A Predictive Model of Gender Pay Disparity in the Private Sector
Open Access DepositedGender pay disparity is a prominent issue in the United States (U.S.) workforce, where women receive lower salaries than men when working in the same or equivalent roles. This work aims to design regression models that provide insight into the salaries of men and women in Science, Technology, Engineering, and Mathematics (STEM) fields, identifying common inequities that are difficult to detect from simple data. Despite numerous efforts to promote equal pay, women in STEM positions in the private sector continue to receive lower pay than men with similar skills and responsibilities. Gender pay disparity has been documented as early as 1869. However, the U.S. Equal Pay Act (EPA), which prohibits gender based pay discrimination, was not enacted until 1963. Although more than 60 years have passed since the EPA was passed, little progress has been made in closing the pay gap. Diversity, equity, and inclusion initiatives have not eradicated pay inequality. More significantly, recent gender pay discrimination lawsuits further demonstrate that women are still fighting to receive equal pay. This research aims to stimulate positive socioeconomic and sociocultural change by identifying solutions that can help separate the factors influencing pay variance and reveal the primary sources of differences among men and women workers. It utilizes historical salary data to examine the interplay between gender, education, and age on median salaries. A regression model was developed to identify strong indicators of salary. Conclusions indicate that, when education and age are controlled for, women receive lower salaries than men working in similar positions. A regression model was developed to predict when gender pay disparity will be resolved if current legislation and organizational hiring and compensation practices remain unchanged. Historical salary data shows that the gender pay gap has changed by only a small margin over the last decade. The regression model utilizes averages of critical variables, such as gender, age, and education, to forecast the time scale for achieving pay parity using past trend data. Furthermore, a case study was conducted to examine the salaries of men and women working in STEM occupational fields in both the private and public sectors, demonstrating that the gender pay disparity is greater in the private sector than in the public sector. This study dispels the common misconception that pay equity can be achieved using existing private sector pay systems. Research indicates that in the private sector, negotiation power and organizational discretion are factors that contribute to the perpetuation of the gender pay gap. Conversely, a uniform pay system minimizes the gender pay gap. This research proposes that federal government compensation and promotion policies can serve as a baseline model to eliminate pay inequality. This Praxis suggests that, based on existing laws and reforms, achieving gender pay parity in the private sector is not expected until 2082. Over the last decade, the gender pay gap has remained stagnant in the private sector. In contrast, the gender pay gap in the public sector is less prevalent, particularly in STEM occupational fields. Research findings corroborate that without the reconstruction of laws and compensation behaviors, achieving gender pay equity will continue to remain a long-term endeavor.
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