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Twisting 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.
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The Grandkids Aren't Alright: The Intergenerational Effects of Prenatal Pollution Exposure
November 2020
Working Paper Number:
CES-20-36
Evidence shows that environmental quality shapes human capital at birth with long-run effects on health and welfare. Do these effects, in turn, affect the economic opportunities of future generations? Using newly linked survey and administrative data, providing more than 150 million parent/child links, we show that regulation-induced improvements in air quality that an individual experienced in the womb increase the likelihood that their children, the second generation, attend college 40-50 years later. Intergenerational transmission appears to arise from greater parental resources and investments, rather than heritable, biological channels. Our findings suggest that within-generation estimates of marginal damages substantially underestimate the total welfare effects of improving environmental quality and point to the empirical relevance of environmental quality as a contributor to economic opportunity in the United States.
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The EITC and Intergenerational Mobility
November 2020
Working Paper Number:
CES-20-35
We study how the largest federal tax-based policy intended to promote work and increase incomes among the poor'the Earned Income Tax Credit (EITC)'affects the socioeconomic standing of children who grew up in households affected by the policy. Using the universe of tax filer records for children linked to their parents, matched with demographic and household information from the decennial Census and American Community Survey data, we exploit exogenous differences by children's ages in the births and 'aging out' of siblings to assess the effect of EITC generosity on child outcomes. We focus on assessing mobility in the child income distribution, conditional on the parents' position in the parental income distribution. Our findings suggest significant and mostly positive effects of more generous EITC refunds on the next generation that vary substantially depending on the child's household type (single-mother or married family) and by the child's gender. All children except White children from single-mother households experience increases in cohort-specific income rank, own family income, and the probability of working at ages 25'26 in response to greater EITC generosity. Children from married households show a considerably stronger response on these measures than do children from single-mother households. Because of the concentration of family types within race groups, the more positive response among children from married households suggests the EITC might lead to higher within-generation racial income inequality. Finally, we examine how the impact of EITC generosity varies by the age at which children are exposed to higher benefits. These results suggest that children who first receive the more generous two-child treatment at later ages have a stronger positive response in terms of rank and family income than children exposed at younger ages.
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An Evaluation of the Gender Wage Gap Using Linked Survey and Administrative Data
November 2020
Working Paper Number:
CES-20-34
The narrowing of the gender wage gap has slowed in recent decades. However, current estimates show that, among full-time year-round workers, women earn approximately 18 to 20 percent less than men at the median. Women's human capital and labor force characteristics that drive wages increasingly resemble men's, so remaining differences in these characteristics explain less of the gender wage gap now than in the past. As these factors wane in importance, studies show that others like occupational and industrial segregation explain larger portions of the gender wage gap. However, a major limitation of these studies is that the large datasets required to analyze occupation and industry effectively lack measures of labor force experience. This study combines survey and administrative data to analyze and improve estimates of the gender wage gap within detailed occupations, while also accounting for gender differences in work experience. We find a gender wage gap of 18 percent among full-time, year-round workers across 316 detailed occupation categories. We show the wage gap varies significantly by occupation: while wages are at parity in some occupations, gaps are as large as 45 percent in others. More competitive and hazardous occupations, occupations that reward longer hours of work, and those that have a larger proportion of women workers have larger gender wage gaps. The models explain less of the wage gap in occupations with these attributes. Occupational characteristics shape the conditions under which men and women work and we show these characteristics can make for environments that are more or less conducive to gender parity in earnings.
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Determination of the 2020 U.S. Citizen Voting Age Population (CVAP) Using Administrative Records and Statistical Methodology Technical Report
October 2020
Authors:
John M. Abowd,
J. David Brown,
Lawrence Warren,
Moises Yi,
Misty L. Heggeness,
William R. Bell,
Michael B. Hawes,
Andrew Keller,
Vincent T. Mule Jr.,
Joseph L. Schafer,
Matthew Spence
Working Paper Number:
CES-20-33
This report documents the efforts of the Census Bureau's Citizen Voting-Age Population (CVAP) Internal Expert Panel (IEP) and Technical Working Group (TWG) toward the use of multiple data sources to produce block-level statistics on the citizen voting-age population for use in enforcing the Voting Rights Act. It describes the administrative, survey, and census data sources used, and the four approaches developed for combining these data to produce CVAP estimates. It also discusses other aspects of the estimation process, including how records were linked across the multiple data sources, and the measures taken to protect the confidentiality of the data.
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Male Earnings Volatility in LEHD before, during, and after the Great Recession
September 2020
Working Paper Number:
CES-20-31
This paper is part of a coordinated collection of papers on prime-age male earnings volatility. Each paper produces a similar set of statistics for the same reference population using a different primary data source. Our primary data source is the Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files. Using LEHD data from 1998 to 2016, we create a well-defined population frame to facilitate accurate estimation of temporal changes comparable to designed longitudinal samples of people. We show that earnings volatility, excluding increases during recessions, has declined over the analysis period, a finding robust to various sensitivity analyses. Although we find volatility is declining, the effect is not homogeneous, particularly for workers with tenuous labor force attachment for whom volatility is increasing. These 'not stable' workers have earnings volatility approximately 30 times larger than stable workers, but more important for earnings volatility trends we observe a large increase in the share of stable employment from 60% in 1998 to 67% in 2016, which we show to largely be responsible for the decline in overall earnings volatility. To further emphasize the importance of not stable and/or low earning workers we also conduct comparisons with the PSID and show how changes over time in the share of workers at the bottom tail of the cross-sectional earnings distributions can produce either declining or increasing earnings volatility trends.
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United States Earnings Dynamics: Inequality, Mobility, and Volatility
September 2020
Working Paper Number:
CES-20-29
Using data from the Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files, we study changes over time and across sub-national populations in the distribution of real labor earnings. We consider four large MSAs (Detroit, Los Angeles, New York, and San Francisco) for the period 1998 to 2017, with particular attention paid to the subperiods before, during, and after the Great Recession. For the four large MSAs we analyze, there are clear national trends represented in each of the local areas, the most prominent of which is the increase in the share of earnings accruing to workers at the top of the earnings distribution in 2017 compared with 1998. However, the magnitude of these trends varies across MSAs, with New York and San Francisco showing relatively large increases and Los Angeles somewhere in the middle relative to Detroit whose total real earnings distribution is relatively stable over the period. Our results contribute to the emerging literature on differences between national and regional economic outcomes, exemplifying what will be possible with a new data exploration tool'the Earnings and Mobility Statistics (EAMS) web application'currently under development at the U.S. Census Bureau.
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Identifying U.S. Merchandise Traders: Integrating Customs Transactions with Business Administrative Data
September 2020
Working Paper Number:
CES-20-28
This paper describes the construction of the Longitudinal Firm Trade Transactions Database (LFTTD) enabling the identification of merchandise traders - exporters and importers - in the U.S. Census Bureau's Business Register (BR). The LFTTD links merchandise export and import transactions from customs declaration forms to the BR beginning in 1992 through the present. We employ a combination of deterministic and probabilistic matching algorithms to assign a unique firm identifier in the BR to a merchandise export or import transaction record. On average, we match 89 percent of export and import values to a firm identifier. In 1992, we match 79 (88) percent of export (import) value; in 2017, we match 92 (96) percent of export (import) value. Trade transactions in year t are matched to years between 1976 and t+1 of the BR. On average, 94 percent of the trade value matches to a firm in year t of the BR. The LFTTD provides the most comprehensive identification of and the foundation for the analysis of goods trading firms in the U.S. economy.
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Trends in Earnings Volatility using Linked Administrative and Survey Data
August 2020
Working Paper Number:
CES-20-24
We document trends in earnings volatility separately by gender in combination with other characteristics such as race, educational attainment, and employment status using unique linked survey and administrative data for the tax years spanning 1995-2015. We also decompose the variance of trend volatility into within- and between-group contributions, as well as transitory and permanent shocks. Our results for continuously working men suggest that trend earnings volatility was stable over our period in both survey and tax data, though with a substantial countercyclical business-cycle component. Trend earnings volatility among women declined over the period in both survey and administrative data, but unlike for men, there was no change over the Great Recession. The variance decompositions indicate that nonresponders, low-educated, racial minorities, and part-year workers have the greatest group specific earnings volatility, but with the exception of part-year workers, they contribute least to the level and trend of volatility owing to their small share of the population. There is evidence of stable transitory volatility, but rising permanent volatility over the past two decades in male and female earnings.
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Validating Abstract Representations of Spatial Population Data while considering Disclosure Avoidance
February 2020
Working Paper Number:
CES-20-05
This paper furthers a research agenda for modeling populations along spatial networks and expands upon an empirical analysis to a full U.S. county (Gaboardi, 2019, Ch. 1,2). Specific foci are the necessity of, and methods for, validating and benchmarking spatial data when conducting social science research with aggregated and ambiguous population representations. In order to promote the validation of publicly-available data, access to highly-restricted census microdata was requested, and granted, in order to determine the levels of accuracy and error associated with a network-based population modeling framework. Primary findings reinforce the utility of a novel network allocation method'populated polygons to networks (pp2n) in terms of accuracy, computational complexity, and real runtime (Gaboardi, 2019, Ch. 2). Also, a pseudo-benchmark dataset's performance against the true census microdata shows promise in modeling populations along networks.
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