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What Influences Citizen Forecasts? The Effects of Information, Elite Cues, and Social Cues

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Abstract

The emergent literature on citizen forecasting suggests that the public, in the aggregate, can often accurately predict the outcomes of elections. However, it is not clear how citizens form judgments about election results or what factors influence individual predictions. Drawing on an original survey experiment conducted during the campaign for the United Kingdom’s Brexit referendum, we provide novel evidence of what influences citizen forecasts in a so-far unexplored context of direct democracy. Specifically, we investigate the effect of voting preferences and political sophistication, in addition to three “exogenous factors” that we manipulate experimentally—i.e., social cues, elite cues and campaign arguments. Our findings indicate that citizens are reasonably accurate in their predictions, with the average forecast being close to the actual result of the referendum. However, important individual heterogeneity exists, with politically sophisticated voters being more accurate in their predictions and less prone to wishful thinking than non-sophisticated voters. Experimental findings show that partisan voters adjust their predictions in response to cues provided by their favorite party’s elites and partly in response to campaign arguments, and the effects are larger for low-sophisticated voters. We discuss the mechanisms accounting for the experimental effects, in addition to the implications of our findings for public opinion research and the literature on citizen forecasting.

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Data Availability

The data and the code to reproduce all the analyses described in the main text and online appendixes is available at https://dataverse.harvard.edu/dataverse/morisi.

Notes

  1. Fisher and Shorrocks (2018) have used citizen forecasts as a possible method for predicting the result of the Brexit referendum, but have not investigated the determinants of such forecasts.

  2. We refer to “accuracy” in a purely descriptive sense. This does not exclude that citizens guess it right simply by chance.

  3. To obtain a correct estimate of the average forecast, we considered only the participants in the control condition, and re-weighted the sample in order to compensate for the under-representation of partisan voters in the control condition (see description of the experimental design in the next section).

  4. Even if we find that citizens’ average prediction fell short of the true result, we cannot establish whether this is simply due to the process of averaging out errors on either sides, or whether it indicates that citizens possess information about the behavior of the electorate that is not fully captured by their own preferences.

  5. If we use instead the absolute value of the forecast error as an alternative measure of accuracy, we obtain very similar results (see Model 2 in Table A3 in Appendix A).

  6. These respondents were assigned to the untreated control condition and we consider them only in the observational analysis.

  7. We thank an anonymous reviewer for suggesting this possibility.

  8. An exception is multi-option referendums (Wagenaar, 2020).

  9. Since the result of the Brexit referendum was close to the threshold of 50%, we cannot disentangle whether this “close prediction” derives from an accurate guess or is simply due to chance, as a completely uninformed best guess for a referendum result should be 50%. Further research on referendums where one side wins by a large margin would help disentangle these two possibilities.

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Acknowledgements

The authors gratefully acknowledge the financial support of a Danish Council for Independent Research Sapere Aude Grant (DFF-4003-00192B). Thanks to Rune Slothuus, and workshop participants at the Zurich/ETH CIS seminar, the London School of Economics and Political Science, University of Vienna, and poster session attendees at the 2017 International Society for Political Psychology annual scientific meeting, and three anonymous reviewers for comments on earlier versions of this research.

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  1. Collegio Carlo Alberto, Piazza Arbarello 8, 10122, Turin, Italy

    Davide Morisi

  2. London School of Economics, London, WC2A 2AE, England

    Thomas Leeper

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Correspondence to Davide Morisi.

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Morisi, D., Leeper, T. What Influences Citizen Forecasts? The Effects of Information, Elite Cues, and Social Cues. Polit Behav 46, 21–41 (2024). https://doi.org/10.1007/s11109-022-09811-4

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