BY Brandon Hallstrand (University of Wisconsin – Stout)

1. A County Level Analysis of Educational Attainment in the United States by Social, Economic and Geographic Variables BY Brandon Hallstrand (University of Wisconsin – Stout) Kunjan Upadhyay (University of Wisconsin - Stout) 2010Wisconsin Economics Association Annual Conference

2. Outline • Introduction • Prior Studies • Model • Data and Descriptive Statistics • Regression Analysis • Conclusion • Future Work

3. Introduction • Education is Important • Huge Disparities within the country. • US is currently Ranked 16th in Education amongst 26 other OECD Countries. • Organization for Economic Cooperation and Development (OECD) • Dropped from 1st position in 1995

4. Figure 1: its “Percentage of Tertiary-Type A Graduates to the Population at the Typical Age of Graduation Measure for 2010,” (Organization for Economic Cooperation and Development, 2010). http://stats.oecd.org/index.aspx?queryid=23112

5. Prior Studies • Racial, gender cohort dropout rates in Chicago Public Schools (Allensworth & Easton 2001). • High school Drop outs and graduation rates in central region (Randel, Moore & Blair 2008). • Focus on Specific Regions, gender, race • One Study Points Out Data Problems • Hidden Crisis in High School Dropout Rate (Sum et. al 2003).

7. Full Models

8. Reduced Models

9. Data and Descriptive Statistics1990

10. Data and Descriptive Statistics2000

11. Data and Descriptive StatisticsPanel

12. Regression Analysis • Used Minitab 16 Statistical Software • Best Subsets • Chose Models for Simplicity and Fit

13. Regression Analysis

14. Regression Analysis (cont.)

15. Conclusion • Local Educational Spending and Per Capita Income have consistent inverse effects • Effective way of reducing High School Dropouts • increase in spending and income from 1990 to 2000 coincides with a substantial decrease in the dropout rates. • Whites, blacks, Native Americans and others have positive coefficients • Relative to areas with high numbers of Hispanics and Asians; Areas with high numbers of whites, blacks, Native Americans and or others, have higher dropout rates. • This Differs from Model to model, area to area.

16. Future Work • Better way to manage racial categories • 1990 Data Set Problem • Relative Population Size Vs. Exact Sampling • Change in local spending & lagged spending • Perhaps Panel Year Value takes away from Spending value

17. Questions & Comments

18. Thank You!!!