LOGO Analysis of Unemployment Qi Li Trung Le David Petit Brian Weinberg Dwaraka Polakam Doug...

LOGO

Analysis of Unemployment

Qi Li Trung Le

David PetitBrian Weinberg

Dwaraka PolakamDoug Skipper-Dotta

Team #4

Team #4

Table of Contents

Concepts of Unemployment1

Descriptive Data Analysis2

Statistical Analysis3

Conclusions 4

Questions?5

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Concepts of Unemployment

Employed Unemployed Not Looking

Population

Labor ForceLabor 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

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Descriptive Statistics

Data from prior studies

Variables

Unemployment Rate No Degree/Degree Men/Women White/Minority

Other Rates Crime Rate Suicide Rate Welfare Budget Annual Income Per Capita

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Descriptive Statistics Histograms

Crime Rate

Annual Income

Suicide Rate

Welfare Budget

Unemp Rate

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Descriptive Statistics

Histograms

No Degree

Women

White

Minor

Unemp Rate

Men

Degree

Exploratory Data Analysis

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Test for Equality of Means Between SeriesDate: 11/25/10 Time: 21:04Sample: 1 10Included observations: 10 Method df Value Probabilityt-test 18 -0.619531 0.5433Satterthwaite-Welch t-test* 15.10255 -0.619531 0.5448Anova F-test (1, 18) 0.383819 0.5433Welch F-test* (1, 15.1025) 0.383819 0.5448*Test allows for unequal cell variances Analysis of Variance Source of Variation df Sum of Sq. Mean Sq.Between 1 0.8405 0.8405Within 18 39.417 2.189833Total 19 40.2575 2.118816Category Statistics

Variable Count Mean Std. Dev. Std Mean ErrWOMEN_UNEMP 10 5.32 1.109354 0.350809

MEN_UNEMP 10 5.73 1.774542 0.56116All 20 5.525 1.455615 0.325485

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

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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.

Dependent Variable: UNEMP_RATE

Method: Least Squares

Date: 11/25/10 Time: 21:20

Sample: 1 10

Included observations: 10

Variable Coefficient Std. Error t-Statistic Prob.

C 0.014542 0.109522 0.132776 0.8981

MEN_UNEMP 0.536652 0.037684 14.2407 0

WOMEN_UNEMP 0.460234 0.060281 7.634859 0.0001

R-squared 0.999796 Mean dependent var 5.538

Adjusted R-squared 0.999738 S.D. dependent var 1.4607

S.E. of regression 0.023633 Akaike info criterion -4.409

Sum squared resid 0.00391 Schwarz criterion -4.318

Log likelihood 25.04513 Hannan-Quinn criter. -4.5086

F-statistic 17187.56 Durbin-Watson stat 3.3868

Prob(F-statistic) 0

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Without a constant, the regression variables have even greater significance



Date: 11/25/10 Time: 21:15

Sample: 1 10



MEN_UNEMP 0.531968 0.01241 42.86486 0

WOMEN_UNEMP 0.468 0.013667 34.24331 0






Durbin-Watson stat 3.327676

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Unemployment rates between those with a degree and those without differ significantly

Test for Equality of Means Between Series

Date: 11/25/10 Time: 21:06

Sample: 1 10


Method df Value Prob

t-test 18 -5.630431 0.000

Satterthwaite-Welch t-test* 12.48443 -5.630431 0.001

Anova F-test (1, 18) 31.70175 0.000

Welch F-test* (1, 12.4844) 31.70175 0.001

*Test allows for unequal cell variances

Analysis of Variance

Source of Variation df Sum of Sq. Mean Sq.

Between 1 32126055 32126055

Within 18 18240917 1013384

Total 19 50366972 2650893

Category Statistics

Variable Count Mean Std. Dev.Std. Err. Of

Mean

DEGREE_UNEMP 10 1547.6 582.9332 184.3397

NO_DEGREE_UNEMP 10 4082.4 1298.829 410.7259

All 20 2815 1628.156 364.0668

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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



Date: 11/25/10 Time: 21:18

Sample: 1 10



C 1.394668 0.4133 3.37449 0.0118

DEGREE_UNEMP 0.001512 0.00135 1.12447 0.2979

NO_DEGREE_UNEMP 0.000442 0.0006 0.73203 0.4879







Prob(F-statistic) 0

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With the Constant removed both variables become significant

Small coefficients imply a very small effect on the unemployment rate



Date: 11/25/10 Time: 21:19

Sample: 1 10



DEGREE_UNEMP -0.002632 0.00083 -3.169111 0.0132

NO_DEGREE_UNEMP 0.00235 0.00032 7.341046 0.0001



S.E. of regression 0.233243 Akaike info criterion 0.1034

Sum squared resid 0.43522 Schwarz criterion 0.1639

Log likelihood 1.483058 Hannan-Quinn criter. 0.037

Durbin-Watson stat 0.492591

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Annual Income is not significant when regressed with a constant

Low t-stat and R2

Dependent Variable: AN_INC_PER_CAP


Date: 11/25/10 Time: 21:24

Sample: 1 10



C 28599.63 5233.213 5.465023 0.0006

UNEMP_RATE 1099.2 916.7016 1.199081 0.2648

R-squared 0.152344 Mean dependent var 34687



Sum squared resid 1.29E+08 Schwarz criterion 19.6719

Log likelihood -96.05681 Hannan-Quinn criter. 19.545


Prob(F-statistic) 0.264805

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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

Dependent Variable: CRIMERATE


Date: 11/25/10 Time: 21:26

Sample: 1 10



C 125.2415 16.1442 7.75768 0.0001

UNEMP_RATE 1.131003 2.827978 0.399933 0.6997


Adjusted R-squared -0.102948 S.D. dependent var 11.8






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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

Dependent Variable: SUICIDE_RATE


Date: 11/25/10 Time: 21:31

Sample: 1 10



C 10.31478 0.368486 27.9923 0

UNEMP_RATE 0.1268 0.064548 1.964442 0.0851








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Welfare regressed against unemployment shows a significant relationship between the two

Intuitively, as the number of unemployed people grows, the greater demand for welfare

Dependent Variable: WELFARE_BUDGET


Date: 11/25/10 Time: 21:34

Sample: 1 10



C 1131949 327896.7 3.45215 0.0087

UNEMP_RATE 159511.5 57437.65 2.777124 0.024

R-squared 0.490849 Mean dependent var 2015323

Adjusted R-squared 0.427205 S.D. dependent var 332568


Sum squared resid 5.07E+11 Schwarz criterion 27.9472




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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



Date: 11/28/10 Time: 12:20

Sample: 1 10



AN_INC_PER_CAP -0.000411 0.000113 -3.64743 0.0148

CRIMERATE -0.083554 0.02457 -3.40071 0.0192

SUICIDE_RATE 4.728742 1.383211 3.418669 0.0189

WELFARE_BUDGET 5.61E-06 1.13E-06 4.979503 0.0042

C -32.63094 11.73778 -2.77999 0.0389





Log likelihood -2.602719 F-statistic 23.1103

Durbin-Watson stat 2.027352 Prob(F-statistic) 0.00201

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Statistical Analysis

Income

WelfareSuicide

Constant

Crime

Unemployment

What does it effect?

–

+

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Statistical Analysis

UnemploymentUnemployment

Significant Regressions

Education Sex Ethnicity

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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)

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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**

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Future Investigations

Next time, I top down approach how does state and county unemployment break down.

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Future Investigations

Or a bottom up approach that considers the dynamic between US unemployment and international unemployment.

LOGO

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Technical Appendix

Country Rates: Interest Growth Inflation Jobless Exchange Current Account

United States 0.25% 2.00% 1.20% 9.60% 82.92 -123

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2010 9.7 9.7 9.7 9.9 9.7 9.5 9.5 9.6 9.6 9.6

2009 7.7 8.2 8.6 8.9 9.4 9.5 9.4 9.7 9.8 10.1 10 10

2008 5 4.8 5.1 5 5.4 5.5 5.8 6.1 6.2 6.6 6.9 7.4

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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

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