analysis of unemployment

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Analysis of Unemployment

Qi Li Trung Le

David PetitBrian Weinberg

Dwaraka PolakamDoug Skipper-Dotta

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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 unemployedUnemployment 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

MenDegree

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 0.8981MEN_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 5.538Adjusted R-squared 0.999738 S.D. dependent var 1.4607S.E. of regression 0.023633 Akaike info criterion -4.409Sum squared resid 0.00391 Schwarz criterion -4.318Log likelihood 25.04513 Hannan-Quinn criter. -4.5086F-statistic 17187.56 Durbin-Watson stat 3.3868Prob(F-statistic) 0

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Without a constant, the regression variables have even greater significance

Dependent Variable: UNEMP_RATE

Method: Least Squares

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

R-squared 0.999796 Mean dependent var 5.538

Adjusted R-squared 0.99977 S.D. dependent var 1.460706

S.E. of regression 0.022134 Akaike info criterion -4.60651

Sum squared resid 0.003919 Schwarz criterion -4.54599

Log likelihood 25.03255 Hannan-Quinn criter. -4.6729

Durbin-Watson stat 3.327676

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Exploratory Data Analysis 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 10Included observations: 10 Method df Value Probt-test 18 -5.630431 0.000Satterthwaite-Welch t-test* 12.48443 -5.630431 0.001Anova F-test (1, 18) 31.70175 0.000

Welch F-test* (1, 12.4844) 31.70175 0.001*Test allows for unequal cell variancesAnalysis of Variance Source of Variation df Sum of Sq. Mean Sq.

Between 1 32126055 32126055Within 18 18240917 1013384Total 19 50366972 2650893Category Statistics

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

MeanDEGREE_UNEMP 10 1547.6 582.9332 184.3397

NO_DEGREE_UNEMP 10 4082.4 1298.829 410.7259All 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

Dependent Variable: UNEMP_RATEMethod: Least SquaresDate: 11/25/10 Time: 21:18Sample: 1 10Included observations: 10

Variable Coefficient Std. Error t-Statistic Prob. C 1.394668 0.4133 3.37449 0.0118

DEGREE_UNEMP 0.001512 0.00135 1.12447 0.2979NO_DEGREE_UNEMP 0.000442 0.0006 0.73203 0.4879



S.E. of regression 0.15385 Akaike info criterion -0.662Sum squared resid 0.165688 Schwarz criterion -0.57

Log likelihood 6.311784 Hannan-Quinn criter. -0.762

F-statistic 402.1441 Durbin-Watson stat 0.437Prob(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

Dependent Variable: UNEMP_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 0.1639Log 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

F-statistic 1.437796 Durbin-Watson stat 0.41066

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


Sum squared resid 1228.599 Schwarz criterion 8.10944




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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




Sum squared resid 0.640059 Schwarz criterion 0.54961




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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

Dependent Variable: UNEMP_RATEMethod: Least SquaresDate: 11/28/10 Time: 12:20Sample: 1 10Included observations: 10

Variable Coefficient Std. Error t-Statistic Prob. AN_INC_PER_CAP -0.000411 0.000113 -3.64743 0.0148

CRIMERATE -0.083554 0.02457 -3.40071 0.0192SUICIDE_RATE 4.728742 1.383211 3.418669 0.0189

WELFARE_BUDGET 5.61E-06 1.13E-06 4.979503 0.0042C -32.63094 11.73778 -2.77999 0.0389

R-squared 0.948687 Mean dependent var 5.538Adjusted R-squared 0.907637 S.D. dependent var 1.46071S.E. of regression 0.443928 Akaike info criterion 1.52054Sum squared resid 0.98536 Schwarz criterion 1.67184Log likelihood -2.602719 F-statistic 23.1103Durbin-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

Unemployment

Significant Regressions

Education Sex Ethnicity

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ConclusionRecap:

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

analysis of unemployment

Documents

unemployedunemployment

rate method

mean dependent var

welch ftest

dependent var1

female unemployment

schwarz criterion

included observations