Time

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CountryX government wanted to investigate existence of gender discriminationin the labor market. According to the argument by Women RightsAssociation, female workers are less educated than their malecounterparts. However, the Employers’ Association attributes anypossible gender gap on work experience where male workers are said tobe more experienced than female workers. This is because femaleworkers spend most of their time outside the labor market taking careof the children.

Thisassignment contains statistical analyses and tests using the datafrom the recent labor market survey of country X. The data setcomprised of 2,858 workers.

Outof the 2858 employees taken for the survey, 42.8% were female while57.2% were males. This is as shown in the table below.

GENDER

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Female

1224

42.8

42.8

42.8

Male

1634

57.2

57.2

100.0

Total

2858

100.0

100.0

Evidenceof differential returns to education by gender

Accordingto the Women’s Rights Association, the returns to education forfemale workers are significantly lower than for male workers. Thiscan be evidenced by analysis of the years of schooling and tests ofcognitive ability among the workers based on gender.

Yearsof schooling

Itcan be observed that male workers have relatively higher years ofschooling than their female counterparts. For instance, those with 20years of schooling include 9 female workers and 18 male workers whilethose with 12 years of schooling include 500 female workers and 710male workers. The comparative bar graph above is a clear indicationthat despite women in employment being lower than men their years ofschooling are far too low when compared with men.

Itcan be observed from the figure below that earning is directlyproportional to years of schooling

Thisimplies that since females have fewer years of schooling than males,then their earnings will definitely be lower than for males.

Testsof Cognitive ability

Itcan be seen that male workers have higher cognitive ability thanfemale workers. Cognitive ability can be described as the brain basedskills that are required to carry out tasks from the simplest to themost challenging. This can be attributed to ability to learn,remember, solve problems and pay attention rather than the dependencyon actual knowledge. Years of schooling and job experience plays amajor role in contributing to the cognitive ability.

Relationshipbetween tests of cognitive ability and Earnings

Asit was analyzed, test of cognitive ability was more positive for maleworkers than for female workers. The scatter of the earnings andtests of cognitive ability reveal that the workers with high scoresin cognitive ability earn more than those with low scores. Thisimplies that since female workers have lower scores of tests ofcognitive ability, then they’ll tend to earn less than their malecounterparts.

WorkExperience based on gender

Accordingto reports by Employer’s Association, women have less workexperience than male workers. To ascertain this argument, theanalysis was carried out and the results are as shown in the figurebelow.

Thetrend in years of experience seems to vary considerably based ongender. It can be observed from the figure above that female workershave lower years of experience than their male counterparts. This,according to Employer’s Association, is majorly because femaleworkers tend to spend a lot of time taking care of the children. Thestatistical test for this argument can be evaluated from the analysisof potential time spent outside the labor market.

Toillustrate how the work experience affects earnings, the graph belowwas generated

Thescatter plot above is a clear indication that earning is directlyproportional to years of experience. Therefore, a worker with moreyears of experience will tend to earn more compared to the one withless years of experience.

Fromthe previous analysis, it was determined that female workers have fewyears of experience than male workers. Therefore, in overall, femaleworkers will earn less compared to male workers.

Potentialtime spent outside the labor market

Yearsspent outside the labor market is the difference of years spentschooling and years of experience. It can be observed from the figureabove that female workers spent more years outside the labor marketthan males. This, as argued by the Employer’s Association, couldhave been caused by the fact that women spent a lot of time rearingchildren rather than working.

AdditionalData

Theregression analysis was carried out to estimate the relationshipbetween the years of schooling, tests for cognitive ability and yearsof work experience. Simple linear regression was specifically used tomodel the relationship between the dependent variables years ofexperience and tests of ability, and independent variable years ofschooling. The correlation coefficient, R, and coefficient ofdetermination, R2,facilitate determination of the level of correlation. Ideally, thevalue should tend towards unity for a strong correlation.

Linearregression was used to determine the correlation in tests ofcognitive ability, years of work experience and gender. The valuesobtained from the regression analysis are as shown below.

Testsof cognitive ability and years of experience

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.220a

.049

.048

2.1267

.049

145.838

1

2856

.000

a. Predictors: (Constant), TEST

Theabove table presents the Rand R2values. The R value is a representation of simple correlation. Avalue of 0.049 represents a considerably weaker correlation in yearsof experience and tests for cognitive ability. On the other hand, R2depicts how much of total variation in dependent variable, years ofexperience, EXP, can be explained using the independent variable,tests of cognitive ability. In this case, 4.8% can be explained,which is relatively low.

Testof cognitive ability and years of schooling

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.605a

.367

.366

7.1790

.367

1653.142

1

2856

.000

a. Predictors: (Constant), S

TheR value is 0.367 represents a relatively stronger correlation inyears of schooling and tests of cognitive ability. R2depicts that 36.6% of tests of cognitive ability can be explained byyears of schooling, which is relatively higher.

Coefficienttables

Thecoefficients table presents the information necessary to predictyears of experience from tests of cognitive ability. This also helpsin determining whether tests of cognitive ability statisticallycontribute to the model as illustrated in the ‘sig’ column.

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

5.146

.223

23.092

.000

TEST

.053

.004

.220

12.076

.000

a. Dependent Variable: EXP

Therefore,the regression equation can be presented as

Yearsof experience = 5.146 + 0.053(Test of Cognitive ability). Thisimplies that tests of cognitive ability have very little significanceon the years of experience.

Testof cognitive ability and years of schooling

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

18.928

.769

24.624

.000

S

2.305

.057

.605

40.659

.000

a. Dependent Variable: TEST

Theabove coefficients table presents the information necessary topredict years of schooling from tests of cognitive ability.

Theyears of schooling can be predicted using the equation

Yearsof schooling = 18.928 + 2.305 (Test of Cognitive Ability)

Thisimplies that years of schooling significantly influence tests of thecognitive ability.

Regressionanalysis for male and female workers

Regressionanalysis for the number of workers based on gender and the years ofexperience shows that female workers are more affected by years ofschooling than their male counterparts. This can be described by thecoefficient of determination, R2,which is higher for female workers than for males. This is as shownin the figure below.

Regressionof tests for cognitive ability and gender

Theregression analysis of tests of cognitive ability and gender presentsa platform to establish the relationship between the number ofworkers based on gender and the cognitive ability. The results ofanalysis are as shown in the figure below.

TheR value for male workers is higher than for the female workers. Thisimplies that male workers have higher cognitive scores than females.

Discussionand Conclusion

Theresults of the analysis revealed that male workers fair comparativelybetter than their female counterparts. In terms of years ofschooling, female workers are less compared to male workers while interms of years of experience, male workers appear to be moreexperienced than female workers.

Theregression analysis illustrates very weak correlation in years ofexperience and tests for cognitive ability and a relatively strongercorrelation between years of schooling and tests for cognitiveability. Also, the analysis results showed that many women tend tospend more time outside the labor market than males.

Theresults of the analysis support the argument by Women RightsAssociation of the female workers being less educated than their malecounterparts. Male workers having more than ten years of schoolingare far too many than the female counterparts. Additionally, theargument by Employer’s Association of the male workers having moreyears of experience than female workers is true. This is wellrevealed from the regression analysis of the number of workers basedon gender against years of experience having a higher coefficient ofdetermination for male workers than for female workers. TheEmployer’s Association also attributed the low number of femaleswho are experienced in their work to the time spent outside the labormarket while taking care of children. Ideally, this can be consideredto be true though the data did not have any provision for womentaking care of the children.

Asthe government of country X, the arguments by Women RightsAssociation and Employers Association on the current state of femaleworkers in the labor market can be considered to be true. Fromstatistics, only 42.8% of the women are in employment compared to57.2% of the male workers in the country. It is critical for thegovernment to understand that years of schooling among female workersappear to be relatively low than in male workers. Also, the countryhas more males with more years of work experience than femaleworkers. It is also imperative for the government to take intoconsideration the time spent by women outside the labor market.Though the Employer’s Association argued that females spent moretime outside the labor market taking care of the children, thevalidity and reliability of this argument is still unclear. First,there statistics revealed no data related to child rearing, andsecond, there are other reasons that can contribute to many femalesspending more time outside the labor market other than just takingcare of the children.

Itis clear from the analysis that female workers are relatively lesscompetitive than their male counterparts in the labor market in termsof education and years of experience. Using years of experience asdependent variable and years of schooling as independent variable,the regression analysis revealed little correlation. This impliedthat years of experience cannot be explained by years of schooling.Ideally, years of schooling and years of experience should have astrong correlation. On the other hand, a regression analysis of yearsof schooling as independent variable and tests of cognitive abilityas dependent variable revealed a relatively stronger correlationimplying that cognitive ability is a function of years of schooling.

Asthe government, there is need to promote education among women aswell as investigate on the issues that make most of them waste a lotof time outside the labor market. spent outside the labor marketsignificantly affects the work experience. For a country to remaincompetitive in terms of gender and labor, then the government shouldformulate measures that will ensure that women do not lag behind ineducation and their needs are taken care of in order to reduce thetime spent outside the labor market. This will translate directly toincreased cognitive ability and work experience among women.

Limitationsof the Analysis

Themajor limitation of the current analysis is the fact that the numberof female workers was not equal with the number of male workers.Female workers were 42.8% while male workers were 57.2%, a differenceof 14.4%. Therefore, comparing the female and male workers could havebeen more accurate if the workers representation in terms of genderwas equal. Another limitation is due to the fact that some of thedata given was extremely large to represent effectively using theSPSS. As such, the data was generated using SPSS but representedusing Excel application. For instance, representing comparativescatter chart from regression analysis of male and female and gettingthe coefficient of determination is represented more elaboratelyusing Excel than SPSS application. Transferring data from SPSS toExcel is time consuming and at times may result to inaccuracies.

References

AgrestiA, Finlay B. Statistical methods for the social sciences. UpperSaddle River, N.J.: Pearson Prentice Hall 2009.