POLS 207 Chapter 12
« previous | Sunday, November 29, 2012 | next »
Liberals v. Conservatives
Conservatives: (character fault of individual)
- Crime: some just drawn to crime, and those individuals are incarcerated
- Poverty: individuals fail to make effort to get a job; laziness
- More Efficiency and better performance
Liberals: (society's failure to provide needs; education fixes everything)
- Crime: Criminals are uneducated and poor; so better education and jobs will fix it
- Poverty: not enough jobs or not taught necessary skills to get job
- Redouble education and employment efforts
Education
Education has declined since 1970s. Math scores peaked recently (even better than 1970s, but verbal is still abysmal)
US has one of least centralized education systems in the world.
Measured by:
- % of population aged 25+ with HS completion
- % of population aged 25+ with bachelor's+ degree
Measurement includes time lag: we have to wait for current students to reach 25 yrs of age before data matters
- contemporary relationships are not proper relationships to study
Encourage educated people to move to state
Encourage uneducated people to leave
No Child Left Behind
- standardized test scores to evaluate schools
- financial incentives to schools for improving test scores and penalties for not improving
- students at poorly-performing schools may move to better-performing school
- decentralized choice is unchangeable principle
- permit inconsistent evaluation criteria and exemptions from evaluations
- insufficient funding from central government
- do not require funding threshold from local governments
Local schools: unfunded mandates
Conservative politicians: funding not always necessary for success and cannot guarantee success.
Poverty
Poverty rate drop from 1960 to 1969 (22% to 12%)
- Kennedy: "New Frontier"
- Johnson: "Great Society"
Consistently affects African-Americans and Hispanics more than Anglo or Asian.
In history, poverty has shifted:
- from older to younger;
- from those who paid taxes for a long time to those who haven't or can't
- from group with highest voter turnout to lowest turnout
Analysis
- Largest welfare program is Medicaid
- Next is SNAP (USDA Supplemental Nutrition Assistance Program)
- Then TANF (Temporary Assistance for Needy Families)
- Smallest is SCHIP (State Children's Health Insurance Program)
No time lag
TANF and Medicaid both have strong (negative) relationships with poverty levels.
Poverty does not cause welfare
Crime
Long-term trend is increase in crime rates; oscillates
Reforms tend to be undertaken only under federal court order.
Analysis
Implausible that state criminal justice expenditures or state incarceration causes state crime.
Can't find plausible factors or attributes that would make us think these relationships are spurious
Analysis
- strong negative correlation between HS completion and poverty
- correlations do not provide sufficient evidence of causal relationships.
- empirical linkages between poverty, crime, and education.
Multivariate
Relationships involving more than 2 vars.
- From a larger list of independent vars, smaller number provide "good fit" with dependent var.
- Assessment of how well combined vars fit with dependent variables
- Estimate of direction and relative importance and independent effects is presented
Report Impact of each independent variable controlling for the impact of other independent vars (indep. effects)
- Variance Explained
- Percentage of how well independent vars combined account for pattern of dependent var.
- Higher is better
Variables used:
- Per capita income
- Metropolitan pop.
- region (non-southern)
- self-identified liberal pop.
- self-identified Democrat pop.
- control of legislature by Democratic party
- major party competition in legislature
- turnout in governor election
- legislative professionalism
- governor's formal powers
Education
- HS completion
- % with bachelor's degree: strong positive
- Turnout in election: strong positive
- College
- per capita income: strong positive
Relationship may be mutually causal, but cannot conclude that income causes education.
Poverty Rate
Per capita income: strong negative (same as bivariate)
% state legislature controlled by Democrats: noteworthy positive
Medicaid are positively related (not negative as in bivariate)
Police and Justice Expenditure
% Liberal pop: strong positive
Metropolitan pop: noteworthy positive
May be equally or more related to population values, location, lifestyle
Summary
- Multivariate models explain large variance (77% to 88%)
- Only one to three vars are strong (out of several)
- No single var was consistently strong
- Per capita income: positively related to college, negatively related to poverty . . . could be causal relationships involved
- Governor election turnout: positively related to HS completion, not related to college, negatively to poverty . . . probably spurious
- Strong bivariate relationships are usually not strong in multivariate
Abortion
- Roe v. Wade (1972)
- woman's right to abortion fell under privacy protected by 14th Amendment
- Webster v. Reproductive Health Services (1989)
- States retained power to place restrictions on how abortions are provided
- States not obligated to provide services directly or financially support providers
Measured as number of abortions per 1000 women between ages 15–44.
Consistently declining since 1981
- pro-life
- restrict availability of abortions (during first trimester)
- reduce funding
- make abortions more difficult to perform and obtain
- pro-choice
- make abortion available to those who want it
- oppose efforts to make exercise more difficult
Abortion rate related to metropolitan pop: strong positive
restrictiveness related to % legislative control by democratic party: negative
Bivariate Analysis
Negative relationship between law restrictiveness and rates
HOWEVER
correlation between past and current abortion rates is very strong and positive:
- hard to see how changes in restrictiveness have affected rates
Scatterplots and correlations are insufficient to solve puzzle
Multivariate Analysis
Only self-identified liberal pop: strong positive
Restrictiveness not strongly related when other factors are controlled.
Policy and rates are not merely and directly related to each other
Conclusion
Different measures of same data will produce completely different results
Those who want to find empirical relationships to support beliefs can do so without difficulty.
Problems:
- Sought info is not always available
- Irregular schedule for data availability
- Time lag
Findings:
- Government are reactive, not proactive, about crime
- greater crime rates :: greater incarceration rates
- greater violent crimes :: more spent on criminal justice
- States with more restrictive abortion laws have lower abortion rates
Correlations do not prove causal relationships: doesn't prove liberals are right
Multivariate: factors other than spending had greater impact:
- throwing money at problem is sometimes necessary to improve things, but rarely (if ever) sufficient to do so