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Citizen Forecasting 2020: A State-by-State Experiment

Published online by Cambridge University Press:  15 October 2020

Andreas E. Murr Open the ORCID record for Andreas E. Murr [Opens in a new window]  and
Michael S. Lewis-Beck
Andreas E. Murr
Affiliation:
University of Warwick, England
Michael S. Lewis-Beck
Affiliation:
University of Iowa
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Abstract

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Information

Type
Forecasting the 2020 US Elections
Information
PS: Political Science & Politics , Volume 54 , Issue 1 , January 2021 , pp. 91 - 95
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the American Political Science Association

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References

REFERENCES

Fisher, Stephen D., and Lewis-Beck, Michael S.. 2016. “Forecasting the 2015 British General Election: The 1992 Debacle All Over Again?” Electoral Studies 41 (1): 225–29.Google Scholar
Graefe, Andreas. 2014. “Accuracy of Vote Expectation Surveys in Forecasting Elections.” Public Opinion Quarterly 78 (S1): 204–32.Google Scholar
Jennings, Will, Lewis-Beck, Michael S. , and Wlezien, Christopher. 2020. “Election Forecasting: Too Far Out?” International Journal of Forecasting 36 (3): 949–62.CrossRefGoogle Scholar
Leiter, Debra, Murr, Andreas E., Ramírez, Ericka Rascón, and Stegmaier, Mary. 2018. “Social Networks and Citizen Election Forecasting: The More Friends the Better.” International Journal of Forecasting 34 (2): 235–48.Google Scholar
Lewis-Beck, Michael S., and Stegmaier, Mary. 2011. “Citizen Forecasting: Can UK Voters See the Future?” Electoral Studies 30 (2): 264–68.Google Scholar
Lewis-Beck, Michael S., and Tien, Charles. 1999. “Voters as Forecasters: A Micromodel of Election Prediction.” International Journal of Forecasting 15 (2): 175–84.CrossRefGoogle Scholar
Murr, Andreas E. 2011. “‘Wisdom of Crowds’? A Decentralized Election Forecasting Model That Uses Citizens’ Local Expectations.” Electoral Studies 30 (4): 771–83.Google Scholar
Murr, Andreas E. 2015. “The Wisdom of Crowds: Applying Condorcet’s Jury Theorem to Forecasting US Presidential Elections.” International Journal of Forecasting 31 (3): 916–29.CrossRefGoogle Scholar
Murr, Andreas E. 2016. “The Wisdom of Crowds: What Do Citizens Forecast for the 2015 British General Election?” Electoral Studies 41 (1): 283–88.CrossRefGoogle Scholar
Murr, Andreas E. 2017. “Wisdom of Crowds.” In The SAGE Handbook of Electoral Behaviour, ed. Arzheimer, Kai, Evans, Jocelyn, and Lewis-Beck, Michael S., 835–60. London: SAGE.Google Scholar
Murr, Andreas E., and Lewis-Beck, Michael S.. 2020. “Replication Data for Citizen Forecasting 2020: A State-by-State Experiment.” Harvard Dataverse. doi:10.7910/DVN/S1594S.Google Scholar
Murr, Andreas E., Stegmaier, Mary, and Lewis-Beck, Michael S.. 2016. “Using Citizen Forecasts We Predict That with 362 Electoral Votes, Hillary Clinton Will Be the Next President.” London School of Economics American Politics and Policy Blog. Available at http://blogs.lse.ac.uk/usappblog/2016/11/03/using-citizen-forecasts-we-predict-that-with-362-electoral-votes-hillary-clinton-will-be-the-next-president.Google Scholar
Murr, Andreas E., Stegmaier, Mary, and Lewis-Beck, Michael S.. 2017. “New British Election Forecast: Conservatives Gain 31 Seats and Have 77% Chance of Controlling a Majority. Washington Post Monkey Cage. Available at www.washingtonpost.com/news/monkey-cage/wp/2017/06/06/can-people-rather-than-pollsters-accurately-predict-thursdays-u-k-election/?utm_term=.41f7430ecc58.Google Scholar
Murr, Andreas E., Stegmaier, Mary, and Lewis-Beck, Michael S.. 2019. “Citizen Forecasting 2019: A Big Win for the Conservatives.” London School of Economics British Politics and Policy Blog. Available at https://blogs.lse.ac.uk/politicsandpolicy/citizen-forecasting-2019-a-big-win-for-the-conservatives.Google Scholar
Murr, Andreas E., Stegmaier, Mary, and Lewis-Beck, Michael S.. n.d. “Vote Expectations Versus Vote Intentions: Rival Forecasting Strategies.” British Journal of Political Science. doi:10.1017/S0007123419000061.Google Scholar
Supplementary material: PDF

Murr and Lewis-Beck supplementary material

Tables A1-A3

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Murr and Lewis-Beck Dataset

Dataset

https://doi.org/10.7910/DVN/S1594S
Link