Papers Containing Keywords(s): 'earnings age'
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Viewing papers 1 through 9 of 9
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Working PaperEmployer Dominance and Worker Earnings in Finance
August 2024
Working Paper Number:
CES-24-41
Large firms in the U.S. financial system achieve substantial economic gains. Their dominance sets them apart while also raising concerns about the suppression of worker earnings. Utilizing administrative data, this study reveals that the largest financial firms pay workers an average of 30.2% more than their smallest counterparts, significantly exceeding the 7.9% disparity in nonfinance sectors. This positive size-earnings relationship is consistently more pronounced in finance, even during the 2008 crisis or compared to the hightech sector. Evidence suggests that large financial firms' excessive gains, coupled with their workers' sought-after skills, explain this distinct relationship.View Full Paper PDF
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Working PaperPay, Productivity and Management
September 2021
Working Paper Number:
CES-21-31
Using confidential Census matched employer-employee earnings data we find that employees at more productive firms, and firms with more structured management practices, have substantially higher pay, both on average and across every percentile of the pay distribution. This pay-performance relationship is particularly strong amongst higher paid employees, with a doubling of firm productivity associated with 11% more pay for the highest-paid employee (likely the CEO) compared to 4.7% for the median worker. This pay-performance link holds in public and private firms, although it is almost twice as strong in public firms for the highest-paid employees. Top pay volatility is also strongly related to productivity and structured management, suggesting this performance-pay relationship arises from more aggressive monitoring and incentive practices for top earners.View Full Paper PDF
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Working PaperU.S. Long-Term Earnings Outcomes by Sex, Race, Ethnicity, and Place of Birth
May 2021
Working Paper Number:
CES-21-07R
This paper is part of the Global Income Dynamics Project cross-country comparison of earnings inequality, volatility, and mobility. Using data from the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files we produce a uniform set of earnings statistics for the U.S. From 1998 to 2019, we find U.S. earnings inequality has increased and volatility has decreased. The combination of increased inequality and reduced volatility suggest earnings growth differs substantially across different demographic groups. We explore this further by estimating 12-year average earnings for a single cohort of age 25-54 eligible workers. Differences in labor supply (hours paid and quarters worked) are found to explain almost 90% of the variation in worker earnings, although even after controlling for labor supply substantial earnings differences across demographic groups remain unexplained. Using a quantile regression approach, we estimate counterfactual earnings distributions for each demographic group. We find that at the bottom of the earnings distribution differences in characteristics such as hours paid, geographic division, industry, and education explain almost all the earnings gap, however above the median the contribution of the differences in the returns to characteristics becomes the dominant component.View Full Paper PDF
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Working PaperTwisting the Demand Curve: Digitalization and the Older Workforce
November 2020
Working Paper Number:
CES-20-37
This paper uses U.S. Census Bureau panel data that link firm software investment to worker earnings. We regress the log of earnings of workers by age group on the software investment by their employing firm. To unpack the potential causal factors for differential software effects by age group we extend the AKM framework by including job-spell fixed effects that allow for a correlation between the worker-firm match and age and by including time-varying firm effects that allow for a correlation between wage-enhancing productivity shocks and software investments. Within job-spell, software capital raises earnings at a rate that declines post age 50 to about zero after age 65. By contrast, the effects of non-IT equipment investment on earnings increase for workers post age 50. The difference between the software and non-IT equipment effects suggests that our results are attributable to the technology rather than to age-related bargaining power. Our data further show that software capital increases the earnings of high-wage workers relative to low-wage workers and the earnings in high-wage firms relative to low-wage firms, and may thus widen earnings inequality within and across firms.View Full Paper PDF
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Working PaperPay, Employment, and Dynamics of Young Firms
July 2019
Working Paper Number:
CES-19-23
Why do young firms pay less? Using confidential microdata from the US Census Bureau, we find lower earnings among workers at young firms. However, we argue that such measurement is likely subject to worker and firm selection. Exploiting the two-sided panel nature of the data to control for relevant dimensions of worker and firm heterogeneity, we uncover a positive and significant young-firm pay premium. Furthermore, we show that worker selection at firm birth is related to future firm dynamics, including survival and growth. We tie our empirical findings to a simple model of pay, employment, and dynamics of young firms.View Full Paper PDF
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Working PaperThe Parental Gender Earnings Gap in the United States
January 2017
Working Paper Number:
CES-17-68
This paper examines the parental gender earnings gap, the within-couple differences in earnings over time, before and after the birth of a child. The presence and timing of children are important components of the gender wage gap, but there is selection in both decisions. We estimate the earnings gap between male and female spouses over time, which allows us to control for this timing choice as well as other shared external earnings shifters, such as the local labor market. We use Social Security Administration Detail Earnings Records (SSA-DER) data linked to the Survey of Income and Program Participation (SIPP) to examine a panel of earnings from 1978 to 2011 for the individuals in the SIPP sample. Our main results show that the spousal earnings gap doubles between two years before the birth of the first child and the year after that child is born. After the child's first year of life the gap continues to grow for the next five years, but at a much slower rate, then tapers off and even begins to fall once the child reaches school-age.View Full Paper PDF
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Working PaperEarnings Inequality and Mobility Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data
January 2017
Working Paper Number:
CES-17-24
Using earnings data from the U.S. Census Bureau, this paper analyzes the role of the employer in explaining the rise in earnings inequality in the United States. We first establish a consistent frame of analysis appropriate for administrative data used to study earnings inequality. We show that the trends in earnings inequality in the administrative data from the Longitudinal Employer-Household Dynamics Program are inconsistent with other data sources when we do not correct for the presence of misused SSNs. After this correction to the worker frame, we analyze how the earnings distribution has changed in the last decade. We present a decomposition of the year-to-year changes in the earnings distribution from 2004-2013. Even when simplifying these flows to movements between the bottom 20%, the middle 60% and the top 20% of the earnings distribution, about 20.5 million workers undergo a transition each year. Another 19.9 million move between employment and nonemployment. To understand the role of the firm in these transitions, we estimate a model for log earnings with additive fixed worker and firm effects using all jobs held by eligible workers from 2004-2013. We construct a composite log earnings firm component across all jobs for a worker in a given year and a non-firm component. We also construct a skill-type index. We show that, while the difference between working at a low-or middle-paying firm are relatively small, the gains from working at a top-paying firm are large. Specifically, the benefits of working for a high-paying firm are not only realized today, through higher earnings paid to the worker, but also persist through an increase in the probability of upward mobility. High-paying firms facilitate moving workers to the top of the earnings distribution and keeping them there.View Full Paper PDF
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Working PaperUSING THE PARETO DISTRIBUTION TO IMPROVE ESTIMATES OF TOPCODED EARNINGS
April 2014
Working Paper Number:
CES-14-21
Inconsistent censoring in the public-use March Current Population Survey (CPS) limits its usefulness in measuring labor earnings trends. Using Pareto estimation methods with less-censored internal CPS data, we create an enhanced cell-mean series to capture top earnings in the public-use CPS. We find that previous approaches for imputing topcoded earnings systematically understate top earnings. Annual earnings inequality trends since 1963 using our series closely approximate those found by Kopczuk, Saez, & Song (2010) using Social Security Administration data for commerce and industry workers. However, when we consider all workers, earnings inequality levels are higher but earnings growth is more modestView Full Paper PDF
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Working PaperComparing Measures of Earnings Instability Based on Survey and Adminstrative Reports
August 2010
Working Paper Number:
CES-10-15
In Celik, Juhn, McCue, and Thompson (2009), we found that estimated levels of earnings instability based on data from the Current Population Survey (CPS) and the Survey of Income and Program Participation (SIPP) were reasonably close to each other and to others' estimates from the Panel Study of Income Dynamics (PSID), but estimates from unemployment insurance (UI) earnings were much larger. Given that the UI data are from administrative records which are often posited to be more accurate than survey reports, this raises concerns that measures based on survey data understate true earnings instability. To address this, we use links between survey samples from the SIPP and UI earnings records in the LEHD database to identify sources of differences in work history and earnings information. Substantial work has been done comparing earnings levels from administrative records to those collected in the SIPP and CPS, but our understanding of earnings instability would benefit from further examination of differences across sources in the properties of changes in earnings. We first compare characteristics of the overall and matched samples to address issues of selection in the matching process. We then compare earnings levels and jobs in the SIPP and LEHD data to identify differences between them. Finally we begin to examine how such differences affect estimates of earnings instability. Our preliminary findings suggest that differences in earnings changes for those in the lower tail of the earnings distribution account for much of the difference in instability estimates.View Full Paper PDF
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