Is Nate Silver Worse than Crackhead Jim? The Success and Tautology of Election Forecasting

Nate Silver, widely considered as the preeminent election forecaster, uses Bayesian methods in his models. What is Bayesian statistics? It just happens that some of our team members have been studying Bayesian concepts, so we hope this explanation could be somewhat helpful in informing you of the foundational methodology that Silver uses to forecast. The questions we discuss include: - Was Nate Silver right in 2016? (He was and wasn’t). - Can we even judge whether a forecaster is right or wrong? - Are elections chaotic systems that we cannot predict or controlled systems that we can? - Should forecasters incorporate the likelihood of a “Black Swan” event like a coup or contested elections in their models? - Do alternative facts (or truths) exist? - Do we have enough data to make predictions for someone like Trump? This is a brief recap to our election night livestream, in which we had a four-hour long discussion on various topics such as the evolving nature of our political discourse, the future of ObamaCare after elections, Biden’s clean energy plan, etc. You may visit policypunchline.com/op-ed to read more about the application of Bayesian methods in today’s political debates, and you may watch our entire livestream on our YouTube channel.