Forecasting presidential elections
Download
1 / 53

FORECASTING PRESIDENTIAL ELECTIONS: - PowerPoint PPT Presentation


  • 196 Views
  • Updated On :

FORECASTING PRESIDENTIAL ELECTIONS . N. R. Miller POLI 423. 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

Related searches for FORECASTING PRESIDENTIAL ELECTIONS:

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'FORECASTING PRESIDENTIAL ELECTIONS:' - prosper


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

Forecasting election outcomes l.jpg
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 l.jpg
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 l.jpg
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 l.jpg
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 l.jpg
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.


Slide7 l.jpg

  • 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?


Slide9 l.jpg
2000 were held today, who would you vote for?”


Slide10 l.jpg
2004 were held today, who would you vote for?”


Slide11 l.jpg
2008 were held today, who would you vote for?”


Lichtman s keys to the white house l.jpg
Lichtman’s were held today, who would you vote for?”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.


Polling and survey research today17 l.jpg
Polling and Survey Research Today were held today, who would you vote for?”

  • 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 l.jpg
Polling and Survey Research Today (cont.) were held today, who would you vote for?”

  • 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 l.jpg
Predictive Models were held today, who would you vote for?”

  • 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.


Ps 1 problem 2 l.jpg
PS #1: Problem 2 were held today, who would you vote for?”

The predictive models constructed by Abramowitz, Fair, Lewis-Beck, and others all use information concerning (i) the performance of the economy and (ii) the popularity of the incumbent President (and perhaps other information) that is available long before the election in order to predict the percent of the popular vote received by the Presidential candidate of the party the controls the White House. (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.) Attached you will find data for economic performance and Presidential popularity for each Presidential election from 1948 through 2008, as well as the percent of the popular vote received by the incumbent party’s Presidential candidate for 1948-2008. Also find and fill in the data for “Streak” and “Electoral Votes.” Can you devise some kind of rule or formula based on this data to predict the percent of the popular vote won by the incumbent party candidate? According to your rule or formula, is President Obama likely to be re-elected?


Slide21 l.jpg

YEAR were held today, who would you vote for?” is the Presidential election year.

INC is 1 if the incumbent President is running for re-election; 0 if “open-seat” election.

GDP is real annualized GDP growth over the Fall, Winter, and Spring quarter preceding the election (e.g., from October 1, 2011 through June 30, 2012 (from U.S. Department of Commerce, Bureau of Economic Analysis, http://www.bea.gov/national/index.htm#gdp).

UNEMP is the Unemployment Rate in July preceding the election (from U.S. Department of Labor, Bureau of Labor Statistics, http://data.bls.gov/timeseries/LNS14000000).

ΔUN is the change in the Unemployment Rate from July of the year preceding the election to July of the election year.

STRK is “streak,” i.e., the number of consecutive elections won by the incumbent party

PRES is the incumbent President’s approval rating in the first Gallup Poll taken after June 30 of the election year (Gallup Reports and http://www.gallup.com/).

PV is the percent of the two-party (i.e., excluding Perot, Nader, etc.) popular vote won by the incumbent party candidate.

EV is the number of electoral votes won by the incumbent party candidate (including “faithless electors”). The total number of electoral votes was 531 prior to 1960, 537 in 1960, and 538 since 1960

* 39 electoral votes were cast for States Rights Democrat candidate J. Strom Thurmond

** 14 “unpledged” electoral votes were cast for Harry F. Byrd.

*** 45 electoral votes were cast for American Independent Party candidate George C. Wallace.


Summary statistics all elections excluding 2012 l.jpg
Summary Statistics: All Elections (excluding 2012) were held today, who would you vote for?”


Summary statistics incumbent vs open seat elections excluding 2012 l.jpg
Summary Statistics: Incumbent vs. were held today, who would you vote for?”Open-Seat Elections(excluding 2012)


Scattergram of pv by pres l.jpg
Scattergram of PV by PRES were held today, who would you vote for?”


Scattergram of pv by pres labelled by year l.jpg
Scattergram of PV by PRES were held today, who would you vote for?”(Labelled by YEAR)


Scattergram of pv by pres with regression line l.jpg
Scattergram of PV by PRES were held today, who would you vote for?”(with Regression Line)


Definition of regression line and r squared l.jpg
Definition of Regression Line and R Squared were held today, who would you vote for?”




Scattergram of pv by gdp l.jpg
Scattergram of PV by GDP Basis of PRES Only


Pres by gdp including 2012 l.jpg
PRES by GDP (including 2012) Basis of PRES Only




Pv by unemployment l.jpg
PV by Unemployment Basis of PRES Only


Pv by unemployment incumbent vs open seat elections l.jpg
PV by Unemployment: Basis of PRES Only Incumbent vs. Open-Seat Elections




Delta by unempl l.jpg
DELTA by UNEMPL Basis of PRES Only


Pv by delta incumbent vs open seat elections l.jpg
PV by DELTA: Basis of PRES OnlyIncumbent vs. Open-Seat Elections


Pv by streak l.jpg
PV by STREAK Basis of PRES Only


Pv by inc l.jpg
PV by INC Basis of PRES Only


Pv by gdp and pres and inc l.jpg
PV by GDP and PRES (and INC) Basis of PRES Only

  • Multiple Regression Equations:

    PV = 36.13 + 0.467 x GDP + 0.298 x PRES

    R² = 0.736; Adj. R² = 0.695

    2012: PV = 36.13 + 0.467 x 2.6 + 0.298 x 47 = 51.35

    PV = 35.48 + 0.439 x GDP + 0.278 x PRES + 2.48 x INC

    R² = 0.792; Adj. R² = 0.740

    2012: PV = 35.48 + 0.439 x 2.6 + 0.278 x 47 + 2.74 = 52.42

  • For comparison:

    PV = 36.12 + 0.337 x PRES 2012: 51.96

    PV = 47.45 + 1.18 x GDP 2012: PV = 52.52


A summary of predictions l.jpg
A Summary of Predictions Basis of PRES Only


Predictive models 2004 l.jpg
Predictive Models: 2004 Basis of PRES Only


Predictive models presented at apsa 2008 l.jpg
Predictive Models Presented at APSA 2008 Basis of PRES Only

Political ScientistPredicted 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 l.jpg
Predictive Models: 2012 Basis of PRES Only


Alan abramowitz 2012 l.jpg
Alan Abramowitz 2012 Basis of PRES Only

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.


Ev by pv l.jpg
EV by PV Basis of PRES Only



Devpc by dpv l.jpg
DEVPC by DPV Basis of PRES Only



Electoral maps 1956 vs 1984 l.jpg
Electoral Maps: 1956 vs. 1984 Basis of PRES Only


ad