Summary: Often cited, but overly simplistic, comparisons of earnings between men and women fail to account for differences in hours worked, family commitments, occupational and life-style choices, not to mention the hazardous and arduous conditions of labor intensive jobs typically performed by men. When these differences are properly taken into consideration, it becomes clear that claims of widespread discrimination are baseless.
Discussion: In June 2011, President Obama claimed that2, "Women still earn just 77 cents for every dollar a man earns." This figure originates from the US Census Bureau report for the year 2010 which compares the median* full-time earnings of women to those of men3. A separate report by the Bureau of Labor Statistics (BLS) for the same year reports a different value of 81% for earnings ratio4. (The BLS report compared weekly earnings, whereas the Census Bureau report compared annual earnings.)
In the UK, the Annual Survey of Hours and Earnings for 2011 found that men's median full-time weekly earnings were £538, compared with £440 for women6. This yields a weekly female-male ratio of 82%, a value almost identical to that given in the BLS 2010 report in the US. However, the UK survey report doesn't quote this figure itself but, instead, calculates the pay gap using hourly median earnings (excluding overtime), and determines the value to 10.5%.
The narrowing of the pay gap as the time period used to measure it decreases can be explained by the fact that men work more hours than women in full-time employment. Indeed, the Annual Survey of Hours and Earnings for 2011 finds that men in full-time employment work on average 40.2 hours per week, compared with women who work 37.4 hours7, (i.e. men work, on average, 7.5% more). Furthermore, the survey finds the proportion of pay attributed to overtime and bonuses are significantly higher for men than for women8. The use of hourly earnings, excluding overtime, rather than weekly or yearly earnings, thus eliminates differences due to the hours worked and overtime rates, giving a more accurate result.
Nevertheless, an apparent pay gap of 10.5% remains, even when taking into account overtime and hours worked. The UK Home Office website provides an explanatory breakdown of this pay gap9, as follows:
- 22% is due to the different industries and occupations in which women work
- 21% is due to differences in years of full-time work
- 16% is due to the negative effect on wages of having previously worked part-time or of having taken time out of the labor market to look after family
- 5% is due to formal education levels
This leaves 36% unexplained by any of the above factors. Applying this proportion to the UK earnings ratio would leave an unexplained pay gap of only 3.8%. Although the UK Home Office, itself, admits that this differential as 'unexplained', it suggests that discrimination may be an important factor, but provides no justification for this claim.
For those working part-time, rather than full-time, the UK Annual Survey of Hours and Earnings finds that pay gap is negative at -4.8%. This means that women actually earn more than men for the same number of hours in part-time employment10.
Turning back to full-time employment, however, a study conducted by American and Korean researchers in 2004 investigated the reasons for the wage gap, including the unexplained proportion often attributed to discrimination. They concluded:11
"In simple models, personal and work characteristics account for two-thirds of the pay gap, but one-third is accounted for by other considerations. Many allege that discrimination explains this one-third. In particular, they allege that women are relegated to poor paying jobs, and thus women in general have lower wages because they are crowded into women’s jobs. In short, they claim occupational segregation is responsible for women’s inferior economic wellbeing.
"This study investigated the relationship between occupational sex segregation and wages. The empirical findings refute the claim that the number of women in one’s occupation negatively influences wages. Instead, the paper supports hypotheses relating to efficient job matching. Women choose female jobs to earn a relatively greater amenity package than they would have received elsewhere. Similarly men choose male jobs to earn relatively more."The figures reported by the US Census Bureau, the Bureau of Labor Statistics and the Office for National Statistics in the UK, all clearly show that men earn more than women overall. This is undeniably the case. However, often cited, but overly simplistic, comparisons of earnings fail to account for differences in hours worked, family commitments, occupational and life-style choices, not to mention the hazardous and arduous conditions of labor intensive jobs typically performed by men (men account for 92% of all workplace fatalities in the US in 201012). When these differences are properly taken into consideration, it becomes clear that claims of widespread discrimination are baseless.
In fact, according to the most recent US Bureau of Labor Statistics, nearly 4 in 10 working wives out-earned their husbands in 200913. Just what would it take to close the overall pay gap still further? Would national policies designed to restrict the numbers of men in high-paying jobs be needed, for example? Or, perhaps, would it be necessary to deny women personal freedoms concerning life-style and family so that they, in effect, have no choice but to spend more time at the workplace?
*Note. The term median is a statistical measure which refers to the midpoint in a sequence of observed data values. It is not the same as the average, or mean, value. It is generally accepted that the use of the median gives a more representative picture than the average value in many cases, especially where a few exceptionally high or low observed values (outliers) may skew the results.
1. Example: Pay Equity & Discrimination. Institute for Women's Policy Research. Link: http://www.iwpr.org/initiatives/pay-equity-and-discrimination/
2. White House (June 04, 2012). Remarks by the President on Equal Pay for Equal Work via Conference Call. Link: http://www.whitehouse.gov/the-press-office/2012/06/04/remarks-president-equal-pay-equal-work-conference-call
3. United States Census Bureau. Income, Poverty, and Health Insurance Coverage in the United States: 2010. Page 5. Link: http://www.census.gov/prod/2011pubs/p60-239.pdf
4. Bureau of Labor Statistics. Women in the Labor Force: A Databook, December 2011. Page 1. Link: http://www.bls.gov/cps/wlf-databook-2011.pdf
5. Heather Boushey (March 11, 2010). Strengthening the Middle Class: Ensuring Equal Pay for Women. Testimony of Heather Boushey (Senior Economist, Center for American Progress Action Fund) before the U.S. Senate, Committee on Health, Education, Labor, and Pensions. Link: http://www.americanprogressaction.org/issues/2010/03/pdf/Boushey_testimony.pdf
6. Office for National Statistics. 2011 Annual Survey of Hours and Earnings (based on SOC 2010). Page 1. Link: http://www.ons.gov.uk/ons/dcp171778_256900.pdf
7. Office for National Statistics. 2011 Annual Survey of Hours and Earnings (based on SOC 2010). Page 24. Link: http://www.ons.gov.uk/ons/dcp171778_256900.pdf
8. Office for National Statistics. 2011 Annual Survey of Hours and Earnings (based on SOC 2010). Page 23. Link: http://www.ons.gov.uk/ons/dcp171778_256900.pdf
9. UK Home Office (August 2012). Link: http://www.homeoffice.gov.uk/equalities/women/women-work/
10. Office for National Statistics. 2011 Annual Survey of Hours and Earnings (based on SOC 2010). Page 7. Link: http://www.ons.gov.uk/ons/dcp171778_256900.pdf
11. Soo Kyeong Hwang and Solomon William Polachek (2004). Occupational Self-Selection and the Gender Wage Gap: Evidence From Korea and United States. Link: http://www2.binghamton.edu/economics/wp04/WP0413.pdf
12. US Department of Labor, Bureau of Labor Statistics, Current Population Survey, and Census of Fatal Occupational Injuries, 2012. Page 10. Link: http://www.bls.gov/iif/oshwc/cfoi/cfch0009.pdf
13. Bureau of Labor Statistics. Women in the Labor Force: A Databook, December 2011. Page 78. Link: http://www.bls.gov/cps/wlf-databook-2011.pdf