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Predicting Elections

adapted and updated from a feature on ABC News’ Nightline.

In 2012 Barack Obama and

Mitt Romney ran for President.

All the TV networks and both

campaigns knew by 3pm Central

Time that Obama had won the

election.

In 2008 Barack Obama and John

McCain ran for President.

All the TV networks and both

campaigns knew by 11:00am

Central Time that Obama had

won the election.

In 2004 George W. Bush ran

against John Kerry for President.

All the TV networks and both

campaigns knew by 4:00pm

Central Time that Bush had won

the election.

In 1996 Bill Clinton and Bob Dole

ran for President.

All the TV networks and both

campaigns knew by noon Central

Time that Clinton had won the

election.

In every election, the networks wait to

broadcast this information until 8pm

Central Time, when polls in the

majority of states have closed.

In every election since 1964—

except for 2000—the networks knew

the outcome before the time the

evening news was broadcast.

Why is it that TV networks are almost always right when they predict elections?

1. They are careful to take a large,

good sample

In most election years,

the networks pool their

resources to take a

stratified random

sample of as many as

10,000 voters.

After the problems in 2000, they have

surveyed 40 – 50,000 people each

election.

2. They repeatedly poll each

state before the election,

looking for consistency in

the results. They use the

results to pre-sort states by

how they expect them to

vote (red vs. blue).

Pre-sorting lets them put most

resources into “toss-up” states (like

Iowa) that could go either way.

3. They compute an estimate of each

candidate’s percentage of the vote,

including a margin of error, and

only call states where the victory

margin victory exceeds the margin

of error.

EXAMPLE

Poll says the Republican

will win South Dakota with

58% + 3%

The Republican will

probably get somewhere

between 55% and 61%

Call South Dakota for

the Republican.

EXAMPLE

Poll says Democrat will win

Nevada with 51% + 3%

The Democrat could get

anywhere between

48% and 54%

Nevada is too close to call.

4. The mathematics of statistics

gives them confidence that

their results will be correct

between 95 and 99% of the

time.

How it’s Done

Forecasting Election Outcomes

• Let us consider how — and how accurately and how far in advance — the outcome of Presidential elections can be predicted.

• We need to distinguish between • short-term forecasts (made shortly before the Presidential election), and • long-term forecasts (made at the outset of the general election

campaign or even earlier). • We will consider three types of forecasts:

• pre-election polls and surveys; • a more or less qualitative scoring method; and • predictive models based on long-term patterns in aggregate data.

Pre-Election Polls

• In the relatively distant past, pre-election polls taken even shortly before election day have sometimes been disastrously and famously wrong — most notably • a Literary Digest poll predicted the defeat of President Roosevelt in 1936, and • the Gallup Poll (and almost all other polls) predicted the defeat of President

Truman in 1948.

The Literary Digest Polls

• The Literary Digest collected from telephone companies and state motor vehicle departments lists with the names and addresses of telephone subscribers and registered automobile owners.

• The magazine then mailed out many millions of “sample ballots” to these names and addresses.

• Many people did not respond, of course, but the Digest still received millions of ballots, on the basis of which it forecast the outcome of the election.

• This procedure was quite successful in predicting the Republican presidential victories in the 1920s and also Franklin Roosevelt’s victory in 1932.

• But in 1936 it predicted that President Roosevelt would be badly defeated for re-election by Alf Landon, when in fact he won in one of the greatest Presidential landslides of all time.

• Can you account for why the Literary Digest forecasts that had previously been successful failed so badly in 1936?

Gallup and Other Polls

in 1948

• Gallup (and other) polls still used quota sampling (rather than random sampling).

• There were relatively few polling organizations, each of which took relatively few polls.

• Gallup averaged together the results of their several most recent polls.

• Gallup stopped polling altogether about two weeks before the election.

• There were two third-party candidacies, support for which was hard to predict

• In the election itself, Truman ran relatively weakly in the Northeast but much more strongly in the farm belt and the West. • Hence the famous Chicago Tribune photo.

Polling and Survey Research Today

• Today most commercial and media polls) use well tested methodologies, • based on some variant of random sampling, and with

• considerable care going into the wording of the questions and their assembly into a questionnaire.

• Most such polls are very accurate, giving very similar estimates.

• However, all such polls are subject to sampling error, stated in terms of a margin of error of ± X% that depends largely on sample size.

• They are also subject to “house effects” pertaining to mode of interview, call-back procedures, various adjustments, and (especially) their “likely voter” screen.

• Pre-election polls ask something like “If the election were held today, who would you vote for?”

• Such polls taken many months in advance of an election bear no reliable relation to the actual outcome.

• Hence the question: why are American Presidential election campaign polls so variable [over time] when voters [in the aggregate] are so predictable?

2000

2004

2008

Lichtman’s Keys to the White

House

• Lichtman developed this system in 1981, in collaboration with Volodia Keilis-Borok, a [Soviet] world-renowned authority on the mathematics of prediction models.

• It presumes that presidential elections are primarily referenda on how well the party holding the White House has governed during its term, but taking account of more than economic performance.

• The Keys further presumes that “by default” the incumbent party (that controls the White House) wins unless six or more keys are false [turned against the incumbent]. • The keys gives specificity to this idea of how presidential elections

work, assessing the performance, strength, and unity of the party holding the White House to determine whether or not it has crossed the threshold that separates victory from defeat.

2008 2012 2016?

1. T F T F T F

2. T F T F T F

3. T F T F T F

4. T F T F T F

5. T F T F T F

6. T F T F T F

7. T F T F T F

8. T F T F T F

9. T F T F T F

10. T F T F T F

11. T F T F T F

12. T F T F T F

13. T F T F T F

Polling and Survey Research Today

• Today most commercial and media polls) use well tested methodologies, • based on some variant of random sampling, and with • considerable care going into the wording of the questions and their

assembly into a questionnaire.

• Most such polls are very accurate, giving very similar estimates.

• However, all such polls are subject to sampling error, stated in terms of a margin of error of ± X% that depends largely on sample size. • In general, the margin of error is inversely proportional to the

square root of sample size. • Margin of error = X%: if we took a great many random sample of

this size from the same population, 95% of them would come within ±X% points of the “true value” (population parameter).

Polling and Survey Research Today (cont.)

• Different polls are also subject to “house effects” pertaining to mode of interview, call-back procedures, various adjustments, and (especially) their “likely voter” screen.

• Poll averages/aggregates are more accurate than individual polls, e.g., Real Clear Politics Poll Average

• But all polls ask (literally or in effect): “If the election were held today, how would you vote?” • And voters may change their voting intentions.

• The claim of predictive models (e.g., Lichtman) is that they can predict how voters will vote (in the aggregate) better than voters can.

Predictive Models

• Forecasting models constructed by social scientists seek • to predict the percent of the popular votes received by

the Presidential candidate of the party the controls the White House, and

• to do this using information that is available well before the election (e.g., in mid-summer).

• All such models use information pertaining to • the recent performance of the economy, and • the recent popularity of the incumbent President

• The models differ with respect to the exact measures of economic performance and Presidential popularity that are used and with respect to what other variables [if any] are also used.

Predictive Models: 2004

Predictive Models Presented at APSA 2008

Political Scientist Predicted Obama Vote Brad Lockerbie 58% Thomas Holbrook 55.5% Alan Abramowitz 54.3% Christopher Wlezien 52.2% Alfred Cuzan 51.9% Helmut Norpoth 50.1% Michael Lewis-Beck 50.07% James Campbell Wait till Labor Day Department of Commerce has revised second-quarter growth from 1.9%

to 3.3%

Predictive Models: 2012

Alan Abramowitz 2012

PV = 47.3 + (.107*NETAPP) + (.541*Q2GDP) + (4.4*TERM1INC) • PV stands for the predicted share of the major party vote for the

party of the incumbent president; NETAPP stands for the incumbent president’s net approval rating (approval – disapproval) in the final Gallup Poll in June; Q2GDP stands for the annualized growth rate of real GDP in the second quarter of the election year; and TERM1INC stands for the presence or absence of a first-term incumbent in the race.

• In order to incorporate this polarization effect in the Time for Change Model, I added a new predictor (POLARIZATION) for elections since 1996.** The estimates for the revised model are as follows:

PV = 46.9 + (.105*NETAPP) + (.635*Q2GDP) + (5.22*TERM1INC) – (2.76*POLARIZATION) • **For elections since 1996, the polarization variable takes on the value 1 when there is

a first-term incumbent running or when the incumbent president has a net approval rating of greater than zero; it takes on the value -1 when there is not a first-term incumbent running and the incumbent president has a net approval rating of less than zero.

Model: Electoral Vote outcome as a factor of popular vote outcomes

EV by PV: Incumbents vs. Open Seat

Democratic Party vote Share:

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