Out or sample prediction errors
Because the model in my AER-paper uses in-sample errors, it may
underestimate the uncertainty in the upcoming election results. To see
how important this is, I estimated the out-of-sample errors. The average
absolute prediction error in the state level vote share increases from 3
percent in-sample to 3.7 percent out-of-sample. Most of this is due to
larger out-of-sample national swings.
This has large impacts on the estimated probability of winning. For
example, in the estimates made October 1,
using variance estimates based on
the out-of sample errors, Obama’s chance of winning drops by around 10
percent compared to when using in-sample predictions. This is because
large national prediction errors are more likely when measured out of
sample. Obama's average
vote-share and number of electoral votes remain at the same levels.
While using the out-of-sample errors does make a difference for the
probability of winning, it does little to the optimal campaign
strategies. Graph 3 to the right shows the equilibrium visit shares for
based on variances using the distribution of the out-of-sample errors.
the exact description of how I proceeded, see