Transcript How do voters decide? G. Michael Weiksner Stanford University April 2, 2008

How do voters decide?
Preliminary results from a field experiment
G. Michael Weiksner
Stanford University
April 2, 2008
Agenda
•
•
•
•
Why local primaries
Theory & Predictions
Methodology
Preliminary Results
– A short-term effect
– Why?
Why local primaries
• Not well understood
• In low information environment, information
treatment should have a larger impact
• Regularly occurring
– More opportunities to research
– Possibility to generalize to large class of elections
Theory & Predictions
• Dahl: “A person’s interest or good is whatever that person
would choose with fullest attainable understanding of the
experiences resulting from that choice and its most relevant
alternatives”
– Our information conditions are close to a practical operationalization
of “full-information” voting—does it make a difference? Are citizens
competent under better circumstances?
• Popkins: “Low information rationality,” or using heuristics or
shortcuts to the information to make decisions
– Information should reduce reliance on heuristics, like voting for the
candidate who shares my gender
Methodology
A Randomized Field Experiment
• Mundane realism: the subjects are in a realistic
setting
• Internal validity: causal inference appropriate
through random assignment
• Generalizable: ideally, random sampling
• Cheap & easy to administer
E.g., Iyengar’s MAPSS talk, 2/6/07 and Green’s talk
2/13/07
Methodology (cont’d)
Procedure
• Orlando primaries, Tues Sept. 5, 2006
– Orlando Sentinel uses theVoterGuide.org to collect candidate data on
22 races including Governor, Senate, Congress, non-partisan judges
• 514 participants recruited from online panel on Thurs Aug 31
– Skews towards more education, politically aware, male
– Randomly assigned to condition differing by kind and amount of
election information
– 307 participants responded to follow up survey (Sept 6-7)
• Surveyed on vote intentions, vote choice, attitudes and
general and campaign-specific knowledge
Research design
R X 1 O1
O2
R X 2 O1
R X 3 O1
R X 4 O1
O2
O2
O2
Party,
Vote Choice,
Attitudes,
Demographics
Turnout,
Vote Choice,
Bio & Issue
Knowledge,
Contact Information Only
Biographical
Information
Issue Information
Random Assignment
Condition
Contact
Information Only
Biographical
Information
Issue
information
All Information
T1 Vote Choice-Executive
Likelihood ratio test
Issue
Bio
Governor
0.024 *
0.732
FL Attorney General
0.047 *
0.134
FL Chief Financial Officer
0.046 *
0.683
Orange County Mayor
0.028 *
0.006 **
T1 Vote Choice-Legislative
Likelihood ratio test
Issue
Bio
US Senate
0.158
0.085
US Congress 5th
0.246
0.238
US Congress 8th
0.655
0.759
US Congress 15th
0.814
0.697
US Congress 24th
0.008**
0.313
Florida Senate - 8th
0.424
0.772
Florida house - 36
0.963
0.204
Florida House - 41
0.015*
0.072
T1 Vote Choice - Judicial
Likelihood ratio test
Issue
Bio
County Judge – 17
0.380
0.040 *
County Judge – 6
0.477
0.012 *
County Judge – 7
0.778
0.768
County Judge – 5
0.726
0.289
Circuit Judge 5th Group 7
0.027
0.124
Circuit Judge 9th Group 5
0.304
0.005 **
Circuit Judge 18thF
0.796
0.836
Reduce support for
the leading candidate?
n = 2,335 voter * races
Reduce gender-based voting?
n = 1,412 voter * races
Percent who vote for
candidate of same gender
0.62
0.61
0.60
0.59
0.58
0.56
0.54
Male
Female
0.52
0.51
0.51
0.50
0.48
0.46
No Biographical Information
Biographical Information
Summary of results
• No long –term effects
• Election information makes a difference in local primary vote
choice
– Issue information changes choices in many executive races
– Issue information changes some choices in legislative races
– Biographical information changes choices in judicial
• Some evidence that information affects vote choice through
gender
- No consistent story (yet?) for why issue information changes vote
choice
- Among males, biographical information reduces gender-based voting
- Among females, biographical information increases gender-based
voting
Parting thoughts…
• Memory aids are really important and interesting potential
impact of mail & internet voting
• What is the point of local primaries?
• Future research:
–
–
–
–
Can we replicate the gender results in a lab experiment?
How would these results differ in a general election?
Would deliberation make a difference?
What impact does social information (i.e., personal endorsements)
have?
– Would edited information make a difference?
– Does one-sided information make a difference?
Random Assignment (cont’d)
Age
N
Female
M
SD
Gen'l Political
Knowledge
M
SD
M
SD
No issue info
No Bio 133
Bio
124
47.9
48.1
14.4
14.4
0.368 0.484
0.339 0.475
0.882
0.866
0.193
0.203
Issue Info
No Bio
Bio
48.0
48.9
15.1
13.7
0.402 0.492
0.505 0.502
0.860
0.902
0.244
0.190
112
105
T2 Vote Choice
Likelihood ratio test
Issue
Likelihood ratio test
Bio
Issue
Bio
Governor
0.128
0.621
Attorney General
0.734
0.444
Cty Judge 17
0.664
0.087
CFO
0.567
0.570
Cty Judge 6
0.982
0.082
OC Mayor
0.691
0.307
Cty Judge 4
0.128
0.492
U.S. House 8Th
0.193
0.243
Cty Judge 5
0.781
0.206
U.S. House 13Th
0.144
0.581
Crct 5 Judge
0.139
0.092
U.S. House 24Th
0.259
0.994
Crct 9 Judge
0.780
0.148
State Senate 8
0.165
0.441
Crct 18 Judge
0.890
0.326
State House 41
0.083
0.253
T1 Results
Source
Issue Information
Endorsement Knowl. Item
Candidates on Issues
Biographical Information
Endorsement Knowl. Item
Candidates on Issues
Issue x Biographical Information
Endorsement Knowl. Item
Candidates on Issues
Error
Endorsement Knowl. Item
Candidates on Issues
df
F
Eta
p
1
1
3.385
8.666
0.082
0.130
0.066
0.003
1
1
22.310
1.391
0.205
0.052
0.000
0.239
1
1
0.349
0.367
0.026
0.027
0.555
0.545
506
506
0.170
0.055
T1 Vote Choice – Governor
Issue Information
No
Yes
Democrats
Carol Castagnero
Glenn Burkett
Jim Davis
John M. Crotty
Rod Smith
Republicans
Charlie Crist
Michael W. St. J
Tom Gallagher
Vernon Palmer
Likelihood ratio test
Bio Information
No
Yes
1.4
1.8
22
2.9
11.9
0.8
1.7
21.1
0.4
17.3
1.2
1.2
20.8
1.9
12.4
1.2
2.4
22.4
1.6
16.5
36.1
1.1
11.9
1.8
29.5
0.4
11.4
0.4
35.9
0.8
10.4
1.5
30.2
0.8
12.9
0.8
.024 *
.732
T1 Results
N
Endorsement
Knowledge Item
M
SD
Understand
candidates on the
issues
M
SD
No Issue Info
No Bio Info
139
0.165
0.373
0.268
0.168
Bio Info
136
0.360
0.482
0.305
0.188
No Bio Info
117
0.120
0.326
0.342
0.204
Bio Info
118
0.271
0.446
0.354
0.191
Issue Info
T2 Turnout, Knowledge
N
T2 Turnout
T2 Issue
Knowledge
M
M
SD
SD
T2 Biographical
Knowledge
M
SD
No issue info
No Bio Info
90
64.4
48.1
0.157 0.217
0.419
0.351
Bio Info
76
61.8
48.9
0.202
0.23
0.482
0.320
No Bio Info
66
63.6
48.5
0.25 0.251
0.523
0.327
Bio Info
74
64.8
48.1
0.207 0.221
0.421
0.346
Issue Info