Click on the entries below for an overview of relevant research conducted by the PollyVote team.

1. Research on the combined PollyVote
  1. Graefe, A., Jones, R. J. J., Armstrong, J. S. & Cuzán, A. G. (2016). The PollyVote forecast for the 2016 American Presidential ElectionPS: Political Science & Politics, 49(4), 687-690.
  2. Graefe, A. (2015). German election forecasting: Comparing and combining methods for 2013. German Politics, 24(2), 195-204. [Replication data available here.]
  3. Graefe, A. (2015). Accuracy gains of adding vote expectation surveys to a combined forecast of US presidential election outcomesResearch & Politics, 2(1), 1-5. [Replication data available here.]
  4. Graefe, A., Armstrong, J. S., Jones, R. J. Jr. & Cuzán, A. G. (2014). Combining forecasts: An application to electionsInternational Journal of Forecasting, 30(1), 43-54. [Replication data available here.]
  5. Graefe, A., Armstrong, J. S., Cuzán, A. G. & Jones, R. J. Jr. (2014). Accuracy of combined forecasts for the 2012 presidential elections: The PollyVotePS: Political Science & Politics, 47(2), 427-431. [Replication data available here.]
  6. Graefe, A., Armstrong, J. S., Jones, R. J. Jr. & Cuzán, A. G. (2013). Combined Forecasts of the 2012 Election: The PollyVoteForesight – The International Journal of Applied Forecasting, Issue 28, 50-51.
  7. Graefe, A., Jones, R. J. Jr., Armstrong, J. S. & Cuzán, A. G. (2012). The PollyVote’s year-ahead forecast of the 2012 U.S. presidential electionForesight – The International Journal of Applied Forecasting, Issue 24, 13-14.
  8. Graefe, A., Armstrong, J. S., Jones, R. J. Jr. & Cuzán, A. G. (2009). Combined Forecasts of the 2008 Election: The PollyVoteForesight – The International Journal of Applied Forecasting, Issue 12, 41-42.
  9. Cuzán, A. G., Armstrong, J. S. & Jones, R. J. Jr. (2005). The Pollyvote: Applying the Combination Principle in Forecasting to the 2004 Presidential Election, Paper presented at the 2005 International Symposium on Forecasting, San Antonio.
  10. Cuzán, A. G., Armstrong, J. S. & Jones, R. J. Jr. (2005). How we computed the PollyVoteForesight: The International Journal of Applied Forecasting, Issue 1, 51-52.
2. Further research on election forecasting
    1. Graefe, A. (2016). Issue-handling beats leadership: Issues and Leaders model predicts Clinton will defeat Trump. Research & Politics (forthcoming).
    2. Graefe, A. (2016). Forecasting proportional representation elections from non-representative expectation surveys. Electoral Studies, 42, 222-228.
    3. Graefe, A. (2015). Improving forecasts using equally weighted predictorsJournal of Business Research, 68(8), 1792-1799. [Replication data available here.]
    4. Graefe, A. (2014). Accuracy of vote expectation surveys in forecasting electionsPublic Opinion Quarterly, 78(S1), 204-232. [Replication data available here.]
    5. Graefe, A., & Armstrong, J. S. (2014). Forecasts of the 2012 U.S. presidential election based on candidates’ perceived competence in handling the most important issuePolitical Science Research and Methods, 2(1), 141-149.
    6. Graefe, A., Küchenhoff, H., Stierle, V. & Riedl, B. (2015). Limitations of Ensemble Bayesian Model Averaging for forecasting social science problemsInternational Journal of Forecasting, 31(3), 943-951.
    7. Graefe, A. (2013). Issue and leader voting in U.S. presidential electionsElectoral Studies, 32(4), 644-657.
    8. Jones, Randall J. Jr. & Cuzán, A. G. (2013). Expert judgment in forecasting American presidential elections: A preliminary evaluation2013 APSA Annual Meeting Paper.
    9. Graefe, A., & Armstrong, J. S. (2013). Forecasting elections from voters’ perceptions of candidates’ ability to handle issuesJournal of Behavioral Decision Making, 26(3), 295-303.
    10. Graefe, A., & Armstrong, J. S. (2012). Predicting elections from the most important issue: A test of the take‐the‐best heuristicJournal of Behavioral Decision Making, 25(1), 41-48.
    11. Armstrong, J. S. & Graefe, A. (2011). Predicting elections from biographical information about candidatesJournal of Business Research, 64, 699-706.
    12. Cuzán, A. G. (2008). Predicting the results of the 2010 midterm Elections: Judgment, econometrics, and prediction marketsForesight – The International Journal of Applied Forecasting, Issue 21, 41-44.
    13. Graefe, A. & Armstrong, J. S. (2011). Who should be nominated to run in the 2012 U.S. Presidential Election? Long-term forecasts based on candidates’ biographies2011 APSA Annual Meeting Paper.
    14. Cuzán, A. G. & Bundrick, C. M. (2009). Predicting presidential elections with equally weighted regressors in Fair’s equation and the fiscal modelPolitical Analysis 17(3), 333-340.
    15. Jones, R. J. Jr. (2008). The state of presidential election forecasting: The 2004 experienceInternational Journal of Forecasting 24(2), 310-321.
    16. Jones, R. J. Jr. & Cuzán, A. G. (2008). Forecasting U.S. Presidential Elections: A Brief ReviewForesight – The International Journal of Applied Forecasting, Issue 10, 29-34.
    17. Jones, R. J. Jr., Armstrong, J. S. & Cuzán, A. G. (2007). Forecasting Elections Using Expert Surveys: An Application to U. S. Presidential Elections2007 APSA Annual Meeting Paper.
    18. Armstrong, J. S. & Cuzán, A. G. (2006). Index methods for forecasting: An application to American presidential electionsForesight – The International Journal of Applied Forecasting, Issue 3, 10-13.
3. Research on automated journalism
  1. Graefe, Andreas (2016). Guide to Automated Journalism. Tow Center for Digital Journalism, Columbia Journalism School, New York City.
  2. Graefe, A., Haim, M., Haarmann, B. & Brosius, H.-B. (2016). Readers‘ perception of computer-written news: Credibility, expertise, and readabilityJournalism (forthcoming).
  3. Haim, M. & Graefe, A. (2016). Automated news: Better than expected?. ICA 2016 – Annual Conference of the International Communication Association, Fukuoka, Japan, June 9-13, 2016.
  4. Berger, M., Haim, M., Graefe, A., Brosius, H.-B., & Hess, T. (2015). Aktuelles Stichwort: Computational Journalism. Medienwirtschaft, 12(1), 20-23.