Adam Sutton Chia-Jung Liu Grant Volk Yin Chu Can Shen Robert Matarazzo Andrew Ratcliffe Ruben Bos

 Highest since Great Depression  Effects well being of population  Effects well being of economy  Implicit effects on policy development and reformation

 To understand the correlation, if any, between unemployment rates and population characteristics

 State Expenditures  Percentage of population that is White, African-American, and Hispanic  Percentage of population with no health insurance  Percentage of temporary jobs  Percentage population over 25 with a bachelor’s degree  Income per capita  Homeless per 1000  Number of citizens participating in the food stamps program  Crimes per 100,000 citizens  Percentage of blue collar jobs  Data taken across 51 observations including 50 states and the District of Columbia

Variable (1)Variable (2)R-squaredF-Statistics PROB Percent bachelorsIncome per capita Percent blue collarPercent bachelors Blue collarIncome per capita Food stampsCrime per 100, Food stampsState expenditures Percent without health carePercent white Percent without health carePercent black Percent without health carePercent Hispanic Crime per 100,000 per state Percent white Crime per 100,000 per state Percent black Crime per 100,000 per state Percent Hispanic Percent without health careCrime rate per 100,000 people

 Correlations between two signs of wealth  Bachelors degree and income per capita  Correlations between two signs of poverty  Lack of health care and food stamp participants  Lack of significant negative correlations between a sign of wealth and a sign of poverty

Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar Unemployment RateCrime per 100,000 per state Unemployment RateParticipation in food stamps program Unemployment RateHomeless per 1000 per state Unemployment RateIncome per capita Unemployment RatePercent of adults with bachelors Unemployment RatePercent of African Americans per state Unemployment RatePercent of Hispanics per state Unemployment RatePercent of whites per state Unemployment RatePercent of pop with no health care Unemployment RatePercent of jobs that are temp Unemployment RateState expenditures

 Percentage of population that is White and Hispanic  Percentage of population with no health insurance  Percentage of temporary jobs  Percentage population over 25 with a bachelor’s degree  Income per capita  Percentage of blue collar jobs

Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar Unemployment RateCrime per 100,000 per state Unemployment RateParticipation in food stamps program Unemployment RateHomeless per 1000 per state Unemployment RateIncome per capita Unemployment RatePercent of adults with bachelors Unemployment RatePercent of African Americans per state Unemployment RatePercent of Hispanics per state Unemployment RatePercent of whites per state Unemployment RatePercent of pop with no health care Unemployment RatePercent of jobs that are temp Unemployment RateState expenditures

Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar Unemployment RateCrime per 100,000 per state Unemployment RateParticipation in food stamps program Unemployment RateHomeless per 1000 per state Unemployment RateIncome per capita Unemployment RatePercent of adults with bachelors Unemployment RatePercent of African Americans per state Unemployment RatePercent of Hispanics per state Unemployment RatePercent of whites per state Unemployment RatePercent of pop with no health care Unemployment RatePercent of jobs that are temp Unemployment RateState expenditures

Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar Unemployment RateCrime per 100,000 per state Unemployment RateParticipation in food stamps program Unemployment RateHomeless per 1000 per state Unemployment RateIncome per capita Unemployment RatePercent of adults with bachelors Unemployment RatePercent of African Americans per state Unemployment RatePercent of Hispanics per state Unemployment RatePercent of whites per state Unemployment RatePercent of pop with no health care Unemployment RatePercent of jobs that are temp Unemployment RateState expenditures

Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar Unemployment RateCrime per 100,000 per state Unemployment RateParticipation in food stamps program Unemployment RateHomeless per 1000 per state Unemployment RateIncome per capita Unemployment RatePercent of adults with bachelors Unemployment RatePercent of African Americans per state Unemployment RatePercent of Hispanics per state Unemployment RatePercent of whites per state Unemployment RatePercent of pop with no health care Unemployment RatePercent of jobs that are temp Unemployment RateState expenditures

Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar Unemployment RateCrime per 100,000 per state Unemployment RateParticipation in food stamps program Unemployment RateHomeless per 1000 per state Unemployment RateIncome per capita Unemployment RatePercent of adults with bachelors Unemployment RatePercent of African Americans per state Unemployment RatePercent of Hispanics per state Unemployment RatePercent of whites per state Unemployment RatePercent of pop with no health care Unemployment RatePercent of jobs that are temp Unemployment RateState expenditures

 State Expenditures  Percentage of population that is African- American  Homeless per 1000  Number of citizens participating in the food stamps program  Crimes per 100,000 citizens

 State expenditures and food stamp participation  In order to study the variables related to state spending against unemployment  Determined that food stamp participation is the most significant variable while state expenditures is not

 Normal residuals  No heteroskedasticity

 Crime rate and income per capita  In order to study the effects of poverty and unemployment  Highly significant regression did exist  Crime rate is highly significant while income is not  Introduction of dummy variable for DC  DC’s data was much higher than the 50 states  R-squared value increased because the absence of DC’s data decreased the sum of residuals

 Introduction of dummy variable for DC  DC’s data was much higher than the 50 states  R-squared value increased because the absence of DC’s data decreased the sum of residuals

 Normal residuals  No heteroskedasticity

 Crime rate, food stamps, and homeless per 1000  In order to test the three most highly significant variables against unemployment  Determined that a significant relationship exists with participation in the food stamps program being the most significant variable

 Normal Residuals  No heteroskedasticity

 Introduction of dummy variable for DC  Increased R 2 by decreasing sum of residuals

 Percent of population with no health insurance does not correlate with unemployment rate  Percent of adults with bachelors does not correlate with unemployment rate

 Unemployment positively correlated with:  Participation in the food stamps program  Homeless rate per 1000 people  Crime rate per 100,000 people  Should be the goal of the government to decrease unemployment by a reallocation of funds  Would lead to decrease in crime, homeless rate, and poverty

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