Gender and Pay in Accounting

By

Institution

Gender and Pay in Accounting

Introduction

Background

Individual pay or wage is an essential social, economic, and political tool in most economies. Compensation for employees’ work or services provides disposable income as a cost for labor. This disposable income plays a critical role in the monetary and fiscal policies of all economies. It is, therefore, the interest of most economies to intervene in labor markets when the allocations and distributions of pay and compensation are uncompetitive (Gatta, 2017). Some of the ways in which governments and other stakeholders intervene in labor markets are through minimum wages and income taxation. This solves the economic aspect of pay and compensation.

However, there are some social factors of employee compensation that the government of little or no control over. For example, wage differences exist for employee wages between ethnicities and gender. There is sufficient research evidence to the existence of the wage gap between male and female employees. Data and research findings reveal than men earn more than their female colleagues (Anon., 2019). These differences in earnings, gender pay gap, systemically exist within most sectors of global economies. Regulation of this systemic pay discrimination has not been fruitful due to the existing complexities in labor contracts and other variables on compensation.

Various reasons contribute to the gender pay gap. According to Payscale (2020), women earn 81 cents for every dollar earned by men. This represents the uncontrolled gender pay gap using median pay. However, when the pay is controlled for job and qualification, women earn 98 cents for every dollar that a man earns. The differences in the gender pay gap for both controlled and uncontrolled statistics show the extent of systemic pay discrimination.

The large difference in the uncontrolled pay gap is majorly due to the differences in the cost of living between regions, education level, job experience, and employee performance. It is expected that women would earn equal to men when they perform similar tasks with similar qualifications. However, this is not the case (Moyser, 2019). This is evidence of discriminative remuneration to the disadvantage of female workers. There are various efforts by governments and other stakeholders to even the gender pay gap, including the requirement for reporting on this gap by employers in multiple countries.

Objectives of the Study

This study is conducted to fulfill the following objectives.

1. To determine the relationship between wage pay gap and labour force participation for women.
2. To determine the relationship between wage pay gap and the proportion of women managers.
3. To establish the annual changes in the gender pay gap.

Research questions

The following main research question will be evaluated in the study: Do men earn significantly higher wages than women?

The following specific research questions will be evaluated to answer the main research question.

Research question 1: What is the relationship between wage pay gap and labor force participation for women?

Research question 2: What is the relationship between the wage pay gap and the share of women managers?

Research question 3: Has the gender pay gap significantly changed between 2014 and 2018?

Motivation of Project

The wage pay gap has been attributed to various factors. Moreover, various solutions to the gender wage gap have been suggested. Some of the solutions include increasing the number of working women and the number of women in management. The study seeks to determine the effectiveness of these solutions in reducing the gender wage gap. Quantitative research is conducted to assess the impact of the increased number of employed women and women managers in reducing the gender wage gap.

Theoretical and Contextual Literature Review

Theoretical Literature

The gender pay gap is a leading concern for social protection stakeholders. The objective is to improve equality and equity in the labor market. However, the method and modalities of executing the equality and equity policies in the labor market present a challenge to both employers and regulators (Tomaskovic-Devey & Skaggs, 2002). The main objective of the employer and regulators is to eliminate both intentional and unconscious bias in hiring and remuneration.

One of the credible ways in which organizations and employers can resolve the gender pay gap is the use of compensation audits. There is little regulation on pay and compensation for employees (Blau & Kahn, 2017). Institution of regular human resource audits on compensation would identify and help in eliminating the instances of pay differentials among employees with similar work and qualifications (Conley, et al., 2019). While executing the audit, it would be necessary for the auditors and employers to recognize the difference between equal pay and equitable pay. Thus, the unique attributes of each job position would be gauged against the pay since most employees do not perform similar tasks.

Another measure that can counter the pay gap between male and female employees is narrowing the range for starting salaries (Blau & Kahn, 2017). A narrow range for starting salary for employees would ensure that all employees have relatively uniform staring salaries, which would consequently translate to smaller gaps after a promotion or career progression (Kollonay-Lehoczky, 2016).  Starting salaries of employees have a high correlation to subsequent pay offers in other jobs in the same organization and other organizations. Therefore, when the starting salaries for employees are standardized and their differences minimized, they are likely to progress in their pay at a relatively uniform rate. This measure can be implemented in conjunction with a model of a uniform model for a pay rise. In order to reduce future inequalities, a uniform model for raising employee salaries would ensure that employee salaries are matched to their roles, qualifications, and experience.

Lastly, enhancing diversity in the workplace plays a key role in narrowing the gender pay gap. Employing people from both gender and various ethnicities in both junior and managerial positions ensure that business decisions, including human resource, are cognizant of the identities of the workforce and their needs (Leslie, et al., 2016). For example, there are fewer women in managerial positions than men. Recruiting more women into administrative positions would effectively narrow the gender pay gap (Rubery, 2015). Women would be more effective in advocating and representing issues and disparities affecting them.

Contextual Literature

Blau and Kahn (2017) showed that there had been significant changes in the factors contributing to pay inequality among men and women since the 1970s. Also, Blau and Kahn noted that the gender pay gap has been declining during this period. In their analysis of US labor statistics, Beaudry and Lewis (2014) found a declining gender pay gap, which they associated with changes in the demand of skills to the advantage of technical skills. The technical skills were observed to be disproportionate, with a larger proportion of male workers having the skills than female workers. Flory et al. (2014) associated the wage gap to the tendency of female workers to be averse to work environments that were deemed competitive. However, Conley et al. (2019) reveal that the pay gap is still significant despite the significant reversal of the education gap in favor of women.

According to Blau and Kahn (2017), there have been significant changes in the factors that previously contributed to the gender wage gap. Years of education changed significantly from -0.2 to +0.2 in a period of 30 years between 1981 to 2011 while the work experience gap reduced from 7 years to 1.4 years in the same period. The significance of education and experience has been declining over the years. However, Blau and Kahn (2017) noted that as the significance of education and experience factors fell, the significance of other factors like unionization continued to increase over the years.

Hegewisch et al. (2010) found a significant influence of gender segregation in occupation as contributing to the gender wage gap. They observed an inverse relationship between the proportion of women in employment within a profession and the gender wage gap. According to Bishu and Alkadry (2017), the gender wage gap decreased when the proportion of women in the occupation increased. Another research by Tomaskovic-Devey and Skaggs (2002) and Levanon et al. (2009) found gender segregation as a significant contribution to the gender pay gap.

Polachek (2014) reviewed the relationship of the gender pay gap with life cycles. He found significant differences in the gender pay gap based on marital status. The gender pay gap between single men and women was found to be smaller than the gender pay gap between married men and women. Further, Humlum et al. (2019) found an association between the gender pay gap and age among women. Parental responsibilities and maternity in women significantly increased the wage gap. In addition, the wage gap increased with aging. There is little or no wage gap for younger workers. However, the gap begins to widen at maternity and widens with age. According to Bertrand et al. (2010), the gender pay gap increased due to career interruptions as well as training, and average hours in a week worked.

Sulis (2012) and Blau et al. (2013) found the prevalence of women working in part-time work as a contribution to the gender wage gap. This prevalence is linked to maternity career disruption for women. These part-time jobs are usually low-level positions that have lower wage rates. Other studies have discovered various contributing factors to the gender pay gap. Gauchat et al. (2012) found globalization as an equalizing factor in reducing the gender pay gap. The gender pay gap is observed to decrease with respect to increasing international trade and foreign direct investments (Menon and Van der Meulen Rodgers, 2009; Oostendorp, 2009).

Methodology

Research Design

A quantitative research design will be used to analyze the research data and answer the research questions.

Sampling

The sample data represents data variables from all 36 OECD countries. A convenience and non-probability sample of the reported data for the OECD counties is selected for the study. This is selected due to the completeness of gender pay gap data for recent years.

Data Collection

Secondary data is used in the study. It is collected from the reported measures of the gender pay gap for OECD countries for the five years between 2014 and 2018. The OECD online database of country reports is the source of the research data. The data variables to be collected for the study include the annual wage pay gap, annual labor participation rate for women, and the annual share of employed who are women managers. According to the OECD, the gender wage gap is defined as the difference between male and female median wages divided by the male median wages. Labor force participation is reported as the percentage of the population aged between 15 -64 who are either employed or seeking work. The percentage of women managers is the proportion of employed people who are working women managers. For analysis, both the annual gender wage gap and the average gender wage gap for the five years will be considered. The five-year average labor force participation rate for women and the five-year average proportion of women managers will be considered.

Data Analysis

Both descriptive and inferential statistics will be used to analyse the data and test hypotheses. These statistics will be used to report the measures of central tendency and distribution for the research variables.  Normality tests are conducted to determine the data conformity to the assumptions of statistical tests. Parametric hypothesis tests will be conducted on the datasets.

Correlational analysis will be carried out to answer the first and second research questions. Pearson’s correlation analysis is appropriate in determining the relationship between two quantitative variables (Eichler & Zapata-Cardona, 2016). Specifically, Pearson’s correlation test will be used to determine the significance of the relationship between the average gender wage gap for the five years and the average labor force participation rate for women. Similarly, Pearson’s correlation test will be used to determine the relationship between the average gender wage gap for the five years and the average share of women managers for the five years. The significance of the relationships will be evaluated at a 5% level of significance.

In order to answer the third research question, the analysis of variance will be used to determine the significance of the differences in the average annual gender wage gap for the five years. The analysis of variance (ANOVA) will be an appropriate test for more than two categorical groups (years). Either the one-way ANOVA or the repeated ANOVA will be used to test the statistical results (Rosnow & Rosenthal, 1992). The average annual gender wage gaps will be comparatively evaluated to determine whether there is a significant annual reduction. In addition, the ANOVA test will determine whether a significant change exists for the gender wage gap from the beginning of the sample period to the end of the sample period. The results of the ANOVA test will be evaluated against a 5% level of significance.

Ethical Consideration

The data used in the study represents processed employment figures reported for various countries. The data is published and, thus, would not require confidentiality. However, care is taken to avoid misrepresentation of individual countries’ data and information. Therefore, careful recording and editing of the data is considered to reduce the likelihood of erroneous recording or misrepresentation of country information.

Data Analysis and Results

Table 1 below shows the descriptive statistics for the research variables.

Table 1: Descriptive statistics

The average gender wage gap for the five years is 13.58%, with a standard deviation of 7.09%. The minimum gender wage gap measure for the five years is 3.4%, while the maximum is 35.86%. The average labour participation rate for women is 55.39%, with a standard deviation of 8.55%. The minimum labour participation rate for women is 32.42%, while the maximum is 78.72%. The average proportion of women in management is 4.86%, with a standard deviation of 2.85%. The minimum proportion of women managers is 0.32%, while the maximum is 11.84%.

A normality test of the research variables is conducted to determine their conformity to the normality assumption. The table below shows the results of the normality test.

Table 2: Normality test

The gender wage gap data for the five years as well as the average gender wage gap violate the normality assumption. The labour participation rate for women and the proportion of women in management conform to the normality assumption.

Relationship Between Gender Wage Gap and Labour Force Participation for Women

The relationship between the gender wage gap and labour force participation for women is evaluated. Table 3 below shows the results of the correlation analysis.

Table 3: Correlation results for labour participation and the gender wage gap

The correlation coefficient for the relationship between the gender wage gap and labor force participation for women is 0.149. The correlation between the two variables is weak and insignificant at 5% level of significance (p-value = 0.384).

The results of the correlation analysis imply that an increase in the proportion of women in the workforce does not significantly affect the gender wage gap. Therefore, the calls to increase the number of working women in the workforce in order to narrow the gender wage gap may not hold true.

Relationship Between Gender Wage Gap and Share of Women Managers

A correlation analysis is conducted to determine the relationship between the proportion of women managers in the workforce and the gender wage gap. Table 4 below shows the correlation results for the analysis.

Table 4: Correlation results for the share of women managers and the gender wage gap

The correlation coefficient for the relationship between the share of women managers and the gender wage gap is -0.008. The correlation between the two variables is very weak and insignificant at 5% level of significance (p-value = 0.963).

An increase in the number of women in management positions has been suggested as one of the measures to narrow the gender wage gap. However, the results of the study imply that both variables do not significantly relate to each other. Therefore, increasing the number of women managers may not yield the desired results of reducing the gender wage gap.

Changes in Gender Wage Gap

The 5-year change in the gender wage gap trend is analyzed. It is assumed that progressive policies geared towards reducing the wage gap have been effective over the years. Thus, the average gender wage gap in 2014 is expected to be significantly lower than the average gender wage gap in 2018. An analysis of variance (ANOVA) is conducted to determine the significance of the difference between the average annual gender wage gap for the 36 countries.

Table 5: Descriptive statistics for year averages

There are substantial differences in mean annual gender wage gap for each of the years. However, data reporting is highly irregular for each of the years. Therefore, a one way ANOVA test would not be appropriate because it could lead to bias in the number reporting. Thus, a repeated measured ANOVA is conducted to evaluate the significance of the difference between the mean annual gender wage gap. Table 6 below shows the descriptive statistics of the repeated measures ANOVA.

Table 6: Descriptive statistics of matched samples

The table above shows substantial differences in the gender wage gap for the five years. The highest gender wage gap is in 2014, while the lowest is in 2018. Table 7 below shows the results of the repeated-measures ANOVA.

Table 7: Results of repeated measures

The repeated measures ANOVA results show insignificant differences in mean annual gender wage gap for the five years, F(1,8) = 2.571, p-value = 0.148, partial eta squared = 0.243. Therefore, the mean gender wage gap has not significantly changed for five years. Hence, the data shows stagnation in the gender wage gap for the period between 2014 and 2018.

References

Anon., 2019. The gender pay gap: equal work, unequal pay. New York, NY: New York Times Educational Publishing.

Beaudry, P. & Lewis, E., 2014. Do male-female wage differentials reflect differences in the return to skill? Cross-city evidence from 1980-2000. Am Econ J Appl Econ, 6(2), p. 178–194.

Bertrand, M., Goldin, C. & Katz, L., 2010. Dynamics of the gender gap for young professionals in the financial and corporate sectors. Am Econ J Appl Econ, 2(3), p. 228–255.

Blau, F., Brummund, P. & Liu, A., 2013. Trends in occupational segregation by gender 1970–2009: adjusting for the impact of changes in the occupational coding system.. Demography, 50(2), p. 471–492.

Blau, F. & Kahn, L., 2017. The gender wage gap: extent, trends, and explanations.. J Econ Lit, 55(3), p. 789–865.

Conley, H. et al., 2019. The gender pay gap and social partnership in Europe: findings from “Close the deal, fill the gap. New York, NY: Routledge.

Flory, J., Leibbrandt, A. & List, J., 2014. Do competitive workplaces deter female workers? A large-scale natural field experiment on job entry decisions. Rev Econ Stud, 82(1), p. 122–155.

Gatta, M. L., 2017. Gender pay gap. London: SAGE Publications Ltd.

Gauchat, G., Kelly, M. & Wallace, M., 2012. (2012) Occupational gender segregation, globalization, and gender earnings inequality in US metropolitan areas. Gend Soc 26(5):, 26(5), p. 718–747.

Hegewisch, A., Liepmann, H., Hayes, J. & Hartmann, H., 2010. Separate and not equal? Gender segregation in the labor market and the gender wage gap.. s.l., IWPR Briefing Paper, 377.

Humlum, M., Nandrup, A. & N, S., 2019. Closing or reproducing the gender gap? Parental transmission, social norms and education choice. J Popul Econ, 32(2), p. 455–500.

Kollonay-Lehoczky, 2016. The Right to Equal Opportunities and Equal Treatment in Matters of Employment and Occupations without Discrimination on the Grounds of Sex, Article 20, in Bruun, N. Lörcher, K., Schömann, I. and Clauwaert, S. (eds). The European Social Charter and the Employment Relation Oxford: Hart.

Levanon, A., England, P. & Allison, P., 2009. Occupational feminization and pay: assessing causal dynamics using 1950–2000 US census data. Soc Forces, 88(2), p. 865–891.

Menon, N. & Rodgers, V. d. M., 2009. (2009) International trade and the gender wage gap: new evidence from India’s manufacturing sector.. World Dev 37(5):, 37(5), p. 965–981.

Moyser, M., 2019. Measuring and analyzing the gender pay gap: a conceptual and methodological overview. Ottawa: Statistics Canada.

Oostendorp, R., 2009. Globalization and the gender wage gap. World Bank Econ Rev, 23(1), pp. 141-161.

Payscale, 2020. The state of Gender Pay Gap 2020. [Online]
Available at: https://www.payscale.com/data/gender-pay-gap
[Accessed 25 April 2020].

Polachek, S., 2014. Equal pay legislation and the gender wage gap. IZA World of Labor.

Rubery, J., 2015. The Motherhood Pay Gap: A review of the issues, theory and international evidence. Conditions of Work and Employment Series working paper no. 57. Geneva, International Labour Organization.

Sulis, G., 2012. Gender wage differentials in Italy: a structural estimation approach. J Popul Econ, 25(1), pp. 53-87.

Tomaskovic-Devey, D. & Skaggs, S., 2002. Sex segregation, labor process organization, and gender earnings inequality. Am J Sociol, 108(1), pp. 102-128.