How physical appearance impacts athletes’ income.

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How physical appearance impacts athletes’ income.

Category: Accounting

Subcategory: Design

Level: Masters

Pages: 1

Words: 550

Review of literature
As Dr. Daniel Hamermeshput it: “Modern society is obsessed with beauty” (Hamermesh, 2011, p. 3).In 2005, the average American husbandspent 32 minutes of his day bathing, dressing, and grooming. Meanwhile, the average American wife spent 44 minutes engaging in these activities on a daily basis.Additionally, no age limit on vanity was found. The average single American woman, age 70 and older, devoted43 minutes daily to these activities(Hamermesh, Frazis&Stewart, 2005).
Modern society also spends billions on beauty enhancing products. According to the 2008 Consumer Expenditure Survey, the average American household spent $718 on women’s and girls’ clothing, $427 on men’s and boy’s clothing, and $655 on infant’s apparel. Such spending totaled roughly $400 billion and accounted for nearly 5% of all consumer spending that year (Hamermesh, 2011).
The crucial role of beauty in society was evident in the results of a 2004 telephone survey conducted in the United States. According to these randomly selected respondents, discrimination based on physical appearance and economic status was more predominant than discrimination based on ethnicity. In the same way, this cohort reported having been victims of discrimination based on appearance more frequently thanany other form of discrimination(Kuran&McCaffery, 2004).
The importance of physical appearance expands worldwide. In China, for the 2008 Summer Olympics, producers put a cutter girl on stage and had her lip-sync the singing of a less attractive child (Hamermesh, 2011).In Brazil, women are held to unrealistically high beauty standards.At the same time, however, there is a common belief that all women have the right to beauty. Therefore,it is almost the norm for Brazilian women between the ages of 18 to 65 to resource to plastic surgery and each year approximately 30% of theseprocedures are subsidized by the government. In 2010, more than 1.2 million plastic surgeries were executed, making this country the second largest consumer of plastic surgery in the world(Edmonds, 2010).
Because ofthe social concern, beauty was a topic that sparked the interest ofDr. Daniel Hamermesh.From an economic standpoint, he describedbeauty as a scarce resourcedue to: (1) genetic differences in people’s appearances, and (2) socially-constructed criteria used to differentiate good looking people from the rest. Additionally, he usedphysiognomy as a basis for judgment about human beauty and believedin a substantial agreement worldwide on what constitutes human beauty. As a result, he argued that since beauty was scarce and tradable, then all labor markets generated premium pay for good looks and pay penalties for bad looks(Hamermesh, 2011).
When economist Hamermesh first tested this hypothesis via a survey in the 1970s, which captured the response of 1,495 American women and 1,279 men between the ages of 18 and 64, the results were supportive of it. Once earnings were compared to the ratings of participants’ looks, it was found that below-average looking women (rated 1 and 2, on the 5-point rating scheme) earned 3% less than the average looking women (rated as 3, on the 5-pointrating scheme). Below-average looking men, on the other hand, earned 22% less than the average. Also, above-average looking women (rated 4 or 5, on the 5-point rating scheme) earned 4% more than the average looking woman, while the above-average looking men earned 3% more(Hamermesh, 2011).
In a study that examined whether the economic returns of beauty in Australia changed between the 1980s and 2000s, it was found that such a “beauty premium” was constant(Borland & Leigh, 2013).In 2018, Czech researchers Anyzova and Mateju also examined the role of attractiveness in the labor market of their native country. Their purpose was to test whether a positive correlation existed between attractiveness and earnings even when cognitive skills, social background, occupational status, and individual characteristics were controlled for. This study used data from the Czech Republic’s first-large scale survey built to measure attractiveness. The results gathered supported the researchers’ hypothesis. Primed age women, or women between the age of 30 and 35,who were considered above-average (top 25% on the attractiveness scale) earned 15% more than the below-average looking women (bottom 25% on the attractiveness scale). “The difference in income between primed-age men of above-average and below-average attractiveness was 9%”(Anyzova&Mateju, 2008, para. 12).
Mobius and Rosenblat (2006)discovered three reasons as to why the beauty premium exists. According to their results, (1) Physically attractive workers were more confident and higher confidence helped increase their wages. (2) Physically attractive workers were wrongly considered more able by employers. (3) Physically attractive workers had better oral skills including social skills, which facilitated raises duringthe wage negotiation process.
Salter, Mixon, and King (2012)also explored this topic using data from the real estate industry. Their analysis suggested that beauty and transactions were negatively correlated since more attractive agents completed fewer sales than their counterparts. Nonetheless, it was found that more attractive agents generated a higher dollar value per transaction than their counterparts. Therefore, it was concluded that beauty complemented agents’ production-related characteristics, which is why they produced a clearly superior outcome (Salter, Mixon& King, 2012).
In 1994, the beauty premium phenomenon encouraged Hamermesh and Biddle to examine whether it was gender sensitive or not and the data suggested that it was. The 9% of working men participants perceived as homely or below-average looking gotpaid 10% less hourly, other things equal. The 32% considered as handsome or above-average looking earned 5% more, other things equal (Hamermesh& Biddle, 1994). “Among women there [was] some evidence of premium for good looks, with an average of about 4%. The penalty for bad looks was only 5%” (Hammermesh& Biddle, 1994, p. 18).Consequently, they concluded that men were penalized more for bad looks than women were. Such a conclusion contradicted Wong and Penner’s (2016), who found that women were rewarded twice as much than men for their good looks.
Since Dr. Hammermesh’s work mainly focused on the impact that physical appearance has on the income of traditional professionals,this paper will examine whether the “beauty premium” exists among professional athletes as well.
As there was no any other published survey data on athletes’ looks and their income, I had to conduct the survey physically. The participants in the study were all athletes from local basketball and soccer teams in the area who included players and coaches. Local participants were chosen mainly due to budget and time constraints. While as a researcher, I would have loved to find out how famous athletes in fancy clubs were paid based on their looks, this would not have been possible in the present circumstances. Each participant was first explained the details of the study and what it aimed to achieve as well as their expected role.
Physical contact was made with them before the actual survey to seek consent. This was done over a period of one week until I was sure I had the right number of participants. It is important to note that no individual approached declined to be part of the study. The initial sample was 50 individuals, but after considering time and resource constraints, this number was cut down to 28. This was because interviews had to be conducted physically with the athletes. This sample is consistent with Hogg & Tanis (2014) who argue that a minimum sample of 25 to 30 individuals is satisfactory. It was important to ensure the research used the right number to maintain and secure the validity of the results and survey in general. From the sample, 10 were female (35.7%) while 18 were male (64.3). Race and age considerations were also made. The participants were observed and interviewed on the club premises. The area or location of the interview and observation depended on the convenience and comfort of the participants. This was important in ensuring that they were as comfortable as possible when responding to the questions asked.
Interviews were chosen along the observation method in the survey to ensure that the responses were got on time. It was determined that the response rate might have been low if questionnaires were used as the researcher had no control over the respondents. It would also not have been possible to push them to respond and send the questionnaires on time. Qu & Dumay (2011) are of the opinion that interviews are one of “the most important data collection methods” that are different from the conversations held on a daily basis. The researcher observed the participating athletes physically to determine their level of “handsomeness” or “beauty”. The participants had to be categorized on a five-point scale basis with looks ranging from “beautiful” or strikingly handsome” to “homely” in line with Hamermesh and Biddle (1994). The categories were as follows:
1) Strikingly handsome or beautiful
2) Good looking for the age
3) Average for age
4) Quite plain5) Homely
The observation was done while the interview was continuing. To minimize bias on my side while analyzing the physical looks, I took along a visiting student to offer the balance. The physical ratings were then adjusted on an average basis. Interviews were conducted to determine the number of control variables that would be essential for the study. It was determined that factors like the experience or number of years in the club might have had an impact on the earnings. Others might have been the qualifications from soccer academies or coach training institutions. The perception of the participant regarding whether their physical appearance had a hand in the income they earned was also important. Among the questions asked were “How many years have you been at this club? “Did you perform well in any sports academy you might have attended?” “Do you think your looks determine the salary you make?”
Data Analysis and Design
Once data was acquired, a descriptive analysis was made to describe the observations. Correlation analysis was then made to determine whether the different variables were related in a significant way. The dependent variable was income while the independent variable was physical appearance. Control variables included experience, achievements, and qualifications. Regression analysis was then done to determine whether there was a relation between the various variables used in the study.
Anyzova, P., &Mateju, P. (2018). Beauty still matters: The role of attractiveness in labour market outcomes.Sage Journals, 33, 269-291.
Borland, J., & Leigh, A. (2013). Unpacking the beauty premium: What channels does it operate through, and has it changed over time? Economic Record, 90, 17-32.
Edmonds, A. (2010). Beauty, Sex, and Plastic Surgery in Brazil. North Carolina, NC: Duke University Press.
Hamermesh, S. D. (2011). Beauty pays: Why attractive people are more successful. Princeton, NJ: Princeton University Press.
Hamermesh, S. D., & Biddle, E. J. (1994). Beauty and the labor market. American Economic Association, 84, 1174-1194.
Hamermesh, S. D., Frazis, H., &Stewart, J. (2005). Data watch: The American time use survey. American Economic Association, 19, 221-232.
Hogg, R., & Tanis, E. (2014). Probability and Statistical Inference (9th ed.). london: Pearson.
Kuran, T., &McCaffery, J. E. (2004). Expanding discrimination research: Beyond ethnicity and to the web. Social Science Quarterly, 85, 713-730.
Mobius, M. M., &Rosenblat, S. T. (2006). Why beauty matters.American Economic Review, 96, 222-235.
Qu, S.Q. & Dumay, J. (2011). The qualitative research interview. Qualitative Research in Accounting & Management, 8(3), 238-264.
Salter, P. S., Mixon Jr., G. F., & King, W. E. (2012). Broker beauty and boon: A study of physical attractiveness and its effect on real estate brokers’ income and productivity. Applied Financial Economics, 22, 811-825.
Wong, S. J., &Penner, M. P. (2016). Gender and the returns to attractiveness. Research in Social Stratification and Mobility, 44, 113-123.

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