The election modelers of the world have a tough job. They’re relied on to offer election predictions months and sometimes years in advance of national contests that many people, from mainstream pundits to the candidates themselves, live and die by. Consequently, so do the modelers.
But just how accurate are election forecasts? With election observers increasingly pinning their hopes on crystal ball types like Nate Silver, who came to prominence after successfully predicting former president Barack Obama’s victories in every U.S. state in 2008 and 2012, errant results can derail mainstream storylines and reveal biases.
The 2016 presidential election is a good example of this, when Silver’s modeling outfit FiveThirtyEight, along with numerous other state, federal and independent election data sources, greatly overestimated support for Hillary Clinton (of course, as it turned out, she did win the popular vote). Silver appeared to take the fall for his colleagues, writing in a lengthy election retrospective about the “challenges of poll interpretation” and the “pervasive groupthink among media elites.”
