Analysis of Unemployment

1. Analysis of Unemployment Team #4 Qi Li Trung Le David Petit Brian Weinberg Dwaraka Polakam Doug Skipper-Dotta

2. Table of Contents 1 2 3 4 5 Concepts of Unemployment Descriptive Data Analysis Statistical Analysis Conclusions Questions? Team #4

3. Concepts of Unemployment Population Employed Unemployed Not Looking Labor Force Labor Force: People willing to work at market equilibrium wage, both employed and unemployed Unemployment Rate: Number of Unemployed/Labor Force Keynesian View: Unemployment consists of excess labor supply in market economy Classical View: The unemployed consist of those searching for jobs Group #4

4. Descriptive Statistics • Data from prior studies Team #4

5. Unemployment Rate No Degree/Degree Men/Women White/Minority Other Rates Crime Rate Suicide Rate Welfare Budget Annual Income Per Capita Variables

6. Descriptive Statistics • Histograms • Unemp Rate • Crime Rate • Annual Income • Welfare Budget • Suicide Rate Team #4

7. Descriptive Statistics • Histograms Unemp Rate No Degree Women White Minor Men Degree Team #4

8. Exploratory Data Analysis • Unemployment rates between Men and Women have no significant difference • High f-test probability • A labor market that does not discriminate on the basis of sex Team #4

9. Exploratory Data Analysis • Unemployment Rate is Regressed against male unemployment rate and female unemployment rate • The regression is Significant as seen by the F-stat • The variables are both equally significant in the unemployment rate as seen by their the t-stat • Therefore male and female unemployment rates are very close. Team #4

10. Exploratory Data Analysis • Without a constant, the regression variables have even greater significance Team #4

11. Exploratory Data Analysis • Unemployment rates between those with a degree and those without differ significantly Team #4

12. Exploratory Data Analysis • There is no significant relationship (as seen by the t-stats) between having a degree and being unemployed or having no degree and being unemployed • Intuitively this seems very wrong and can be accounted for by the constant. • In the next slide the constant will be removed Team #4

13. Exploratory Data Analysis • With the Constant removed both variables become significant • Small coefficients imply a very small effect on the unemployment rate Team #4

14. Exploratory Data Analysis • Annual Income is not significant when regressed with a constant • Low t-stat and R2 Team #4

15. Exploratory Data Analysis • This regresses the Unemployment rate vs the Crime rate • We found that the unemployment rate is not a significant factor in the crime rate as seen by the low f-stat and the low t-stat Team #4

16. Exploratory Data Analysis • This regression has the Unemployment Rate vs Suicide Rate • We found that there is a slight relationship between the two • The f-stat is low, but the R2 indicates that there is some relationship between the variables Team #4

17. Exploratory Data Analysis • Welfare regressed against unemployment shows a significant relationship between the two • Intuitively, as the number of unemployed people grows, the greater demand for welfare Team #4

18. Exploratory Data Analysis • Here the Unemployment Rate is regressed against multiple variables • All variables are significantly contribute to the Unemployment Rate • Annual Inc per cap coefficient is negative, suggesting a higher income implies a lower unemployment rate • Surprisingly, as crime rate increases unemployment decreases Team #4

19. Statistical Analysis + What does it effect? Welfare Suicide Unemployment Income – Constant Crime Team #4

20. Unemployment Significant Regressions Education Sex Ethnicity Statistical Analysis Team #4

21. Conclusion • Recap: • Regressing unemployment rate with these a few durations has no meanings. • Unemployment rates between Men and Women have no significant difference • We can compare different sample means: • Unemployment rates between Men and Women have no significant difference: • Unemployment rates between Degree and No Degree have significant difference: • Regress unemployment rate with men and women unemp (with c and without c): • Regress unemployment rate with degree and no degree unemp (with c and without c): • Regress annual income with unemployment rate (not significant, no relationship): • Regress crime rate with unemployment rate (not significant, no relationship): • Regress suicide rate with unemployment rate (not significant, some relationship): • Regress welfare budget with unemployment rate (significant, strong relationship): • Regressing unemployment rate with these four variables has no meanings. • Regress Unemployment with Annual Income, Crime rate, Suicide rate, Welfare budget(Significant) Team #4

22. Conclusions • I have no money and cannot get any work • Father, can’t I have a piece of bread • I say father, could you get some specie claws? • I’m so hungry • My dear, cannot you continue to get some food for the children I don’t care for myself • I say Sam, I wonder where we are to get our Costs • **Warrant Distraint for rent** Team #4

23. Future Investigations • Next time, I top down approach how does state and county unemployment break down. Team #4

24. Future Investigations • Or a bottom up approach that considers the dynamic between US unemployment and international unemployment. Team #4

25. Thank You ! Team #4

26. Technical Appendix Team #4

27. Works Cited • http://www.bls.gov/cps/ • http://en.wikipedia.org/wiki/Unemployment • http:://en.wikipedia.org/wiki/File:Panic1873.jpg • http://upload.wikimedia.org/wikipedia/commons/c/ce/Chomage-oecd-t3-2009.png Team #4