DETERMINANT OF SALARY

Determinants of Salary

Determinants of Salary

Introduction

The salary of a person certainly depends on various factors depending on the education and other related factors. In this study we are trying to manipulate the relationship between the changes in salary depends upon which factors and these factors are either significant or not. Therefore, we shall use the salary as the dependent variable which depends upon the movement of higher education and also the experience of work. The following econometric model will be used in the study:

……… (A)

Where (SAL) is the salary of the workers working in the UK manufacturing calculated in (£), and (EDU) is the Education level with respect to the number of years of study and (EX) is the Experience of the workers in UK firms.

There term 'u' is known as the stochastic error term and it plays the major role in looking at the impact of dependent variable on the independent i.e. in our case is SAL, EDU and EX respectively. The greater the error term is, the more variation lies in the model and thus lealds to biased results. The major focus of the analyst always remain at minimizing 'u' as more as possible for the reason to get the best and reliable estimators in the regression model.

Answers to the Questions

The ignoring of experience variable does not make a good sense because it is a significant variable as salary highly depends upon the experience of the workers. The more experience, the more salary workers will get.

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The above results shows that salary tends to change, with respect to experience, at a different rate depending on the level of experience. In the above equation, the derivative of the model has been taken with respect to EX in order to see the change in salary while there is a change occur in the experience of a person. The results show that the resulting change is positive because all the variables will remain positive. Therefore, we can conclude that the change in salary due to the change in experience is always positive.

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The above equation shows the change in salary with respect to any change in education levels. Also there is a possibility that salary might change, with respect to experience, at a different rate depending on education levels. In the above equation, the derivative of the model has been taken with respect to EDU in order to see the change in salary while there is a change occur in the educational background of a person. The results show that the resulting change is positive because all the variables will remain positive. Therefore, we can conclude that the change in salary due to the change in educational background is always positive.

Dependent Variable: LOG(SAL)

Included observations: 1287

Variable

Coefficient

Std. Error

t-Statistic

Prob.  

C

3.806871

0.160796

23.67519

0.0000

LOG(EDU)

0.644862

0.046593

13.84034

0.0000

LOG(EX)

0.603378

0.045160

13.36103

0.0000

R-squared

0.230555

F-statistic

192.3678

Adjusted R-squared

0.229357

Prob(F-statistic)

0.000000

Durbin-Watson stat

1.947907



The estimated coefficients are highly significant because of the higher t - values and the P<0.05. The coefficients shows that the normal salary without any education and experience e3.8 because the model was measured in log ...