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Information flow between prediction markets, polls and media: Evidence from the 2008 presidential primaries

Urmee Khan and Robert Lieli

International Journal of Forecasting, 2018, vol. 34, issue 4, 696-710

Abstract: Are the forecast errors of election-eve polls themselves forecastable? We present evidence from the 2008 Democratic Party nomination race between Barack Obama and Hillary Clinton showing that the answer is yes. Both cross-sectional and time series evidence suggests that market prices contain information about election outcomes that polls taken shortly before the contests do not. Conversely, election surprises relative to polls too Granger cause subsequent price movements. We then investigate whether the additional information in prices could come from the media coverage of these campaigns, and uncover a set of complex relationships between pollster’s surprise, price movements, and various aspects of media coverage. Prices anticipate the balance and content of media coverage, but not the volume. On the other hand, it is the volume of media coverage, not the balance or content, that anticipates the surprise element in election outcomes. Moreover, Granger causality between prices and election surprises barely changes after controlling for media coverage, and causality from media volume to surprises persists too after controlling for price movements. Taken together, the results suggest that both prices and the volume of media coverage contain independent election-relevant information that is not captured in polls.

Keywords: Prediction markets; Opinion polls; Information aggregation; Media coverage; Granger causality (search for similar items in EconPapers)
Date: 2018
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Related works:
Working Paper: Information Flow Between Prediction Markets, Polls and Media: Evidence from the 2008 Presidential Primaries (2017) Downloads
Working Paper: Information Flow Between Prediction Markets, Polls and Media: Evidence from the 2008 Presidential Primaries (2016) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:34:y:2018:i:4:p:696-710

DOI: 10.1016/j.ijforecast.2018.04.002

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