Presidential models, mainly in the near-term elections, have been the norm since 2000. This year, Joe Biden has occasionally been on the radar of 400 electoral votes, which we haven’t ever seen since Bill Clinton or George HW Bush. In addition, races to the US Senate and the legislative states are of paramount importance. So we spent less time on the presidential race.
But today, let’s dive in presidential model a little. It is revised to take into account lessons from 2016. In this section we’ll tell you Joe Biden’s November probability of winning – but also why we’re emphasizing it.
At its core, the PEC Presidential model is the same as it was in 2012 and 2016. It starts with snapshots of current polls, transforming them into a virtual lead in the Electoral College. That virtual lead, corresponding to popular support, is called Meta-margin. The race will have to rotate much to the bottom to create a perfect electoral election topple. Meta-Margin is a sharp measure of the timely response and low noise to political events. One example is Trump’s response to the coronavirus pandemic in mid-April.
To make a prediction, the Meta-margin is projected forward in time by assuming drift in either direction. That assumption takes the form of a distribution that captures (1) the opinion movement in either direction, (2) a systematic error, which correlates polling on all state and (3) the likelihood that conditions will return to the expected average (Bayesian “before”). Bayesian previously assumed that Trump was likely to perform within the range he had from February so far, in other words, slightly better than current conditions.
In response to 2016, we changed the drift function. For time scales greater than two months, the difference is set smaller because the volatility in public opinion has been greatly reduced since the mid-1990s. But more importantly, during the main campaign period , the drift function is never less than two percentage points. This takes into account the voting error of some points that happened in 2016.
Here’s what the drift function looks like in 2016 versus now:
As you can see, it now has a pieced together view. But for what we need, a “hurricane strike zone” in November, it will do.
The red “storm strike zone” represents the one-sigma range, where about two-thirds of the result will decrease. The yellow color represents two sigma, or 95% of the results.
The new drift function will give Hillary Clinton around 80% probability of winning in 2016 the night before the election, as opposed to what we announced at home, 93%.
With the new increased uncertainty, the probability of a random drift now indicates a high probability of winning for Biden. If you want to track it, it’s in the data directory. The Bayesian probability, higher, is the first value. However, these probabilities do not affect factors exogenous to the polls, such as difficulty in mail voting. They are also not what I consider the main product of the model. I highly recommend you think twice before focusing on it.
as i wrote in the aftermath of the 2016 election and again in Columbia Newspapers Magazine, probabilities are the wrong metric for 2020. They encourage complacency rather than positive citizenship. And more than ever, now is the time for active citizenship.
Instead, we are emphasizing Meta-margin. At 6.4 points in favor of Biden, this means returns will have to change, or be much wrong to facilitate a flip-flop between Biden and Trump. This number is more than double the error in the 2016 poll.
More important than Meta-margin is the power of voters. We are emphasizing voters’ power over three important types of racing: the presidential race, the US Senate race, and the state legislative race. Voter power is defined as the ability of one or a small group of voters to move the probability of one of three important questions:
Chairman: provides tipping point assistance to bring Biden or Trump above 270 EV.
The US Senate: provides critical support for 50 Democratic seats plus independent seats.
State legislature: provides tipping point support to gain control of a department of the state legislature, in states that would result in bipartisan control over redistricting.
In any case, the power of the voter tells you where to work as a citizen. That’s what we are calling the “Moneyball 2020” approach.
To this day, the states with the highest power per voter are:
Chairman: Nevada, Arizona, North Carolina.
The US Senate: Montana, Alaska, South Carolina, Kansas.
State legislature: Kansas, Texas, North Carolina.
The states listed more than once are in italicized.
Voters in North Carolina this year have been particularly strong. That shouldn’t come as a surprise, as North Carolina is a regular battleground for parties. But there were also a few surprises: Montana, Texas, and most of all, Kansas.
Over the next few weeks, we’ll dive into a few states and explain why they are so important.
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