|Table 1: National popular two-party vote forecasts|
Index models, which were added as a separate component to the PollyVote in 2012, use a different method and different information than econometric models. First, in contrast to traditional methods such as regression analysis, the index method does not estimate weights from the data but uses prior knowledge to determine the variable weights (Graefe, 2015). Second, index models rely on different bits of knowledge than econometric models, such as information about candidates’ biographies (Armstrong and Graefe, 2011) or their perceived issue-handling and leadership competence (Graefe, 2013; Graefe and Armstrong, 2012; 2013; 2014). Table 1 shows the forecasts from the index models that are currently available as well as the combined index model forecast.
An analysis of the 2012 election showed that the decision to add index models to the PollyVote was beneficial. At all times, the five-component PollyVote had a lower error than what would have been achieved with a four-component version (Graefe et al., 2014).
- Armstrong, J. S., & Graefe, A. (2011). Predicting elections from biographical information about candidates: A test of the index method. Journal of Business Research, 64(7), 699-706.
- Graefe, A. (2015). Improving forecasts using equally weighted predictors. Journal of Business Research, 68(8), 1792-1799.
- Graefe, A. (2013). Issue and leader voting in U.S. presidential elections. Electoral Studies, 32(4), 644-657.
- Graefe, A., & Armstrong, J. S. (2014). Forecasts of the 2012 U.S. presidential election based on candidates’ perceived competence in handling the most important issue. Political Science Research and Methods, 2(1), 141-149.
- Graefe, A., & Armstrong, J. S. (2013). Forecasting elections from voters‘ perceptions of candidates‘ ability to handle issues. Journal of Behavioral Decision Making, 26(3), 295-303.
- Graefe, A., & Armstrong, J. S. (2012). Predicting elections from the most important issue: A test of the take‐the‐best heuristic. Journal of Behavioral Decision Making, 25(1), 41-48.
- Graefe, A., Armstrong, J. S., Jones, R. J. J., & Cuzán, A. G. (2014). Accuracy of combined forecasts for the 2012 Presidential Elections: The PollyVote. PS: Political Science & Politics, 47(2), 427-431.