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2. Further research on election forecasting

    1. Graefe, A. (2017). Political markets. In K. Arzheimer, J. Evans & M. S. Lewis-Beck (Eds.), The SAGE Handbook of Electoral Behaviour, Volume 2 (pp. 861-882). London: Sage.
    2. Graefe, A. (2017). Prediction market performance in the 2016 U.S. presidential electionForesight – The International Journal of Applied Forecasting, 2017(45)38-42.
    3. Graefe, A. (2016). Issue-handling beats leadership: Issues and Leaders model predicts Clinton will defeat Trump. Research & Politics, DOI: 10.1177/2053168016679364.
    4. Graefe, A. (2016). Forecasting proportional representation elections from non-representative expectation surveysElectoral Studies, 42, 222-228.
    5. Graefe, A. (2015). Improving forecasts using equally weighted predictorsJournal of Business Research, 68(8), 1792-1799. [Replication data available here.]
    6. Graefe, A. (2014). Accuracy of vote expectation surveys in forecasting electionsPublic Opinion Quarterly, 78(S1), 204-232. [Replication data available here.]
    7. 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.
    8. 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.
    9. Graefe, A. (2013). Issue and leader voting in U.S. presidential electionsElectoral Studies, 32(4), 644-657.
    10. Jones, Randall J. Jr. & Cuzán, A. G. (2013). Expert judgment in forecasting American presidential elections: A preliminary evaluation2013 APSA Annual Meeting Paper.
    11. 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.
    12. 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.
    13. Armstrong, J. S. & Graefe, A. (2011). Predicting elections from biographical information about candidatesJournal of Business Research, 64, 699-706.
    14. 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.
    15. 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.
    16. 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.
    17. Jones, R. J. Jr. (2008). The state of presidential election forecasting: The 2004 experienceInternational Journal of Forecasting 24(2), 310-321.
    18. 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.
    19. 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.
    20. 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.
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