red vs. blue? the personal and geographic bases of cleavages
TRANSCRIPT
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Red vs. Blue?
The personal and geographic bases of cleavages
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The map that started it all, 2000
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I. Overview of Fiorina
A. The “Red vs. Blue” story1. 50/50 Nation: Americans are split down the
middle into Red (pro-Republican) and Blue (pro-Democrat) voters
2. Polarization: The Red/Blue divide has been growing over time
3. Geographic Divide: Red America is a very different place than Blue America
4. Partisanship: Partisan bickering has been on the increase
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B. Fiorina’s Contribution
1. 50/50 Nation: Fiorina agrees
2. Polarization: Fiorina disagrees
3. Geographic Divide: Fiorina disagrees
4. Partisanship: Fiorina distinguishes between elite-driven and mass-driven partisanship, argues that elite polarization produces partisan discord among voters
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C. Unanswered Questions
1. Why do some people identify as Republican while others identify as Democrat?
2. Are there regional divides aside from the mythical Red/Blue one?
3. Is elite partisanship increasing?
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II. The Individual Divide
What causes people to support one party instead of the other?
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A. Intergenerational Effect
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B. Race and Ethnicity
If you can pick one characteristic about a person and then predict their own party identification, ask about race and ethnicity: better predictor than age, sex, income, education, geography, etc.
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1. Racial Dividea. About 90% of African-Americans Vote Democratic
‘04
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b. Race Trumps Rural Issues: Rural Counties by Race/Ethnicity
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County Map of 2004 Results
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c. Race trumps gender, age, and income
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2. The Ethnic Divide: Latinosa. Latinos favor Democrats
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b. Need to control for registration: large differences
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c. Latinos are diverse: Country of Origin Effects
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d. Effects of income, education, and residency
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e. Immigration attitudes cross party lines
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3. Asian-Americans: Pro-Democrat
a. Similarities to Latino vote:Majority too young or noncitizensCountry of origin effectsImportance of immigration and language
issuesDecreasing Democratic advantage? Mixed
results due to small sample sizes
b. Election 2004: Asian-Americans vote for Kerry by 3:1 margin
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4. Native Americans: Pro-Democrat
No exit polling data – findings based on geographic comparisons
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Native American Counties
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County Map of 2004 Results
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C. Income: Better predictor since 1980s
2004 Exit Polls: Overall Income %R %D
<$15K 36% 63% $15-30K 41% 58% $30-50K 48% 51% $50-75K 55% 44% $75-100K 53% 46% $100-150K 56% 43% $150-200K 57% 43% >$200K 62% 37%
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1. Effect is not an artifact of race-class connection
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2. Inequality has polarized parties
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D. Religiosity Fiorina: Salience of religion better predictor than denomination
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E. The Gender Gap
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1. Early gap was race-based, but recent increase is not
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2. Fiorina’s Explanation
Women more dovish on security Women more pro-government on
social programs Since 1970s Democrats have been
both more dovish and more pro-government on social programs gender gap
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3. Puzzle: Regional variation in the gender gap
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F. Population Density
1. Urban areas trend Democratic, Rural areas trend Republican
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a. Election 2004: County Map of 2004 Results
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County Map of Population Density: Republicans Win Most Rural Counties
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b. Shift in Rural Partisanship: Rural support for Republicans (Blue) and Democrats (Red)
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c. Rural/Urban Voters Have Similar Priorities…
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d. …But Different Ideologies
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e. Two Core Divisions: Religion and Guns
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f. Rural Voters Reverse the “Gender Gap”
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2. The suburban majority: Voting splits on North/South lines
Suburbs split 50-50 in 2000, 53-47 in 2004
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G. Age
1. Democrats do well among the very young and the old
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G. Age
1. Democrats do well among the very young and the old
2. But young are most likely to be independents
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3. Gender outweighs age
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H. Education? Little effect…
Education appears to increase Republican ID, but.. Education increases income, which may be
responsible Controlling for income results in no effect or
even pro-Democratic shift Very high levels of education (PhD)
dramatically increase Democratic ID Education does tend to bring party ID in line
with professed ideology
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I. Conclusions About Party ID
Republican Self-
Identification
White Race
Anglo Ethnicity
Republican Parents
Male
Highly Religious
Rural
Age 25-40
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III. Regional Divides?A. Voting History
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B. General Political Regions
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1. West Coast
Stereotype: Wealthy, elite liberalism.
Reality: Elite liberal coalition with Latinos
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2. Rocky Mountains
Libertarian Conservatives: No
Taxes, No Government Regulation
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3. Great Plains
Religious Conservatism But Economic
Populism
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4. Great Lakes
In transition from
Blue-Collar (Economically Liberal, Socially Conservative)
to
Suburban (Economically Conservative, Socially
Moderate)
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Map of Industrialization – Great Lakes = Old Industry
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5. Northeast
Big-Government Liberalism: Both
Social and Economic
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a. Sex Ed: Cultural Liberalism in the Northeast
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b. Liberal Crime Policy: Northeast and Victims’ Rights
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c. Values: Women’s Age at First Marriage (Darkest = 27+)
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6. The South
States Rights and Limited
Welfare
but
Big-Government Conservatism (Pro-Business)
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a. North-South Divide: Origins
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b. The Southern Shift: 1950-1980
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Wallace for President 1968
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c. Southern uniqueness todayi. The “Bible Belt”
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Southern Religious Homogeneity
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ii. High poverty, Low welfare
Poverty Rates 2004: Darker = Higher Rate
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% Households Receiving Cash Welfare
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Medicaid Eligibility by State
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iii. Still lower education
Percent Completed High School or GED By Age 25
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iv. Hard-line anti-crime policy
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Example of Southern Uniqueness: Execution of Juveniles (2004)
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7. Summary: Alignments
Exception to Region
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C. How stable and homogenous are these regions?
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1. Abortion: Legal everywhere, but laws differ…
“Partial Birth” Abortion Bans
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2. Alternate Family Structures: Gay Adoption Banned (Blue) or Allowed (Orange)
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3. Crime Policy: Imprisonment Rates
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4. Economic Issues: Right to Work
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5. Liberty vs. Safety: Gun Control
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6. Multiculturalism: “English Only” Laws
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D. What underlies the regional divide?
1. Smaller cultural regions?
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2. Patterns of Issue Salience?
Many regions have multiple loyalties (opportunities for change or new regional divides). Possible examples:Rockies values low taxes over less social
regulationGreat Lakes values economic
performance/policy over social issuesGreat Plains values religiosity over economic
populism
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IV. Is Elite Partisanship Increasing?
A. Introducing NOMINATE scores: An unbiased method for measuring political differences
1. Assumption 1: Political decisions are connected – position on one issue helps to predict position on other issues
2. Assumption 2: Whatever connects issue positions is a continuum, so we can rank people on this underlying dimension
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B. Voting based on an ideological continuum
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C. Finding the underlying dimension: An example
A B C D
Jose Y Y N Y
Keisha Y N N N
Pat N Y Y Y
Three legislators, four bills (A through D). What rank-
ordering best explains
these voting patterns?
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1. Rank-Order the legislators
A B C D
Jose Y Y N Y
Keisha Y N N N
Pat N Y Y Y
Options:JKPJPKKJPKPJPJKPKJ
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1. Rank-Order the legislators
A B C D
Jose Y Y N Y
Keisha Y N N N
Pat N Y Y Y
Options:JKPJPKKJPKPJPJKPKJ
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1. Rank-Order the legislators
A B C D
Jose Y Y N Y
Keisha Y N N N
Pat N Y Y Y
Options:JKPJPKKJP
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2. Rank-Order the Bills
A B C D
Jose Y Y N Y
Keisha Y N N N
Pat N Y Y Y
Options:ABCDABDCACBDACDBADBCADCBBACDBADCBCADBDACCABDCBAD
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3. Evaluate the Rank-Orderings to Predict Votes
Iss. Rank JKP JPK KJPABCD
ABDC
ACBD
ACDB
ADBC
ADCB
BACD
BADC
BCAD
BDAC
CABD
CBAD
A B C D
J Y Y N Y
K Y N N N
P N Y Y Y
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a. Check each combination
A B C D
J Y Y N Y
K Y N N N
P N Y Y Y
First combination to check: JKP and ABCDJ K P
A B C D
Implications: J more likely to vote for A than K 0J more likely to vote for A than P 1K more likely to vote for C than J 0K more likely to vote for D than J -1K more likely to vote for A than P 1K more likely to vote for B than P -1P more likely to vote for D than K 1P more likely to vote for D than J 0
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b. Now re-check with different policy positions
A B C D
J Y Y N Y
K Y N N N
P N Y Y Y
First combination to check: JKP and ABCDJ K P
ABC DA BC DA BCDA B CD
Etc…
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c. Repeat for every possible combination
NOMINATE scores generated using a supercomputer
Note that none of the possible orderings is likely to be correct all of the time, given dozens or hundreds of legislators and bills (all roll-call votes in which 2.5% or more disagree)
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4. Which combination performs best?
Iss. Rank JKP JPK KJPABCD 17 7 4
ABDC 23 11 -2
ACBD 11 -2 12
ACDB -5 0 17
ADBC 14 9 13
ADCB 9 12 9
BACD 4 17 22
BADC 2 6 26
BCAD 13 11 2
BDAC 19 -2 21
CABD 21 21 -4
CBAD -1 24 13
Possible Implication:
K loves B and hates C, while P loves C and
hates B. Everyone and
everything else is moderate.
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5. Now suppose there are multiple dimensions….
Examples: Social freedom vs Economic freedom International cooperation and international militancy All of the above (4 dimensions!)
Authors find one or two dimensions are all that is needed: Currently just one (liberal vs. conservative). Very high (.81) correlation with hand-coded scores of
liberalism vs. conservatism – the computer found something that matches our understanding!
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5. Now suppose there are multiple dimensions….
Examples: Social freedom vs Economic freedom International cooperation and international militancy All of the above (4 dimensions!)
Authors find one or two dimensions are all that is needed: Currently just one (liberal vs. conservative). Very high (.81) correlation with hand-coded scores of
liberalism vs. conservatism – the computer found something that matches our understanding!
Sometimes a second dimension (Regionalism: North-South power balance, bimetalism/free silver, civil rights)
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Example: 91st House (1969-70)O
ppos
ition
to
Civ
il R
ight
s
Conservatism
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B. What can NOMINATE tell us about polarization?
1. Whether there are two dimensions or one: Is the liberal-conservative continuum a good way to categorize politicians?
2. How far apart each party’s legislators are from each other (party unity)
3. How far apart one party’s legislators are from the other party’s legislators (polarization)
4. Whether the parties have dramatically changed (realignment)
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Video: Plotting NOMINATE scores over time by Party
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C. Further Evidence of Party Polarization
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D. Explaining party polarization
1. Mass polarization? Fiorina says no.
2. Politicians becoming more extreme? Self-defeating to move away from median voter
3. Hypothesis: Party activists have become more extreme
a. Explains lack of mass shift
b. Also explains elite shift – activists are key to candidate success and are known to be more extreme than either the public or candidates themselves!
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4. Evidence: Activist polarization
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V. Assessing Red vs. BlueA. The regional divide(s):
1. Fiorina: “Red America” and “Blue America” are myths2. Regional divides do exist, with important differences
between regions3. Regions are not monolithic; even within regions there are
important differences4. Smaller regions = more accuracy but less parsimony
(choice of six regions seems to balance these concerns)B. Party Strength:
1. Fiorina: Parties about equal -- closely divided2. Party ID: Demographic and personal factors alter party
strength over timeC. Polarization:
1. Fiorina: Low public polarization – not deeply divided2. NOMINATE: High elite polarization on one dimension3. Best explanation: Nomination system has drawn in
extreme “issue activists” who have pulled parties apart