‘The poll that matters is the one that happens on Election Day.’
Heather Wilson, a Republican Party leader
I was savouring a delightful pea – and – mint risotto at the U.S. Election Watch event hosted by the U.S. Embassy in Singapore last Wednesday. Held at one of those grand hotels, the event had an air of anticipation — everyone was buzzing about the U.S. presidential election results.
Around 6.40 pm, Donald Trump’s victory remarks streamed live from West Palm Beach, Florida, and the whole room broke out in applause.
Earlier that morning, my team and I’d given a talk titled “Why Trump 2.0 Might Be Good for Investors.” It drew a crowd full of questions.
They were fired up, wanting to know every possible outcome: Who’s likely to win? Is it Trump’s race to lose?
Could Kamala Harris ride her momentum to a win? What might a potential Trump comeback mean for the markets, China and beyond?
Politics wasn’t even my thing until a few years ago. Back in 2020, a well-funded foundation and a political party roped me and a couple of other specialists into an election forecasting project. It was new territory for me, but since then, I’ve had my eyes opened to how many people are suddenly invested in the math behind political headlines.
Predicting political outcomes, I’ve learned, is a far more hazardous profession than predicting a country’s stock market. But here we were, trying to do both: predicting the outcome of the elections and the resulting impact of the political and policy changes on the economy and financial markets.
Thankfully, the U.S. economy isn’t entirely at the mercy of Washington’s decisions. Increasingly, its economy has become technologically driven and industrially diversified with an exceptional entrepreneurial spirit. And if anyone understands this, it’s Goldman Sachs alumnus and U.S. Vice President – elect JD Vance.
With the most established Asian American business leaders craving this peek into the future, the spotlight was intensifying on a part of my specialty that isn’t especially well understood: the mathematical techniques used by election forecasters in their predictive models. This task is somewhat different from the polls that we’re all familiar with.
I want to lay out what matters more about election forecasting, some of the reasons their predictive models can yield such differences (like predicting better chances for Trump in some models and better chances for Harris in others) and what I think people should take note about forecasting and models so they don’t drive themselves crazy trying to game out the future over the next few weeks.
First, the difference between polling and forecasting (and predictive models) boils down to this: Polls only give you a snapshot of voter opinion at a particular moment. By contrast, election forecasters try to look ahead and assess the likelihood of a particular outcome.
Forecasters draw on those polls as they build a predictive model, into which they continually feed more polls and make adjustments (more on that below) to compute the chances of a given candidate winning.
So while a poll might have shown that Harris was ahead of Trump by two percentage points in a given state — e.g., 49 per cent to 47 per cent — a predictive model might have estimated that she won the presidency in 53 out of every 100 times the model was run.
Some forecasters’ models thought Trump was slightly favoured, some thought Harris was slightly favoured, and some saw the race as a true coin flip for either candidate. Just as I find polling to be often misunderstood, election forecasting is even more complicated, making it even more likely that the results of a forecast will be badly misinterpreted.
There are considerable debates about what election forecasters should take into account. Think of an election model like a recipe for chocolate chip cookies.
The goal is the same: produce the most accurate forecast of how an election will go (or produce the best chocolate chip cookie). However, how you get there can vary significantly; we have an analysts’ collection of 16 chocolate chip cookie recipes, some requiring sea salt and one with coconut sugar. In election forecasts, there’s the main ingredient, of course: polls.
Some forecasters believe that an election model should be driven entirely by the results of public opinion polls, arguing that such polls are the only real window into how voters might behave and votes are the only metric that matters in the end.
Some models might give more weight to polls with a track record of accuracy or polls conducted more recently. For instance, the poll my team ran last week held more sway in BlackRock’s model than an older poll from the newspapers but carried less weight than a new one from a university.
Other models include the equivalent of that sea salt or coconut sugar, taking into account factors like incumbency and the economy — sometimes I call it the fundamentals. This can get tricky, as you might imagine.
Typically, being an incumbent is considered an asset in an election, but what happens when the incumbent is unpopular and globally we are seeing incumbent politicians being ousted left and right? Or take the economy. Which is the best indicator of how the economy may affect the election? The website FiveThirtyEight used 11 economic indicators in its model.
Meanwhile, roughly 62 percent of voters in a recent poll said they thought the economy was bad. Ultimately, voters will cast their ballots, and a new president will be elected, regardless of what a forecast says.
This is where we see the gap between what people say and what they do — what’s known as the difference between expressed preferences and revealed preferences. If you go around and ask people whether they would willingly pay more tax to fund, say, excellent free education for all then the answer is pretty much an overwhelming yes.
Yet as the tax authorities of various countries have found when you collect those extra taxes, people are a great deal more reticent about handing over the cash. You don’t know how someone values something until they’ve got to put their money where their mouth is.
So, if people don’t always act on what they say, why bother with forecasting? In short, a forecast gives a window into how a campaign might assess the race and make choices about which strategy to deploy.
A campaign that is losing ground may need to make some major adjustments to get back on track, or a campaign that is surging may begin taking fewer risks so as not to squander its newfound advantage. Knowing who is up and who is down can help news consumers better understand why candidates and campaigns make the decisions they do.
Just as different pollsters use different methods to measure public opinion, the forecasters who use those poll results to make predictions are also using different ingredients to build their models. The solution for you, the savvy news consumer? Consume a wide variety. There’s no such thing as too many chocolate chip cookies — I mean, election models.
The views expressed here are those of the columnist and do not necessarily represent the views of Sarawak Tribune.
