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Is a woman's earning potential equal to that of a man - Research Paper Example

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Variations in levels of income have been an inspiration for much empirical research and debate ever since the mid nineteenth century. In addition, statistics and figures for analyzing variations in income levels have since increased in availability…
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? March 9, Is a Woman’s Earning Potential Equal to that of a Man? Variations in levels of income have been an inspiration for much empirical research and debate ever since the mid nineteenth century. In addition, statistics and figures for analyzing variations in income levels have since increased in availability. Many factors affect the earnings that individuals make, including level of education, gender, race, social backgrounds, and occupational differences. In studies to disentangle discrepancies in annual incomes between men and women, a significant portion of the difference remains unexplainable and highly controversial. Many researchers attribute the unexplained variation to gender discrimination in the workplace, although numerous research efforts try to explicate the particular elements that contribute to the unexplained variation. This report focuses on determining whether women and men have any significant differences in their annual incomes for determinate years of education. Introduction The advances feminist movements have made a significant contribution to the income parity for men and women over the last few decades. The income gap for women and men started to decrease or significantly in the 70s. For 1980 to 1990, income disparity stood at 60.2% and 71.6%, a 3.4% increase (Carmen, Proctor & Smith, 50). From 1990 to 2000, the change was from 71.6% and 73.7%, a change of 2.1% (Carmen et al, 50). From 2000 to 2010, the ratio of women to men’s income rose from 73.7% to 77%, a 3.3% upsurge (50). However, significant differences still abound in the income levels between men and women, especially for high paying jobs. According to a report in the New York Times, in the late 2009, for jobs paying over $100,000, the income disparity widens considerably (Rampell, 1). The Bureau of Labor Statistics reported that women made 80% of what men made. Sample of men and women showing Number of years of education and annual income In a research done be PayScale, an online for workers to compare their salaries against other people working on the same jobs, the users self-report their own salary data (Rampell, 1). The study uses five categorizations for men and women using five educational levels. According to each level of education, the number of years varies. Up to bachelors level, the years of education are more determinable, but for masters and PhD degree programs. According to a research by the Bureau of Labor Statistics, analyzing the income anomalies between women and men, the comparisons were against level of education or years of learning. Income levels and years of learning for women (US Census Bureau, 1) Educational Level Years of Education Women’s Income High School 12 21,117 Some College 14 25,185 Bachelor's 16 36,532 Masters 18 45,730 Doctorate 20 54,666 Income levels and years of education for men (US Census Bureau, 1) Educational Level Years of Education Men’s Income High School 12 32,085 Some College 14 39,150 Bachelor's 16 52,265 Masters 18 67,123 Doctorate 20 78,324 A comparison in income levels for men and women (US Census Bureau, 14) Educational Level Years of Education Men’s Income Women’s Income Average Income Women as a % of Men's 1 High School 12 32,085 21,117 26,601 65.8% 2 Some College 14 39,150 25,185 32,168 64.3% 3 Bachelor's 16 52,265 36,532 44,399 69.9% 4 Masters 18 67,123 45,730 56,427 68.1% 5 Doctorate 20 78,324 54,666 66,495 69.8% Background on the number of years of education and annual income The number of years of learning a person has considerably affects a person’s annual income level. As the number of years of education increases, the income also increases, although inherent differences still exist within these differences. For instance, persons with a bachelor’s degree tend to earn almost double the incomes of high school graduates. According to a 2005 study on income and gender by the Bureau of Labor Statistics (US Bureau of Labor Statistics 2), women of similar educational levels with men earned significantly less in comparison to their male counterparts. The differences in income gap on this front rose with an increase in number of years spent learning. For instance, women with master’s degree had incomes of over $5,000 less when compared to their male counterparts with just a bachelor’s degree. Against their male counterparts with master’s education, the women had over $15,000 less in average income. Other factors against which income levels vary against educational levels include race and ethnicity, experience, interstate differences and occupational differences. Of particular concern for many researchers are the gaping variations in the income differences between men and women, even after provision for other income influencing factors. As of 2009, women in the United States made 77% of what men made, a figure consistent with one reported the previous year (US Census Bureau 50). In the research, conducted by the United States Census Bureau, men made an average of $47,127 while women averaged at a considerably lower $36,278. However, this figure does not account for skill, experience and the level of education or the hours worked, the only consideration was that the job was full-time. The conclusion of the study was, therefore, the wholesome presumption that the differences were because of gender discrimination. The conclusion is not definite, and the interaction and interplay with other factors requires considerable analysis. However, prior studies have found the disparity unexplainable above a certain level. This report tries to compare income gap disparity for men and women with regard to their level of education. Gender pay disparities are also attributable to the age of the women involved. For instance, fresh graduates in their early twenties earn the highest salaries in comparison to their male colleagues, making about 92.5% the salary of their male colleagues (Bureau of Labor Statistics 9). As the years go by, women’s salary falls to about 75% that of the male colleagues. In an independent study by Queens College (Sam 1), fresh female graduates starting in their careers actually made more than their male colleagues did. For instance in Dallas, women earned about 120% of what men made, a similar trend is observable in states like New York, Chicago, Boston, and Minneapolis (Sam 1). However, larger number of women attaining college education, especially in urban setups, explains the higher salary discrepancy. On a national scale, the age group, of women between 20-24 years, earned 89% the salary of the male counterparts (Sam 1). Despite the seeming conclusiveness of years of education as a satisfactory parameter in comparison of the gender pay disparities, the innate nature of education also plays a major role in the level of income for men and women. Stereotypes abound in course choices women take in higher levels of education, and with the acknowledged impact, occupational variations have on income levels, women pay levels vary wildly in comparison to the men’s for similar years of education. Possible Explanation in Differences in pay between Men and Women Admittedly, the gender differences in pay gaps are explainable by a range of factors that affect men and women’s labor trends. However, even after allowing for explained differences, there were consistent factors that contributed to the difference between the pay gap of men and women. The committee believes that discrimination against women accounts for the unexplained variation. The impact of the attribute to the gender pay disparities is still indefinite. However, a research by the Yale University places the significance of the explained factors at just 27%, another study by the Michigan University estimates that women make just 81.7% of what men make after making adjustments for variations in demographic variations, family situations, job permanency, and work experience (Robert, Corcoran and Courant 417). A number of studies suggest that the differences in income disparities between men and women are traceable to their gender-based social impacts. For instance, in a research by a renowned economist June O’Neill, young women, who were just starting on their careers and without children, earned around 98% the amount of income their male counterparts made (O’Neill 4). The study also claimed to have found a bare 8% of unexplained variation in the gender significance to the pay scales for men and women in comparable labor environments, after adjusting for other factors affecting personal incomes (O’Neill 4). Career progression, a factor that indisputably affects the pay of individuals, appears to work against women in the labor market. For instance, in a research to investigate the promotion trend among women and men with similar qualifications in terms of experience and level of education, the research pointed to the fact that women were significantly less likely to get promotion than men were. Promotion goes hand in hand with an increase in pay, and, therefore, women with similar qualifications and years of experience earned less on average because there were less promotion opportunities given to them when compared to men. In addition, employers steer women into low-paying jobs and men into high-paying jobs. Stereotypes that discriminate against social groups such as ethnic minorities and status in society are also rife in the employment culture for women (Nicholas 1). Women, just like some groups of ethnic minorities face a multitude of stereotypes in relation to their work-related competencies. Studies seeking to pitch the performance of men and women in the workplace consistently suggest that men get better ratings as employees from most clients by up to 19% (Nicholas 1). The difference is despite the fact that the men and women had a similar experience level, level of education and work performance and work environments. Customers also report men to be more professional and approachable in comparison to women, a factor that also makes women’s career progression, and by extension, the pay levels to remain significantly lower than men’s salaries (Nicholas 1). The social biases whittle away any parity education might offer women in the workplace. Parental demands on women significantly dent their ability to reach pay parity with men average. Childbearing responsibilities demand more from women, and perpetuate some of the biases and unfounded stereotypes that plague women in the workplace. For instance, maternity leaves keep many employers from giving women positions in higher management levels. Men tend to suffer imperceptible impacts in their work performance and commitment because of parenting responsibilities. An even attempt to eliminate this form of bias by the introduction of paternity leaves for men has done little to mitigate this impact. A possible explanation for the persistent difference between annual incomes for men and women is the biasing reality of women assuming more active family roles in comparison to men who are more available for corporate duties. Therefore, they come off as less serious candidates for senior roles in organizations. According to the Bureau of Labor Statistics, married women make about 75.5% of what married men make, regardless of the level of education adjustment (US Bureau of Labor Statistics 14). Mean and standard deviation for the number of years of education The mean number of years for the samples is 16 years, while the standard deviation of 8 years of education. The Annual Income Mean and Standard deviation The mean for the level of income for men is $53,789 for men and $36,646 for women (through calculations from the above data). The average mean for both men and women is $44,789. Graph for annual income and years of education Scatterplot showing association of the number of Years of education and annual income Correlation Correlation between Income and Years of Education Men 0.9943 Women 0.9925 Average for Men and Women 0.9939 Correlation measures the relationship between two variables. Sometimes correlation implies causality, but not always. The correlation coefficient ranges between +1 and -1, where +1 implies a high positive relationship between the variables and the -1 implies a high negative relationship between the two variables. From the above calculations, it is apparent that when a person has more years of learning they also have higher of incomes. With closer observation, the relationship between years of education and annual income for women is lower than for men, meaning that more years of learning contribute more to the annual income a man earns in comparison to what a woman earns, although just marginally. Linear regression on the scatterplot Equation for the linear regression Let Y be the average annual income for both men and women in dollars Let X be the number of years of education Let a and b are constants, and b is the gradient of the line The value of a = $26,601, the lowest average income for both men and women, otherwise called the Y intercept The general equation is Y = a + bX The gradient is y/x, taking the average of y ($44,789) and the average of x (16), the gradient becomes 44,789/16 = $2,799.31 The equation of the linear equation is, therefore, Y = 26,601 + 2,799X Y is the annual income and X are the years of learning, the equation is for average values for both men and women. Recommendations The GAO (Government Accountability Office) proposes that the Department of Labor and Equal Employment Opportunity Commission needs to be more vigilant in perpetuating the enforcement and implementation of anti-discrimination laws with regard to gender in the US labor market (GAO 1). The unexplained percentage for the gender pay disparity, which accounts for the greater portion of the pay gap difference, is attributable to gender-based discrimination in the workplace. Conclusions The results from the above analysis conclusively establish that a woman’s pay is not equal to that of a man for similar educational levels. Gender-related pay disparities continue to subsist over an underlying multiplicity of factors. Many factors affect the income gap between men and women include occupational differences, length in working hours, job permanency, educational level, race and ethnicity, and interstate variations. While each of the factors plays a major role in the gender pay disparities, discrimination based on gender account for a significant portion of the pay discrepancies. Statistical analysis using graphical tools give credence to the fact that broad variations occur in the pay levels among women and men, even when all other factors are in consideration. From the scatterplot, we can see that there exists a positive correlation between the level of annual income and years of education. However, the correlation is higher for men than women, meaning women benefit less from higher number of years of learning in comparison to men. With the use of the linear regression line, it is apparent that the lowest annual income for men is $32,085, and $21,117 and an average of $26,601 for high school education level of learning, which involves 12 years of learning. The maximum for men is $78,324. Moreover, for similar years of learning, men earn significantly higher annual incomes than women do. In summary, income inequalities abound between men and women. Men earn consistently higher than women do for all levels in years of education. In addition, as the years of learning increase, the income disparities increase. For instance, on average, women with doctorate degrees earn less than men with master’s level degree earn. Consequently, women with master’s degree earn less than men with a bachelor’s degrees earn. The variations in annual incomes of women and men within the same educational levels are considerably bigger, with the biggest observable difference found among people with doctorate education, who have 20 years of education at $23,658. Works Cited Carmen, D, Proctor, B and Smith, J. Income, Poverty, and Health Insurance Coverage in the United States: 2009. Census Bureau. 2009. P. 50. Web. 9 March 2012 < http://www.census.gov/prod/2010pubs/p60-238.pdf> Fawcett, C. “Did women’s Lib Movement Increase Income Gap in the US?” Freakonomics.com. 2011. Web. 9 March 2012 < http://www.freakonomics.com/2011/07/20/did-womens-lib- movement-increase-income-gap-in-the-u-s/> GAO. “Women’s Earnings: Federal agencies should better monitor their performance in enforcing anti-discrimination laws”. GAO. 2008. Web. 9 March 2012 Nicholas, B. “A customer bias in favor of white men”. New York Times. 2009. P. D6. Web. 9 March 2012 O’Neill, J. “What do wage differentials tell us about labor Market Discrimination?” NBER Working paper no. 11240. 2005. Web. 9 March 2012 Rampell, C. “Women Earn Less than Men, especially at the Top”. The New York Times.2009. Web. 9 March 2012 < http://economix.blogs.nytimes.com/2009/11/16/the-gender-pay- gap-persists-especially-for-the-rich/> Robert, W, Corcoran, M, and Courant, P. Pay differences among the highly paid: the male- female earnings gap in Lawyers statistics. Journal of Labor Statistics. 1993. P. 417. Print. Sam, R. “For young Earners in Big City, a gap in women’s favor”. The New York Times. 2007. Web. 9 March 2012 < http://www.nytimes.com/2007/08/03/nyregion/03women.html?ex= 1343793600&en=8941c5442f49a9a4&ei=5088&partner=rssnyt&emc=rss> US Bureau of Labor Statistics. Highlights of Women’s Earnings in 2009. US Bureau of Labor Statistics. 2010. Pp. 9. Web. 9 March 2012 < http://www.bls.gov/cps/cpswom2009.pdf> US Census Bureau. “Personal income distribution for males, age 25+ according to educational Attainment”. US Census Bureau. 2006. Web 9 March 2012 < http://pubdb3.census.gov/macro/032006/perinc/new03_127.htm> US Census Bureau. “Personal income distribution for females, age 25+ according to educational Attainment”. US Census Bureau.2006. Web 9 March 2012 < http://pubdb3.census.gov/macro/032006/perinc/new03_253.htm> US Congress Joint Economic Committee. “Invest in Women, Invest in America”. US Congress Joint Economic Committee. 2010. p. 80. Web. 9 March 2012 < http://jec.senate.gov/ public/?a=Files.Serve&File_id=9118a9ef-0771-4777-9c1f-8232fe70a45c> Read More
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