Naive

Complexity tends to harm forecast accuracy. That is, the accuracy of very simple models, such as a naïve no-change model, is often difficult to beat by more complex models. One reason for using a no-change model could be that one concludes from prior knowledge that the situation is stable. Another reason might be that, in many situations, prior knowledge is insufficient to improve upon a no-change forecast (Green & Armstrong, 2015).

The 2020 PollyVote averages forecasts from two naïve models, namely the electoral cycle model by Norpoth (2014) and a 50/50 model.

In including a naïve component, the PollyVote adheres to the principle of conservatism in forecasting by acknowledging the situation’s underlying uncertainty (Armstrong, Green, & Graefe, 2015)

References

Armstrong, J. S., Green, K. C., & Graefe, A. (2015). Golden rule of forecasting: Be conservative. Journal of Business Research, 68(8), 1717-1731. 

Green, K. C., & Armstrong, J. S. (2015). Simple versus complex forecasting: The evidence. Journal of Business Research, 68(8), 1678-1685.

Norpoth, H. (2014). The Electoral Cycle. PS: Political Science & Politics, 47(2), 332-335.