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Are Election Results More Unpredictable? A Forecasting Test

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Harvard Dataverse2019-03-01 更新2026-04-09 收录
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Changes in voters’ behaviour and in the campaign strategies that political parties pursue are likely to have increased the importance of campaigns on voters’ electoral choices. As a result, scholars increasingly question the usefulness and predictive power of structural forecasting models, that use information from ‘fundamentals’ variables to make an election prediction several months before Election Day. In this paper, we empirically examine the expectation that structural forecasting models are increasingly error-prone. For doing so, we apply a structural forecasting model to predict elections in six established democracies. We then trace the predictive power of this model over time. Surprisingly, our results do not give the slightest indication of a decline in the predictive power of structural forecasting models. By showing that information on long-term factors still allows making accurate predictions of electoral outcomes, we question the assumption that campaigns matter more now than they did in the past.

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2019-01-01
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