Predicting Presidential Elections Two Common (Empirical) Approaches: Fundamentals Presidential Approval Rates Unemployment Rates GDP Growth Polls Horserace polls in the leadup to election … or both at the same time

Fundamentals Prediction Strategy: Common Indicators: Analyze relationship between one or many indicators and past electoral performance Use this relationship to predict current outcome based on the same indicators Common Indicators: Presidential Approval Rate at time of election GDP Growth Rate, Unemployment Rate, Consumer Sentiment, and other Economic Indicators Consecutive Terms by Incumbent Party (Three consecutive terms by one party has been rare)

Strengths and Weaknesses of Fundamentals Strengths: Captures recurring patterns; can predict well in advance of the election; cuts away punditry and “spin” Weaknesses: Ignores any election-specific facts; Nothing about the candidates or their policies is included in analysis

(Simplistic) Example: Presidential Approval Inputs: Last Gallup Approval Rating of incumbent president before Election Day and incumbent’s party’s two-party vote share in that year’s election Data begin in 1948 with the advent of recurring scientific polling on presidential approval

(Simplistic) Example: Presidential Approval Result: Expectation is that Hillary Clinton would win because of President Obama’s 54% Approval Rate Errors large enough to change that result have happened (1960, 2000) and look fairly similar: reasonably popular two-term president leaving office and their party’s next candidate (Nixon, Gore) fails to win a third term. More sophisticated analyses that use multiple indicators imply that the election should be close, with either Clinton or Trump slightly favored depending on the combination of variables. There is no “Trump” variable.

Polling Prediction Strategy: Ask voters who they plan to vote for! Not so simple...

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Polling Prediction Strategy: Ask voters who they plan to vote for Average (or aggregate) the results of those polls Estimate uncertainty in the averages and simulate outcomes to determine the likelihood of results of interest

Strengths and Weaknesses of Polling Strengths: Captures election-specific information, including voters’ evaluations of the candidates; fundamentals are presumably “baked into” polls; reasonably predictive of results Weaknesses: Polling is highly inexact and prone to error; many assumptions are necessary to construct a single poll, many more to aggregate them; aggregation of polls will not neutralize errors if many pollsters make the same incorrect assumptions; Fewer than 10% of those called for a poll answer the questions, creating selection effects Note the many recent failings of polling: the 2015 British Elections, the 2016 “Brexit” Referendum, the 2015 Israeli Election, the 2016 Democratic Primary in Michigan

(Simplistic Example): Polling Inputs: Last ten national polls of Clinton v. Trump, converted to two- party vote share. Outlet Clinton Trump Clinton 2-Party LA Times 43% 47% 47.8% ABC 49% 51.0% IBD 45% 51.1% 44% 46% 48.9% 41% 52.9% 50% 52.6% Economist 51.6% FOX News 52.7% Pew 53.8% 51% 54.3% AVERAGE 47.6% 44.5% 51.7%

(Simplistic Example): Polling Now, make a simplistic assumption about uncertainty to simulate the national popular vote:

(Simplistic Example): Polling Can also analyze at the state level. Here’s Florida: Outlet Clinton Trump Clinton 2-Party Remington 44% 48% 47.8% NY Times 42% 46% 47.7% Emerson 45% 50.5% NBC 50.6% Dixie Gravis 47% Bloomberg 43% 48.9% Florida Atlantic U 51.7% U of North Florida 39% 52.4% Bay News 9 51.6% AVERAGE 44.7% 44.8% 50.0%

(Simplistic Example): Polling Florida simulated:

(Simplistic Example): Polling The winner is determined by the Electoral College, so state expectations can be combined. For example: 49.5% chance for Clinton in Florida 60% chance for Clinton in North Carolina What is the probability she wins both? .297 Neither? .202 At least one? 0.501 This calculation can be carried through for all 50 states (plus DC) to produce estimates for how often Clinton would accumulate the necessary 270 Electors to win.

Non-Simplistic Examples: 538, New York Times’s The Upshot, Huffington Post’s Pollster, and others These can also take into account the “fundamentals.” They can do more sophisticated corrections, weighting polls based on quality and past predictive power They also recognize that errors are likely correlated (if Clinton underperforms in Ohio, she is also likely to underperform in Iowa)

538 as of Monday