Purpose:The relationship between wages and education has been a subject of interest to the economist for a long period of time.
The issue of income inequality has been highly discussed about and one of the prime causes for these disparities is the level of education attainment. For an individual to have a perfect mix of skill, one needs to have adequate level of education, and hence the difference in the level of wages can be seen. It can be seen in almost all organizations, higher the level of authority, higher the requirement of level of education and so as the level of salary because the decision making power in an individual in higher position only comes with higher qualifications. The purpose of this report is to study the impact that education creates on wages of an individual. In order to identify the impact I have constructed a simple linear regression model by taking earning per hour and years of education as the units for wages and education respectively.Background:In today’s modern world, education plays a vital role.
It has been proven through many studies from around the world at different time intervals that the higher the level of education, higher will be the level of their income. The interests of economists towards this issue got stimulated around 1950s after observing growth in production and income with the rising education levels. Economists have been studying and analysing the increasing and steep inequality in wages amongst the labour market for a couple of decades now. Although this has been an issue that existed for many generations in the economics field, various economists have studied and found that level of education as one of the reasons for this inequality. For example, new innovations in terms of technology have made it mandatory for organizations to hire labours that are skilled with the changing technologies and innovations. Education, without a doubt, is important for someone to deal with these challenges of innovations efficiently.
Thus labour force started being considered as Human Capital for any organisation and the skills, job suitability and the ability to apply the skills all come with the level of education. Method:In order to analyse the relation between wages and education, a simple linear regression concept has been used as it measures how strong the connection exists in between the given variables. Education is used as an independent variable and wages as the dependent one. The linear regression has been used to predict the value of the dependent variable (wages, Y) with the value of the independent variable (education, X) being known. The descriptive analysis and statistics are then recorded and data collected for the regression analysis is presented through a scatter diagram. The straight line or the best fit line obtained through the regression represents the relation between the two variables. The general form of the straight line describing itself is:Y=?+?X, where Y is the dependent variable, X is the independent variable and ? is the slope of the line. The positive relation of the variables shows the line in the upward direction and negative relation towards the downward direction.
With the increase in the value of ?, the line gets steeper. This line can be used to predict the value of wages for a given value of the level of education. Result:• As per the given data there were 100 numbers of observations and the following statistical details were derived: Wages (earning per hour,$) Education (in years)Mean 22.30 13.76Standard Deviation 14.02 2.
72Minimum 4.33 6Maximum 76.39 21• The following scatter diagram was also developed with the help of the provided data: The scatter diagram shows a positive relation between earnings per hour and level of education as the line is upward sloping. • The regression equation to predict the wages with the given level of education can be estimated as:Y=2.123X-6.914• The regression equation Y=2.123X-6.914 that can be applied to our variable a Wages=2.
123* Education-6.914.The slope coefficient ? is 2.123 and is interpreted as: for each year rise in level of education, the earning per hour is increased by 2.123 units and simultaneously, each year decline in the level of education will result in wages decreased by 2.
123 units.• There is a significant relation between wages and educationkkkllllllllllll explain p value• Kkkkkkkkkkk• a) Predicted wage for a person with 12 years of education:- Wages=2.123* Education-6.914 Wages=2.123*12-6.
914 =$18.562/hr b) Predicted wage for a person with 14 years of education:- Wages=2.123* Education-6.914 Wages=2.123*14-6.914 =$22.
808/hr The difference in the hourly wage rate is: =$22.808 per hour- $18.562 per hour =$4.246/hrDiscussion: As can be concluded from the above results, the upward slope in the scatter diagram shows a positive relation between wages and education. The obtained results are consistent with the previous findings of the economists where a positive relation has been observed, i.
e., higher the level of education, higher will the income be.One of the major strength of this analysis is that it can be used to influence and incentivize individuals to invest on their own education and reflect on the benefits that can be achieved, higher the education, higher could be their earnings.
The achieved framework can aid policy makers in implementing policies that helps them understand the level of education required to achieve a certain level of income and its growth. There are however some limitations to the analysis. Only education and wages as variables have been used as variables assuming any other factors as constant. There could be various factors that could influence the result such as age, level of experience, the absorptive capacity of an indicidual.
Also this analysis has been conducted with a limited number of observations. More observations would calculate results that could generalise the relationship between wages and education. With the available number of data and observations, a positive relation has been depicted; this analysis gives an insight to economists and other researchers as a guide to carry on further analysis with varied data and additional variables.
This analysis can also provide some insight on the national level to fill in the poverty issue and increase awareness regarding education. Any country could use the benefits of a highly skilled workforce. In addition, there could be implications used to avoid the technology skill mismatch. The advancement of technology should be balanced by the learning of the available workforce to match up with technology upgrade.Recommendation:The following three recommendations can be taken into concern for future analysis:• More empirical and robust data should be provided in future in terms of wage growth, and productivity growth to be compared alongside the level of education.• In order to organise more significant results in future, other factors such as willingness to learn, how well the learnt knowledge is absorbed by an individual and whether or not the person has been exposed to new technologies.• These kind of analyses can be used to feed in the policy as a basis for monitoring income and growth productivity developments since the relationship is confirmed with evidence.