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The Crystal Ball

The Crystal Ball. Forecasting Elections in the United States. I. Long-Term Forecasts: Can we do better than flipping a coin?. Elections have patterns: Winning streaks Streaks tend to be 2-4 elections long. C. The weighted coin flip model.

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The Crystal Ball

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  1. The Crystal Ball Forecasting Elections in the United States

  2. I. Long-Term Forecasts: Can we do better than flipping a coin? • Elections have patterns: Winning streaks • Streaks tend to be 2-4 elections long

  3. C. The weighted coin flip model 1. Best guess for Presidential elections years in advance

  4. 2. Performance: Better than flipping a coin…

  5. D. Congress • President’s party usually loses seats during midterms • More seats to defend = higher probability of losing seats (esp. in Senate -- outperform in 2010 and your seats in swing states will be difficult to hold in 2016). Dems outperformed in 2006: now have 23 seats to defend vs. only 10 for GOP.

  6. 3. Otherwise, bet on the incumbents

  7. II. Short-term forecasts • Opinion polls: How well do they predict elections?

  8. Accuracy Depends on Timing

  9. B. The Wisdom of Crowds 1. How often is the public right? (early Oct)

  10. 2. Electoral Stock Markets • You can “buy” stock in a candidate (real money futures contracts)  essentially a form of gambling • Theory: people who invest money have a huge stake in the outcome, so have incentives to weigh information carefully (invisible hand)

  11. Congress 2006: Blue (DH/DS) comes from behind Black (DH/RS) and Red (RH/RS)

  12. III. Statistical Models • Presidential Elections: Models attempt to predict popular vote share. Incumbent party vote share depends on… • Presidential Popularity: Job Approval • Economy: Real GDP Growth, Unemployment Rate, Personal Disposable Income • Incumbency: 4 years helps, 8 years hurts

  13. 2012 Prediction 2008

  14. III. Statistical Models • Presidential Elections: Models attempt to predict popular vote share. Incumbent party vote share depends on… • Presidential Popularity: Job Approval • Economy: Real GDP Growth, Unemployment Rate*, Personal Disposable Income • Incumbency: 4 years helps, 8 years hurts

  15. 2012 Prediction 08

  16. McCain 2008 Obama 2012 (projected from 1st two quarters) Bush 2004 Gore 2000

  17. III. Statistical Models • Presidential Election Variables: Models attempt to predict popular vote share. Incumbent party vote share depends on… • Presidential Popularity: Job Approval • Economy: Real GDP Growth, Unemployment Rate*, Personal Disposable Income • Incumbency: 4 years helps, 8 years hurts

  18. 2012 Prediction

  19. 4. Labor Day Polls: Good predictors of winner, poor predictors of vote share

  20. 5. What about race? • Lewis-Beck and Tien(2008) noted correlation between attitudes towards race and support for Obama in primaries • If same relationship held for general election, prediction of McCain share shifted from 42.4 to 49.9 (Actual = 46.5) • = some evidence of a racial effect (but should be reflected in polls)

  21. Lewis-Beck and Tien (2009): “We argue that the expected landslide did not materialize, because a portion of the electorate could not bring itself to vote for a black candidate. What portion? In our paper, we estimated that number, on net, at 11.5%. If we apply that correction to this current Obama forecast, we get 58.7 × 0.885 = 51.9 %. This estimate is very close to the two-party popular vote share that candidate Obama won.”

  22. Tien, Nadeau, and Lewis-Beck (2012) “Our evidence, drawn from an analysis comparable to that carried out for 2008, suggests Obama will pay a racial cost of three percentage points in popular vote share. In other words, his candidacy will experience a decrease in racial cost, if a small one. In 2008, this racial cost denied Obama a landslide victory. In the context of a closer election in 2012, this persistent racial cost, even smaller in size, could perhaps cost him his reelection.”

  23. 6. Catastrophe and the Limits to the Predictions • Most of the 2008 models performed poorly, consistently underestimating Obama support • Some authors argue the Wall Street meltdown was unforeseeable • But did it determine the race?

  24. Campbell (2012) claims it did:

  25. B. Presidential Election Models: Comparison Models overestimated incumbent % in ‘92, ‘96, ‘04, ‘08 and underestimated in ‘00

  26. C. Congressional Elections: Key Variables • Timing: President’s party tends to lose seats in midterms (worse for Democrats) • Exposure: How many seats are exposed? • House: Party has higher % of seats than historical average • Senate: Number of each party’s seats up for grabs • The referendum model: Presidential approval helps/harms incumbent party

  27. D. House seats: approval, growth, and timing

  28. House seat model performance

  29. E. Senate Seats: Exposure, Referendum, and Partisan Advantage

  30. F. Recent models: Taking the Electoral College into Account • National-level Congressional models use votes-to-seats curves • Models are essentially poll-based, although some add state-level economic data to polls • Examples: 538 and Princeton • Weaknesses: State polls are volatile, national economic data excluded, no control for incumbency effects

  31. IV. Do Campaigns Matter? Yes…but we still don’t know exactly how

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