Abstract
To assess the employment opportunities of older job-changers in the years prior to retirement, this study examines the how the breadth of occupations in which they find employment narrows as they age past their prime working years and how this differs by gender and educational attainment. The results indicate that workers who change jobs in their early 50s find employment in a reasonably similar set of occupations as prime-age workers, with opportunities narrowing at older ages. They also indicate that job opportunities broadened significantly for better-educated older workers since the late 1990s. While job opportunities now narrow significantly for less-educated men in their late 50s, this narrowing primarily occurs in the early 60s for women and better-educated men. In contrast to previous research, the study finds that employer policies that emphasize hiring from within are less important barriers to the hiring of older job-seekers. The study also finds that the narrowing of job opportunities is associated with a general decline in job quality as measured by median occupational earnings, a decline associated with differences in occupational skill requirements and the underlying economic environment. These results suggest that older hiring is not as limited to a select few occupations as it had been in previous decades, and that policy reforms aimed at increasing opportunities and improving labor market fluidity might best be served if they focused on less-educated men.
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Notes
Munnell and Sass (2008) and authors’ calculations using Current Population Survey data.
The study calculates median earnings for each occupation excluding workers with imputed earnings. Hirsch and Schumacher (2004) and Bollinger and Hirsch (2006) report that many of these imputed values are based on matched observations from entirely separate occupations, and so the imputed values are not representative of that occupation’s earnings.
The two scores – importance and level of skill required – are both normalized so that they vary over a range from 0 to 1. While the O*NET database includes scores for thousands of minutely-defined skills, we use only 59, aggregated into these 14 categories.
We do not use CPS-provided weights, because the analysis stacks together multiple years. The regression analysis uses weights constructed from the number of respondents in the occupation.
Lorenz Curves are most commonly used to assess income and wealth inequality. See Kennickell (2009) for a survey.
The estimation that produces the fitted curve also produces a confidence interval for that curve, allowing for hypothesis testing of whether the fitted curve is statistically different from the 45-degree line. The fitted curve is constrained to start at (0,0) and end at (1,1).
In the regression, each observation is weighted by that occupation’s total hires over age 50. Weighting assures that occupations that have a greater share of the labor market also have a greater influence on the estimation.
The Gini coefficients for the groups separated only by age (the first three rows) are not a weighted average of the subgroups defined by gender and education because the number of occupations that are large enough for inclusion varies across the groups. Similarly, the all-period Gini coefficients are not a weighted average of the period-specific Ginis because of decreasing sample size.
The histograms plotted by time period tell a similar story to the Gini coefficients.
The CPS does not distinguish between defined benefit and defined contribution pension plans.
Hirsch et al. (2000) also found this relationship with working outdoors, though not with strength.
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The study was funded by the Alfred P. Sloan Foundation (grant number 2014–6-20).
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The research reported herein was pursuant to a grant from the Alfred P. Sloan Foundation (2014–6-20). The findings and conclusions expressed are solely those of the authors and do not represent the views of the Alfred P. Sloan Foundation or Boston College.
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Rutledge, M.S., Sass, S.A. & Ramos-Mercado, J.D. How Does Occupational Access for Older Workers Differ by Education?. J Labor Res 38, 283–305 (2017). https://doi.org/10.1007/s12122-017-9250-y
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DOI: https://doi.org/10.1007/s12122-017-9250-y