  15. A possible problem of adjusting for respondents issue preferences is that they might be affected by the treatment itself, leading to post-treatment bias. At the same time our analyses of range effects presented above showed no evidence of the exposure to extreme alternatives influencing issue preferences. Also, we get similar results when we adjust for predetermined covariates in the pooled model such as partisanship.

  16. We restrict our attention here to the first two studies (i.e. first four experiments) where we measured respondents’ own issue preferences (on the same scale as their perceived ideological position of policies). For each respondent, we calculated the perceived spatial distance of the two moderate policy alternatives by taking the absolute value of her rating of a given policy and her own issue preference. We then defined perceived relative proximity to the moderate liberal alternative by taking a respondents’ perceived distance from the moderate liberal policy and subtracting that from her perceived distance from the moderate conservative policy.

  17. In the terminology of framing theory, our stimuli can be considered repeated “weak frames”, which have shown to have very limited impact on attitudes (Chong and Druckman 2007).

  18. For instance, we would not expect any treatment effects for a sample in which all subjects have extremely liberal or conservative issue preferences.

  19. We provide more detail about this survey in the SI.

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Author information

Authors and Affiliations

  1. Department of Politics, New York University, New York, USA

    Gabor Simonovits

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  1. Gabor Simonovits
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Correspondence to Gabor Simonovits.

Additional information

Data for Study 2 was collected by the Omnibus Survey of the Laboratory for the Study of American Values (LSAV) at Stanford University. The author thanks Steve Callander, Pat Egan, Simon Ejdemyr, Neil Malhotra, Julia McLean, Erik Peterson, Itamar Simonson, Paul Sniderman and Mike Tomz for helpful comments. All remaining errors are mine. The data and code necessary to replicate the numerical results is available at the Journals Dataverse at http://dx.doi.org/10.7910/DVN/EXVUEA.

Electronic Supplementary Material

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Supplementary material 1 (pdf 302 KB)

Appendix

Appendix

See Tables 5 and 6.

Table 5 Demographics
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Table 6 Randmization check
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Simonovits, G. Centrist by Comparison: Extremism and the Expansion of the Political Spectrum. Polit Behav 39, 157–175 (2017). https://doi.org/10.1007/s11109-016-9351-y

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