A 2004 report by the author reviewed data from Census 2000 and concluded "There is a substantial gap in median earnings between men and women that is unexplained, even after controlling for work experience (to the extent it can be represented by age and presence of children), education, and occupation." This paper extends the analysis and concludes that once those characteristics are controlled for, no further explanatory power is attributable to race or Hispanic origin.
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Using Administrative Earnings Records to Assess Wage Data Quality in the March Current Population Survey and the Survey of Income and Program Participation
November 2002
Working Paper Number:
tp-2002-22
The March Current Population Survey (CPS) and the Survey of Income and Program
Participation (SIPP) produce different aggregates and distributions of annual wages. An excess of
high wages and shortage of low wages occurs in the March CPS. SIPP shows the opposite, an
excess of low wages and shortage of high wages. Exactly-matched Detailed Earnings Records
(DER) from the Social Security Administration allow comparing March CPS and SIPP people's
wages using data independent of the surveys. Findings include the following. March CPS and
SIPP people differ little in their true wage characteristics. March CPS and SIPP represent a
worker's percentile rank better than the dollar amount of wages. Workers with one job and low
work effort have underestimated March CPS wages. March CPS has a higher level of
"underground" wages than SIPP, and increasingly so in the 1990s. March CPS has a higher level
of self-employment income "misclassified" as wages than SIPP, and increasingly so in the 1990s.
These trends may explain one-third of March CPS's 6-percentage-point increase in aggregate
wages relative to independent estimates from 1993 to 1995. Finally, the paper delineates March
CPS occupations disproportionately likely to be absent from the administrative data entirely or to
"misclassify" self-employment income as wages.
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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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Occupation Inflation in the Current Population Survey
September 2012
Working Paper Number:
CES-12-26
A common caveat often accompanying results relying on household surveys regards respondent error. There is research using independent, presumably error-free administrative data, to estimate the extent of error in the data, the correlates of error, and potential corrections for the error. We investigate measurement error in occupation in the Current Population Survey (CPS) using the panel component of the CPS to identify those that incorrectly report changing occupation. We find evidence that individuals are inflating their occupation to higher skilled and higher paying occupations than the ones they actually perform. Occupation inflation biases the education and race coefficients in standard Mincer equation results within occupations.
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Social, Economic, Spatial, and Commuting Patterns of Informal Jobholders
April 2007
Working Paper Number:
tp-2007-02
A significant number of employees within the United States can be considered "informal" or
"off-the-books" workers. These workers, who by definition do not appear in administrative wage
records, are distinct from the larger group of private jobholders who do appear in administrative
records. However, while socioeconomic and spatial information on these individuals is readily
available in standard datasets, such as the 2000 Decennial Census Long Form, it is not possible
to identify the informal workers by only using such data because of the lack of accurate, formal
wage records. This study takes advantage of firm-based data that originates in Unemployment
Insurance administrative wage records linked with the Census Bureau's household-based data in
order to examine informal jobholders by their demographic characteristics as well as their
economic, commuting, and spatial location outcomes. In addition this report evaluates whether
informal jobholders should be included explicitly in future labor-workforce analyses and
transportation modeling. The analyses in this report use the sample of workers who lived in Los
Angeles County, California.
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Social, Economic, Spatial, and Commuting Patterns of Self-Employed Jobholders
April 2007
Working Paper Number:
tp-2007-03
A significant number of employees within the United States identify themselves as selfemployed,
and they are distinct from the larger group identified as private jobholders. While
socioeconomic and spatial information on these individuals is readily available in standard
datasets, such as the 2000 Decennial Census Long Form, it is possible to gain further information
on their wage earnings by using data from administrative wage records. This study takes
advantage of firm-based data from Unemployment Insurance administrative wage records linked
with the Census Bureau's household-based data in order to examine self-employed jobholders -
both as a whole and as subgroups defined according to their earned wage status - by their
demographic characteristics as well as their economic, commuting, and spatial location
outcomes. Additionally, this report evaluates whether self-employed jobholders and the defined
subgroups should be included explicitly in future labor-workforce analyses and transportation
modeling. The analyses in this report use the sample of self-employed workers who lived in Los
Angeles County, California.
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Social, Economic, Spatial, and Commuting Patterns of Dual Jobholders
April 2007
Working Paper Number:
tp-2007-01
Individuals who hold multiple jobs have complex working lives and complex commuting
patterns. Economic and spatial information on these individuals is not readily available in
standard datasets, such as the 2000 Decennial Census Long Form, because the survey questions
were not designed to collect details on multiple jobs. This study takes advantage of firm-based
data from the Unemployment Insurance administrative wage records, linked with the Census
Bureau's household-based data, to examine multiple jobholders - and specifically a sentinel
group of dual jobholders. The study uses a sample from Los Angeles County, California and
examines the dual jobholders by their demographic characteristics as well as their economic,
commuting, and spatial location outcomes. In addition this report evaluates whether multiple
jobholders should be included explicitly in future labor-workforce analyses and transportation
modeling.
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A Task-based Approach to Constructing Occupational Categories
with Implications for Empirical Research in Labor Economics
September 2019
Working Paper Number:
CES-19-27
Most applied research in labor economics that examines returns to worker skills or differences in earnings across subgroups of workers typically accounts for the role of occupations by controlling for occupational categories. Researchers often aggregate detailed occupations into categories based on the Standard Occupation Classification (SOC) coding scheme, which is based largely on narratives or qualitative measures of workers' tasks. Alternatively, we propose two quantitative task-based approaches to constructing occupational categories by using factor analysis with O*NET job descriptors that provide a rich set of continuous measures of job tasks across all occupations. We find that our task-based approach outperforms the SOC-based approach in terms of lower occupation distance measures. We show that our task-based approach provides an intuitive, nuanced interpretation for grouping occupations and permits quantitative assessments of similarities in task compositions across occupations. We also replicate a recent analysis and find that our task-based occupational categories explain more of the gender wage gap than the SOC-based approaches explain. Our study enhances the Federal Statistical System's understanding of the SOC codes, investigates ways to use third-party data to construct useful research variables that can potentially be added to Census Bureau data products to improve their quality and versatility, and sheds light on how the use of alternative occupational categories in economics research may lead to different empirical results and deeper understanding in the analysis of labor market outcomes.
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Gender Segregation Small Firms
October 1992
Working Paper Number:
CES-92-13
This paper studies interfirm gender segregation in a unique sample of small employers. We focus on small firms because previous research on interfirm segregation has studied only large firms and because it is easier to link the demographic characteristics of employers and employees in small firms. This latter feature permits an assessment of the role of employer discrimination in creating gender segregation. Our first finding is that interfirm segregation is prevalent among small employers. Indeed men and women rarely work in fully integrated firms. Our second finding is that the education and gender of the business owner strongly influence the gender composition of a firm's workforce. This suggests that employer discrimination may be an important cause of workplace gender segregation. Finally, we estimate that interfirm segregation can account for up to 50% of the gender gap in annual earnings.
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Evaluating Race and Hispanic Origin Responses of Medicaid Participants Using Census Data
April 2015
Working Paper Number:
carra-2015-01
Health and health care disparities associated with race or Hispanic origin are complex and continue to challenge researchers and policy makers. With the intention of improving the measurement and monitoring of these disparities, provisions of the Patient Protection and Affordable Care Act (ACA) of 2010 require states to collect, report and analyze data on demographic characteristics of applicants and participants in Medicaid and other federally supported programs. By linking Medicaid records to 2010 Census, American Community Survey, and Census 2000, this new large-scale study examines and documents the extent to which pre-ACA Medicaid administrative records match self-reported race and Hispanic origin in Census data. Linked records allow comparisons between individuals with matching and non-matching race and Hispanic origin data across several demographic, socioeconomic and neighborhood characteristics, such as age, gender, language proficiency, education and Census tract variables. Identification of the groups most likely to have non-matching and missing race and Hispanic origin data in Medicaid relative to Census data can inform strategies to improve the quality of demographic data collected from Medicaid populations.
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More than a Million New American Indians in 2000: Who are They?
March 2013
Working Paper Number:
CES-13-02
Over a million people reported their race as American Indian in the 2000 U.S. Census but did not report that race in the 1990 Census. We investigate three questions related to this extraordinary population change: (1) Which subgroups of American Indians had the greatest numerical growth? (2) Which subgroups had the greatest proportional increase? And (3) is it plausible that all 'new' American Indians reported multiple races in 2000? We use full-count and high-density decennial U.S. census data; adjust for birth, death, and immigration; decompose on age, gender, Latino origin, education, and birth state; and compare the observed American Indian subgroup sizes in 2000 to the sizes expected based on 1990 counts. The largest numerical increases were among non-Latino youth (ages 10-19), non-Latino adult women, and adults with no college degree. Latinos, highly-educated adults, and women have the largest proportionate gains, perhaps indicating that 'American Indian' has special appeal in these groups. We also find evidence that a substantial number of new American Indians reported only American Indian race in 2000, rather than a multiple-race response. This research is relevant to social theorists, race scholars, community members, program evaluators, and the Census Bureau.
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