Work Patterns Partially Explain Difference between Men's and Women's Earnings
GAO-04-35, Oct 31, 2003
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Despite extensive research on the progress that women have made toward equal pay and career advancement opportunities over the past several decades, there is no consensus about the magnitude of earnings differences between men and women and why differences may exist. According to data from the Department of Labor's Current Population Survey (CPS), women have typically earned less than men. Specifically, in 2001, the published CPS data showed that for full-time wage and salary workers, women's weekly earnings were about three-fourths of men's. However, this difference does not reflect key factors, such as work experience and education, that may affect the level of earnings individuals receive. Studies that attempt to account for key factors have provided a more comprehensive estimate of the earnings difference. However, recent information is lacking because many studies on earnings differences relied on data that predated the mid-1990s. But, even when accounting for these factors, questions remain about the size of and reasons for any earnings difference. To provide insight into these issues, Congress asked that we examine the factors that contribute to differences in men's and women's earnings.
Of the many factors that account for differences in earnings between men and women, our model indicated that work patterns are key. Specifically, women have fewer years of work experience, work fewer hours per year, are less likely to work a full-time schedule, and leave the labor force for longer periods of time than men. Other factors that account for earnings differences include industry, occupation, race, marital status, and job tenure. When we account for differences between male and female work patterns as well as other key factors, women earned, on average, 80 percent of what men earned in 2000. While the difference fluctuated in each year we studied, there was a small but statistically significant decline in the earnings difference over the time period. Even after accounting for key factors that affect earnings, our model could not explain all of the difference in earnings between men and women. Due to inherent limitations in the survey data and in statistical analysis, we cannot determine whether this remaining difference is due to discrimination or other factors that may affect earnings. For example, some experts said that some women trade off career advancement or higher earnings for a job that offers flexibility to manage work and family responsibilities.