Recent Blog Posts
-
The Year in Research
Dec 31 20089:13 am EDT -
Mind Your Value Judgements
Dec 19 20087:52 pm EDT -
S.E.C. Short-Sale Ban: Pretty Much Useless
Dec 19 20083:45 pm EDT -
Advice from Japan: Don't Forget TARP 1
Dec 19 20082:31 pm EDT -
Chart of the Day: Money Market Stress Easing
Dec 18 20088:57 pm EDT
Links
- Junk Charts

- Economic Principals

- New York Federal Reserve Research

- Sabernomics

- Statistical Modeling, Causal Inference, and Social Science

- Sabermetric Research

- St. Louis Fed Research

- Bluematter

- NBER Working Papers

- TierneyLab

- Numbers Guy

- Social Science Statistics Blog

- DataPoints: The Dismal Scientist Blog

- Institute for the Study of Labor

- Predictably/Irrational

- Decision Science News

- Research Recap

- Econbrowser

- Center for Economic Policy Research

- Economist's View

- B.I.S. Working Papers

- Geary Behaviour Centre

- Real Time Economics

- Federal Reserve Working Papers

- C.B.O. Director's Blog

- Curious Capitalist

- VoxEU

- Freakonomics

- Philadelphia Fed Research

- O.E.C.D. Factblog

- MoneyScience

- Journal of Interest

- STATS Blog

- Email me

- EconTalk

- EconPapers

- Marginal Revolution

- Tim Harford

- Jeff Frankel

- Institute for the Study of Labor

- Social Science Research Network

And the Winner Is...Prediction Markets!
There were three types of prognosticators that tried to forecast the outcome of year's elections:
Economic models - This group largely relies on economic variables like inflation and GDP growth to make its predictions. Examples here include models from Yale economist Ray Fair, Moody's Economy.com, and Macroeconomic Advisers.
Smart Polls - This group tried to control for a whole host of variables that could potentially introduce bias into individual polls (like gender, income, regions voting history, etc.) Big players here are FiveThirtyEight and Stochastic Democracy.
Prediction Markets - If you're reading this blog, I'm assuming you know what these are.
Before we take a look at how these three groups did last night, there are three caveats:
I'm ignoring probability distributions, margins of error, confidence intervals, standard errors and all that, and will only highlight the final raw numbers that the sources themselves advertised except in the case of the Iowa Electronic Markets where I pulled the vote-share number from Nov. 3rd's close.
As of the writing of this post, 97 percent of the total vote has been counted, so vote-shares may change. Post will be updated to reflect this.
I'm giving Missouri to McCain and North Carolina to Obama.
Here's a table that shows each source's prediction and how far off they were. Not everyone had predictions for both vote-share and electoral votes. For space reasons, only Obama is included:
Vote-Share Obama | Electoral Votes Obama | Vote-Share Error | Electoral Error | |
| Actual | 53.1 | 364 | -- | -- |
| BetFair | -- | 364 | -- | 0 |
| FiveThirtyEight | 53.1 | 349 | 0 | 15 |
| Intrade | -- | 364 | -- | 0 |
| I.E.M. | 53.5 | -- | 0.4 | -- |
| Macro. Advisers | 54.3 | -- | 1.2 | -- |
| Fair Model | 51.9 | -- | 1.2 | -- |
| Stochastic Democracy | 53.8 | 366 | 0.7 | 2 |
(Correction 1: I initially had FiveThirtyEight's vote-share number at 52.3%, but then realized that this included third-party votes, which is not what the Actual vote-share value reflects. That number is (Obama or McCain votes)/(Obama plus McCain votes). The other vote-share values are also in this form.)
(Correction 2: The folks at Stochastic Democracy wrote in to tell me that I had selected the wrong prediction for their electoral vote number. It's actually 366, not 353.)
By and large, everybody got the big picture correct. But Intrade and BetFair were right on the nose in the electoral college category while FiveThirtyEight was identically close in vote-share. So the original title of this post will have to change to It's a Tie! Coming in second was I.E.M. followed by Stochastic Democracy while the economic models pulled up the rear. (Which makes sense since economic models are handicapped by having to use older data.)
To reiterate, this isn't scientific and just for fun, so FiveThirtyEight doesn't have to eat its words just yet.






