Also it examines the limitations that may arrive due to considering only education as the factor of the wage inequality. Furthermore, it takes into account the other factors that may result in the different wages of people.
In this paper I would try to establish the fact that education is a determinant of wage inequalities. For the purpose of my research I’ve collected a data set which has pre tax wages and salary. Against this data set I’ve taken a data set that records the highest grade attended by the individuals. These two data sets are taken specifically to test my hypothesis correctly. For the purpose of the analysis I have also used many literature reviews.
The data set that has been used for the education records the highest grade of the individual. This data set has been designed in such a way that it captures the number of years of education for the individuals. The range is from 0 years spent in education to 8 years spent after college in education. Further, it shows that on average in the US, people drop out of the college after their second years. The data set that used for the purpose of the analysis of the income is the personal wage and monthly income of all the individuals in the United States. The range for this data set is not specified which means that it applies to all individual cases.
From the data sets that were used, the interesting deduction that one can make is that the correlation of the wage or the salary income and the highest grade attended by the individuals is very high that is -0.8 for 18,447,324 individual cases. (IPUMS samples) The standard errors that have been recorded here are approximately equal to zero which means that the T-static value is 0.00. This ensures that the coefficient of the correlation is statistically significant no matter what confidence level is taken. This is because the null hypothesis (the correlation coefficient equals zero) can be rejected at all levels of