Data scraping help (thank you!)
Anyone care to help me extract some Wisconsin State Assembly results from this database? I am applying this proposed gerrymandering standard to t...
Senate: 48 Dem | 52 Rep (range: 47-52)
Control: R+2.9% from toss-up
Generic polling: Tie 0.0%
Control: Tie 0.0%
Harris: 265 EV (239-292, R+0.3% from toss-up)
Moneyball states: President NV PA NC
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My article on Presidential poll aggregation is now published, in the International Journal of Forecasting. You can read it here. It’s part of a special issue on Presidential forecasting; when I have the other articles I will link those as well. Read about the origins of a rather odd hobby!
I think there’s a typo in the link titled ‘here’: surely it should be http://math.princeton.edu/~sswang/wang15_IJF_origins-of-poll-aggregation.pdf?
Yikes. Thank you!
This is going to do wonders for your h-index.
Thank goodness the h-index cannot decrease.
You mentioned Bayesian predictors, specifically Linzer’s Votamatic. One feature of Votamatic is the almost eerie lack of movement. There may be some scatter at the state level but his Obama vs. Romney prediction did not change for several months before the election.
The PEC, by contrast, is full of cliff-edges, such as the one after the first Obama-Romney debate.
Given that Votamatic and PEC both nailed the EV, how significant are the movements of the PEC? Did Romney really have an even chance after that debate?
That’s an excellent summary of the action over the past few election cycles. I’ll probably send people to it as a reference on the subject.
Drew Linzer also did remarkably well at calling the 2014 midterm, if I recall correctly. I’m going to be closely watching whatever he does over the coming year.