Period effects, cohort effects, and the narrowing gender wage gap
Introduction
Between 1970 and 1980, the female-to-male ratio of median annual earnings of full-time year-round workers, a commonly cited measure of the gender wage gap, narrowed from just below 60% to 64.2% (U.S. Census Bureau, 2010). By 1990, the gap had closed to 71.9%. Over the next two decades, the gap continued to move toward parity but at a slower pace, hitting 76.9% in 2000 and 81.2% in 2010.
A large body of research examines overall period trends in the gender wage gap, highlighting the narrowing but persistent wage inequality (Blau and Kahn, 2006a, Blau and Kahn, 2006b, Cotter et al., 2004, O’Neill, 2003). Unfortunately, despite the abundance of research on the gender wage gap, important questions remain. In particular, the role of cohorts is under investigated. Cohorts are often discussed descriptively but excluded from multivariate analyses (e.g. Blau and Kahn, 2000, Cotter et al., 2004). Other times, intercohort inequality is directly examined, but the analysis is restricted to a comparison of only two or three cohorts (e.g. Avellar and Smock, 2003, Miech et al., 2003), and frequently further limited to an analysis of certain high prestige occupations like doctors, lawyers, or engineers (e.g. Dinovitzer et al., 2009, Morgan, 1998, Noonan et al., 2005, Prokos and Padavic, 2005). These lines of research are undoubtedly important and insightful, but leave questions about the larger temporal trends in gender wage inequality.
First, existing research on inter-cohort inequality demonstrates that the gender wage gap varies by cohort. Yet, because existing research is largely limited to the comparison of only a handful of cohorts, the full extent of the variation is unknown. While it seems plausible and indeed likely that gender wage inequality for each successive cohort is less great than gender wage inequality in each preceding cohort, existing social science research does not offer a clear account of these variations because it does not specify multivariate models that consider all cohorts while uniquely identifying cohort and period effects. Thus, an obvious and important question remains: to what extent are younger cohorts more equal than older cohorts?
Second, when cohort is excluded from models of the gender wage gap, time trends do not accurately reflect period effects. Specifically, ample research notes a period decline in the gender wage gap. However, because these models do not account for cohort, it is unclear how much of this decline over time is due to period effects and how much is due to cohort effects. If we simultaneously model period and cohort, to what extent is the narrowing of the gender wage gap due to period effects and to what extent is it due to cohort effects?
In the research presented here, we draw data from the Current Population Survey to examine period and cohort effects on the gender wage gap. We offer cohort specific estimates of the gender wage gap, and by simultaneously modeling age, period, and cohort, we offer a reassessment of the time trend in the gender wage gap. By separating period and cohort effects, our analysis offers a more nuanced understanding of temporal changes. Specifically, while past research clearly shows a narrowing of the gender wage gap, we offer estimates of the unique role of period effects and cohort effects in lessening gender wage inequality.
Section snippets
Estimating period and cohort effects
Sociologists and demographers have long used age–period–cohort analysis to study time-specific phenomena. Put succinctly, age–period–cohort analysis identifies an outcome of interest (here, the phenomena of interest is the gap in wages between men and women), and then distinguishes three types of time-related variations in the outcome of interest: age effects (variation produced by the physiological or social process of aging), period effects (variations produced by events that simultaneously
Sample
We use data from the March supplements of the Current Population Survey (CPS) from 1976 through 2010. The CPS is the most nationally representative survey of individual earnings that is conducted on an annual basis. Unlike the Panel Study of Income Dynamics, which is restricted to persons selected in a few specific years, the CPS sample is designed to be nationally representative in each survey year. We used the CPS data provided by theIntegrated Public Use Microdata Series (King et al., 2010).
Descriptive statistics
Table 1 shows trends in wages, disaggregated by period and age. Each cell shows one age group in a particular time period. The table allows us to examine the progression of wages across ages in a particular time period or across time periods for a particular age. We can also follow the progression of ‘cohorts’ down the diagonal.
Limitations
The issue of selection into employment may complicate our findings. Male and female wages are based on men and women who happen to be employed at a specific point in time. Generally, it is reasonable to expect that men and women who participate in the labor force and who are employed at any given time will have higher wages than those who drop out of the labor force. This is likely to be especially true for women. It is well known that women who have greater potential earning power (for
Discussion and conclusion
The results from the multivariate analysis demonstrate the importance of simultaneously accounting for age, period, and cohort effects. In each case, the impact of age, period, and cohort are transformed when additional effects are accounted for. When age and cohort are controlled for, the narrowing of the gender wage gap after 1994 is shown to be an artifact of cohort replacement effects. That is, because successive cohorts experience a continuous narrowing of the gender wage gap (until the
Acknowledgments
We thank Philip Cohen and the anonymous SSR reviewers for their comments on earlier drafts of this article.
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These authors contributed equally to the manuscript and are listed in alphabetical order.