Introduction
There has been intensive research on the gender wage gap, yet much of the research has yielded different results. For example, according to the Institute for Women’s Policy Research (2016), in 2015 female full-time workers made only 80 cents for every dollar earned by men, a gender wage gap of 20 percent. However, a 2009 Report by CONSAD Research Corporation stated that the gender wage gap is quite narrow compared to other findings: between 4.8 and 7.1 percent. Why is it that we see different percentages of the wage gap? The reason we see wider gaps or narrower gaps is due to what variables are being controlled for. In the Women’s Policy Research data, the authors didn’t control for any variable except for “full-time employee.” This can result to a larger wage gap for several reasons. One reason is that type of occupation was not controlled for. Being a full-time carpenter versus a full-time physician will affect the wages of both men and women. Likewise, a full-time college professor will have higher wages than a full-time high school teacher. Another issue with the data was that not only did it take median wages for full-time men and full-time women without controlling for occupation, but they also didn’t specify the amount of hours each employee worked. Working full-time does not necessarily mean someone must work the maximum full-time hours. Companies commonly require from 35 to 40 hours per week to be defined as full-time (United States Department of Labor, 2016), and if an employee works 40 hours and another employee works 50 hours a week, then that will affect wages. In the CONSAD (2009) report, the researchers controlled for variables such as human capital variables (schooling and work experience), the family division of labor, compensating wage differentials, and gender differences in occupation. They also controlled for career interruption among workers with specific gender, age, and number of children. CONSAD (2009) stated, “Statistical analysis that includes those variables has produced results that collectively account for between 65.1 and 76.4 percent of a raw gender wage gap of 20.4 percent, and thereby leave an adjusted gender wage gap that is between 4.8 and 7.1 percent.” The main and probably the most important reason we see percentage differences of the wage gap across many studies is due to what is being controlled for. Taking the average wages of male employees and female employees will create a larger wage gap due to employees working different hours, whether or not they are full-time or part-time, which occupation they’re in, whether or not they take time off for family reasons (sick spouse, children), negotiation and many other factors. The more factors being controlled for, the narrower the wage gap gets.
In this post, I will discuss an overview of the wage gap and show that when controlling for many factors, the wage gap narrows by quite a lot. The variables that contribute to narrowing the wage gap are family status, gender differences in occupation, hours worked, human capital variables (education, age, and experience), salary negotiation, and differences in benefit coverages. There are still many factors that can influence the narrowing of the wage gap and although discrimination may be a possible factor of it, controlling or measuring every person’s individual decision could be difficult to accomplish. Since all possible factors cannot be fully controlled, we do not see the gender wage gap closing. We do however see the gap narrow down when controlling for the factors listed above.
Family Status
One important factor that affects the wage gap is family status of both men and women. With single men and single women (no kids), the wage gap is generally less than 10%, meaning that single women earn more than 90% of what single men make (Polachek & Xiang, 2014). This does not take into account occupation type and experience. When looking at age ranges and higher paying jobs (executive/director positions), women and men at earlier ages (20-35), hold a similar percentage of director positions, but after 35 the gap widens (Payscale, 2005). This is shown in Figure 1. Although Payscale (2005) mentioned that education and experience may affect the opportunity gap or wage gap, that doesn’t seem to fully explain why younger women are holding similar or the same positions as men in certain fields. It’s around the age of 35 where we see the gap widen.
 |
Figure 1 shows that
at the start of their career, men and women hold similar amount of Director
level positions, then widens at around 35, and then shrinks again at the age of
50. Source: Payscale (2005)
|
One factor that isn’t mention is family status and whether or not the woman is married and has younger children. There is a slight decrease in the gap after the age of 50 which could be due to the fact that someone’s child or children at that age are less dependent on the mother or the parents, thus allowing women to obtain director level positions. Women who have younger children may have to make certain sacrifices to ensure that their child is being taken care of.
Although single women and single men hold similar positions and the gap between their earnings are very narrow, Married women earn less than married men. There is a 30-40% wage gap between married women and married men (Budig and England, 2001). When looking further into that statistic it is shown that married women with children earn less than married women without children (Harkmess and Waldfogel, 2003). This may be due to the fact that the mother takes time off to be with the child especially if there isn’t child care available. Regardless of why the mother chooses to take time off of work (in regards to the child), there is a trend that married women make less than single women (Budig and England, 2001). Also, married women who space their births widely apart receive even lower wages (Polachek, 1975) than women who have children around the same time. This may be due to the fact that there is longer investment in both children since the mother will most likely take maternity leave for the first child to breast feed and be with the child for x amount of time and then will have to do this again years later. Waldfogel (1998) shows that having children lowers a women’s pay by about 10%, after controlling for age, education, experience, race, ethnicity and marital status. Budig and England (2001) find about a 7% wage penalty per child.
Not only do women on average take maternity leave (at least 6 weeks) to be with their children for the most essential part of the infant’s life, but they also tend to delay entering the workforce or go back part time to pick up the child from a child care center, relieve the babysitter, nurse the baby, and most importantly let their body physically heal from the birth process (Enz et al. n.d). Taking time off and coming back right away as a part-time employee will affect earnings if the mother was full-time before. Becker’s (1985) analysis focused on the longer hours that mothers tend to spend in activities listed above including taking care of the child, and found that these responsibilities (when controlling for hours) could reduce the effort that they put into their market jobs, and thus decreasing their hourly wages compared to men. Family status is one of the main factors that narrow the wage gap.
Gender Differences in Occupation
Occupation type is another measurable variable of the wage gap. Gender differences in occupation are shown to make up 50 and 60 percent of the raw gender wage gap (CONSAD, 2009). If for example, someone is a high school teacher versus a mechanical engineer, one will see a wage gap no matter what the sex of the individual is. If the teacher is a male and the mechanical engineer is a female, the mechanical engineer would most likely earn more than the teacher (if controlling for hours worked). When looking at occupational differences around the United States and other western societies, there is a larger gap between what males go into versus females (World Bank, 2011). When looking cross-culturally, especially in underdeveloped countries and Islamic states, the gap between occupation choice between men and women decrease substantially (World Bank, 2011).
 |
| Figure 2 Women in Tanzania enter the agriculture work force at a greater amount than women in Brazil. This may be due to economic patterns and growth. Source: WDR 2012 team estimates based on the International Income Distribution Database (I2D2). |
In Figure 2 above, it shows the female occupation difference between a low income country (Tanzania) with a GDP per capita of $439 and a middle-income country (Brazil) with a GDP per capita of $4,399. This graph illustrates the effect on occupation type women go into when considering economic growth (World Bank, 2011). In Tanzania versus Brazil, women are more likely to go into the field of agriculture. Although agriculture is one of the bases of both countries’ economy, fewer women choose to go into agriculture in Brazil. Why is this the case? Since Tanzania is still a developing country, agriculture is still a main component of the country’s growth (Haugen, 2009). Agriculture is responsible for three quarters of merchandise exports and gives jobs to about 80 percent of the population. Agricultural income is the main source of income for the poor, especially in rural areas (Sarris, et al., 2006).
Not only do we see similarities in the fields that men and women go into in developing countries, but when looking at some Islamic states such as Iran, Oman and Saudi Arabia, there is a trend showing more women going into a science based field (American Sociological Association, 2011) narrowing the gap between men and women going into science fields.
 |
| Figure 3 shows the percentage of women who graduated with science degrees depicted by the light green bar. Source: UNESCO Data Center, 2010 |
Figure 3 shows the number of female graduates and the percentage of women who graduated with a science degree. The most women who graduated with a science degree (more than 50%, closer to 70%), were women in Islamic states. When comparing these numbers to women in western societies such as the US, the numbers differ (US Bureau of Labor Statistics, 2016). Even though women receive more graduate degrees in the health and biological sciences as depicted in Figure 4 below, women make up less than 50% in the other sciences: Chemists and materials scientists (36.1%), Environmental scientists and geoscientists (27.5%), all other physical scientists (41.4%) (US Bureau of Labor Statistics, 2016). A flaw in Figure 3 above is that it does not show the type of science degree women in Islamic states graduate with. However, even if we consider this to be an average, women in Islamic states have passed the 50% mark. Does this mean that places such as Iran, Saudi Arabia and the United Arab Emirates have achieved gender equality in the fields that women and men go into? Not exactly. This somewhat relates to the reason why there are similarities in the field men and women go into in developing countries. One factor to why women in these Islamic states enter the STEM fields more often than women in western societies such as the US is because in these states, fields are limited. There are over 90 fields of study options ranging from physics to women studies at the prestigious university of Yale located in the US, and only 76 fields of study options at one of the well-known universities of Iran - Shiraz University - that mostly focus on biological and environmental science, physical science (chemistry, physics), engineering, business, finance, economics, education and law. The closest social science field they offer (excluding psychology) is sociology. Due to the limited amount of choices compared to a US university, Iranian women may decide to go into the most prominent field at the university which is mostly a STEM field. Also, another reason why women may go into the STEM fields more in Iran than the US may be due to the fact that in a more developing country (World Economic Situation and Prospects, 2012) where certain occupations receive the most income or will help one provide for their family, they might choose those fields.
As noted before, universities in the United States provide more options than developing countries or Islamic states. In this case, more options may mean more freedom in what to choose. If a woman in the United States decides to go into ethnic studies rather than engineering, that’s their decision to do so and they have the freedom to do so. However, this may mean that when you control for hours, someone who is an engineer for a company may earn more than someone who may be a teacher or professor for ethnic studies. Countries that don’t offer many fields in the humanities such as gender, women, and ethnic studies and specialize more in STEM related fields may see an increase in participation and graduation in those fields, regardless of sex.
Hourly Differences among the Same Occupation
One’s hours may affect their wages. If someone is working part time and another is working full time, you would expect that the person working full time would receive more wages (when controlling for occupation). What about when two people are working full-time? According to the IRS, the definition of a full-time employee is “an employee employed on average at least 30 hours of service per week, or 130 hours of service per calendar month.” Wages can differ for two full-time employees working the same occupation. If one employee is working 30 hours a week and the other is working 40 hours a week, then the person working more hours receives more wages. The main issue of some of the gender wage gap papers is that even when they control for occupation and state that their data is based on median earning of men versus women based on full-time hours, they don’t specify how many hours the individuals have worked. One example of this is from National Partnership for Women & Families (2016) which note that nationally the median annual pay of a woman who works full-time is $40,742 while a man’s medial annual pay is $51,212. Just looking at the differences of hours worked among individuals who are full-time employees could explain part of the discrepancy. Another aspect that is important that isn’t always noted in these studies is job title which can affect the amount one makes (Polachek, 1981). If two people work in the same field, yet one is a supervisor and the other is a position below them, the difference of their hourly wages might be small but will add up even when controlling for hours worked by both individuals. This can lead to an increase in annual salary of the supervisor versus the person below them.
There are studied differences between the hours worked on average by men and women. Men tend to work more hours than women. In comparison to men, women on average tend to work part time, especially when they are married or have children (Blau and Kahn, 2016). As stated above, women who are single tend to work similar hours to single men. When looking at wage and salary workers in 2013, it is noted that about 26% of women and 13% of men worked part time – less than 35 hours a week (Blau and Kahn, 2016). Although full-time jobs may not always be available for both sexes, this doesn’t fully explain why there is still a ~13% difference in part-time work/hours between men and women. A reason why this gap occurs could be due to flexibility of schedule (Matteazzi et al, 2013). One, women experience more interruptions in their career than men do (i.e. childbearing and childbirth) and this could be a greater variable in why women may drop out or reduce their time in the labor force. They may be searching for childcare or wanting to be there during early stages of infancy and so forth (Matteazzi et al, 2013).
Anyone working part-time compared to someone working full-time not only may have lower wages, but are most likely not unionized, don’t receive benefits and these can also affect wages and decisions in the labor force. Full-time employees who receive benefits may see different wages depending on compensation packages (Currie, 1995) or the amount of hours worked since full-time hours could range.
Education, Experience, and Age
There are other variables that contribute to the wage gap and although these factors do not affect the gap as much as occupation, hours worked and family status (Polachek and Xiang, 2014), these variables still influence the narrowing of the gap and thus should be discussed. Education, experience and age should not be separated from one another because they all reinforce each other. One’s education level may determine their age (if they have their graduate degree, they may be older than someone just receiving their bachelor’s degree). Age and education level may correlate with the amount of experience one has in the field they specialize in. Polachek and Xiang (2016) state that experience made up 8% of gender wage gap in 2010. They also found that in 2010, human capital variables which include age, education and experience accounted for 38% of the wage gap in comparison to 49% in 1980 (Polachek and Xiang, 2016).
Relating education to the wage gap may be difficult because the type of degree obtained matters, but there is also an importance of what field the degree is in. For example, getting a graduate degree in women’s studies may give someone the option of being a professor/researcher, teacher, journalist, and etc. however spaces are limited (HigherEd Jobs, 2017) and some occupations for women’s studies graduates may be more competitive than others. With occupations in the STEM fields, an individual may be able to obtain a career in a field with a bachelor or master’s degree (lab tech for chemistry and biology only require Bachelor’s degree). Some examples are nursing, engineering, computer science, mathematics.
According to the American Enterprise Institute, in 2015, women earned the majority of doctoral degrees for the 7th straight year; there is still a gender wage gap.
 |
Figure 4 shows
graduate degrees among men and women. Fields where women dominate over men are
listed in bold. Source: AEI's report on graduate degrees among male and female
students which used data from Council of Graduate Schools.
|
Some of the fields that women are getting their graduate degrees in may not be as economically demanding as an engineer or physicist for NASA. A field that is still highly demanded and that women are dominating in is the health sciences and more specifically, nursing. When taking account all 50 states, women make up most of the nursing field from ~70% in California to ~90% in Iowa (Kaiser Family Foundation, 2016).
However, when looking at the other fields women graduated from, women on average chose fields such as Arts and Humanities, Biological and Agricultural Sciences, Education, Social Sciences and other fields such as Communication Studies, Ethnic Studies and Gender Studies. In Mathematics and Computer Science, Physics, Physical Sciences, Engineering, and Business, women were less likely to go into those fields from undergraduate schooling up until graduate school. Although fields that women on average tend to gravitate towards are fields that may be demanding such as nursing and education, there is on average a higher demand for people in the STEM field such as computer science, mathematics, physicists and chemists (Glassdoor, 2015). Based on a Glassdoor 2015 list of the 25 highest paying and most demanded occupations, physicians, engineers, lawyers (especially engineers) were on top of the list. There are costs and benefits to entering an occupational field that may be financially beneficial, but inflexible. Working more hours (mostly full-time) may be favorable for an individual, however if there is inflexibility involved (constant deadlines, less time off), then it may be more difficult for women and some men to take time off for family related issues – whether it is childbirth, sick spouse, ill parents, and so on. Working fewer hours with a flexible schedule would be mostly advantageous if a woman is ready to start a family with her partner. She could take time off to be with the infant, to look for childcare, or to fully heal, even if it passes maternity leave time. Although this situation may not be ideal, it is still shown that women tend to work part-time more often than men or completely leave the workforce for family reasons (Pew Research, 2015). Data from Pew Research 2015 states,
“42% of mothers with some work experience reported in 2013 that they had reduced their work hours in order to care for a child or other family member at some point in their career, only 28% of fathers said the same. Similarly, 39% of mothers said they had taken a significant amount of time off from work in order to care for a family member (compared with 24% of men). And mothers were about three times as likely as men to report that at some point they quit a job so that they could care for a family member (27% of women vs. 10% of men).”
Regardless of the reason (although most seem to be family oriented, or being there for the infant during breastfeeding stage) why more women take time off or reduce their hours at work, it is shown that personal decisions relate to the gender wage gap. If on average more women (especially among married women or mothers) take time off or work less hours than men on average, there will be a decrease in wages of the woman than the man if controlling for occupation.
Salary Negotiation
One component to the gender wage gap may be due to salary negotiation on both sides. One who does not negotiate wages, salary, benefits and other packages, may not get them or may obtain a lower salary. In this case, someone who does not negotiate versus someone who does may end up with the short end of the stick. Studies have shown that women on average are more risk averse than men (Charness et al. 2012; Croson and Gneezy, 2009; Stuhlmacher and Walters, 1999). There may be some biological and cultural/social reasons why risk averseness is greater in women than men. A possibility is the social and psychological effect of women asking for a raise (Stuhlmacher and Walters, 1999). Some women may come off as ‘too bossy’ or too demanding if negotiating a raise.
Another aspect of risk averseness may be genetic or hormonal. A 7R minor allele of the DRD4 gene (dopamine receptor) may be a gene associated with financial risk-taking in men – although still attributed to addiction and attention deficit disorders (Dreber et al. 2009). Dreber et al (2009) conducted a study with 24 participants who had the 7R allele (associated with 7R+) and 70 participants without the 7R allele (7R-). They state that on average 7R+ individuals invested more money than individuals who were 7R− in a game where participants invested in a risky investment deal (Dreber et al. 2009). The participants started with $250 and were given the choice to invest from $0-$250. So, if they started with $250 and invested $50, their left over balance would then be $200. A coin was flipped to determine if the investment would be successful or not (50/50 chance of a successful or unfavorable outcome). If the coin showed an unsuccessful outcome, the subject would then have $200. If the coin showed a winning outcome, the amount they invested would be multiplied by 1.5 (50x1.5) then added to $250. Their p value was .023 and their regression value was .05. The researchers suggest that the variation in risk-taking may be explained by 5% with this gene (Dreber et al. 2009). Other genes or biological affects and other cultural/social factors may contribute to the likelihood of risk-taking and especially more recently, financial risk-taking which relates to the wage gap. Dreber et al. (2009) also state that since women are seen having these polymorphisms in the DRD4 gene as well, aggression, competition, and risk taking in men could be testosterone dependent although they did not find an accurate correlation between the two. More research needs to be done to determine the sex differences between the behaviors associated with the 7R allele of the DRD4 gene. Another study found that some women who overeat and have Seasonal Attentive Disorder, have this allele/polymorphisms in the DRD4 gene which may be associated with attention deficits in childhood and mild to moderate obesity in adulthood (Levitan, R.D. et al. 2004). There may be differences in regard to the behavioral effect of the 7R allele in both men and women, however further studies must be done to show significant biological differences between men and women in association with the 7R allele.
Social and cultural differences may be another factor why women are more risk-averse than men. Since women started entering the work force later than men and there were certain gender related behaviors that both men and women adhered to more so in the past than now, there may be a cultural reason why women may be less likely to negotiate (Bilke and Hurtel, 2015). A meta-analysis by Bilke and Hurtel (2015) show that gender differences in economic negotiation depends on context. On average men had slightly better outcomes than women with negotiation, but the gender differences in outcome decrease when the negotiator was provided with information about the bargaining range, and average values of salary. The researchers present a case that if women are given more information or training about negotiation tactics, it may lower the differences in negotiation. They do however note that even if women know their information, some may come off as assertive; deviating from a personality type that is more associated with woman-like behavior (Bilke and Hurtel, 2015).
Compensation Packages in Relation to Occupation Choice and Wages
A variable not discussed as often as the variables listed above is compensation packages and whether there are differences between benefits received by men and women and if this can affect wages (Currie, 1995). Currie (1995) notes that non-wage compensation benefits may account for between 30 to 40% of labor costs in western industrial countries. One study focused on 6 benefits: pensions, health insurance, paid sick leave, paid vacations, disability, and training to determine if there are similarities to benefits that men and women receive and how it may affect wages (Currie, 1995). Currie (1995) points out that in Reed and Holleman’s (1994) study, there are differences in benefit coverages women in small businesses and small firms receive in comparison to men. Reed and Holleman (1994) state, “that while gender gaps in benefits coverage are relatively small among single workers, among married workers, women are less likely to have pensions and health insurance, and more likely to have paid sick leave and paid vacations.” This may be due to the fact that married women on average may already have or are planning to have kids. Paid vacations and sick leave may be advantageous if a mother wants to take time off to be with the child. Businesses might also offer women more sick or vacation leaves if they want to fit maternity leave days in the package (Currie, 1995). When looking at single, young men and women (25-34 years of age) working in firms, there are no significant gender gaps in health coverage, and female workers are even more likely than men to receive sick leave (Currie, 1995). The reason for certain gaps in benefit packages may be due to a variety of reasons, and one factor to explain the pension gap (especially seen among older individuals) may be the fact that women’s labor force participation has been increasing over time, There are more younger women in the labor force than predecessors who may have lived and potentially started working during/after the women’s rights movement. Currie (1995) states that some benefits may be of value to certain individuals of the opposite sex, and some turnover with young women may be correlated with benefits. Table 1 exhibits differences between married and single women and men in regards to hourly wages and likelihood of receiving a certain benefit. Single women tend to receive closer hourly wages to single men in comparison to married women with and without children.
 |
| Table 1 displays wages and benefits separated by categories such as married with or without children and single with or without children. It is shown that more women receive sick leave than men and single women are more likely to receive pension than married women. Source: Adapted from Currie (1993). Tabulations based on the May 1988 Current Population Survey. (1995) |
Single women also are more likely to have a pension compared to single men and are mostly equal to married women. A hypothesis to this is that married men may already include their family in their pension policy or are older than single men, thus more likely to open or receive a pension plan. Though this may be an option, Dushi (2013) from the Social Security Administration states that married individuals, regardless of sex, are more likely than single men and women to receive a pension plan. Percentage difference between married men and married women seem to be insignificant (Dushi, 2013). Males regardless of family status are more likely to receive a disability plan. One reason may be due to the fact that among the sexes, men were and are still more likely to injure themselves severely or die from occupational hazards (Knestaut, 1996; U.S. Department of Labor, Bureau of Labor Statistics, 2016). More research would be valuable in this sector of the wage gap to determine more recent compensation packages related to wages and occupation to see if a similar trend still displays today.
Conclusion
There are many variables and constants that can affect the wage gap. Future discussion of the gender wage gap should take into account major factors that substantially narrow the gap such as family status, occupation (job title as well as gender differences in occupation), and hours worked (CONSAD, 2009; Polachek and Xiang, 2016). However, researchers should not leave behind other variables that contribute to the narrowing of the gap as well such as education, age and experience, salary negotiation, and compensation packages and its effects on wages. Although discrimination may still be a factor in regards to an unclosed gap, it may not be as large as the popular ‘75 cents to a man’s dollar’ myth. Discrimination is a difficult variable to measure and collect data on, however controlling for decisions made by both sexes that are seen cross culturally or seen as a trend over time may be useful to understanding the wage gap as well as moving forward to try to close it (Polachek and Xiang, 2014). Paraphrasing CONSAD’s (2009) concluding statement, although additional research in the gender wage gap is needed, the studies listed conclude that differences in wages between men and women are a result of many variables. Fair and accurate discussions of the wage gap should be had to determine if there needs to be corrective action to ‘fix’ the gap. There may not be much to correct. It is shown that a lot of the main differences in raw wages may mostly be due to the result of individual choices being made by both male and female workers.
References + Other Links
