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

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Presentation on theme: "Adam Sutton Chia-Jung Liu Grant Volk Yin Chu Can Shen Robert Matarazzo Andrew Ratcliffe Ruben Bos."— Presentation transcript:

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

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

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

4  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

5 Variable (1)Variable (2)R-squaredF-Statistics PROB Percent bachelorsIncome per capita 0.6945730.000000 Percent blue collarPercent bachelors 0.7478810.000000 Blue collarIncome per capita 0.4891430.000000 Food stampsCrime per 100,000 0.0475410.124279 Food stampsState expenditures 0.7710990.000000 Percent without health carePercent white 0.2072990.000788 Percent without health carePercent black 0.0430890.143844 Percent without health carePercent Hispanic 0.3336010.000009 Crime per 100,000 per state Percent white 0.3878520.000001 Crime per 100,000 per state Percent black 0.4485050.000000 Crime per 100,000 per state Percent Hispanic 0.0784820.046468 Percent without health careCrime rate per 100,000 people 0.1115410.016613

6  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

7 Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar 0.0406280.156083 Unemployment RateCrime per 100,000 per state 0.2009990.000969 Unemployment RateParticipation in food stamps program 0.1855200.001604 Unemployment RateHomeless per 1000 per state 0.1465120.005568 Unemployment RateIncome per capita 0.0071790.554416 Unemployment RatePercent of adults with bachelors 0.0040370.657805 Unemployment RatePercent of African Americans per state 0.1441860.005991 Unemployment RatePercent of Hispanics per state 0.0343910.192619 Unemployment RatePercent of whites per state 0.0947080.028029 Unemployment RatePercent of pop with no health care 0.0257670.260486 Unemployment RatePercent of jobs that are temp 0.0058820.592693 Unemployment RateState expenditures 0.1471930.005953

8  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

9 Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar 0.0406280.156083 Unemployment RateCrime per 100,000 per state 0.2009990.000969 Unemployment RateParticipation in food stamps program 0.1855200.001604 Unemployment RateHomeless per 1000 per state 0.1465120.005568 Unemployment RateIncome per capita 0.0071790.554416 Unemployment RatePercent of adults with bachelors 0.0040370.657805 Unemployment RatePercent of African Americans per state 0.1441860.005991 Unemployment RatePercent of Hispanics per state 0.0343910.192619 Unemployment RatePercent of whites per state 0.0947080.028029 Unemployment RatePercent of pop with no health care 0.0257670.260486 Unemployment RatePercent of jobs that are temp 0.0058820.592693 Unemployment RateState expenditures 0.1471930.005953

10 Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar 0.0406280.156083 Unemployment RateCrime per 100,000 per state 0.2009990.000969 Unemployment RateParticipation in food stamps program 0.1855200.001604 Unemployment RateHomeless per 1000 per state 0.1465120.005568 Unemployment RateIncome per capita 0.0071790.554416 Unemployment RatePercent of adults with bachelors 0.0040370.657805 Unemployment RatePercent of African Americans per state 0.1441860.005991 Unemployment RatePercent of Hispanics per state 0.0343910.192619 Unemployment RatePercent of whites per state 0.0947080.028029 Unemployment RatePercent of pop with no health care 0.0257670.260486 Unemployment RatePercent of jobs that are temp 0.0058820.592693 Unemployment RateState expenditures 0.1471930.005953

11 Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar 0.0406280.156083 Unemployment RateCrime per 100,000 per state 0.2009990.000969 Unemployment RateParticipation in food stamps program 0.1855200.001604 Unemployment RateHomeless per 1000 per state 0.1465120.005568 Unemployment RateIncome per capita 0.0071790.554416 Unemployment RatePercent of adults with bachelors 0.0040370.657805 Unemployment RatePercent of African Americans per state 0.1441860.005991 Unemployment RatePercent of Hispanics per state 0.0343910.192619 Unemployment RatePercent of whites per state 0.0947080.028029 Unemployment RatePercent of pop with no health care 0.0257670.260486 Unemployment RatePercent of jobs that are temp 0.0058820.592693 Unemployment RateState expenditures 0.1471930.005953

12 Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar 0.0406280.156083 Unemployment RateCrime per 100,000 per state 0.2009990.000969 Unemployment RateParticipation in food stamps program 0.1855200.001604 Unemployment RateHomeless per 1000 per state 0.1465120.005568 Unemployment RateIncome per capita 0.0071790.554416 Unemployment RatePercent of adults with bachelors 0.0040370.657805 Unemployment RatePercent of African Americans per state 0.1441860.005991 Unemployment RatePercent of Hispanics per state 0.0343910.192619 Unemployment RatePercent of whites per state 0.0947080.028029 Unemployment RatePercent of pop with no health care 0.0257670.260486 Unemployment RatePercent of jobs that are temp 0.0058820.592693 Unemployment RateState expenditures 0.1471930.005953

13 Dependent Variable Explanatory Variable R-squaredF-Statistics PROB Unemployment RatePercent of jobs that are blue-collar 0.0406280.156083 Unemployment RateCrime per 100,000 per state 0.2009990.000969 Unemployment RateParticipation in food stamps program 0.1855200.001604 Unemployment RateHomeless per 1000 per state 0.1465120.005568 Unemployment RateIncome per capita 0.0071790.554416 Unemployment RatePercent of adults with bachelors 0.0040370.657805 Unemployment RatePercent of African Americans per state 0.1441860.005991 Unemployment RatePercent of Hispanics per state 0.0343910.192619 Unemployment RatePercent of whites per state 0.0947080.028029 Unemployment RatePercent of pop with no health care 0.0257670.260486 Unemployment RatePercent of jobs that are temp 0.0058820.592693 Unemployment RateState expenditures 0.1471930.005953

14  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

15  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

16  Normal residuals  No heteroskedasticity

17  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

18  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

19  Normal residuals  No heteroskedasticity

20  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

21  Normal Residuals  No heteroskedasticity

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

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

24  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

25 (End)

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