Research Paper: Stability of Employment Education

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[. . .] These two arguments may actually prove the same cause.

Wheeler (2005) argues that "the fraction of workers in the United States holding jobs (defined by 174 industry-occupation cells) in the bottom and top tails of the distribution of average hourly pay increased between 1983 and 1993." The research conducted in this instance was a meta-analysis of studies done within an industry base that looked at how income was distributed among the workers of that industry alone. After examining the individual industries, Wheeler gleaned the above finding. He said that, "This finding, he concludes, indicates that workers have increasingly been sorted into "good" and "bad" jobs, which further suggests that rising inequality has been the product of growing between-sector dispersion" (Wheeler, 2005). Of course, even though the wage discrepancy in this case was more of a factor within a given industry rather than job market wide, Wheeler did acknowledge that the disparity had more to do with new technologies being introduced into those industries than any other reason.

The second researcher who conducted a meta-analysis of similar studies found that it was not within industry variance that accounted for the disparity in wages, but the technology itself. "Among the 30 (OECD) countries with the largest expansion of college education over the last decades, most still see rising earnings differentials for college graduates" (Schleicher, 2009). The earnings increased in this group of studies because it was done on a wider scope than those conducted observed by Wheeler. This was an international study that examined the Organization for Economic Cooperation and Development countries which are have some of the largest economies and worker bases in the world. Among the largest economies, only China is excluded (along with other population giant India). These countries have largest numbers of college graduates per capita, so the study may be slightly skewed from a true international sample. However, the finding that wages increased for those with more education is telling. Schleicher also stated that "an increase in knowledge workers does not necessarily lead to a decrease in their pay, as is the case for low-skilled workers" (Schleicher, 2009). This means that more people worldwide (especially in China and India) are getting college degrees. That should have caused such a global glut that the pay for these individuals would have evened out over time, but it has not. This is true at the same time that wages for people without a college degree are decreasing steadily worldwide.

Thus, since there is evidence that points to multiple causes for the disparity in wages, there is no easy solution. It is equally apparent that if a person continued through graduate school, that they will earn even more over a lifetime. Maki (2009) found that "If examined on a monthly basis (across all employment sectors), the average is a $2,000 difference between doctorate and master's degree holders and a $1,000 difference between the master's and bachelor degree holders." Graduate degrees are desirable because even though they are more expensive, they bring a monthly income increase that will make up for the expense in a very few years. Maki (2009) also found that benefits for advanced degree holders exceeded pay. He said that

"Beyond issues of hiring needs and lifetime earning potential, advanced degrees provide other advantages such as:

* Opportunity to realize full potential.

* Wider employment opportunities and options.

* Visibility as it distinguishes individuals.

* Validation of academic abilities.

* Options for making career changes.

* Opportunity to study with experts in the field"

Since the average worker will change jobs multiple times in the new economy, having an advanced degree means that transition is much easier. This increases earning potential and experience. Companies are also providing added incentives to these advanced degree holders because they represent a large investment and are difficult to replace, thus adding to the income disparity between them and other workers.

Another issue that must be discussed, but is slightly beyond the scope of this research is that women and minorities, even if they have the same degree, continue to earn less than white males. Kennedy & Vaughn (2004) found that "The median annual income for full-time working adults with a bachelor's degree is $14,848, or 28.9% less for women than for men." This is also true for people with disabilities (Appelman, et al., 2012) and older workers, especially those who reenter the workforce (Kennedy & Vaughn, 2004). Wage disparity seems to be a global constant that no one has found an equitable solution to.


A five question survey was presented to 33 people who held a variety of jobs. Of the 33, six were rejected due to time in career, time since degree completion and lack of service time in a single defined occupational sector. Survey data was taken from the 27 participants for the survey who ranged in age from 35 to 61. The age was limited to those people older than 35 so that the individual would have had more time to establish themselves in their career. This was especially important for those who had finished an undergraduate or graduate degree. The mean of years since graduation was kept above ten for the same reason. The sample was randomized for factors such as gender, ethnicity and job type. These variables were not important to the final analysis desired, so they were not added to the questionnaire or considered in any part of the study. Of the 27 participants nine had only a high school diploma, 13 had finished a bachelor's degree, and five had a graduate degree in some field. Incomes were based on an estimated five-year average and ranged from $17,000 per year to $126,000 per year. The five-year average was used to determine whether income at that level was stable, and to control for wide variations that may have occurred if the last five years had been taken separately.

The data was then examined using simple statistical measures that allowed the researcher to determine trends in the data. Means and standard deviations were obtained from the raw data and then a small analysis of variance was conducted to provide a more detailed view of differences. The results of the data are discussed in the next section.


The survey and question called for very basic statistical analysis that could easily be done using Excel. The printout with the means and standard deviations of the data are in Appendix C. The five participants who had completed a graduate degree had received markedly larger salaries than the other 22 participants the mean was found to be $68,200 and the average cost of their education was $80,200. The second group, those with a bachelor's degree had a mean salary of $53,000, and a mean education cost of $37,773. The diploma group earned an average of $26,577.78, and had a rather negligible mean education cost of $62.22. The reason that there was an education cost for two of the diploma graduates was because they had paid for a GED when they did not finish traditional high school.

It can be seen from these numbers that, as the literature has revealed, there was a hierarchical yearly earnings structure from graduate degree recipients, to those with bachelor's degrees, and then those with only a high school diploma completed. This data followed the hypothesis of the project, but it was more interesting to look at the standard deviations of the groups. There was not a wide variance for the high school group, but salaries were widely varied for both the undergraduate and graduate groups. This was so especially with the graduate group. This was also true of the education expenses for the groups. This demonstrated that degree type (which was not taken into account in the response) had a greater bearing on the earning potential than any other factor. This is inconsistent with the findings that income disparity is greater within industries than when it is looked at more globally. The cost of education depended on the degree the person attained, the school they went to (and whether it was private or public), and how long they spent in school getting the degree. These factors were consistent regardless whether the person was getting a BS/BA or an advanced degree.

A final calculation was made to control for the cost of education to determine if this evened out the relative earnings potential. Randomly assigning 20 years to the time that it would take to pay off student loans, each mean value of education cost was divided by those 20 years and that controlled mean was subtracted from the earnings mean. Although this did lower the expected earnings of the undergraduate and graduate populations, it did not even them out enough to conclude that the degrees themselves were not worth the expense. This calculation basically confirmed that cost of education was still worthwhile over time.


It is simple to conclude that level of education does increase potential earnings, but there… [END OF PREVIEW]

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Cite This Research Paper:

APA Format

Stability of Employment Education.  (2012, November 30).  Retrieved July 17, 2019, from

MLA Format

"Stability of Employment Education."  30 November 2012.  Web.  17 July 2019. <>.

Chicago Format

"Stability of Employment Education."  November 30, 2012.  Accessed July 17, 2019.