Analysis of Factors Influencing the Salary of Female Employees: A Regression Approach

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Salary of female employeesPage1of11Analysis of Factors Influencing the Salary of Female Employees: A Regression ApproachMemorandumTo:From:Data AnalystsDate:Mar 9, 2015Subject:Checking the dependence of Salary of female employees on the other variablessuch asjob grade,education level etc.Using the provided regression analysis results, discuss how various factors (such as age,education level, years of experience, and others) influence the salary of female employees. Howdoes the inclusion of different explanatory variables impact the gender wage gap, and what doesthis imply for addressing salary disparities in the workplace? Provide a detailed interpretation ofthe results and suggest potential strategies for improving pay equity based on the findings.Word count requirement: 750-1000 words.

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Salary of female employeesPage2of11******************************************************************************PurposeThis memorandum provides an analysis ofdependence of salary on other factors such asthe gender of employee,education level, job grade,age,experience level and many other relatedvariables.Specifically, we examined the relationship betweensalary and gender so as to analyzethe how the salary of female employees changes if othersaidfactors are taken into consideration.BackgroundThegender pay gap(also known asgender wage gap,male–female incomedifference,gender gap in earnings,gender earnings gap,gender income difference) is thedifference between male and female earnings expressed as a percentage of male earnings,according to theOECD.TheEuropean Commissiondefines it as the average difference between men’s and women’shourly earnings. It is generally suggested that the wage gap is due to a variety of causes, such asdiscrimination in hiring,differences in education choices, discrimination in salary negotiations,differences in the types of positions held by men and women, differences in the pay of jobs mentypically go into as opposed to women (especially highly paid high risk jobs), and differences inamount of work experience, and breaks in employment.AnalysisObjectivesOur study sought to determinethe following:(1)The factorsor combination of characteristicsthat influences the salary structure of afemale employee.

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Salary of female employeesPage3of11(2)How addition of one more factor changes the dependence of salary on female factor.That is,how the size of the coefficient for the Female variable changes as we addadditional explanatory variables.MethodologyTheMicrosoft Excel 2007Data AnalysisRegressionfunctionwasused to generatemultiple regressionsuponvariouscombinations of variables and to determinefor each regressionthecoefficient of determination,R2,todeterminethe degree to which variation insalaryoffemale employeescan beexplained by the variablesselected. Theadjusted R2for eachregression wasalsomonitored to determine whetheradditional variables mayhavebeensuperfluous.Reliabilityof the coefficientswasassessed by examining statistics such asp-values.Variablesfor which data wasavailableincluded the following:Variables Employed in AnalysisExplanatoryVariableUnitsAbbreviationFemale*1 or 0femaleAgeYearsAgeYears prioryearsyrspriorYears experianceYearsYrsexperEducation level1,2 or 3EduclevEducation level =i†1,2 or 3Index 1,2,3*Femalevariable with value1 means female and 0 means male.†Education levelwith higher value indicating more education.ResultsThe analysis began with a review of scatter plots of Salary v. variables such as Age,female. While female alone (Figure 1) produced a low coefficient of determination (R2less than13%), Age(Figure 2) produced a slightly higher, though still weak explanatory relationship(17%) to Salary.

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