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Student Loan debt affects the economy of the country and other sectors relying on government funding. The rate at which student loan debts are increasing each year is alarming. A study conducted between the third quarters of 2003 to the third quarter of 2013 shows how fast student loan debt increase. The data gathered show that in 2003, student loan debts totaled to $250 billion. In 2008, it had increased to $610 billion. By 2013 it had reached $1.03 trillion (Brown et al., 2015). The high student loan debt means that the borrowing rate is higher than the repayment rate. Several factors influence the repayment rate of the loan. After school, some people find it hard to get jobs, and this makes it hard for them to repay the loan. Some do get jobs, but the remuneration given is too little it cannot be enough for the person to pay back the loan and still have some leftover. Age is one of the other factors that affects the repayment rate. I believe, as people grow old, their responsibilities increase. Some start a family, and since the money received remains at a constant even with the increase in responsibilities, people find it hard to their responsibilities and student loan debt. My research question is if age can affect the student loan repayment rate? The purpose of this study is to prove that with age come additional responsibilities that make it hard for people to pay back their loan. The practical significance of the study is to mobilize young people to repay the loan because it would be hard for them to repay once they grow older and the number of dependents increases.
Popular opinion is that income affects loan repayment, and to some extent, I concur with this opinion. The truth is, one can earn $5000 and comfortably repay the loan, and someone else can earn $10000 and struggle to repay. The difference comes in because of responsibilities. The individual earning $5000 may have no dependents and no huge costs, meaning that he/she had much money to spare. The individual earning $10000 may have several dependents and other bills that need to get paid to mean that the money may be a lot, but the responsibilities this individual has surpassed the amount earned. This analogy is what inspired my research. Some researchers agree with me that others do not. Ratcliffe&McKernan (2015) agree with me. They assess the type of people worried about repaying their loan. They identify several groups, one of which being people with financially dependent children meaning that once a person starts a family, their repayment rate decreases significantly.
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Scott-Clayton & Li (2016) don’t agree with me. According to them, racial differences play a significant role in student loan repayment. Scott-Clayton & Li claim that after graduation, African-American accumulate a debt of $7400 more than the white counterparts. Studies show that the main reason for this disparity is employment opportunities. Whites are presented with more employment opportunities than African Americans, which puts them at a position of being able to repay the loan. Recent studies work under the theory that the unpredictability of the labor market plays a contributing factor in the ever-increasing student loan debt. The findings of past studies are consistent in that most of them identify factors such as income, type of institution the student attended, racial disparities, and whether or not the individual completed the degree program for which they took out a loan to study. Prior studies concentrated on the labor market and never concentrated on personal issues. My research will not only look at the labor market but will also asses personal responsibilities as a contributing factor to the ever-increasing student loan debt.
Recent studies show that income, race, background, and whether or not the person has a college degree play an essential role in determining the repayment rate. The studies show that people with high income repay the loan at a much faster rate than people with a low income. Racial groups affect the repayment rate in that blacks have a lower repayment rate than whites. In comparison, African Americans have a higher debt than whites. Hispanics also fall in the same category as blacks. This high rates in blacks and Hispanics show that Hispanics and blacks still find it hard to integrate into the workforce after graduation than the whites. Racial discrimination in the workplace is still rampant, which explains why these minorities find it hard to get jobs after graduation. Background plays a role in that person from a low-income family lack the funds to pay for tuition and upkeep, which makes them take huge loans. After graduation, they find themselves with high debt, and with the unpredictable labor market; it takes them a while to offset the debt that they accumulated in college. Finally, some individuals take out a loan, but they drop out before they can complete the program. Between the dropouts and those who stick it out and get the degree, those with a degree repay the loan at a much faster rate than those who did not graduate. Those with a degree are at a better chance of getting a well-paying job than those who did not make it easier for them to offset their debts.
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With this information, I expect to prove my hypothesis that age does affect the repayment rate. The hypotheses I am working with is that as people grow old, responsibilities increase, which makes it hard for them to pay their loan. When a person is younger, and they don’t have a lot of responsibilities or dependents, it is easier for the person to fit the student loan debt into their budget. Also, many people like to offset the loans so that they can focus their money on other investments that will help grow their wealth. The reason why I explored this line of thought is that as one grows older, they want to do things like buy a house, start a family, and invest, among other things. These items need to get financed, and if the student has a debt, it becomes hard for them to pay the loan because they need to fund particular necessities.
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The X and Y variables in my research are age and student loan debt. I will mainly look at whether age and loan repayment rate relate. I want to prove that younger people pay their student loan debt at a much faster rate than middle age or older individuals. I will look at the student loan debt for each age group between 25yrs and 45yrs. When drawing the graph with age in the X-axis and student loan debt in the Y-axis, I believe that the graph will show a positive correlation. The student loan debt is the dependent variable, and the independent variable is age.
The three additional questions and answer sets to get used in measuring the variables include:
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1) 25-29
2) 30-34
3) 35-39
4) 40-45
1) $0-$5000
2) $5001-$10000
3) $10001-$15000
4) $15001-$20000
5) $20001 and above
1) Weekly
2) Monthly
3) Bi-monthly
4) Quarterly
5) None of the above
As can be seen from the above set of questions, the respondents will choose from the answers provided. Also, the information collected won’t look at specifics but will categorize the answers for easy analysis. For example, in question two, where the student is asked about their outstanding debt, the student won’t provide the specific figure of their outstanding debt but will choose the rank in which their debt fits.
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The research will also make use of composite measures. The measure that will get used in this research includes indexes. As is always the case, indexes depend on the aggregation of indicators used in the research. The indicators in this research include age, number of dependents, income, other financial obligations. When combining the indicators, I will use the average function because it provides a better understanding of the indicators and how they interact. Also, composite measures are done using the average function. The highest value on the composite measure will indicate low student debt, while low measures will indicate high student debt. The advantages of my design are that it is simple to analyze the data. In calculating the index, I won’t need to perform complex calculations. Also, it is easier for the reader to interpret. The disadvantage is that there are many generalizations. It would be hard to have the specific figure of the student debt accumulated by the student.
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The population under study is individuals who have graduated from college/university but are yet to offset their student loan debt. When conducting the research, I will sample the population since I can’t reach all the people in the category. I will make use of the simple random sampling technique. My sample will include individuals between 25 and 45 years of age. The size of the population to partake in the survey is 500 people. The participants will be randomly selected from the list of debtors I will have at hand. There won’t be any specific characteristics that will determine the inclusion and exclusion of an individual. The only reason that might lead to the exclusion of someone fitting in that age group is if they graduated in the past two years. The sampling technique that I chose is appropriate because I want to give each person an equal opportunity to participate in the research, but it also has its flaws. The research I will be conducting will include a large population, and this method can be disadvantageous with a large population (Robinson, n.d.). For the information gathered to be completely accurate, I will need a list of all the people fitting my target population, but it will be impossible for me to get a hold of that list.
The research encountered certain problems; for example, some participants wanted compensation for partaking in the study, some were skeptical and thought that we were after them because of their debt; some people took too long to resend the filled application questions, etc. In the future, I would try and be clear to the respondents that we are not after collecting the debt but conducting a survey. Also, I would try and provide incentives to the respondents to motivate them to submit the survey answers on time. The changes I would make in a future study is to include individuals with student loans, yet they did not complete their college education. The project will require funding because I need to motivate the respondents by giving them incentives. The future study will help the people to understand why individuals who did not complete their college education have high student loan debt despite having a high income.
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