Wages and Education - Identifying the Hypothesis of Three Separate Articles

Wages and Education - Identifying the Hypothesis of Three Separate Articles

The following paper is identifying the hypothesis of three separate articles. The selected articles in this essay are related to wages of individuals. The first article analysis is titled “Human Capital vs. Signaling Explanations of Wages” in the article the authors explain the differences of sorting models and human capital models in the work force. The second article is “Difference in wage levels among metropolitan areas: Less-educated workers in the United States” the article describes how five characteristics affect the wages of individuals in the United States. After identifying the hypothesis of the articles the next step is to test the hypothesis using T-test, ANOVA, and chi square. At the end of the testing the students interpret the results.
”Human Capital vs. Signalling Explantions of Wages.”

In the Fall of 1995, The Journal Of Economic Perspectives published an article on employees that have higher education, earn higher wages than those who don’t. The wage differences are attributed to schooling and work history. The states that well educated employees are less likely to resign or to be absent. These employees are also less likely to smoke, drink and use illegal drugs. The article attributes the levels of education to unfavorable employees. Singnalling and screening serve to “sort” workers according to their unobserved abilities (Weiss, 1995).

The “sorting models” is viewed as an extension of human capital models. However there is a difference among both. The human capital theory concentrates on the role of learning in determining the return to schooling. The sorting model serves as a signal or filter for productivity differences that firms cannot reward directly (Weiss, 1995). Empirical regularities are better explained by learning or sorting considerations. The article examines the correlation between wages and education. The relationship between wages and job tenure is also examined.

The positive relationship between wages and schooling is directly attributed to higher education. This is associated to skills learned during the later years of schooling. According to Altonji’s (1995) research using data from the National Longitudinal Survey, he estimated that the “increase in earnings associated with particular courses holding years of education fixed” (Weiss, 1995). It was evident that demographic characteristics play an important role in secondary schooling. Evidence presented by Weiss (1988), shows that all of the relationship between high school graduation and earnings can be explained by the lower quit propensities and lower rates of absenteeism of high school graduates (Weiss, 1995).

Education improves productivity in certain technical and managerial jobs. However education alone does not justify labor productivity.
The hypothesis for the article “Difference in wage levels among metropolitan areas: Less-educated workers in the United States”, is Our empirical work suggests that all five factors influence the relative wages of less-educated workers, but that the industry mix and unionization plays the biggest role. The five factors that are being studied are minimum wage, unionization, the strength of labor demand, industry composition and demographic composition. The researchers from the article accepted the null hypothesis and rejected the alternate. The category of minimum wage was divided in three groups which were: less educated than a high school diploma, high school diploma, and bachelors degree. The minimum wage factor affects the less educated workers by a ten percent increase in minimum wage affecting the less educated worker between one and four percent. Unionization was the factor that affected the men with less than a high school education. Forty percent of the total effect of the unionization on less educated men’s salary is increased by bargaining power or increased threat effects. Labor demand has a moderate positive impact on wage levels. The labor demand raises wages for less-educated workers and the labor demand impacts men more than women. Industry composition appears to be the single most important influence on the wages of women, with the three high-wage industries: finance, insurance, real estate. The demographic composition appears to have no important impact on metropolitan wage levels. The studies did back up the hypothesis of the researchers.(Easton, 2000)

Does education give you all the skills you need to make the capital you want? The Job Competition Theory (Thurow, 1975) it assumes that work-related skills are mainly acquired on the job and not on education. Although the majority of these skilled workers are older they are not as educated as younger employees that are coming in. More and more employees that are coming into the work force are coming in educated and are throwing off wages for all the skilled workers. According to the March Current Population Survey people that have 4 or more years of college evidently make money that people with high school diplomas. Employees with 16 years of education generally make 60% more than a high school graduate that has 12 years of education. If you are a high school dropout even with the job skills developed they will make 32% less than someone with a high school diploma. According the Economic Review there are only three elements that were measured high school graduates, some college and college graduate. According to the review high school graduates made no more than $19,000, employees with some college make at least 20% more which place them at $22,500 and employees with a college degree like previous stated make 60% which is over $35,000.

Reference
Weiss, A. (1995, Fall). Human Capital vs. Signalling Explanation of Wages. The Journal Of
Perspectives, 9(4), 133-154.
Easton, T., & King, M. C. (2000). Differnce in wage levels among metropolitan areas: Less-
educated workers in the United States. Regional Studies, 34.1
Rupert, Schweltzer, Lossin, Turner. (1996). Earning, Education and Experience. Economic
Review 1996. Retrieved from Google Scholar http://clevelandfed.org