As the presidential race finishes out the last two weeks, it’s clearly a close race. In the past I have recommended prediction markets, and right now these are giving Trump about 60% odds. There have been lately a few big bettors coming into the markets and primarily betting on Trump, so there has been speculation of manipulation, but even at 60-40 the race is pretty close to a toss-up.
Another tool many use to follow the election are prediction models, which usually incorporate polling data plus other information (such as economic conditions or even prediction markets themselves). One of the more well-known prediction models is from Nate Silver, who right now has the race pretty close to 50-50 (Trump is slightly ahead and has been rising recently).
But Silver’s model, and many like it, is likely very complicated and we don’t know what’s actually going into it (mostly polls, and he does tell us the relative importance of each, but the exact model is his trade secret). I think those models are useful and interesting to watch, but I actually prefer a much simpler model: Ray Fair’s President and House Vote-Share Models.
The model is simple and totally transparent. It uses just three variables, all of which come from the BEA GDP report, and focuses on economic growth and inflation (there are some dummy variables for things like incumbency advantage). Ray Fair even gives you a version of the model online, which you can play with yourself. Because the model uses data from the GDP report, we still have one more quarter of data (releasing next week), and there may be revisions to the data. So you can play with it (and one of the variables uses the 3 most recent quarters of growth), but mostly these numbers won’t change very much.
Ray Fair at Yale runs one of the oldest models to use economic data to predict US election results. It predicts vote shares for President and the US House as a function of real GDP growth during the election year, inflation over the incumbent president’s term, and the number of quarters with rapid real GDP growth (over 3.2%) during the president’s term.
Currently his model predicts a 49.28 Democratic share of the two-party vote for President, and a 47.26 Democratic share for the House. This will change once Q3 GDP results are released on October 30th, probably with a slight bump for the dems since Q3 GDP growth is predicted to be 2.5%, but these should be close to the final prediction. Will it be correct?
Probably not; it has been directionally wrong several times, most recently over-estimating Trump’s vote share by 3.4% in 2020. But is there a better economic model? Perhaps we should consider other economic variables (Nate Silver had a good piece on this back in 2011), or weight these variables differently. Its hard to say given the small sample of US national elections we have to work with and the potential for over-fitting models.
But one obvious improvement to me is to change what we are trying to estimate. Presidential elections in the US aren’t determined by the national vote share, but by the electoral college. Why not model the vote share in swing states instead?
Doing this well would make for a good political science or economics paper. I’m not going to do a full workup just for a blog post, but I will note that the Bureau of Economic Analysis just released the last state GDP numbers that they will prior to the election:
Mostly this strikes me as a good map for Harris, with every swing state except Nevada seeing GDP growth above the national average of 3.0%. Of course, this is just the most recent quarter; older data matters too. Here’s real GDP growth over the past year (not per capita, since that is harder to get, though it likely matters more):
Region
Real GDP Growth Q2 2023 – Q2 2024
US
3.0%
Arizona
2.6%
Georgia
3.5%
Michigan
2.0%
Nevada
3.4%
North Carolina
4.4%
Pennsylvania
2.5%
Wisconsin
3.3%
Still a better map for Harris, though closer this time, with 4 of 7 swing states showing growth above the national average. I say this assuming as Fair does that the candidate from the incumbent President’s party is the one that will get the credit/blame for economic conditions. But for states I think it is an open question to what extent people assign credit/blame to the incumbent Governor’s party as opposed to the President. Georgia and Nevada currently have Republican governors.
Overall I see this as one more set of indicators that showing an election that is very close, but slightly favoring Harris. Just like prediction markets (Harris currently at a 50% chance on Polymarket, 55% on PredictIt) and forecasts based mainly on polls (Nate Silver at 55%, Split Ticket at 56%, The Economist / Andrew Gelman at 60%). Some of these forecasts also include national economic data:
Gelman suggests that the economy won’t matter much this time:
We found that these economic metrics only seemed to affect voter behaviour when incumbents were running for re-election, suggesting that term-limited presidents do not bequeath their economic legacies to their parties’ heirs apparent. Moreover, the magnitude of this effect has shrunk in recent years because the electorate has become more polarised, meaning that there are fewer “swing voters” whose decisions are influenced by economic conditions.
But while the economy is only one factor, I do think it still matters, and that forecasters have been underrating state economic data, especially given that in two of the last 6 Presidential elections the electoral college winner lost the national popular vote. I look forward to seeing more serious research on this topic.
Economist Writing Every Day 