Per Capita State and Local Nontax revenue and Total Revenue – Nontax revenue is where the state gains money from nontax sources. These are things such as gun licenses, college tuition and fees, library membership, speeding fines. They are not taxes but they make money for the local government. The relationship between the two is positive (r = .94), so the more nontax revenue there is, the greater the total revenue will be. Many states have high nontax revenue – Texas is one of these. This means that tax rates are actually quite low, because the revenue comes from other fees for services that the public wants.Per Capita State and Local Revenue and Expenditure – Strong positive relationship (r = .83). This means that the higher a states revenue is, the more they will spend on services.States with older populations need more spending on services – emergency services, healthcare etc.States with an older population will have a lower population of children. There is a negative relationship between these two variables (r = -.75). Texas has about 25% of its population between 5-17 and 10% of it’s population over 65 years. There is extremely close to the regression line. States such as Florida have a high population of people over 65 years and only about 15% of the population is school age children.Per Capita Income and Poverty 2010 – moderate negative relationship between the two variables (r = -.61). If per capita income increases, the amount of those in poverty decreases. Connecticut have a high per capita income and a low poverty rate, they are on the regression line. Texas is an outlier, although the per capita income is fairly high, the poverty rate is higher than it should be, as predicted. Mississippi has a low per capita income and an extremely high poverty rate (around 25%). Utah is a good outlier because it has a lower per capita income but also a low rate of poverty.Infant Mortality and Life Expectancy – Strong negative relationship (r = -.82). The higher the infant mortality rate, the lower the life expectancy. States such as Mississippi have a high infant mortality rate and low life expectancy age. States that have a low infant mortality rate and higher life expectancy are Florida and Hawaii. Texas is below the regression line meaning that people are not living as long as they should. According to the infant mortality rate, the life expectancy should be 79.5 years when it is actually 79 years.Per Capita Income and Poverty 2010 – If you divide the graph into quadrants you get a better analysis of the data. States such as NY and California have High Income and High Poverty; Texas is also included in this. High Income and Low poverty states are Connecticut and Massachusetts etc. Low Income and High Poverty states are Louisiana and Mississippi etc. most of the Southern states are in this category. Low income and low poverty states are Utah, Maine etc. Utah has a low income because of the high number of children that are not earning in their state.Violent Crime and Incarceration – There is no relationship (r = .06). Many people are incarcerated for drug related offences, but these figures are about to drop in states that have just legalized Marijuana. People are not being incarcerated for just violent crime, it is a myriad of offences and therefore there is no correlation.Business Climate and Quality of Life Ranking – positive weak relationship (r = .32) States that have a strong business climate will also have a better life quality for their residents.Issues in Empirical AnalysesMeasurementVariable LinkageIs there a relationship?With correlation you cannot measure cause and effect, therefore you must use more sophisticated tools.Casual Relationship – A relationship in which a causes b. There is a clear link that can be defined. Such as high levels of education and high levels of income. A better education leads to a higher income, not true for all cases though.Spurious Relationship – The correlations are very high but there is no causal relationship. Correlation does not mean causation. This can be because of an intervening variable, or an unknown variable that links the two.Divided Partisan Control and Medicare Payments to Disabled – All States. When you collect the data there seems to be a correlation. (r = .42). So this relationship suggest that when there is divided government, the higher the Medicare payments to the disabled. If you take out the Southern states from the data, there is no relationship. Southern states have lower payments normally and normally do not have divided government.States governments act differently; they all use their powers differently and spend differently. States create different types of public policy depending on their population.Texas Population is predicted to be more Hispanic than White in the next few years.Previously, local government did not pay much towards public education (20%) and state government provided the rest (80%). However, today the local government pays more for public education than the state. In 2007, states paid 44% and local government paid 56%. Texas Supreme Court then said this was unconstitutional, since education is a right in the Texas Constitution. This means that the state government should pay the majority of the cost for school funding.State and local spending is only 37% of the government expenditure and Federal expenditure is now 63%. Spending decreased by the Federal government after WWII. This meant that state and local rose to compensate the difference.POLS 207 1st Edition Lecture 5Outline of Last Lecture I. State Relationships and DifferencesOutline of Current Lecture II. CorrelationsA. Graphs available on lecture slidesIII. Issues in Empirical Analysesa. Measurementb. Variable linkagec. Is there a relationship?IV. State GovernmentsCurrent Lecture: CorrelationsThe strength of a relationship is measured on a scale from -1 – 1. Educational Attainment – If you graduate from high school, you are more likely to graduate fromcollege. Positive relationship with a score of .49. Percentage Metropolitan and Per Capita Income – Relationship seems to suggest that people who live in urban areas will also have higher incomes. The type of occupations that are availablein the city have a higher income than in rural areas. More urban a state is, the higher the income level.Percentage Metropolitan and Abortion Rate – r=.67. This means that girls who live within cities are more likely to