DETAILS

Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the National Academies Press. 

(Request Permission) Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences.

Copyright © National Academy of Sciences. All rights reserved.

THE NATIONAL ACADEMIES PRESS

Visit the National Academies Press at NAP.edu and login or register to get:

– Access to free PDF downloads of thousands of scientific reports

– 10% off the price of print titles

– Email or social media notifications of new titles related to your interests

– Special offers and discounts



 

GET THIS BOOK

FIND RELATED TITLES

This PDF is available at SHARE

CONTRIBUTORS

   

SUGGESTED CITATION

http://nap.edu/25822

Measuring Alternative Work Arrangements for Research and

Policy (2020)

172 pages | 6 x 9 | PAPERBACK

ISBN 978-0-309-67847-6 | DOI 10.17226/25822

Committee on Contingent Work and Alternative Work Arrangements; Committee on

National Statistics; Division of Behavioral and Social Sciences and Education;

National Academies of Sciences, Engineering, and Medicine

National Academies of Sciences, Engineering, and Medicine 2020. Measuring

Alternative Work Arrangements for Research and Policy. Washington, DC: The

National Academies Press. https://doi.org/10.17226/25822.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

Committee on Contingent Work and Alternative Work Arrangements

Committee on National Statistics

Division of Behavioral and Social Sciences and Education

A Consensus Study Report of
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE NATIONAL ACADEMIES PRESS 500 Fifth Street, NW Washington, DC 20001

This activity was supported by a contract between the National Academies of Sciences, Engineering, and Medicine and the U.S. Department of Labor, Bureau of 

Labor Statistics, under Sponsor Award #: 1625 DC-18-C-0007. Support for the 

work of the Committee on National Statistics is provided by a consortium of federal 

agencies through a grant from the National Science Foundation, a National Agricultural Statistics Service cooperative agreement, and several individual contracts. Any 

opinions, findings, conclusions, or recommendations expressed in this publication 

do not necessarily reflect the views of any organization or agency that provided 

support for the project.

International Standard Book Number-13: 978-0-309-67847-6

International Standard Book Number-10: 0-309-67847-1

Digital Object Identifier: https://doi.org/10.17226/25822

Additional copies of this publication are available from the National Academies 

Press, 500 Fifth Street, NW, Keck 360, Washington, DC 20001; (800) 624-6242 or 

(202) 334-3313; http://www.nap.edu. 

Copyright 2020 by the National Academy of Sciences. All rights reserved.

Printed in the United States of America

Suggested citation: National Academies of Sciences, Engineering, and Medicine. 2020. 

Measuring Alternative Work Arrangements for Research and Policy. Washington, DC: 

The National Academies Press. https://doi.org/10.17226/25822.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

The National Academy of Sciences was established in 1863 by an Act of 

Congress, signed by President Lincoln, as a private, nongovernmental institution to advise the nation on issues related to science and technology. Members 

are elected by their peers for outstanding contributions to research. Dr. Marcia 

McNutt is president.

The National Academy of Engineering was established in 1964 under the charter of the National Academy of Sciences to bring the practices of engineering 

to advising the nation. Members are elected by their peers for extraordinary 

contributions to engineering. Dr. John L. Anderson is president.

The National Academy of Medicine (formerly the Institute of Medicine) was 

established in 1970 under the charter of the National Academy of Sciences to 

advise the nation on medical and health issues. Members are elected by their 

peers for distinguished contributions to medicine and health. Dr. Victor J. Dzau 

is president.

The three Academies work together as the National Academies of Sciences, 

Engineering, and Medicine to provide independent, objective analysis and advice 

to the nation and conduct other activities to solve complex problems and inform 

public policy decisions. The National Academies also encourage education and 

research, recognize outstanding contributions to knowledge, and increase public 

understanding in matters of science, engineering, and medicine. 

Learn more about the National Academies of Sciences, Engineering, and Medicine 

at www.nationalacademies.org. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

Consensus Study Reports published by the National Academies of Sciences, 

Engineering, and Medicine document the evidence-based consensus on the 

study’s statement of task by an authoring committee of experts. Reports typically include findings, conclusions, and recommendations based on information 

gathered by the committee and the committee’s deliberations. Each report 

has been subjected to a rigorous and independent peer-review process and it 

represents the position of the National Academies on the statement of task.

Proceedings published by the National Academies of Sciences, Engineering, and 

Medicine chronicle the presentations and discussions at a workshop, symposium, 

or other event convened by the National Academies. The statements and opinions contained in proceedings are those of the participants and are not endorsed 

by other participants, the planning committee, or the National Academies.

For information about other products and activities of the National Academies, 

please visit www.nationalacademies.org/about/whatwedo.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

v

COMMITTEE ON CONTINGENT WORK AND 

ALTERNATIVE WORK ARRANGEMENTS

SUSAN N. HOUSEMAN (Chair), W.E. Upjohn Institute for Employment 

Research, Kalamazoo, MI

KATHARINE G. ABRAHAM, University of Maryland, College Park

ANNETTE BERNHARDT, University of California–Berkeley

JENNIFER DYKEMA, University of Wisconsin–Madison

DIANA FARRELL, JPMorgan Chase Institute, Washington, DC 

ARNE L. KALLEBERG, University of North Carolina at Chapel Hill

KRISTEN M. OLSON, University of Nebraska–Lincoln

BARBARA J. ROBLES, Federal Reserve Board, Washington, DC

MICHAEL R. STRAIN, American Enterprise Institute, Washington, DC

DAVID WEIL, Brandeis University, Waltham, MA

CHRISTOPHER MACKIE, Study Director

ANTHONY S. MANN, Program Associate

FIONA GREIG, Consultant, JPMorgan Chase Institute, Washington, DC
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

vi

COMMITTEE ON NATIONAL STATISTICS

ROBERT M. GROVES, (Chair), Office of the Provost, Georgetown 

University

LAWRENCE D. BOBO, Department of Sociology, Harvard University

ANNE C. CASE, Woodrow Wilson School of Public and International 

Affairs, Princeton University

MICK P. COUPER, Institute for Social Research, University of Michigan

JANET CURRY, Woodrow Wilson School of Public and International 

Affairs, Princeton University

DIANA FARRELL, JPMorgan Chase Institute, Washington, DC

ROBERT GOERGE, Chapin Hall at The University of Chicago

ERICA L. GROSHEN, School of Industrial and Labor Relations, Cornell 

University

HILARY HOYNES, Goldman School of Public Policy, University of 

California–Berkeley

DANIEL KIFER, Department of Computer Science and Engineering, The 

Pennsylvania State University

SHARON LOHR, School of Mathematical and Statistical Sciences, 

Arizona State University, Emerita

JEROME P. REITER, Department of Statistical Science, Duke University

JUDITH A. SELTZER, Department of Sociology, University of 

California–Los Angeles 

C. MATTHEW SNIPP, Department of Sociology, Stanford University

ELIZABETH A. STEWART, Departments of Mental Health and 

Biostatistics, Johns Hopkins Bloomberg School of Public Health

JEANETTE M. WING, Data Science Institute, Columbia University

BRIAN HARRIS-KOJETIN, Director

CONNIE F. CITRO, Senior Scholar
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

vii

This report reflects the contributions of many colleagues who generously gave their time and expert advice. The U.S. Bureau of Labor Statistics 

(BLS) sponsored the project to help guide their efforts to improve and modernize the Contingent Worker Supplement (CWS) to the Current Population 

Survey (CPS). An integral component of the federal economic statistics 

system, the CPS provides critical information on U.S. labor market conditions and trends. The CWS was developed in the 1990s to measure aspects 

of the employment relationship—specifically, the temporary or contingent 

nature of jobs and certain nonstandard or alternative work arrangements. 

As outlined in this report, a somewhat broader measurement approach is 

now required to address research and policy information needs pertaining 

to the changing nature of work in the economy. 

The panel thanks BLS staff who helped shape the project scope. They 

provided comprehensive information about the CPS and CWS programs 

and conveyed the agency’s priorities for next steps in the development of 

the CWS. At the very first meeting of the panel, William J. Wiatrowski, 

deputy commissioner of BLS, outlined the agency’s vision and strategy for 

measuring employment in the modern economy and articulated goals for 

this study. During subsequent meetings, BLS Commissioner William Beach 

(who began his tenure in the position March 2019) added clarity to this 

discussion. Anne Polivka, supervisory research economist in the Office of 

Employment and Unemployment Statistics, shared her extensive knowledge 

of the CWS and the CPS—describing objectives of the survey, its strengths 

and limitations, and its design and methodology. Julie Hatch Maxfield, 

associate commissioner for the Office of Employment and Unemployment 

Acknowledgments
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

viii ACKNOWLEDGMENTS

Statistics, presented findings from the May 2017 CWS and walked the panel 

through the agency’s experience adding questions about web-mediated 

employment. Finally, the panel benefited from expert coordination and 

leadership throughout the project from Jennifer Edgar, associate commissioner for Survey Methods Research. 

The panel also benefited greatly from presentations on topics central 

to the panel’s charge by experts outside the BLS. Participants in open session meetings provided insights about the policy context for measuring 

alternative work, different measures of worker well-being, and the roles 

of non-BLS surveys and administrative data in measuring alternative work 

arrangements. Carolina F. Young, policy advisor, Office of U.S. Senator 

Mark R. Warner, discussed Congressional developments such as proposed 

legislation that would direct the U.S. Treasury to study tax issues for webmediated economy workers, and the kinds of data needed to inform this 

work. Alastair Fitzpayne, executive director of the Aspen Institute’s Future 

of Work Initiative, and Shelly Steward, research manager for the Initiative, 

informed the panel about their organization’s efforts to identify policy 

solutions to the challenges facing workers in the 21st century. They also 

described the Gig Economy Data Hub, developed in partnership with the 

New York State School of Industrial and Labor Relations at Cornell, an 

online resource summarizing data sources relevant to the study of independent and nontraditional work. 

Susan Lambert of the University of Chicago’s School of Social Service 

Administration presented information to the panel about policy issues 

affecting worker well-being and provided key insights about the problem 

of unpredictable work schedules, particularly as they affect the well-being 

and security of low-income and low-skill workers. Tim Bushnell, Economic 

Research and Support Office, and Toni Alterman, Division of Surveillance, 

Hazard Evaluations and Field Studies, both of the National Institute of 

Occupational Safety and Health, informed the panel about their agency’s 

efforts to develop a taxonomy of work arrangements to examine their relationships with worker safety, health, and well-being. 

Gene Zaino, founder and executive chairman of MBO Partners, provided details to the panel about his organization’s work on policy issues 

and research characterizing the independent workforce. Cynthia Davidson 

and Steve Berchem of the American Staffing Association (ASA) presented 

information to the panel about survey and policy work at their organization—most notably the ASA Staffing Employment and Sales Survey, which 

collects information from firms to estimate temporary and contract staffing 

industry employment, sales, and payroll. 

Leif Jensen of Penn State University presented findings from his surveybased research exploring urban-rural variation in informal work activities 

and discussed strategies for measuring these patterns. Dmitri Koustas of 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

ACKNOWLEDGMENTS ix

the University of Chicago added to the panel’s knowledge base about what 

can be learned about alternative work arrangements from tax and from 

personal financial services data—particularly for jobs mediated through 

online platforms. Mike Udell and Diane Lim from the District Economics 

Group provided a rich accounting of the role of tax data in measuring 

alternative work arrangements, identifying advantages and limitations of 

such data to measure alternative employment. Jim Spletzer of the Center 

for Economic Studies, U.S. Census Bureau, detailed work being conducted 

at the Census Bureau that involves combining data sources; he assessed the 

potential of linking CPS microdata to tax data, described how this kind of 

data linkage is done, and summarized what might be learned about alternative work arrangements using this approach. Additionally, Fiona Greig, 

from the JPMorgan Chase Institute and a consultant to the project, provided insights into the use of private sector data in understanding alternative work arrangements. The panel thanks all of these individuals for their 

contributions to the study process.

The panel could not have conducted its work efficiently without the 

capable staff of the National Academies of Sciences, Engineering, and Medicine: Brian Harris-Kojetin, director of the Committee on National Statistics, provided institutional leadership and substantive contributions during 

meetings; Kirsten Sampson Snyder, Division of Behavioral and Social Sciences and Education, coordinated the review process flawlessly; and Marc 

DeFrancis provided thorough final editing that improved the readability 

of the report. We also thank senior program associate Anthony Mann for 

his well-organized and efficient logistical support of the panel’s meetings, 

as well as his contribution formatting this report. The panel is especially 

indebted to Christopher Mackie of the Committee on National Statistics, 

who was the study director for the project. Chris played an invaluable role 

in organizing meetings; synthesizing input from panel members, outside 

experts, and reviewers; and helping to draft the report and response to 

external reviews. 

Finally, and most importantly, I would like to add a note of appreciation for fellow panel members who formed the core of the study 

team. This report reflects the collective expertise and commitment of all 

panel members: Katharine G. Abraham, University of Maryland; Annette 

Bernhardt, University of California–Berkeley; Jennifer Dykema, University 

of Wisconsin–Madison; Diana Farrell, JPMorgan Chase Institute; Arne L. 

Kalleberg, University of North Carolina at Chapel Hill; Kristen M. Olson, 

University of Nebraska–Lincoln; Barbara J. Robles, Federal Reserve Board; 

Michael R. Strain, American Enterprise Institute; and David Weil, Brandeis 

University. This group—chosen for their diverse perspectives, backgrounds, 

and subject matter knowledge—gave generously of their time to attend meetings and to collaborate in the writing of this report. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

x ACKNOWLEDGMENTS

This Consensus Study Report was reviewed in draft form by individuals 

chosen for their diverse perspectives and technical expertise. The purpose 

of this independent review is to provide candid and critical comments that 

will assist the National Academies of Sciences, Engineering, and Medicine 

in making each published report as sound as possible and to ensure that 

it meets the institutional standards for quality, objectivity, evidence, and 

responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process.

We thank the following individuals for their review of this report: David 

Autor, Department of Economics, Massachusetts Institute of Technology; 

Susan J. Lambert, School of Social Service Administration, University of 

Chicago; Thomas L. Mesenbourg, retired, U.S. Census Bureau; Lawrence 

Mishel, Distinguished Fellow, Economic Policy Institute; Jean Opsomer, 

Senior Statistician, Westat, Inc.; Stanley Presser, Sociology Department and 

Joint Program in Survey Methodology, University of Maryland; Alexandrea 

J. Ravenelle, Department of Sociology, University of North Carolina–

Chapel Hill, and visiting scholar, Institute for Public Knowledge, New York 

University; and Carolina F. Young, policy advisor, Office of U.S. Senator 

Mark R. Warner.

Although the reviewers listed above provided many constructive comments and suggestions, they were not asked to endorse the conclusions or 

recommendations, nor did they see the final draft of the report before its 

release. The review of the report was overseen by Robert A. Moffitt, Department of Economics, Johns Hopkins University, and Alicia L. Carriquiry, 

Department of Statistics, Iowa State University. They were responsible 

for making certain that an independent examination of this report was 

carried out in accordance with the standards of the National Academies 

and that all review comments were carefully considered. Responsibility 

for the final content rests entirely with the authoring committee and the 

National Academies. 

Susan N. Houseman, Chair

Committee on Contingent Work and 

Alternative Work Arrangements
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

xi

Contents

Summary 1

1 Introduction: Motivation for the Study 15

1.1. The Changing Nature of Work, 15

1.2. Informing Research and Policy, 19

1.3. The Measurement Role of the Contingent Worker 

Supplement, 25

1.4. Charge to the Panel, 30

2 Measurement Needs for Understanding the Changing Nature 

of Work 33

2.1. Employment: Measuring All “Significant” Sources of 

Work Income, 36

2.2. Job Types: Categories of Alternative Work Arrangements, 40

2.3. Key Job Characteristics Affecting Worker Outcomes and 

Well-being, Employer Strategies, 43

2.4. Information about Alternative Work Arrangements That 

Could Be Provided by Businesses, 50

3 Role of the Contingent Worker Supplement in Fulfilling 

Measurement Needs Related to Alternative Work Arrangements 53

3.1. Overview of the Contingent Worker Supplement, 54

3.2. CWS Scope: Universe of Workers and Work Activities, 58

3.3. Categorizing Work and Workers, 67
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

xii CONTENTS

3.4. Insecurity in Hours, Jobs, and Earnings, 75

3.5. Other Information Needed for Understanding Alternative 

Work Arrangements and Their Implications for Workers, 80

4 The Role of Other Data Sources in Measuring Alternative 

Work Arrangements 87

4.1. Other Household Surveys, 88

4.2. Establishment and Other Business Surveys, 90

4.3. Government Administrative and Commercial Data, 94

4.4. The Longer-Term Promise of Combining Data Sources, 100

References 103

Appendixes

A Biographical Sketches of Committee Members 111

B Summary of June 10, 2019, Workshop 115
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

Summary

MOTIVATION FOR THE STUDY: BETTER DATA 

TO INFORM RESEARCH AND POLICY

Business structures, employment relationships, job characteristics, and 

worker outcomes have changed in the United States over the last few 

decades—in some ways unpredictably. The way people work, for whom 

they work, how that work is arranged, and how they are paid are all elements of the evolving labor market. The goals of businesses to be more 

flexible and to lower costs continue to shape employment relationships, 

aspects of which have been enabled by new technologies. 

A high level of interest exists among policy makers and researchers in 

addressing concerns about the future of work in the United States. These 

concerns are heightened by the perceived fracturing of relationships between 

workers and employers, the loss of safety net protections and benefits to 

workers, the growing importance of access to skills and education as the 

impacts of new technologies and automation are felt, and the market-based 

pressure that companies face to produce short-term profits, sometimes at 

the expense of long-term value. These issues, as well as related ones such 

as wage stagnation and job quality, are often associated with alternative 

work arrangements (AWAs)—which include independent-contractor and 

other nonemployee jobs, work through intermediaries such as temporary 

help agencies and other contract companies, and work with unpredictable 

schedules—although they also pertain to many standard jobs (Howell and 

Kalleberg, 2019). A better understanding of the magnitude of and trends 

1
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

2 MEASURING ALTERNATIVE WORK ARRANGEMENTS

in AWAs, along with the implications for job quality, is needed to develop 

appropriate policies in response to the changing nature of work.

Along with addressing challenges inherent in AWAs, policies also need 

to nurture the positives created by innovative new employment models. 

People often value being their own boss and the scheduling flexibility that 

some AWAs afford. And, from the perspective of businesses, companies may 

use independent contractors not just to lower costs, but also to tap into 

skills pools with the agility required to maintain competitiveness. Sustaining 

a strong economy requires that policies be designed to make new employment models work well both for workers and for the organizations that 

hire them. One policy goal is to protect the lower-paid workers who are 

vulnerable to abuse as part of a “race to the bottom” while simultaneously 

enabling on-shore economic growth for the higher-skilled and higher-paid 

jobs where workers often have choices. 

Congress and other policy makers will move forward on legislation and 

advocacy regarding the future of work in some capacity with or without 

data-based evidence. This makes it all the more urgent to improve the data 

infrastructure for studying the alternative worker population.

MEASUREMENT NEEDS FOR UNDERSTANDING 

THE CHANGING NATURE OF WORK

Changes in the structure of work—specifically growth in temporary 

work—were already apparent by the 1980s. Recognizing a need for highquality data that could be used for analyzing these trends shaping the labor 

market, the U.S. Bureau of Labor Statistics (BLS) developed the Contingent 

Worker Supplement (CWS) of the Current Population Survey (CPS), which 

was first administered in 1995.1 The Supplement has been fielded five times 

since 1995, at irregular intervals depending on funding, most recently in 

2017. The CWS was implemented to measure aspects of the employment 

relationship—specifically, whether people’s jobs were temporary or contingent in nature, and hence less secure. The supplement also measures work 

arrangements thought to be associated with lower commitment by companies to their workforce. The CWS currently collects information from 

individuals identified as employed in the CPS only about their main job, 

defined by BLS as the job associated with the most hours worked. 

Although much has changed in the 25 years since the first CWS was 

implemented, the broad measurement objectives as originally conceived are 

1As defined by BLS, contingent workers are those who “do not expect their jobs to last or 

who report that their jobs are temporary.” They also do not have an implicit or explicit contract for ongoing employment. Available: https://www.bls.gov/cps/contingent-and-alternativearrangements-faqs.htm.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

SUMMARY 3

still relevant today. Indeed, when BLS received funding to field a new round 

of the CWS in 2017, a primary objective was to assess how the number of 

workers in contingent work and AWAs had changed since 2005, the last 

time the supplement had been fielded. However, modifications to the survey 

are needed to accurately measure changes in the workforce in a way that 

meets current policy and research requirements.

The charge to the authoring panel of this report was to develop recommendations to help guide BLS in its efforts to improve and modernize the 

CWS.2 In so doing, the panel’s work reflects research and policy questions 

that have arisen from concerns about the economic and health impacts 

on the population of modern work arrangements, which are evolving in 

response to emerging technologies and the shifting boundaries of where, 

how, and by whom work is performed. These concerns have only been 

heightened during the current critical time for our economy. The onset 

and now deepening impact of COVID-19 has exposed how vulnerable our 

society can be when workers are participating in the labor market without 

an adequate and well-coordinated social safety net. This unprecedented 

economic disruption has made it even more clear the importance of BLS’s 

work to better measure alternative work arrangements in the United States.

In carrying out its charge, the panel assessed (1) the measurement needs 

for monitoring the changing employment landscape and for informing policies designed to mitigate negative effects while preserving the benefits from 

these changes; (2) the role of household surveys, and the CWS specifically, 

in fulfilling the spectrum of measurement needs concerning AWAs; and 

(3) the comparative strengths and weaknesses of the CWS in the context of 

complementary survey and nonsurvey data sources.

THE ROLE OF THE CWS IN MEASURING 

ALTERNATIVE WORK ARRANGEMENTS; 

RECOMMENDATIONS FOR FUTURE ITERATIONS OF THE SURVEY

The CWS measures arrangements concerning the main job of everyone 

who reports having worked during the survey reference period in the basic 

monthly CPS. By design, it does not capture work done by a person to 

generate income that is not reported in response to the core CPS employment questions. The panel considered whether this universe of workers 

and work activities is defined appropriately to capture the information on 

work in contingent and alternative work arrangements needed for policy 

and research. In so doing, issues related to the survey reference week, work 

activities that might not be reported on the main CPS, and secondary 

work activities were all examined. 

2The statement of task is reproduced in full in Chapter 1.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

4 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Survey Scope: The Universe of Workers and Types of Work Covered

Before AWAs can be measured, the universe of respondents (workers) from whom information is being requested must be determined. In 

the current CWS, other than a single question asked of unemployed and 

discouraged workers, questions are asked only of those who are identified 

in the basic monthly CPS as having been employed in the prior week. One 

major survey design feature that could affect which respondents are within 

the scope of the CWS concerns the timing and regularity of respondents’ 

work in relation to the survey’s 1-week reference period. People who report 

being unemployed or not in the labor force may nonetheless engage in work 

activities periodically to supplement household income. Unlike people who 

work a regular weekly schedule or who do not work at all, those whose 

work is sporadic may be missed. The choice of reference period may be 

particularly important for measuring platform or app-based work and 

informal independent contractor work. Analyses of financial account data 

(e.g., Farrell, Greig, and Hamoudi, 2018) indicate that most individuals 

participating in platform work do so during no more than 3 months of the 

year. As a result, platform participation rates are much lower if estimated 

for a particular week as opposed to a longer period.

Recent research (e.g., Abraham and Amaya, 2019; Bracha and Burke, 

2017) also suggests that the standard CPS employment question does not 

capture everyone who performs work for pay during the survey’s reference week. For reasons specified below, some types of AWA work—such 

as performing housekeeping or yard work, providing child care or elder 

care, driving for Uber, and many others—appear especially elusive. One 

possible explanation for this finding is that some people engaged in AWAs 

may not think of themselves as employed in the labor force, especially if 

they have held a standard employer-provided job in the past. In the CWS, 

people whose only employment is work they do not report in response to 

the basic CPS employment question are not asked about the arrangements 

under which that work occurs. This is a potentially important omission. 

The CWS could address these two issues—a short reference period and 

potential under-reporting of certain AWAs—by asking CPS respondents who 

did not report any work in the main CPS a set of initial screener questions. 

At the beginning of the CWS supplement, screener questions should be 

asked of those who did not report any work in the basic monthly CPS. The 

questions should probe into work activities for pay that individuals sometimes do to supplement household income when they are unemployed and 

looking for a steady job or when they are retired or otherwise not steadily 

employed. The questions should ask about such work over a longer reference period, such as 1 month, as well as during the CPS reference period 

(the prior week). (Recommendation 3.1)
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

SUMMARY 5

Further limiting the scope of work activity covered in the CPS is that 

it has traditionally been concerned only with the main job held by respondents. CPS data indicate that the share of workers who held more than 

one job averaged about 5 percent during 2017. However, research based 

on other data sources suggests that secondary work activities are far more 

common (Abraham, Hershbein, and Houseman, 2019; Allard and Polivka, 

2018; Bracha and Burke, 2018). Moreover, evidence suggests that secondary work activities often generate a substantial portion of people’s 

income and can be important for helping households offset a reduction 

in income earned from a main job. For those reporting that they worked, 

it would therefore be extremely useful to follow up about secondary work 

activity. 

For respondents reporting only one job in the basic CPS, the CWS should 

begin with a set of questions about additional work activity. Respondents 

would first be asked if they did anything for pay (to supplement income) 

beyond what they have already reported for their main job. The questions would ask about such work over a longer reference period, such 

as 1 month, as well as about the CPS reference period (the prior week). 

(Recommendation 3.2)

The 2017 CWS already asked respondents with at least one main job about 

additional work they may have done for pay using web platforms. Recommendation 3.2 simply expands this line of inquiry to include other types 

of work.

At least a subset of the questions asked about primary jobs should also 

be asked about the second jobs, whether those second jobs are identified in 

the basic monthly CPS or (as recommended above) in response to a question about additional work asked on the CWS: 

It would be desirable to ask the full battery of CWS questions about all 

secondary jobs held either during the reference week or during the longer 

1-month time frame. At a minimum, the CWS should collect information, 

where applicable, on selected characteristics of one secondary job (when 

there is more than one secondary job, selecting the one with the most 

hours worked). These characteristics should include whether the job is a 

self-employment or independent-contractor arrangement, hours variability, 

and main reason for holding the secondary job. If not already collected 

in the basic monthly CPS, information on hours, earnings, industry, and 

occupation also should be collected. (Recommendation 3.3)

As is always the case when new questions are added to the CPS or its 

supplements, careful cognitive testing will be required: 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

6 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Implementation of the new questions proposed for the CWS (in recommendations 3.1 through 3.3) will require extensive cognitive testing to 

determine the optimal reference period and wording to solicit responses 

about work that was not reported in the main CPS. (Recommendation 3.4)

It is critical for policy purposes that BLS endeavor to capture all work 

activity. Because employment mediated through platforms/apps is perceived 

to be growing rapidly, there is strong research and policy interest in tracking it. To do so, and to address one of the profound policy questions about 

modern employment—how people are piecing together income—some disruption of the CWS is warranted. Adding follow-up probing questions 

to the CWS could potentially affect responses in subsequent waves of the 

main CPS survey. While careful question wording should mitigate any such 

effects, the BLS may want to run tests on outgoing rotation groups to see 

how much additional employment is being picked up in such questions.

Job Types: Categories of Alternative Work Arrangements

The CWS permits the classification of a respondent’s main job into one 

of several mutually exclusive work categories:3

• Temporary agency worker;

• Contract company worker, other than a temporary agency worker;

• Independent contractor;

• Employee, not in an alternative work arrangement; or

• Self-employed, not independent contractor.

This categorization captures whether a worker is an employee of the organization for whom he or she is performing work. The set of AWAs distinguishes between those who are not employees (independent contractors, 

day laborers) and those who are in an intermediated arrangement (temporary agency worker, contract company worker). In the latter, workers are 

employees of a temporary help agency or other type of company that contracts their services to other organizations. On-demand platform work, captured only in the 2017 CWS, is a hybrid of these two job types. Although 

payments to workers in this category are mediated by the platform company, the workers are usually classified as independent contractors. 

Among these categories, there is particularly strong policy and research 

interest in distinguishing between those who are W-2 employees and those 

engaged in various self-employment or nonemployee arrangements. The 

3The CWS also collects information on on-call and day laborer work, which are covered 

in the next section.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

SUMMARY 7

latter are not covered by employment and labor laws such as those regulating wages and hours or guaranteeing collectively bargaining rights. Nor 

are they covered by social insurance programs, such as unemployment 

insurance and worker’s compensation. And finally, they have no access to 

the benefits often provided by employers, such as paid sick leave, health 

insurance, and retirement benefits. If work migrates toward a nonemployer 

structure, pressure will build to adjust social safety net and employment 

laws to mitigate this potential negative side effect of the trend. Recent 

legislative initiatives, such as California’s new law establishing a strict 

test for independent contractor classification, which might result in the 

reclassification of independent contractors such as those working for Uber 

and Lyft as employees, are suggestive of future policy initiatives. 

One challenge that household surveys have in measuring self-employment 

and subcategories of self-employment, such as independent contractors, is 

that respondents vary in their interpretation and understanding of what 

these terms mean. For example, while some respondents may understand 

“self-employment” to mean a status where one is not an employee of an 

organization, others may understand the term to mean the situation of 

owning and operating one’s own business. In coding whether a worker 

is an employee or self-employed, the CPS, like other government household surveys, does not ask respondents who report working whether they 

are employees, but rather whether they work for an organization or are 

self-employed. Those who do work for an organization but are not W-2 

employees may report working for that organization rather than being selfemployed. As a result, surveys may be prone to misidentifying independent 

contractors as employees (Abraham, Hershbein, and Houseman, 2019); this, 

in turn, may help explain why research using administrative data based on 

tax filings shows a greater share of (and higher growth in) individuals with 

self-employment income than does the CPS (Abraham et al., 2020; Abraham 

et al., Forthcoming; Jackson, Looney, and Ramnath, 2017; Lim et al., 2019). 

Given this evidence, a broad approach is needed for measuring independent contract work. Many who work as independent contractors do so 

primarily for one organization and may not think of themselves as obtaining customers on their own in the same way as, say, a self-employed business owner might. For this reason, that definition, which is used in a CWS 

question on independent contractors, is problematic. 

The CWS should continue to ask those identified both as self-employed 

and as employees in the main CPS about their status as an independent 

contractor. However, a broad definition of independent contractor should 

be given in both questions, and the current definition of independent 

contractor used for those identified as wage and salary workers should be 

replaced. (Recommendation 3.5)
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

8 MEASURING ALTERNATIVE WORK ARRANGEMENTS

The goal of the question referenced in recommendation 3.5 is to distinguish between W-2 employees and nonemployees, and the independent 

contractor work measure should include the types of AWAs wherein the 

individual is not an employee. The CWS should also clarify exactly what 

an independent contractor is: 

Cognitive testing should, among other things, determine how well respondents distinguish between employee and nonemployee concepts, and explore 

ways to improve the accuracy of responses. To this end, BLS might clarify 

for respondents that independent contractors are not employees of the 

organization or customers for whom they provide a good or service and/or 

do not have any taxes taken from their pay. (Recommendation 3.6)

As described above, BLS has recently prioritized the measurement of 

web platform work. One reason for this increased interest is that internet 

intermediary companies are formalizing some work arrangements that 

were previously considered informal work. There is also evidence that webmediated options are displacing more traditional job arrangements, as in 

the case of restaurants using web platforms to fill very-short-run staffing 

needs in lieu of hiring workers directly. 

A decision must be made about which web-mediated activities should 

be considered within the scope of the CWS. One distinction that can be 

made is between “work-based” income and income that is generated by 

a combination of work and capital. However, this distinction is blurry, 

because many web-mediated jobs combine capital and labor inputs. For 

example, renting out rooms through AirBnB entails both a capital-based 

component and a work- (or time-) based component. Someone operating 

several properties may be occupied full time in the enterprise. Likewise, 

Uber drivers must own or rent capital in the form of a car that passes the 

company’s equipment standards. How far apart Airbnb and Uber are on 

the labor/capital continuum is an open question, and there is a conceptual 

arbitrariness about drawing the line of inclusion for measurement in labor 

statistics between the two. 

For purposes of measuring web-platform work, BLS should test the option 

of not making a capital/labor distinction. The survey could simply ask 

self-identified platform workers which company (or companies) they work 

with, and then allow the data to be sorted depending on the question at 

hand. If the concern is over what motivates people’s efforts to generate 

income, the distinction regarding the extent to which income is a return on 

income or capital may not be crucial. (Recommendation 3.8)

Additionally, respondents may have difficulty differentiating between platform work that is more capital-based and that which is more labor-based. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

SUMMARY 9

Including all income-generating activities would avoid requiring respondents to make this subjective call.

Job Characteristics: Predictability, Stability, Security

A primary focus of the CWS has been on capturing the security of 

workers’ jobs. The concept of contingency, as measured in the CWS, pertains to whether a worker’s job is temporary in the sense that it is expected 

to last for a limited time. This measure captures job insecurity which, in 

cases where loss of the job results in employment gaps, may lead to employment and earnings instability. Job insecurity is one factor that may result 

in earnings insecurity. 

The CWS also asks wage and salary workers whether they work on an 

on-call or day laborer basis—that is, whether they work only when needed. 

Identifying this type of on-demand work captures a different element of 

earnings insecurity. Even if a job itself is not temporary, as is the case for 

much on-call work, the hours and hence a worker’s earnings may be variable. Although the AWA categories described in the preceding section are 

mutually exclusive, these essential characteristics of jobs may be present in 

all or most work arrangements. 

As opposed to the current approach of classifying workers into the categories of on-call workers or day laborers, the CWS should focus on simply 

describing the characteristics of these and other work arrangements with 

variable hours. (Recommendation 3.10)

A number of surveys (the 2017 American Time Use Survey Annual Leave 

Module is one example) offer options for question wording related to characteristics of jobs that could serve as models for the CWS. 

Schedule predictability and hours instability. The CWS is well suited to 

measure the instability in workers’ employment and earnings that occurs 

when their jobs are short term or performed on an on-call basis. But other 

aspects of schedule variability, such as (un-)reliability and (un-)predictability 

of hours, are also of great interest given their relationship to earnings and 

economic well-being. Many jobs, especially in retail and other service sectors, are highly variable in the timing and quantity of work hours. As with 

temporary work, this kind of variability can lead to economic insecurity. On 

the positive side, for some workers, the employment fluidity of such work 

arrangements has added a welcomed element of flexibility for them to earn 

income. This dichotomy—the implication of both insecurity and flexibility—

points to the importance of measuring and tracking job characteristics that 

directly affect the well-being of workers. The policy implications are clearly 

different if the trend toward irregular hours is being driven by a desire by 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

10 MEASURING ALTERNATIVE WORK ARRANGEMENTS

workers for flexible scheduling versus being driven by a lack of opportunities 

to acquire steady work.

The 2017 CWS found that only 1.9 percent of respondents self-identified as on-call workers, but the research cited above indicates that using a 

broader measure of schedule variability would yield a considerably higher 

rate. Given the prevalence of unpredictability in people’s work schedules, it 

has become important to measure this aspect of employment and earnings 

instability in a large, nationally representative survey: 

For employees, the CWS should inquire into the following aspects of 

schedules and hours:

• Usual hours worked and hours worked last week (on main and secondary jobs);

• Schedule autonomy—who determines the schedule, the employer or the 

worker?

• Schedule predictability—whether the schedule is generally the same 

from week to week or, if it varies, how much notice the worker typically 

receives;

• The amount by which weekly hours vary; and

• Whether a worker must be available if called. (Recommendation 3.11)

Asking respondents for information about their work schedules can also 

reveal insights into people’s motivations for pursuing a different or a second 

job. 

Contingency and job insecurity. A large number of questions on the 

CWS are devoted to measuring the contingency of jobs. Over its history, 

the CWS has uncovered no trend growth in contingent jobs, and BLS’s measures of contingency have not gained currency among policy makers and 

researchers. Moreover, the questions pertaining to expectations about job 

length have proven difficult for respondents to answer. For these reasons, 

some modification of the CWS is warranted.

While the temporary nature of some jobs is a key characteristic that should 

continue to be measured in future CWS surveys, the number of questions 

on contingency should be pared back and the questions that remain should 

be simplified (Recommendation 3.12). 

Other Information Needed to Understand the Implications of 

Alternative Work Arrangements for Workers

A key goal of the CWS is to facilitate an understanding of the relationship between specific work arrangements or job characteristics and worker 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

SUMMARY 11

outcomes. Toward this end, the CWS measures workers’ earnings and benefits as well as their preferences regarding work arrangements. 

Earnings and benefits. The positive relationship between people’s earnings and their well-being is obvious. Much attention has been given to 

the flat earnings growth experienced by workers over recent decades and the 

negative economic, health, and social impacts this has had on families. But 

how this trend relates to changing work arrangements and the expansion of 

AWAs is not fully understood, nor are the potential ripple effects of AWAs 

on conditions in standard employment settings understood. Given the stark 

contrast between higher-skill and lower-skill independent contractors, the 

relationship between AWAs and earnings is not well captured by measures 

of averages. 

Given the employer-delivered nature of many benefits in the United 

States, AWA workers are in some cases disadvantaged with respect to retirement plans, medical care plans, and other benefits. The possible link between 

AWAs on the one hand and wages and access to critical benefits on the other 

is of high policy interest. The onset of a global pandemic has underscored 

the need for increased awareness of the economic vulnerabilities present 

in the labor market. Basic information on the incidence of benefits being 

offered would be useful for discussions about the future of work. 

Reasons for choosing a work arrangement. The current CWS asks temporary workers, temporary agency workers, on-call workers, day laborers, 

and self-employed/independent contractors whether they would prefer a 

“non-contingent” or different job arrangement. The existing line of questions on individuals’ preferences for work in alternative arrangements provides information that is potentially valuable but, for reasons described in 

Chapter 3, difficult to interpret. Nonetheless, it is important to know the 

reasons people engage in AWAs as well as why people hold multiple jobs. 

Questions on job satisfaction, on reasons for working in an alternative 

arrangement, and on the motivation for working a second job/work activity 

would be extremely useful for understanding people’s work patterns.

BLS should ask questions on job satisfaction for all workers in lieu of 

asking job preference questions for selected workers. The BLS should 

continue to ask about reasons for working in selected alternative work 

arrangements, but it should consider moving away from field coding the 

responses and instead provide a preset list of reasons and ask respondents 

to identify the most important. In addition, for those with a second job or 

work activity, BLS should ask about their motivations for holding multiple 

jobs. (Recommendation 3.13)
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

12 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Components of the CWS to Streamline

In order to create survey space, some parts of the current CWS could 

be streamlined. Some questions have proven less useful than others because 

evidence indicates the quality of the resultant data is poor. For example, 

while tracking temporary help employment is important, the incidence 

measured by the CWS is well below that indicated by employer surveys and 

administrative data (Polivka, 1996). Respondents appear to confuse their 

actual employer, the temporary help agency, with the client for whom they 

are performing work. Similarly, while information on contract company 

workers is needed, household surveys may not offer the best method for 

collecting it. Partly because BLS concluded that respondents cannot reliably 

report on the contract arrangements of their employers, the CWS focuses 

on measuring a narrow set of contract company work: individuals who 

work primarily for one client company at the client’s worksite (i.e., remote 

work is not included). This narrow definition misses a lot of contract work.

BLS should consider dropping questions on temporary help agency employment and on contract company work from the CWS to make room 

for other, higher-priority questions. (Recommendation 3.9)

Data supplied by businesses are largely complementary to those 

captured in household surveys and can fill in some information needs. 

Establishment- and firm-level surveys are an underexplored source of data 

on AWAs, especially subcontracted work, that could yield vital information 

about the prevalence and nature of firms’ contracting-out activities. 

Another set of questions in the CWS asks each respondent what they 

or other household members were doing prior to becoming an independent 

contractor, a temporary agency worker, an on-call worker, or a contract 

company worker. Because of the retrospective nature of the question, the 

data quality is likely to be poor. The CWS also asks respondents in AWAs 

or temporary jobs if they have looked for other types of work. Although 

searching for another type of job may be an indicator that workers in alternative or temporary arrangements are dissatisfied with their jobs, questions 

on respondents’ job satisfaction and reasons for working in a particular 

arrangement, discussed above, are a more direct way of obtaining this 

information:

BLS should consider dropping questions on respondents’ job history 

(except possibly for asking about job tenure), on their transitions into 

their current employment arrangements, and on whether they have looked 

for employment in another type of job. (Recommendation 3.14)
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

SUMMARY 13

In general, panel datasets already exist that are much better at tracking job 

history and worker transitions, although samples tend to be small.

THE ROLE OF MULTIPLE DATA SOURCES IN MEASURING 

ALTERNATIVE WORK ARRANGEMENTS 

No single data source is capable of informing all research and policy 

questions regarding AWAs. Fortunately, surveys other than the CPS/CWS 

also add to the knowledge base. They have done so by (1) demonstrating 

how varying definitions affect measures of work arrangements and, closely 

related to that, how question wording and respondent interpretation affect 

estimates; (2) testing the sensitivity of measurement constructs used in surveys, including things like time-reference periods; and (3) covering different outcomes associated with various work arrangements, such as worker 

safety measures, not all of which are within the purview of a single survey.

Nonsurvey data, both public and private, are also valuable sources 

of information. Reflecting the potential of a multipronged data strategy, 

researchers have used surveys, data from the Internal Revenue Service and 

Social Security Administration, and data on individual-level bank transactions to measure participation in online platform work and to shed light 

on the range of jobs from which individuals and households earn income. 

While there are valid concerns about nonsurvey data—for example, 

regarding the representativeness of the people who are covered—such data 

also have some distinct advantages over survey data. Some commercial 

data sources feature administrative-level quality for measures of income, 

spending, and liquid assets. Also, such data are often continuous and highfrequency, based on transactions posted daily, which means that trends 

can be ascertained on a weekly or monthly basis rather than for a single 

reference period. This is critical in the case of online platform work, where 

individuals have been shown to participate sporadically. Both commercial 

and public administrative data offer perspectives unfiltered by low (and 

falling) survey response rates and respondents’ interpretations.

As numerous reports have documented—most recently and prominently the report of the Commission on Evidence-Based Policymaking 

(2017)—the use of administrative data can improve the overall efficiency 

of data programs by reducing agency expenditures, lowering respondent 

burden, encouraging the sharing of information across agencies, and potentially increasing the accuracy of the information collected. In some cases, 

administrative data may be used to replace survey data (NASEM, 2019).

Insights have been gleaned from research using data generated from 

tax records capturing payments by organizations to unincorporated individuals for nonemployee services. Tax data based on individual returns have 

generated evidence of significant numbers of workers combining W-2 and 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

14 MEASURING ALTERNATIVE WORK ARRANGEMENTS

1099/sole proprietor income. Among other findings based on such data, 

the expansion of independent contractor work in recent years appears to 

be driven primarily by online platform economy work—at least among 

tax-compliant workers. 

The capacity to improve the measurement of AWAs, as well as other 

economic statistics, will be influenced by how effectively multiple data 

sources can be drawn from and combined. The limitations of any single 

information source underscore the value of commercial and administrative 

data as complements to government surveys. Their contribution consists 

not only in providing additional estimates with which to triangulate the 

measurement of contingent and alternative work arrangements, but also in 

informing efforts to improve the design of government surveys.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

1.1. THE CHANGING NATURE OF WORK

Business structures, employment relationships, job characteristics, and 

worker outcomes have changed—in some ways, unpredictably—over the 

last few decades. The drive to be more flexible and to lower costs is often 

what motivates businesses to rethink their employment relationship strategies. In some cases, new technologies have enabled new arrangements. It 

was already apparent to researchers by the 1980s that changes were generating a need to develop new measures to track work and workers. 

In response, the U.S. Bureau of Labor Statistics (BLS) developed the 

Contingent Worker Supplement (CWS), first administered in 1995.1 At the 

time, one concern was that the growth in contingent and alternative work 

arrangements, driven by the flexibility and cost-savings goals of businesses, 

signaled less long-term commitment by companies to their workforce. It 

was feared that this in turn might lead to worse outcomes for workers 

(Polivka, 1996). Some evidence suggested that work was becoming more 

precarious—that there was something more unstable about the workplace 

than had been the case in the past (for example, see Osterman, 1999). 

However, how work arrangements are actually changing and what the 

implications of those changes are for workers are empirical questions that 

require high-quality data to answer.

1The economist and labor historian Audrey Freeman, whose original work helped motivate 

the CWS, first used the term “contingent” in 1985 as shorthand for the shift toward temporary or conditional employment with little or no attachment between the employee and the 

employer (Polivka and Nardone, 1989).

1

Introduction: Motivation for the Study

15
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

16 MEASURING ALTERNATIVE WORK ARRANGEMENTS

To begin addressing these questions, the CWS sought to measure key 

aspects of a worker’s employment relationship. Specifically, it sought to find 

out (1) whether the worker’s job was temporary (or contingent) in nature, 

and hence less secure; and (2) whether the worker’s main job—defined 

by BLS as the job associated with the most hours worked—belonged to a 

selected set of alternative work arrangements (AWAs) that differed from 

traditional employment arrangements in important ways that seemed likely 

to matter to workers. Information on five categories of AWAs was collected 

in all six waves of the CWS: (1) employees of temporary help agencies, 

which act as intermediaries by contracting out workers on their payrolls 

to client organizations on a temporary basis; (2) employees of contract 

companies that, like temporary help agencies, contract out employees or 

their services to clients; (3) independent contractors, independent consultants, and freelance workers, who provide services for customers and 

are self-employed; (4) on-call workers, who must be available to work 

when called on; and (5) day laborers, who are selected by employers from 

among workers who congregate at particular spots to work for a day. In 

2017, questions on work performed through mobile apps or online platforms, such as Mechanical Turk, Uber, and Lyft, were added to capture 

this new and rapidly growing type of work arrangement. The BLS does 

not label part-time work as an AWA, but instead measures part-time work 

through the questions asked on the monthly Current Population Survey 

(CPS) questionnaire. 

Although much has changed in the 25 years since the first CWS, the 

broad measurement objectives as originally outlined are still relevant. 

Nevertheless, as this report argues, modifications to the survey are needed 

to meet today’s policy and research needs. This report takes the position 

that improved and expanded measurements of the types of work arrangements covered in the CWS are needed, although research and experience 

with the CWS indicate that in some cases a household survey is not the ideal 

vehicle for collecting the information. 

The work arrangements of particular interest may be broadly categorized into two types: those in which employers do not hire their workers 

as employees and those where work schedules are highly variable and 

unpredictable. With respect to the former, an organization or customer may 

contract directly with workers, in which case the workers are considered selfemployed. Self-employed workers have at times been treated as a black box 

in economic statistics. This belies the reality that much diversity exists within 

the self-employment category. Self-employed workers, for instance, include 

owners of large and medium-sized businesses that have employees and substantial capital investment, independent contractors or freelancers working 

for an organization or through an online platform, and independent contractors or informal workers providing personal services directly to consumers. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

INTRODUCTION: MOTIVATION FOR THE STUDY 17

It also has become apparent that workers’ perceptions are far from 

uniform regarding their own work status. There are systematic differences 

between those who do and do not identify as self-employed even among 

those who are independent contractors.2 For example, people who work at 

large distribution centers and are paid a piece rate often are independent 

contractors but may not see themselves as self-employed. 

While organizations may engage workers as independent contractors 

instead of hiring employees to perform the same tasks, organizations also 

may contract out that work to companies whose employees perform it 

either at the client’s worksite or off-site.3 Temporary-help agencies are one 

type of contract company that acts as a labor intermediary. Temporary-help 

employment grew rapidly in the 1990s, accounting for about 10 percent 

of net employment growth in the economy during the decade, although 

the share of all wage and salary employment that is in the temporary-help 

employment sector has stabilized since 2000 at about 2 percent.4

Outsourcing, whether through independent contractors or contract 

companies, has always been a part of how U.S. corporations operate. 

Nonetheless, evidence suggests that among some leading corporations in the 

United States it has recently become more prevalent. Reports indicate, for 

instance, that temporary workers, contract employees, and vendors account 

for more than half of Google’s workforce, while Amazon relies heavily on 

independent contractors to take orders and to process and deliver goods 

and on contract companies to staff its warehouses.5 Moreover, the advent of 

online platforms and mobile apps such as Uber, Lyft, and Mechanical Turk 

represents a new, technology-enabled business model whereby the platform 

company, like a temporary agency, mediates the employment relationship 

by connecting workers to clients and handles their payment. Unlike the 

typical arrangement at a temporary help agency, at least under current law 

in most states, workers in these arrangements usually are not treated as W-2 

2Evidence from a Gallup survey is provided in Abraham, Hershbein, and Houseman (2019).

3In some cases, the contracted company may hire workers as independent contractors, which 

it then assigns to clients (Weil, 2019).

4Weil (2019) presents estimates of employment in industries where contract work is important and discusses its importance to labor market and worker well-being issues.

5The LA Times (“UC outsources thousands of jobs to private contractors. Is that a good 

idea?” December 1, 2019) reports that these categories of workers make up over 50 percent 

of Google’s global workforce, while also noting that outsourcing is a trend observed not just 

in the private sector but in the public sector as well. For example, The University of California 

system, the state’s third-largest employer, “spends some $523 million a year on outside 

contracts for an estimated 10,000 parking attendants, security guards, custodians, cafeteria 

workers, groundskeepers and patient-care technicians” (https://www.latimes.com/business/

story/2019-12-01/university-of-california-outsources-jobs).
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

18 MEASURING ALTERNATIVE WORK ARRANGEMENTS

employees of the platform company.6 Although jobs carried out through 

online platforms and mobile apps still represent a small share of total 

employment, their number has grown rapidly, and continued growth could 

greatly increase the number of people working as independent contractors. 

Both of the above categories of workers—independent contractors and 

people working for contract companies—may be subject to unpredictable 

work schedules at higher rates than the average across the labor market. 

Even in traditional employer-employee jobs, however, the nature of employment arrangements has changed in many industries and occupations. For 

example, the development of scheduling algorithms has transformed work 

in retail, restaurants, and other services industries. While using such technology may enable companies to better match workers with demand, it also 

means workers may be on-call or otherwise receive little advance notice of 

their schedules from week to week, and variable hours may translate into 

variable earnings. 

Claims about upheavals in the way people now work notwithstanding, 

research is mixed regarding the extent of change in employment relationships in the United States in recent years. Two measurement problems are 

particularly important: (1) trends in independent contractor relationships 

vary considerably as measured across different datasets; and (2) levels of 

self-employment are higher in tax data than in household survey data, 

which appears to be accounted for mainly by independent contracting 

(Abraham et al., 2020; Collins et al., 2019; Lim et al., 2019). Cases of 

workers holding multiple jobs complicate the measurement of workers in 

both instances. 

The CPS Annual Social and Economic (ASEC) Supplement should 

be measuring essentially the same construct of self-employment as tax 

records in the Social Security Administration’s Detailed Earnings Record. 

As Abraham and colleagues (forthcoming) found, however, “there is a 

great deal of disagreement” between the two.7 For the period 1996–2015, 

the researchers found that 66.7 percent of those whose tax data in the 

Detailed Earnings Record showed self-employment income reported no selfemployment income in the CPS and, conversely, 51.5 percent of respondents 

indicating self-employment income in the CPS reported no self-employment 

income in the Detailed Earnings Record. Overall for the period, estimates 

of average annual levels of self-employment are much higher when based 

6Telles (2016) posits the following list of features that characterize online platform, or 

“digital matching firms”: (1) they use information technology to facilitate peer-to-peer transactions, (2) they rely on user-based rating systems for quality control, and (3) they offer workers 

flexibility in deciding their typical working hours and rely on workers to use their own tools 

and assets to provide a service.

7These records are provided to the Census Bureau by the Social Security Administration.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

INTRODUCTION: MOTIVATION FOR THE STUDY 19

on the Detailed Earnings Record (16.4 million) than when they are based 

on the CPS (11.3 million). 

Surveys conducted by the Federal Reserve Board offer a different perspective on the labor market than the CWS because they use a more 

inclusive definition of AWAs, one that incorporates work other than that 

carried out on the main job. The Federal Reserve’s Survey of Household 

Economics and Decisionmaking8 and its Enterprising and Informal Work 

Activity Survey9 both reveal high shares of the workforce to be engaged 

in nontraditional work. The latter survey, for example, estimated that in 

2015, 36 percent of workers did at least some freelance work. One of the 

justifications for expanding the CWS to cover secondary jobs is the high 

rates of independent contractor work found in that and similar surveys. 

Findings based on administrative data or financial data have the potential to provide further complementary insights that may help in the design of 

household surveys. Tax data, for example, indicate that many people with 

wage and salary employment during the year also earn smaller amounts of 

money through self-employment (Collins et al., 2019). Personal financial 

accounts data indicate that participants in the online platform economy 

often are actively engaged in it for just a few months of the year but also 

that, between 2013 and 2018, transportation platforms have grown to 

dominate in both the number of participants and total transaction volume 

(Farrell, Greig, and Hamoudi, 2018). 

The main point here is that different data sources uncover unique and 

sometimes contrasting portrayals of work activity in the United States. The 

contrasting results are not necessarily contradictory, however, as they are 

sometimes simply measuring different aspects of the changing work environment. Moreover, they can inform modifications to the CWS to better 

capture important aspects of the evolving nature of work. 

1.2. INFORMING RESEARCH AND POLICY

Data collection should be driven by the research and policy questions 

that need to be answered, and because the questions change over time, data 

systems must be adapted to fill the information gaps that become exposed. 

Key policy measurement needs are identified and discussed in detail in 

Chapter 2, and solutions for improving measurement in the CWS are out8The survey, its sixth iteration conducted annually since 2013, was last fielded from October 11 

through November 12, 2018. Available: https://www.federalreserve.gov/publications/2019-

economic-well-being-of-us-households-in-2018-description-of-the-survey.htm.

9Available: https://www.federalreserve.gov/consumerscommunities/files/EIWA_Chartbook_

2016.pdf.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

20 MEASURING ALTERNATIVE WORK ARRANGEMENTS

lined in Chapter 3. Here, a few policy measurement needs are introduced 

in a preliminary way.

There is much interest among policy makers and researchers in addressing concerns about the future of work in the United States. These concerns 

are punctuated by the perceived fracturing of relationships between workers 

and employers, by the heightened importance of access to skills and education as the impacts of new technologies and automation are felt, and by the 

market-based pressure that companies face to produce short-term profits, 

sometimes at the expense of long-term value. Additionally, informal work, 

often done under the table, is not well captured in official statistics but is 

of interest for policy, since it may disproportionately be performed by the 

most vulnerable segments of the population—although data are needed to 

assess and quantify even this assertion. 

Although problematic job characteristics such as insecure work hours 

and lack of access to benefits can be found in jobs across the labor market, 

various outsourcing and scheduling practices are of special interest. That 

is because evidence suggests their prevalence is high and growing, giving 

rise to new issues requiring attention from researchers and policy makers. 

Basic questions in need of answers include these: How many workers are 

in these arrangements? What is the impact on earnings of working in these 

arrangements? How many people engage in these work arrangements to 

supplement income from other employment? How do the compensation 

and benefits practices in these arrangements spill over and affect those practices in more traditional work relationships? In what industries are these 

workers engaged, and what is the demographic makeup of this worker population? And finally, what factors motivate people to pursue nontraditional 

work, including among people using AWAs to supplement income, and how 

do these motivations vary across income levels and other demographics? 

Obtaining answers to the above questions requires more than measuring job categories. The real issues concern the nature and quality of modern 

jobs and how they are changing, whether people are on average worse off 

or better off in contract work arrangements than they are in traditional 

employer-based arrangements, and what characteristics of work most affect 

people’s lives in terms of economic security and, in turn, health, stress, and 

family life. It is these characteristics of work (e.g., access to social insurance, 

to employer-provided benefits, and to stable hours and earnings) and their 

links to outcomes that should drive measurement objectives, rather than 

the labels given to the arrangement. The goals of policy are to improve the 

economic security and well-being of workers, whether they are active in 

traditional or nontraditional jobs. 

The policy attention currently demanded to address changing labor 

practices coincides with a critical time for our economy. With unprecedented economic disruption not seen since the Great Depression, it is 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

INTRODUCTION: MOTIVATION FOR THE STUDY 21

crucial that the BLS work to better understand AWAs in the United States. 

The onset and now deepening impact of COVID-19 has exposed how 

vulnerable our society can be when workers are participating in the labor 

market without an adequate and well-coordinated social safety net. This 

report’s recommendations are intended to improve policy makers’ ability 

to address labor market vulnerabilities to prepare for future economic 

downturns. Several of the more urgent policy issues are especially relevant 

for two categories of AWAs highlighted above: independent contracting 

and contract company work. The key distinction regarding the former 

(including most of those who work for online platforms or mobile apps) is 

that such workers, because they are self-employed, do not typically receive 

the protections afforded by employment and labor laws, are excluded 

from many social insurance programs, and are not eligible for employee 

benefits. These characteristics of work as an independent contractor give 

rise to key policy questions: Should some or all of the protections afforded 

to employees under existing laws be extended to independent contractors? 

What are the implications for rethinking the social compact in anticipation 

of future work structures? And, as mandated by the recent AB-5 legislation passed in California, should certain independent contractors, perhaps 

including those who find work through platforms such as Uber and Lyft, 

be classified as employees?10

Policy prescriptions may depend on our understanding of why workers 

take jobs characterized as AWAs. Do they take them by choice, or due to 

lack of choice? How often is independent contracting work a main job 

and how often is it done on a short-term basis to supplement income from 

some other primary source? Data collection on independent contracting 

is complicated by the difficulties survey respondents often are observed to 

have in accurately reporting whether they are contractors or not, an issue 

addressed in detail in Chapter 3.11

Similar policy issues arise for contract company workers. Outsourcing 

of certain tasks has always been a business practice and, in some circumstances, workers as well as firms benefit from these arrangements. In other 

10The enactment in California of Assembly Bill 5 (AB 5) tightens the definition of employment based on an “ABC” test, a guide for employers to determine if a worker should be 

considered an independent contractor or an employee. Its intended effect is to reduce the 

misclassification of employees as independent contractors and could affect the categorization 

of many workers—including ride-hailing drivers, construction workers, food-delivery couriers, 

nail salon workers, and franchise owners—in an effort to reduce insecurity associated with this 

kind of work. Similar legislation is currently being considered in a number of states including 

New York and New Jersey.

11Lack of awareness of employment status can have important consequences for affected 

workers. With respect to unemployment insurance (UI) or workers’ compensation, for example, it may not be until people get laid off or injured on the job that they find out they are not 

employees and are not eligible for benefits. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

22 MEASURING ALTERNATIVE WORK ARRANGEMENTS

circumstances, the literature shows that outsourcing may result in lower 

wages, reduced benefits, and compromised workplace safety.12 The joint 

employment status of contract company workers—wherein control and 

supervision of an employee’s activities are shared among two or more 

businesses—raises some significant questions: What are the obligations 

of a client firm to the workers it employs through an intermediary? Do 

these arrangements reap efficiencies? And, are there adverse consequences 

for workers in terms of wages, benefits, and job safety, and if so in what 

circumstances?13

Policy makers and researchers require information about worker preferences, such as why they work in various arrangements and what the 

implications of these arrangements are for their employment stability, 

wages, benefits, and other aspects of job quality. For example, having 

better data would be helpful to policy makers working on portable benefits 

plans, that is, plans that would be accessible to all workers regardless of 

work arrangement. Several states have introduced bills to create such plans 

and also to make existing programs, such as state paid leave programs 

and state auto-enrollment retirement accounts, more accessible to a wider 

range of workers. During the Obama administration, the U.S. Department 

of Labor identified independent contracting status and the misclassification 

of workers as major areas of policy concern (in a sense as a prelude to the 

state-level efforts described above).14 Another layer of worker well-being is 

affected when workers are pushed to seek secondary or even tertiary jobs to 

supplement income. Workers often are independent contractors or in some 

nonemployee arrangement in such secondary work activities. 

In addition to raising the issues noted above, independent contractor 

and contract company work is sometimes (though not always) temporary 

and irregular in nature. “Contingency,” as measured by the CWS, is part 

of job insecurity; but other temporal aspects of work, such as flexible work 

scheduling and irregularity of hours, may also affect workers’ sense of security. High week-to-week variability in hours, or inadequate notice about 

the timing of hours available, occurs in many contract work arrangements, 

but also in standard W-2 type employment. As noted above, technology has 

enabled growth in the use of scheduling algorithms that attempt to closely 

12See Berlinski (2008), Dube and Kaplan (2010), and Litwin, Avgar, and Becker (2017).

13The U.S. Department of Labor has issued its interpretive rule (a form of regulatory 

guidance) under the Fair Labor Standards Act on determining joint employer status that 

provides a narrow definition of its application. Available: https://www.dol.gov/agencies/whd/

flsa/2020-joint-employment/fact-sheet.

14See Administrator’s Interpretation No. 2015-1 July 15, 2015, issued by the Department 

of Labor’s Wage and Hour Division, concerning the Application of the Fair Labor Standards 

Act’s “Suffer or Permit” Standard in the Identification of Employees Who Are Misclassified 

as Independent Contractors.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

INTRODUCTION: MOTIVATION FOR THE STUDY 23

match worker hours to firm needs, but the resultant flexible or unpredictable scheduling also shifts income risk onto workers. Variability in hours, 

particularly if it is unpredictable, may not be job ending (in the sense that is 

built into a “temp job”) but it may nonetheless lead to economic insecurity 

if a worker cannot count on enough hours to generate an income capable 

of meeting basic needs (Henley and Lambert, 2014). 

Debate over the need for new worker protections, such as minimum 

advance-scheduling requirements, has led to legislation being passed in 

some cities to help offset negative impacts.15 To inform such efforts, key 

job characteristics need to be monitored through regular data collection, 

including variability in timing and number of hours worked and any associated volatility in earnings. 

Along with policies that recognize and address the challenges created 

by emerging AWAs, policies are also needed that recognize and nurture the 

positives created by innovative new employment models. For some workers, 

schedule flexibility may increase productivity and wages. For participants in 

online platform work, attractive features may include the way the platform 

allows them to choose when they work, learn entrepreneurship skills, or 

transition back into work after extended absences. These flexible arrangements may be especially beneficial to people with otherwise limited labor 

market options, such as students, retirees, parents of small children, or 

those who can only find part-time work.

From the perspective of businesses, companies may use independent 

workers not just to reduce costs, but also to tap into talent and skills pools 

with the agility required to maintain competitiveness. The new economy 

requires policies designed to make new employment models work well 

not just for workers, but also for the employers who engage them and for 

the markets in which they operate. University of California officials have 

argued (see footnote 5) that, in addition to saving money as a means of 

curbing further tuition hikes, contractors give them the flexibility required 

to meet complex hiring needs. One policy goal is to protect the lower-paid, 

lower-skilled workers who are vulnerable to abuse as part of a “race to 

the bottom” while simultaneously enabling on-shore economic growth for 

the higher-paid, higher-skilled jobs in which workers tend to have greater 

choice. Despite contrary positions on different sides of these debates, it 

remains an open question whether the platform model—with the wider use 

of contracting and flexibility for workers that arises from it—is incompatible with providing workplace protections like minimum wage or overtime.

15The following site tracks states and localities that have adopted “predictive scheduling” 

requirements with the idea of helping workers better plan their schedules and budgets: https://

www.hrdive.com/news/a-running-list-of-states-and-localities-with-predictive-scheduling-mandates/

540835.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

24 MEASURING ALTERNATIVE WORK ARRANGEMENTS

For all the reasons stated above, policy makers are highly engaged in 

topics related to AWAs and, more broadly, in understanding how jobs are 

changing and what the future of work holds. A report issued by the Senate 

Committee on Appropriations on June 28, 2018, notes that “the Committee is pleased BLS is reporting on the contingent workforce during the 

current fiscal year. The Committee directs BLS to continue capturing data 

on contingent work and alternative work arrangements by conducting the 

Contingent Worker Supplement to the Current Population Survey on a 

biennial basis.”16

At the same time, Congress and other policy makers will move forward 

on legislation and advocacy in some capacity with or without proper databased evidence to replace the assumptions currently in vogue. This policy 

climate makes it all the more urgent to improve the data infrastructure for 

studying how employment relationships are changing and the implications 

for workers and firms. Reliable data are particularly important for policy 

makers as they attempt to develop a consensus on how to move forward in 

a way that is helpful to the population engaged in this kind of work. More 

is known now than several years ago, but there are still many unanswered 

questions and much confusion among policy makers and the general public 

about how work arrangements are changing. To improve the knowledge 

base, a range of sources will need to be tapped, including those from government, academia, and the private sector. 

The type of data needed to address these policy concerns does not rely 

on formal, established categories of employment, because often the categories themselves are shifting or the terminology describing them is changing. 

Instead, what is most relevant are the characteristics of the jobs held by 

American workers, such as their level of earnings, whether they are working 

on an employee or nonemployee basis, whether the job is temporary, whether 

their work schedules are regular and predictable, and whether the jobs provide health insurance, retirement benefits, or time off. These are the characteristics most relevant to understanding and ultimately trying to improve the 

outcomes and well-being of workers engaged in AWAs. For example, having 

a count of the number of jobs categorized as “on-call” according to some 

specific definition is less important than knowing how many jobs have an 

unpredictable work schedule. Similarly, having a count of the number who 

consider themselves independent contractors is less useful than knowing how 

many are hired by an organization or client on a nonemployee basis, regardless of the term used to describe the arrangement. 

16Available: http://src.bna.com/z3y.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

INTRODUCTION: MOTIVATION FOR THE STUDY 25

1.3. THE MEASUREMENT ROLE OF THE 

CONTINGENT WORKER SUPPLEMENT

The CWS is designed, in part, to measure the temporary nature (contingency) of jobs.17 BLS defines contingent workers as those “who do not 

have an implicit or explicit contract for ongoing employment.”18 To date, 

the CWS has been conducted in 1995, 1997, 1999, 2001, 2005, and 2017. 

As described above, the creation of the CWS was motivated by concerns 

during the 1980s about the changing nature of employment and the implications for work policies. Today’s concerns about the changing nature of 

employment are therefore not new. The characteristics of alternative work 

have evolved since the 1980s, however, and some of the issues of concern 

also have changed since the CWS was conceived. Although the panel recognizes the value of maintaining consistency across surveys and believes that 

the broad measurement objectives of the original CWS are still appropriate, the survey requires updating to continue to be relevant for policy and 

research purposes. For example, as alluded to above, the modern labor 

market dictates that more attention be given to measuring the irregularity 

and unpredictability in workers’ hours. 

Of course, no single survey or survey supplement can measure all 

aspects of the changing nature of work. As noted above, a central focus 

of the CWS has been on measuring jobs that are temporary, or contingent, along with measuring work arrangements whose characteristics differ 

from those of standard employee jobs in ways that likely would matter to 

workers. The latter cluster includes the work of independent contractors, 

contract company workers, on-call workers, day laborers, temporary help 

agency workers, and, in the 2017 survey, electronically mediated work (that 

is, work obtained through online platforms or mobile apps that mediates 

the payment from the customer to the worker). For the most part, the categories of work arrangements are defined as mutually exclusive, although 

there is a small overlap between on-call and contract company work in 

all CWS waves, and in 2017 information on electronically mediated work 

was collected for all jobs and could be associated with any arrangement on 

workers’ main jobs.

When the BLS received funding to field a new round of the CWS 

in 2017, a primary objective was to assess how the number of workers in 

17The CPS, of which the CWS is a part, is a monthly survey of about 60,000 households that 

provides data on employment and unemployment in the United States. Special supplements to 

the CPS have been used as an efficient way to collect additional targeted data. The statistics 

produced from the supplements, and from the CPS in general, are often considered to be the 

gold standard. Currently, supplemental questions are asked on a wide range of topics, including veterans’ employment, displaced workers, and students’ employment.

18Available: https://www.bls.gov/cps/wlf-tables24.pdf.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

26 MEASURING ALTERNATIVE WORK ARRANGEMENTS

alternative employment arrangements had changed since 2005, the previous time the supplement was fielded. Another objective was to “measure 

an emerging type of work—electronically mediated work, defined as short 

jobs or tasks that workers find through websites or mobile apps that both 

connect them with customers and arrange payment for the tasks” (BLS, 

2018). Four questions, listed in Box 1-1, were added to the 2017 CWS for 

this latter purpose.19

As currently constructed, the CWS is well positioned to help researchers answer questions about the number of workers in temporary jobs and 

the AWAs covered by the survey, various characteristics of those jobs, 

workers’ job tenure, and workers’ reasons for being in a particular work 

arrangement. In considering how the CWS could be reshaped to better 

measure additional aspects of AWAs, in the chapters that follow the panel 

addresses a number of questions, which are previewed next. 

Within the broad measurement objectives of the CWS, are the work 

arrangements or characteristics of work covered in the survey the most rel19Full documentation of the CWS survey, including the development and results for the four 

questions about independent work done through online platforms, is provided in Current 

Population Survey Staff (2018). 

BOX 1-1

2017 CWS Questions about Electronically Mediated Work

Q1: Some people find short, IN-PERSON tasks or jobs through companies that 

connect them directly with customers using a website or mobile app. These 

companies also coordinate payment for the service through the app or 

website. For example, using your own car to drive people from one place 

to another, delivering something, or doing someone’s household tasks or 

errands. Does this describe ANY work (you/NAME) did LAST WEEK? (If a 

respondent answers “yes” to Q1, they are asked a follow-up question)

Q1a: Was that for (your/NAME’s) (job/(main job, (your/NAME’s) second job)) or 

(other) additional work for pay?

Q2: Some people select short, ONLINE tasks or projects through companies 

that maintain lists that are accessed through an app or a website. These 

tasks are done entirely online, and the companies coordinate payment for 

the work. For example, data entry, translating text, web or software development, or graphic design. Does this describe ANY work (you/NAME) did LAST 

WEEK? (If a respondent answers “yes” to Q2, they are asked the follow-up 

question)

Q2a: Was that for (your/NAME’s) (job/(main job, (your/NAME’s) second job)) or 

(other) additional work for pay?
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

INTRODUCTION: MOTIVATION FOR THE STUDY 27

evant ones, or should some new questions be added and others be dropped 

to make space? 

In other words, what is it that policy makers and researchers most 

need to know about work arrangements and work characteristics to better 

understand the modern labor market? 

Information about work categories and job characteristics is needed 

from the statistical system, although it is possible that some can be better 

captured through administrative data or surveys other than the CWS. 

As argued above, the changing nature of employment arrangements has 

created a measurement need to collect more comprehensive information 

about specific job characteristics faced by workers than is currently done 

in the CWS. A clear example is unpredictable work schedules. Evidence 

from other surveys and research (presented in Chapter 3) indicates a high 

prevalence of schedule unpredictability, giving rise to a highly salient policy 

issue. Collecting this information in a large nationally representative survey 

would help to inform regulatory policy decisions. 

Many issues of interest to policy makers and researchers hinge on the 

distinction between employees (W-2 workers) and the self-employed, which 

includes independent contractors. Thus, it is important to accurately classify workers as employees or self-employed/independent contractors or 

other nonemployees. For many questions, however, it is necessary to capture the characteristics of jobs rather than capturing only a type of work 

arrangement (e.g., working on-call rather than identifying someone as an 

“on-call worker”).

The current CWS collects information only on the main job. Should this be 

expanded to include secondary work activities?

This question relates to the appropriate scope of work to be covered 

in the CWS. Throughout this report, the panel considers the merits (and 

pitfalls) of collecting information on more than one job or work activity. 

Several studies suggest that independent contractor or informal work 

arrangements, including work for online platforms, are often secondary 

work activities that are important to household income (Abraham and 

Houseman, 2019; Farrell, Greig, and Hamoudi, 2018; Robles and McGee, 

2016). More fully understanding the various sources of income for households is important for research and has potentially important implications 

for whether and how policy makers should respond to changing work 

arrangements.

The current CWS collects information on work that has occurred only during a very recent time period. Should this reference period be expanded?

This question also relates to the appropriate scope of work to be 

covered in the CWS, which asks respondents who identified as employed 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

28 MEASURING ALTERNATIVE WORK ARRANGEMENTS

“last week”: “Did you do ANY work for pay (either pay or profit)?” This 

report’s recommendations address the benefits of asking about work for a 

different reference period—for example, to capture work done by participants only sporadically—as well as the potential negatives, which include 

considerations about the ability of respondents to report accurately about 

activities that took place further in the past. 

Is the CWS, a household survey, the best vehicle for collecting the various 

pieces of information needed to inform policies related to work arrangements? And if not, what are alternative data sources?

Because space for questions in the CWS is limited, it is always worth 

assessing whether resources could be shifted to maximize its value for the 

purpose of measuring AWAs. In some cases, topics could be deemphasized 

not because they are unimportant but because other data sources have 

a comparative advantage over household surveys in their collection. An 

example, alluded to above, is the case of temporary agency and contract 

company workers. Workers often may not be fully informed about the 

complicated nature of the business relationships underlying their “employment.” For example, an individual being paid by a staffing firm and assigned 

to a distribution center of a major retailer may report being employed by 

the retailer. The difficulty household survey respondents have in accurately 

reporting such intermediated work arrangements is well documented, and 

information about these arrangements may be better collected through 

other means.

For data that should continue to be collected in the CWS, does the current 

survey instrument fully and accurately capture the desired information or 

are there ways the data could be improved?

In Chapter 3 of this report, the panel identifies situations for which 

cognitive testing and altered question wording could improve the accuracy 

of information collected in the CWS, including for questions about temporary, independent contractor, and online platform or mobile app work.

Recognizing resource limitations, how should the information collected in 

the CWS be prioritized?

Although BLS has decided to reshape the CWS to accommodate the 

measurement needs created by new labor market dynamics, the agency 

also recognizes that there is value to fielding a supplement over time that 

maintains a fixed set of core questions, so that valid time-series comparisons can be made. Almost immediately after BLS released estimates from 

the May 2017 CWS, it received feedback from users (academics, business 

leaders, politicians, and other government researchers) who agreed that the 

capacity to compare estimates from the May 2017 and earlier iterations of 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

INTRODUCTION: MOTIVATION FOR THE STUDY 29

the CWS was helpful. Users also expressed the view, however, that there 

were important questions that were still not possible to answer and that 

needed to be addressed. 

Much of the current survey instrument is devoted to measuring the 

temporariness of the respondent’s job in order to produce statistics on contingency. While contingency is an important job characteristic, the panel 

recommends (in Chapter 3) simplifying this set of questions to make room 

for asking about other aspects of the employment relationship. To allow 

room for higher-priority questions, the panel also recommends that BLS 

consider dropping questions that have been little used by researchers or the 

policy community or that might be better measured using other sources. 

The Value of Multiple Data Sources

Going forward, the data strategy for measuring AWAs will not be compartmentalized in one survey or even necessarily one statistical agency. The 

Foundations for Evidence-Based Policymaking Act of 2018 urges statistical 

agencies to seek opportunities to innovatively combine data sources with 

the goal of improving measurement.20 In this spirit, while the first part 

of the measurement strategy is to improve the BLS surveys, a second part, 

described in Chapter 4, involves exploiting and improving coordination 

among complementary data sources. 

Reflecting the potential of a multiple-source data approach, economic 

researchers have used surveys, tax reports to the Internal Revenue Service, 

data from the Social Security Administration, and transactions information 

from commercial banking accounts to measure different aspects of AWAs 

and, in particular, web platform work activity and income. Although new 

measurement challenges have arisen, especially with the use of “organically” generated commercial data—for example, issues regarding their representativeness and their transparency21—there are also distinct advantages. 

Commercial data, for example, offer detailed, high-frequency information based on transactions posted daily. This data characteristic can allow 

20The law requires, among other things, that statistical agencies become more transparent 

with their data and share their datasets internally and with other government agencies for 

research purposes to the maximum extent possible under the law. Available: https://www.

congress.gov/bill/115th-congress/house-bill/4174/text.

21Unlike survey data, whose properties are well understood as the result of decades of 

methodological research, use of administrative and commercial data is relatively recent. But 

approaches are being developed to assess the quality of new types of data. Japec et al. (2015), 

for example, outlines a “Total Data Error” framework which includes traditional methods 

(which parse potential sources of bias and error into sampling and nonsampling errors) but 

expands the sources of nonsampling error to include measures of error capturing how commercial or organic data are generated, extracted, transformed, loaded, and ultimately analyzed.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

30 MEASURING ALTERNATIVE WORK ARRANGEMENTS

researchers to identify even work that is performed sporadically. Elsewhere, 

insights gleaned from research using tax data have been generated from 

records capturing payments by firms to unincorporated individuals for nonemployee services (e.g., Collins et al. [2019]). For example, tax data indicate that most 1099 online platform work supplements primary W-2 jobs. 

1.4. CHARGE TO THE PANEL

During the first meeting of the panel, held March 29, 2019, BLS leadership outlined their goals for the study and their motivation for commissioning it. Presentations by BLS experts described the history, measurement 

objectives, and past performance of the CWS. Strengths and weaknesses of 

household surveys, and the CPS in particular, for the purpose of measuring contingent and alternative work arrangements were identified. Time 

was also allocated for a discussion among panel members and sponsor 

representatives to sharpen the project statement of task. Box 1-2 lays out 

the scope of the study, which was refined collaboratively during the first 

meeting of the panel. 

In addressing that charge, this panel report is organized into three chapters (beyond this introductory chapter). Chapter 2 assesses the measurement 

needs for monitoring the changing employment landscape and broader 

economy and for informing policy designed to mitigate negative effects 

while preserving the benefits from these changes. The chapter stresses the 

need to measure all work-based sources of income, not necessarily just 

income from “primary” jobs. The chapter also emphasizes the importance 

of monitoring key job characteristics, which often reveal more about effects 

on worker outcomes and well-being than does a sorting of categories of 

alternative work. 

Chapter 3 addresses the role of the CWS within the spectrum of measurement needs. There are many potential sources of information about 

changing work arrangements. Some sources, like the CPS/CWS, are government household surveys, but other kinds of surveys, as well as administrative and commercial data, can play complementary roles. Within this 

context, the comparative strengths and weaknesses of the CWS are assessed 

so that an optimal role for the survey can be considered. Here, recommendations about the conceptual and content scope of the CWS are presented, 

as well as guidance regarding CWS questionnaire design.

Chapter 4 describes in detail the role of complementary (non-CWS) 

survey and nonsurvey data sources in measuring AWAs and the characteristics of workers in these arrangements. Findings emerging from these other 

sources—which include non-BLS household surveys, firm/establishment 

surveys, government administrative data sources, and commercial data 

sources—are reviewed, and lessons for the CWS are drawn. The promise 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

INTRODUCTION: MOTIVATION FOR THE STUDY 31

BOX 1-2

Statement of Task

The Committee on National Statistics of the National Academies of Sciences, 

Engineering, and Medicine will appoint an expert panel to review the Contingent 

Worker Supplement (CWS) of the Current Population Survey (CPS) for the Bureau of Labor Statistics (BLS) in the U.S. Department of Labor. The CWS provides 

key measures of temporary (contingent) work, alternative work arrangements, 

and the “gig” economy. Disagreements, however, exist among researchers, policy 

makers, and other stakeholders about the definitions and measures of these concepts and priorities for future data collection. 

The expert panel’s work and consensus recommendations will be guided by the 

current research and policy questions that need to be answered. Many of these 

questions arise from concerns about the economic and health impacts of modern 

work arrangements on the population, which are rapidly evolving in response to 

emerging technologies, the changing sectoral composition of the economy, and the 

shifting boundaries of where, how, and by whom work is performed. 

The expert panel will carefully review measures of employment, earnings, and 

worker well-being in temporary and alternative work arrangements that can be 

estimated using household survey data, such as those generated by the CWS, 

as well as measures that can be produced using administrative, commercial, and 

combined data sources. The comparative advantages and complementarities of 

different data sources will be assessed. In addition, the expert panel will review 

methodological issues underpinning BLS’s measurement objectives. As part of 

its information-gathering activities, the panel will conduct a workshop to hear the 

perspectives of data users, stakeholders, and both survey and nonsurvey data 

experts.

The panel will produce a consensus report, which will include rapporteurauthored proceedings of the workshop along with conclusions and recommendations for BLS to guide continued improvement of the CWS.

of combining multiple data sources to leverage the strengths of each source 

is also explored. 

An appendix to the volume provides a summary of an open meeting 

of the panel, which included presentations highlighting the perspectives of 

data users and policy makers concerned with the issues created by changing 

work arrangements in the modern economy.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

Driven both by business needs and by the desire of workers for a 

broader set of work options, work arrangements have changed dramatically 

in recent decades. External factors having to do with the macroeconomy, 

such as fallout from the Great Recession, and changing technology have 

also played roles in shaping the emerging models of employment. Internet 

platform-mediated work, at this point only a small component of the overall labor market, is but one example of the flux now being experienced. 

Better data are needed to fully understand these ongoing labor market transitions and to inform new policies being called for to enhance the positive 

aspects of these changes and mitigate the negative impacts. Specifically, data 

are needed to support analyses connecting changes in business structure and 

employment relationships with job and worker outcomes. 

In this chapter, we discuss the changing nature of jobs—whether it is 

the contingency emphasized in the early Contingent Worker Supplement 

(CWS) to the Current Population Survey (CPS) or the broader job security 

and employee protection issues that have emerged since—along with the 

measurement implications. We identify the kinds of information about 

modern work arrangements needed for policy and research purposes and 

consider the priorities for collecting this information. We discuss the scope 

of work and income sources that are important to measure (section 2.1); 

how different categories of work factor into policy strategies (section 2.2); 

and, most importantly, how job characteristics affect worker outcomes 

and well-being, as well as employer hiring practices (sections 2.3 and 2.4). 

The strengths and shortcomings of existing data sources in meeting these 

information needs are also noted. Those sources include but are certainly 

2

Measurement Needs for Understanding 

the Changing Nature of Work

33
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

34 MEASURING ALTERNATIVE WORK ARRANGEMENTS

not limited to the CWS. We leave it to subsequent chapters, however, to 

build on the conceptual discussion here and advance recommendations for 

improving measurement capacity—both through a revised CWS (Chapter 3), and by building on other, potentially complementary data sources 

(Chapter 4).

Periodic, cross-sectional household datasets such as the CWS can 

shed light on some important policy questions related to alternative work 

arrangements (AWAs):

— Among people engaged in AWAs, what is the relationship between 

worker age, education, and other characteristics (gender, race/

ethnicity, immigration status) and job opportunities? 

— Why do workers participate in AWAs? To what extent does participation reflect worker preferences for flexibility or other AWA 

attributes, and to what extent would those in AWAs prefer a standard employment arrangement? 

— Is engagement in AWAs more likely among multiple job holders or 

as a secondary work activity? And what is the impact of multiple 

job holding on worker well-being and on work/life balance?

For other research and policy questions, panel datasets or (as discussed 

in Chapter 4) high-frequency nonsurvey data, such as commercial and 

administrative data, can be instrumental in helping to understand emerging 

labor force dynamics. Examples of such questions include these:1

— Does participation in AWAs increase (due to personal financial 

needs) or decrease (due to reduced demand for services) during 

economic downturns?

— How do AWAs help workers smooth their income and consumption over time?

— What are the career paths that lead into and out of AWAs?

Recognizing the value of longitudinal data collection, Chapter 4 discusses the value of adding job questions to surveys such as the Census 

Bureau’s Survey of Income and Program Participation (SIPP) and the 

National Longitudinal Surveys.

1Although the CWS is a supplement to the CPS, which has a limited longitudinal structure, 

researchers have used the CWS to examine some of the employment dynamics associated with 

AWAs. For discussion on using the limited longitudinal structure of the CPS together with the 

CWS to study the stability of AWAs, see Addison and Surfield (2009) and Houseman and 

Polivka (2000). For discussion of worker paths into AWAs, see Addison and Surfield (2006) 

and Farber (2017).
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

UNDERSTANDING THE CHANGING NATURE OF WORK 35

Other kinds of questions may be best addressed by analyses using 

business-sourced data:

— What kind of firms use AWAs and why?

— How have the activities and occupations where AWAs are used 

changed over time?

— What determines the diffusion of AWA usage in an industry and 

occupation? 

— How does growth in the use of AWAs relate to the increasing 

separation of firms between high-productivity / high-wage and low 

productivity / low-wage firms?

— Are AWAs a first-order result of employment restructuring or a 

second-order effect of business restructuring? 

— How do businesses view their relationship with AWA workers? 

Do they think of themselves as traditional employers? Indirect 

employers? Supply contractors?

— To what extent is the use of AWAs a reflection of more efficient 

ways to organize production, given new technology, versus a 

method to thwart workplace protections and social insurance 

protections?

Finally, the changing business structures affecting employment arrangements come into play, at least indirectly, for an even broader set of social and 

economic questions affecting the well-being of individuals and households:

— What role, if any, is the trend toward AWAs playing in polarizing 

high-skill and low-skill jobs (and the disappearance of “solid” 

middle class jobs) and in the growth of earnings inequality? 

— What is the relationship between AWAs and the trend toward 

declining labor mobility and opportunities for career progression?2

— Is the changing structure of work related to declining labor force participation among certain demographic groups (e.g., white males)?3

— Do AWAs draw people into the workforce who would otherwise 

be nonparticipants?

— Are certain types of AWAs replacing other types?

2Davis and Haltiwanger (2014) provide empirical evidence for a decline in labor market 

mobility.

3If the earnings, benefits, and conditions of work associated with an occupation or industry decline as a result of AWA utilization, the pool of workers in those jobs could decrease, 

affecting labor force participation for particular segments that were once attracted into the 

workforce by those types of jobs.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

36 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Addressing these questions will require many kinds of data and involve 

many research threads. Nevertheless, if we are to gain a better understanding of the future of work, development of the right kinds of data instruments is crucial.

2.1. EMPLOYMENT: MEASURING ALL 

“SIGNIFICANT” SOURCES OF WORK INCOME

Which Work Activities Are in Scope?

In its role measuring the nation’s labor market activities most pertinent 

to research and policy, BLS cannot attempt to capture all sources of income. 

The agency’s focus rightly is on income generated from market work. Work 

activity associated with individuals’ primary jobs therefore is clearly within 

scope, while work conducted for family or friends (e.g., household production) or for a neighbor in a barter-type agreement is just as clearly out of 

scope.4 But much work that routinely takes place—ranging from selling 

used items on eBay or at a flea market to earning income from working a 

second or third job, perhaps sporadically—falls between these extremes. 

Currently in the CWS, deciding what to include as “work for pay” is largely 

up to respondents’ interpretations. 

AWAs are of course not new. Examples of inside contracting systems as 

well as networks of outside contractors could be found in 19th century U.S. 

factories. The growth of standard employment relations in the post–World 

War II period reflected efforts by employers to create strong internal labor 

markets wherein employers could invest in workforce training and expect 

to retain those human capital investments. This made sense for employers 

during the three decades after World War II, as the economy grew and the 

strong position of companies in domestic markets allowed them to negotiate with unions in a way that increased wages and decreased wage inequality. Subsequently, the relationship between workers and firms weakened. 

Beginning in the mid-1970s, macro trends such as globalization and international competition, technological change, and the decline of unions led 

employers in the United States to seek the flexibility to more readily adjust 

the size of their workforces (National Academies of Sciences, Engineering, 

and Medicine, 2017).

4Several surveys—such as the Federal Reserve Board’s Survey of Household Economics and 

Decisionmaking, described in Chapter 4—are oriented to pick up informal work. Specialized 

surveys—for example, a national-level household survey of informal work conducted by 

Jensen, Tickamyer, and Slack (2019)—have even included questions about informal work 

that is done on a barter or other nonmarket/nonmonetary basis. Some of these surveys indicate relatively small amounts of income being generated, but very high participation rates, in 

informal work. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

UNDERSTANDING THE CHANGING NATURE OF WORK 37

Temporary agency employment grew rapidly during the 1970s and 

continued growing all the way through the 1990s, although it still represented a relatively small portion of the overall labor force. As described 

in Chapter 1, by the time the BLS sponsored the first Contingent Work 

Survey in 1995, trends in the temporary help services industry, and in 

outsourcing generally, were readily apparent. However, the share of the 

workforce engaged in temporary help agency work, as measured in 

the CWS, has been fairly stable over the survey’s history, including the 

most recent 2017 wave. 

Since 1995, other forms of work have evolved and grown in relative 

importance, garnering the attention of policy makers and researchers. More 

prominent in today’s economy than temporary help agency work—and 

more salient from the point of view of policy—is independent contracting, 

which includes platform work. Under this arrangement, individuals are 

self-employed rather than being employees of the organizations or individuals for which they perform work. Of the AWAs measured in the CWS, 

independent contracting is the largest group, although the percentage of 

all employment accounted for by this category as measured in the CWS 

changed little between 1995 and 2017.

As described in detail in Chapter 3, however, the CWS estimates likely 

underestimate the proportion of persons who work as independent contractors. In large part this is because the survey asks only about a person’s 

main job, and many people work as independent contractors on a second or 

third job. Research evidence also suggests that many people working solely 

in these nonemployee arrangements are not captured in household surveys 

like the CWS. The independent contractor group is critical for policy, as 

these individuals typically cannot rely on employing organizations for benefits and security, and they are not covered by employment and labor laws 

that provide basic protections to workers (such as minimum wages) and 

access to social insurance programs (such as unemployment insurance 

and workers’ compensation). 

One question of appropriate measurement scope that comes into play 

conspicuously in observing independent contracting concerns the distinction 

between “work-based” income and income derived from a combination of 

work and capital-generated activity. As quickly becomes clear in thinking 

about some of the newer platform companies, the line between these two 

activities can sometimes be blurry. For example, renting out rooms through 

AirBnB often is thought of as deriving income from a capital asset, but it 

also has a work- (time-) based component; in fact, a person operating several AirBnB properties may be occupied full-time in the enterprise. On the 

other hand, even ride-share workers, ordinarily considered to be engaged 

in labor-platform work, must have capital in the form of a car that passes 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

38 MEASURING ALTERNATIVE WORK ARRANGEMENTS

the company’s equipment standards.5 It is an open question how far apart 

on the labor/capital spectrum the work is through platforms such as, say, 

AirBnB and Uber. 

There is a conceptual arbitrariness about drawing the line of inclusion 

for measurement in labor statistics somewhere between the two kinds of 

jobs, labor- versus capital-based. Furthermore, this distinction is a problem 

that is pervasive for all types of self-employment, not just AWAs. Income 

from traditional self-employment also may combine returns to labor and 

capital. Further complicating measurement is the fact that, for most purposes, the relevant concept is net income (essentially what a person would 

report on a Schedule SE), but it may be difficult for households to separate out the costs associated with the work they did “last week” (a point 

reiterated later in this chapter). As discussed below, in the CWS, hours may 

be the best measure of the intensity of the activity.6 We address this issue of 

demarcating returns to capital and labor in later chapters, where we also 

discuss nonsurvey data approaches to measuring the extent of independent 

contracting and other self-employment work and its contribution to the 

economy. 

In recent decades, business restructuring has affected the prevalence of 

AWAs across the economy, and in a way that extends far beyond the comparatively recent emergence of the internet platform-based work alluded 

to above. Profound organizational changes have found major businesses 

focusing on integrating available resources into their value creation process to best provide value to customers and investors; this often involves 

concomitantly contracting with other entities to carry out those efforts 

(Appelbaum and Batt, 2014). The organizations undertaking these activities for lead businesses are guided by exacting standards and high-powered 

incentives to ensure that core competencies are met. These take the form 

of detailed subcontracting and supply-chain requirements; franchise agreements; and, most recently, the highly calibrated incentive systems created 

by platform algorithms. Such restructuring includes but is not limited to 

the AWAs captured in the CWS.7

5There is a growing list of jobs requiring a car that are clearly income-generating—Amazon 

Flex, Uber Works, Doordash, etc.—that are relevant to many of the preamble questions to this 

chapter. These platforms reflect activities previously done as work by workers (as opposed to 

the AirBnB example, which is less clear). 

6An option used in some data collections, such as the Survey of Informal Work Participation 

sponsored by the Federal Reserve Bank of Boston, is to take a “time for income” approach as 

opposed to the current work for income approach. Regarding platform work, an approach 

whereby respondents are asked whether they spent time providing services or selling goods 

for pay could be considered. 

7Weil (2019) argues that the wider definition of “fissuring” implies that the part of the workforce affected by these changes is much larger than is implied by household measures of AWA. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

UNDERSTANDING THE CHANGING NATURE OF WORK 39

Multiple-Job Holders

Changes in the structure of employer-worker relationships in recent 

decades have given rise to a different set of individual and household 

choices. These changes require rethinking the meaningfulness of terms like 

“primary job” and “supplemental work” and of the factors contributing to 

decisions by people to take different kinds of jobs. Data sources such as the 

CWS are needed to better inform questions about how changes in primary 

job characteristics are affecting worker outcomes. Similarly, information is 

needed about the prevalence of additional work beyond the primary job—

much of which is likely to be in AWAs—and the reasons, including financial 

reasons, for taking on additional work. In many cases, secondary jobs are 

critical sources of income for households, and thus information on all jobs 

is necessary to understand how people combine different work activities to 

earn a living. For these reasons, it is necessary for policy purposes to collect 

information about additional work beyond the respondents’ primary job. 

Because secondary work activities are often engaged in sporadically, the 

CPS reference period “in the past week” would not capture them comprehensively. This issue of the length of the reference period used in the survey 

and its potential impact on various estimates of AWA activity is discussed 

in Chapter 3. 

It is not practical for a single survey (or nonsurvey data source for that 

matter) to generate a profile of the full characteristics of all work activities in which people engage. Information about hours and earnings on all 

jobs is essential. Additionally, it would be valuable and within scope for 

the BLS to include questions on why respondents have a second job. Policy 

discussions regarding implications for the well-being of people who engage 

in AWAs often make assumptions about workers’ underlying motivations 

and whether the AWA is their primary or a secondary job. For example, 

some independent contractors may prefer greater job flexibility and a desire 

to pursue entrepreneurial opportunities. This characterization may be most 

accurate when describing workers who seek out AWAs as their main source 

of income. In other cases, AWAs may reflect hard choices made by individuals and households to make ends meet, particularly when they are 

engaged in the work to supplement income earned in a traditional job. 

Nevertheless, even when they are second jobs, AWAs may be an attractive means of fulfilling a desire for supplemental income or satisfying 

targeted savings goals. Probing the assumptions about preferences should 

be combined with mapping preferences against other worker characteristics, such as educational background, age, and experience, as well as job 

characteristics, such as occupation, skill requirements, and industry. A 

deeper understanding of the patterns of preference among workers taking 

on multiple jobs is critical to framing future policy choices. Achieving such 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

40 MEASURING ALTERNATIVE WORK ARRANGEMENTS

an understanding will require both accurate data and sound approaches 

to measuring the full range of market work in which people are engaged.

2.2. JOB TYPES: CATEGORIES OF ALTERNATIVE 

WORK ARRANGEMENTS

The CWS provides key measures of temporary (contingent) work and 

of the AWAs often associated with temporary work, with outsourcing in 

its different forms, and with unpredictable schedules. Disagreements exist, 

however, among researchers, policy makers, and other stakeholders about 

the definitions and measures of these concepts and priorities for future data 

collection.8 As previously discussed, the CWS collects information on the 

following five major types of AWAs:9

— Temporary agency work. In this case, the worker is an employee of 

the temporary help agency and is assigned to work for clients, typically at the client’s worksite. As discussed in Chapter 3, employer 

survey data indicate that the share of the workforce in temporary 

agency employment is understated in the CWS. In May 2017, 

according to the CWS, about 1.4 million workers (0.9% of total 

employment) were paid by a temporary help agency.10

— On-call work. On-call work is a type of on-demand work in which 

the worker is called to work at the job only when needed. In oncall work, like other types of on-demand work, the number or 

the timing of hours worked varies and, importantly, the hours are 

controlled by the employer, not the employee. These characteristics 

are not necessarily unique to on-call work. In May 2017, according 

to the CWS, there were 2.6 million on-call workers (accounting for 

1.7% of total employment).

— Independent contracting. Independent contracting is a type of selfemployment. The term typically refers to the work of those who 

are self-employed and do not own or run a business or do not have 

a sizable capital investment in a business. Independent contractor 

arrangements are often complex, involving tiers of subcontracting 

that may lead to misreporting and undercounting on tax forms. 

Independent contractors also include most types of work on platforms and other informal, nonemployee work arrangements. As 

8For a detailed discussion of these definitional issues, see Allard and Polivka (2018). 

9The CWS also collects information on day laborers but, given their small number as captured in the survey, the BLS does not report this category in its data summaries. 

10This figure, and the parallel estimates for other AWA categories, are available: https://

www.bls.gov/news.release/pdf/conemp.pdf.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

UNDERSTANDING THE CHANGING NATURE OF WORK 41

is discussed in Chapter 3, research evidence also suggests that 

independent contractors are underreported in household surveys. 

In May 2017, according to the CWS, there were 10.6 million independent contractors (6.9% of total employment).

— On-demand, platform-intermediated work. Platform-intermediated 

work, sometimes referred to as “gig” work, may cover personal 

service activities, such as child care, house cleaning, or ride sharing, 

as well as goods-related activities, such as selling goods online or 

renting out property—though each of these activities is often not 

mediated by a platform. As noted above, many people who engage 

in platform work use it to supplement their income, but some rely 

on it as their main source of income. Some platform-intermediated 

activities are done occasionally and do not take much time, and 

thus may not fit neatly into a standard concept of what is considered to be “work” (see Abraham and Amaya, 2019; Farrell, 

Greig, and Hamoudi, 2018). In some cases, internet intermediary 

companies have formalized the arrangements for certain types of 

work previously done on an informal basis. For example, a neighborhood dog walker who previously had operated by word of 

mouth might now use Rover.com, or a person who had previously 

rented out a spare room through classified advertising might now 

use AirBnB. For May 2017, BLS estimated that about 1.0 percent 

of total employment was accounted for by electronically mediated 

workers.

— Contract company work. This category refers to workers, besides 

temporary agency workers, who are employees of a company but 

whose services are contracted out to clients. As discussed in Chapter 3, it can be difficult to measure this category of work because 

it is unclear how accurately contract company workers are able 

to report their status as such. The narrow BLS definition may 

capture that particular part of contract company work with reasonable accuracy—those who work for a company that contracts 

out their services and who primarily work for one client at the 

client’s worksite—but it misses much of the network of contract 

activity that is also of interest. In May 2019, according to the CWS, 

933,000 workers (or 0.6% of total employment) were engaged in 

contract company work.

Even with a blurring of work categories, a key measurement objective 

remains to track whether workers are employees or independent contractors. The policy relevance here is obvious. By virtue of the fact that 

they are self-employed, independent contractors are not covered by a host 

of worker protections, including minimum wage, overtime pay, health and 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

42 MEASURING ALTERNATIVE WORK ARRANGEMENTS

safety rules, sexual harassment laws, and rights to organize and collectively 

bargain, all of which apply only to employees. Nor are they covered by 

social insurance benefits, such as workers compensation and unemployment 

insurance, or by employer-provided benefits, such as health insurance and 

retirement plans.

In addition, the earnings of an independent contractor, net of expenses, 

may in some cases be substantially below those of workers undertaking similar work as employees. For example, it has been estimated that when fully 

accounting for vehicle fuel, amortization, insurance, maintenance, tolls, and 

other costs, drivers working as independent contractors for Amazon Flex 

(the next-day delivery arm of Amazon) received estimated net earnings of 

$5.30 per hour—significantly below the federal minimum wage. This compared to average earnings of $23.10 for UPS drivers and $14.40 for FedEx 

drivers (Vernon, 2018; also see Zaleski, 2018). Similar outcomes may arise 

in certain franchise relationships prevalent in industries like janitorial services and home care, where the franchise agreement may put the franchisee 

in a situation akin to employment rather than running a business (Weil, 

2014, Chapter 6). Higher rates of violations in health and safety, labor 

standards, and other workplace requirements have also been documented 

for those in subcontracted or franchised relationships.11

The implication of these differences between employees and independent 

contractors is that, if work continues to migrate toward a nonemployer 

structure, there will be a need to adjust social safety net and employment 

laws in order to mitigate the potential negative side effect of this trend while 

realizing its potential benefits. From a policy perspective, it is critical to 

capture the distinction between employees and nonemployees. The current 

CWS attempts to do this by asking whether respondents are independent 

contractors, independent consultants, or freelance workers, but the wording of the question may not pick up everyone who is working but not as an 

employee. We return to this issue in Chapter 3 to recommend a modification 

to the wording of relevant questions.

Another data collection implication of these complexities in organizational and legal relationships, and of possible misunderstandings by 

workers concerning their status, is that administrative data can provide 

an important complement to survey data for measuring self-employment, 

including independent contractor work. As discussed in Chapter 4, it also 

may be possible to advance the measurement of independent contract work 

using combinations of survey and nonsurvey (administrative) data.

A final point about categorizing types of work is that, along with the 

evolution of AWAs, standard work arrangements also have experienced 

11See, for example, Grabell, Larson, and Pierce (2013); Jamieson (2014); and Ji and Weil 

(2015).
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

UNDERSTANDING THE CHANGING NATURE OF WORK 43

change. Relative to the more manufacturing-based economy of the past, 

many employer-based jobs now offer fewer benefits (e.g., pensions, health 

care) and may offer less stability. Studies have also documented reductions 

in earnings and benefits for workers whose jobs were subcontracted to third 

parties. These developments serve to lessen the distinction between, say, 

W-2 jobs and some of the AWA categories listed above.

Reiterating the discussion above, a critical distinction for policy discussions about work arrangements is whether a person is considered an 

employee or not. Among the self-employed, it also is useful to know if the 

individual owns or operates a business, or if the individual is an independent contractor or other worker in a nonemployee arrangement. Among 

employees, it would be valuable to know whether the worker is in a bilateral 

or trilateral employment relation. Bilateral employment relations encompass 

standard employment relations as well as direct-hire temporaries. Trilateral 

employment relations involve those who work in intermediated arrangements, such as for temporary help agencies, leasing agencies, or other contract companies. Including descriptions of different types of workplace 

intermediaries would also be a useful path forward and allow some continuity with earlier CWS categories, while acknowledging the problems detailed 

in this section. The important types of distinctions that would be missed 

under such a realignment include franchised relationships and subcontracted 

(and possibly third-party managed) arrangements, but those can be more 

accurately measured through business-focused surveys.12

2.3. KEY JOB CHARACTERISTICS AFFECTING WORKER 

OUTCOMES AND WELL-BEING, EMPLOYER STRATEGIES

The primary research and policy goal motivating the collection of 

data about AWAs in the CWS has been to understand the nature of the 

work, how it is changing, and the implications for worker (and employer) 

outcomes. Most AWA measurements in the CWS were intended to capture 

situations in which workers are not employees of the organization using 

their labor and where there is a weakening of the attachment between 

workers and firms (as in firms’ use of temporary help workers, independent 

contractors, contract company workers, or day laborers). The CWS also 

measures other work arrangements that are characterized by a high level of 

12The specific type of subcontracting referenced here is similar to outsourcing: It reflects a 

decision by a business to take some activity and purchase it as an outside service rather than 

doing it internally. The work itself could still be done by W-2 workers in the business the 

subcontracted work is going to (or it might be to a business that is hiring its workers on a 

1099 basis). The point is that this is work that has been affected by fissuring but would not be 

classified as an AWA even though the impacts of such arrangements still need to be measured 

for the reasons discussed in the report.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

44 MEASURING ALTERNATIVE WORK ARRANGEMENTS

precarity, such as work that is temporary or on-call. Yet work arrangements 

are not always easily labeled. Terminology may not be well understood by 

many respondents, and it may change over time. 

The nature of “employment” itself has become complicated because of 

the impact that this business restructuring has had on the employment relationship. Even “employee” is a contested concept. Workers may not always 

know who their employer(s) is (are) because of the multitiered, fissured 

nature of business relationships and legal complexities. For similar reasons, 

they may not know if they are actually employees or independent contractors (self-employed).13 Independent contractors may accurately report 

working for an employer, particularly if the worker is reliant on one business 

for work (independent contractors are not necessarily hustling for clients).

Given the goals of the CWS and other BLS data programs, a reasonable 

strategy would be to place less emphasis on questions asking respondents to 

classify their job into one of several categories and, instead, ask questions 

that elicit information on the organizational arrangement(s) under which 

people work, specifically job characteristics and work outcomes. This section identifies the key job characteristics and work outcomes on which 

measurement should focus and clarifies why that focus matters. The key job 

characteristics are hours, scheduling variability, and contingency. The key 

work outcomes are earnings, benefits, and workplace safety. 

Job Characteristics

Hours and Scheduling

To support the nation’s basic employment statistics, there is clear value 

in collecting information on total hours from a main job and, in cases 

where a person has more than one job, total hours from all employment. 

As pointed out above, however, variability of schedules and reliability of 

hours are also of considerable interest, given their relationship to job and 

economic insecurity (Henley and Lambert, 2014).14 Collecting this kind of 

information requires going beyond asking respondents only about a “typi13As discussed in Chapter 3, there is also an important distinction between whether people 

know if they are independent contractors or employees and whether the questions on the 

CPS/CWS elicit accurate responses. One conclusion of Abraham, Hershbein, and Houseman 

(2019) is that the latter is a problem, too. Household surveys, including the CWS/CPS and 

American Community Survey, do not ask whether an individual is an employee—only whether 

they work for an employer/organization.

14Indicative of the current policy interest in unpredictable work schedules is U.S. Senator 

Elizabeth Warren’s inclusion of the issue (her “Fair Workweek” plan to give workers more 

advanced notice of their schedules) as part of her presidential platform. Available: https://

elizabethwarren.com/plans/part-time-workers.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

UNDERSTANDING THE CHANGING NATURE OF WORK 45

cal week.” Chapter 3 proposes some alternative approaches to generating 

data that capture the extent of scheduling and income variability. 

When work hours are unpredictable and variable, it is important to 

know who sets the schedules—Is it the worker or the employer?—and with 

how much advance notice. A self-employed person who chooses to work 

20 hours a week represents a very different scenario from a person who 

is limited to the same number of hours but would prefer to work more to 

meet household economic needs. The policy implications are clearly different if the trend toward irregular or reduced hours is being driven by 

workers’ desire for flexible scheduling as opposed to being driven by lack 

of opportunities to acquire “steady work.” In any case, for workers who 

seek flexible work, flexible scheduling may not be an inferior arrangement. 

To take an example, it might turn out that many jobs are characterized 

by week-to-week variability in hours. The growth of scheduling algorithms 

in retail and other service sectors, where workers may not receive much 

notice about work schedules, suggests that the “predictability” distinction/

advantage of W-2 work may be eroding (Henley and Lambert, 2014). It is 

therefore important to collect data on and measure variability in hours for 

all but self-employed workers. As discussed in the next chapter, because 

of the growing importance of these issues, yielding room in the survey from 

the old contingent-work questions and providing additional questions on 

worker preferences regarding hours may be a worthwhile tradeoff. 

Job Insecurity

An essential aspect of work arrangements measured using data from 

the CWS is the “contingency” or, perhaps more accurately, the temporariness and insecurity of certain jobs. As noted at the outset of this chapter, 

the need to measure the perceived expansion of temporary work drove the 

specifications of the CWS initially. The survey is well constructed to pick 

this up, with the caveat that it can be difficult for individuals to accurately 

report how temporary their job is. Compared to many other countries, 

however, the percentage of workers identified as “temporary” is relatively 

low in the United States. This renders the category less important than some 

others, such as independent contracting.15

The characteristic of temporariness is only one factor contributing to 

the sense of job security a worker feels. Job security is more complex than 

simply having a job or not; moreover, rather than being defined as either 

secure or insecure, jobs have aspects that make them more or less secure 

in certain respects. For example, many jobs—including many standard 

15In other countries, temporary workers often have explicitly temporary contracts, so that 

they are a clearly identifiable category; in the absence of these types of contracts in the United 

States, the distinction is less clear-cut.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

46 MEASURING ALTERNATIVE WORK ARRANGEMENTS

employer-employee jobs, especially in retail and other service sectors—have 

an on-call dimension that leads to high variability in the timing and even 

quantity of hours of work. Work variability of this variety leads to a different kind of job insecurity than does temporary work, but nonetheless it 

is important to measure and understand.

People do not think uniformly about temporariness, and it is an open 

question how relevant this job dimension still is to policy. Viewed from 

a positive perspective, temporariness means greater employment fluidity, 

and for some people new temporary work arrangements have added a 

welcome dimension of flexibility to their earning activities. Technologies 

have emerged in the past decade that enable workers to earn extra money 

on the side simply by turning on an app, such as Uber (or any of at least 

128 others16), when they have a free hour or two. This means that some 

workers, such as those whose preferred approach is to pursue a variety of 

short-term jobs, are predisposed to be less concerned about the longevity, 

or “security,” of a job. By their nature, these jobs are not permanent in the 

conventional sense; they are flexible. If an Uber driver works for a month, 

then does something else, and then returns to Uber driving later in the year, 

the concept of temporariness may not be terribly relevant—or at least, in 

that worker’s thinking it may not be an automatic negative. 

On the other hand, for workers who would prefer a more stable commitment by a job provider, temporariness may well be considered a negative 

to their sense of security and well-being. How, then, should job insecurity 

or reliability be measured to take into account these divergent impacts on 

outcomes? Because of these nuances in the ways people view job flexibility 

and job security tradeoffs, it is important to gain a better understanding of 

worker preferences regarding the kinds of work in which they engage or 

that they are pursuing. 

An additional concern arises if, as some evidence suggests, all work has 

increased in precarity over time and workers’ ability to assess insecurity 

is limited and affected by changing expectations (Howell and Kalleberg, 

2019; Kalleberg, 2011). The approach of identifying preferences in work 

type is one useful way to get at this, and it could certainly be pursued 

in household surveys like the CWS. Since many jobs (both standard and 

AWA) are likely to be insecure and hence “temporary” to some extent, a 

potentially useful approach to measuring the insecurity aspect of work 

arrangements is to directly ask respondents about the likelihood that they 

will lose their job and, if they did lose it, how difficult it would be to find 

a new one. These approaches, used in several European surveys, are discussed in Chapter 3.

16Farrell, Greig, and Hamoudi (2018) identify 38 million payments directed through 128 

different online platforms to 2.3 million distinct Chase checking accounts.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

UNDERSTANDING THE CHANGING NATURE OF WORK 47

As explicitly recommended in Chapter 3, the BLS should continue to 

collect data that helps researchers understand why people engage in multiple jobs—including why they pursue platform work on the side. Questions on motivation for working a second job (work activity) are crucial 

for understanding people’s work patterns. Relatedly, questions about job 

satisfaction for all workers may also provide insights into how respondents 

view the relative desirability of different work arrangements.

Work Outcomes

Earnings

The positive relationship between people’s earnings and their well-being 

is obvious. Much attention has been given to the lack of growth in earnings experienced by workers over recent decades and the negative economic, 

health, and social impacts this has had on families. But how does this relate to 

changing work arrangements, an expansion of AWAs, and the potential ripple 

effects back on the conditions in standard employment settings? Whether 

changes in workers’ employment arrangements account for the growth in 

earnings inequality, for example, is an open question. 

Recent research (e.g., Howell and Kalleberg, 2019) argues that the 

growth of AWAs does not account for the decline in job quality, which is 

due more to the decline in the quality of standard jobs. This distinction, 

however, is difficult to make, especially when there is interdependence 

between AWAs and employer jobs. An important issue for further study is 

whether AWAs also create spillover effects that influence earnings and conditions in traditional work relationships. Additionally, some AWAs are not 

well identified in the existing data and may appear as traditional employment arrangements. Outside of certain industries, like temporary help, it 

is notable that contract work, outsourced work, and other fissured work 

arrangements are simply not measured, so workers in those arrangements 

may appear to be in regular wage and salary employment. 

It is difficult to generalize about differences in earnings between workers 

in different arrangements. For example, some highly skilled independent 

contractors in high tech and other professional occupations earn higher 

wages than their counterparts in standard full-time jobs, although they are 

still less likely to have fringe benefits (Kalleberg, 2011; Kalleberg, Reskin, 

and Hudson, 2000). On-call workers, day laborers, and part-time workers, 

however, tend to earn consistently lower pay and have fewer benefits; except 

for part-time workers, they also tend to express a preference for not working 

in these jobs (Barley and Kunda, 2006). 

To accurately compare people working in independent contracting 

arrangements with those working in wage and salary jobs, due to the 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

48 MEASURING ALTERNATIVE WORK ARRANGEMENTS

expenses connected with self-employment it is important to make a distinction between gross earnings and net earnings.17 An example is fuel and 

auto depreciation for platform drivers and delivery workers. As discussed 

in Chapter 3, the CWS ideally would collect information on expenses so 

that both gross and net earnings could be reported. In practice, however, 

it is likely that many independent contractors would find such information 

difficult to report. While it would not be possible to ask occupation-specific 

questions in the CWS, specialized surveys have been used to probe into 

some jobs—such as those connected with driving or auto ownership, where 

the dominant platform models rely on cars for their production process—to 

follow up with questions about expenses. Such a question, for example, 

might ask, “On average, how many miles did you drive for this work?” or 

“How long have you owned the car for which you undertake this work and 

how much did you pay for it?”18

Jobs in various work arrangements may also systematically differ not 

just in terms of the level of earnings but also in the variability of earnings. 

In the CWS, earnings variability could be captured indirectly by questions 

about variability of hours. As with predictability and reliability of work 

hours, predictability of earnings has direct implications for people’s economic security. 

Benefits

Given the employer-delivered nature of many U.S. social welfare protections, workers in alternative arrangements are also likely to be disadvantaged with respect to retirement plans, medical care plans, paid time off, 

and other benefits. This is another case in which it is important to delineate 

information about primary jobs and secondary jobs and determine whether 

the worker has benefits from any job or through the job of someone else 

in the household.

Data are needed to inform policy initiatives, such as the recently 

passed California legislation known as AB 5,19 which seeks to help miti17Asking tax-related questions carries with it the danger of potentially harming survey 

response rates and accuracy. One alternative source that researchers (e.g., Collins et al., 2019; 

Lim et al., 2019) have explored for such information on contract workers is tax returns. A 

perfectly completed tax return (Schedule C) subtracts costs from the gross earnings reported 

on, say, a 1099-K form. A survey could ask respondent if they had expenses, and then, if data 

linking were possible, these records could triangulate to tax data. This possibility is further 

developed in Chapter 4, which underscore how administrative tax data could complement 

data collected in household surveys.

18See for example: https://www.ridester.com/2018-survey. 19The AB 5 law tightens the definition of employment and is intended to reduce the misclassification of employees as independent contractors—common in such sectors as ridehailing drivers, construction workers, food-delivery couriers, nail salon workers, and franchise 

owners—in an effort to reduce the insecurity associated with this kind of work. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

UNDERSTANDING THE CHANGING NATURE OF WORK 49

gate the negative side effects being created by shifts in certain sectors 

toward increased use of independent contracting. Basic information on 

the incidence of benefits being offered, even if it is generated from data 

without much nuance on the level of benefits, would be useful for these 

discussions.

Other Job / Work Outcomes

Workplace health and safety can be affected by factors linked to AWAs. 

An analysis of the Census of Fatal Occupational Injuries found that, in 

2017, about 12 percent of fatal workplace injuries were experienced by 

independent workers (defined as workers with short-term jobs that involve 

a discrete task and have no guarantee of future work). This represents a 

disproportionally higher propensity of death attributable to a workplace 

incident than that experienced by their employee counterparts (Pegula and 

Gunter, 2019). Health and safety risks arising from fissured employment 

relationships can also spill over to other parties; for example, Litwin, Avgar, 

and Becker (2017) find that outsourcing hospital cleaners increases the 

spread of health care-associated infections. As noted above, employment 

protections, rights, and social safety net protections may be negatively 

affected for workers who are in AWAs (e.g., have unstable hours or are oncall) and, if there are spillover effects, even for workers who are designated 

as employees. 

The CWS cannot be the data source to provide statistics about all of the 

above as they relate to work arrangements. Data collection will need to be 

prioritized according to the value the various types of data have in addressing policy issues as well as what it is feasible to collect on a household 

survey. Among the most important kinds of data are those that illuminate 

the following:

• Distinctions of employee versus self-employed/independent 

contractor; 

• Categories of AWAs, such as temporary agency work and platformbased work;

• Job characteristics, starting with earnings and variability in earnings (which the CWS is well suited to address), for primary and 

secondary jobs; 

• Multiple job holding (primary and one secondary job); 

• Control over work schedule; 

• Health insurance support; and 

• Preferences for AWA versus more standard work arrangements.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

50 MEASURING ALTERNATIVE WORK ARRANGEMENTS

2.4. INFORMATION ABOUT ALTERNATIVE WORK 

ARRANGEMENTS THAT COULD BE PROVIDED BY BUSINESSES

Underlying structural relationships have emerged that affect work and 

worker outcomes, and the CWS was created to study the role of AWAs 

in these changes. Workers may not be in the best position, however, to 

report on the sometimes complex work arrangements they have.20 For 

example, workers often are employed by firms that are in contract or subcontract arrangements with other firms that, research suggests, may impact 

the worker outcomes. The CWS only tries to measure workers whose 

employers contract out their services if they primarily work for one client 

at the client’s worksite; otherwise, the contract relationship is deemed too 

complex to ask about in a household survey. 

Information from business surveys, ideally linked with information 

from employee surveys or administrative data, is needed. In many of these 

situations, some work that was once done internally in large businesses has 

now been entirely subcontracted to other firms on a permanent basis, and 

not through a staffing agency, third-party management company, or platform. In these arrangements, the workers may be “traditional employees,” 

but they have been affected by an earlier outsourcing decision. It is important for policy makers to be able to track such trends in the use of subcontracting, which may involve W-2 employment but that “operate under 

very different economic constraints and incentives than had those jobs 

remained inside their original organizations” (Weil, 2019). Although such 

trends would not be captured within the question structure of the CWS, 

they certainly are important in measuring changes in the contracting relationships between companies and to the overall labor market landscape of 

compensation, benefits, and work conditions. 

Business data also are needed to understand broader changes that have 

taken place in recent decades, whereby economic activity has been increasingly dominated by a select group of highly productive and profitable firms. 

Despite sluggish aggregate productivity growth, these leading firms have 

continued to experience steady growth in their productivity and financial 

returns (Furman and Orszag, 2018). As a result, industry sales are increasingly concentrated in firms with higher productivity. Correspondingly, the 

share of sectoral income arising from wages (the labor share) has been 

decreasing (Autor et al., 2017). Thus, as leading firms pull away from the 

pack of other companies in terms of revenue, jobs are not following them 

at the same pace, leading to diverging fortunes for workers who work in 

those firms as compared to those who do not. 

20See discussion of this problem in Weil (2019). 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

UNDERSTANDING THE CHANGING NATURE OF WORK 51

Meanwhile, other analyses have found that growth in earnings 

inequality can be primarily explained by growing differences between

firms rather than within firms (e.g., Barth et al., 2016; Song et al., 2019). 

In particular, the firms that pay the most are becoming less likely to hire 

low-wage workers (Song et al., 2019). At the same time, these studies find 

that very large firms are less likely to be the ones that pay the most. One 

common view is that these trends primarily reflect the growing economic 

dominance of “superstar” firms, which increasingly differ from other 

firms in their sectors in their efficiency, technological sophistication, and 

dynamism (Autor et al., 2017). In this view, recent technological innovations, particularly in the digital economy, have enabled top firms to reap 

the benefits of scale to outstrip the efficiency of their competitors. As 

these firms learn to do more with less, they increase their productivity and 

capital returns but reduce their reliance on workers. 

A critical question is whether the various AWAs and related changes in 

business structure may contribute to explaining the same set of facts. In this 

alternative view, these changes are not simply the result of changes in the 

technology used in production tasks; rather, they largely reflect “fissuring,” 

that is, the shifting of tasks performed within the firm to other parties 

through outsourcing or related forms of contracting (Weil, 2014). The rise 

in measured profitability and productivity of lead firms reflects not only 

that these firms are getting better at what they do, but also that they are 

making changes in choosing which functions to carry out in-house. As firms 

focus on core activities while shifting other activities to outside businesses 

within their industries or in other sectors, lead firms may improve their 

productivity and profitability on paper without fundamentally changing 

the work being done. 

Additional data are needed to understand the extent to which the 

observed divergences between firms directly reflect the standard “superstar” 

view, in which technology contributes to observed changes (such as by providing lower-cost means of monitoring the performance of other entities) 

or the fissuring view. In the fissuring view, rising profits and productivity at 

lead firms may be fully decoupled from trends in aggregate productivity 

growth if firm boundaries change without major changes in overall activity. Growth policies for the economy geared to capital investment would 

play out differently depending on which of the two views, and therefore 

scenarios, is more accurate. Whereas the superstar story would imply a 

tradeoff of greater productivity enhancement but increased inequality, the 

fissuring story would imply that such policies can be expected simply to 

result in greater inequality with little benefit to overall growth. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

Although a number of data sources contribute to the measurement 

and monitoring of labor market trends involving alternative work arrangements (AWAs), the Contingent Worker Supplement (CWS) to the Current 

Population Survey (CPS) is the key instrument within the portfolio of federal economic statistical programs. This chapter presents recommendations 

intended to help guide future iterations of this important survey. It includes 

higher-level, conceptual recommendations as well as more detailed recommendations for improving the survey instrument. 

This chapter’s subsections address the universe of workers and jobs 

covered in the survey (3.2); the categorical distinctions among work 

arrangements it is most important for the survey to make (3.3); and the 

characteristics of AWA jobs it is important to identify (3.4). In the existing survey, the CWS respondents are asked only about their main jobs, 

as identified in the basic CPS questionnaire. As detailed in this chapter, 

the panel recommends broadening that scope to include other activities a 

person may have engaged in for pay. Whereas the current survey measures 

several different AWAs, the most important work-arrangement distinction 

to make is that between independent contractors and other self-employment 

arrangements, on the one hand, and traditional employee arrangements 

on the other. In addition, it is important to capture key characteristics of 

jobs, most notably the predictability of workers’ schedules as well as the 

contingency or temporary nature of jobs. Focusing on the characteristics of 

jobs—and the preferences of workers in relation to those characteristics—

would yield more valuable information than attempting to assign jobs 

to labeled categories. Survey design issues are discussed throughout the 

3

Role of the Contingent Worker 

Supplement in Fulfilling 

Measurement Needs Related to 

Alternative Work Arrangements

53
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

54 MEASURING ALTERNATIVE WORK ARRANGEMENTS

chapter. We begin with an overview of the current structure of the CWS, 

which is helpful to have in mind when considering what to keep and what 

to change in the survey.

3.1. OVERVIEW OF THE CONTINGENT WORKER SUPPLEMENT

This section briefly describes the purpose and current structure of 

the CWS.1 The CWS collects information from individuals identified as 

employed in the CPS concerning their main job and accepts both selfreports and proxy responses. Administered by the Census Bureau using a 

probability sample of about 60,000 households, the CPS asks respondents 

about activities that took place during the week including the 12th of the 

month, which for most respondents is the week prior to the survey interview. The interviews are conducted by well-qualified field staff either by 

phone or in person. The CPS continues to achieve relatively high response 

rates, although they have declined from roughly 92 percent a decade ago 

to roughly 83 percent currently.2

Households participate in the CPS for 4 consecutive months, then 

drop out for 8 months, and finally return for another 4 months before 

being removed from the sample.3 To be eligible to participate in the survey, 

individuals must be 15 years of age or over and not in the Armed Forces. 

People in institutions, such as prisons, long-term care hospitals, and nursing 

homes, are ineligible to be interviewed in the CPS. A strength of the CPS is 

that it collects extensive demographic information for respondents—e.g., on 

age, gender, education, race, marital status, and family income—which can 

be used to describe characteristics of different groups for whom monthly 

labor force data are also collected.

The most recent CWS was conducted as a supplement to the May 

2017 CPS. As usual, it asked questions about persons who held a job for 

pay or profit during the reference week, with a single question also asked 

of people who did not have a job during that week but looked for work 

during the last year and were available for work during the reference week. 

As described in Chapter 1 and as suggested by its name, a central purpose 

of the CWS is to measure the contingency, or temporary in nature, of 

the respondent’s main job. The precise questions asked about this differ 

1In so doing, it elaborates on the description of the CWS and its role in measuring AWAs 

in Chapter 1. The description here draws in part on a presentation to the panel at its first 

meeting (March 29, 2019) by Anne Polivka and Julie Hatch Maxfield and on results from the 

CWS provided by BLS in an article titled “Electronically Mediated Work: New Questions in 

the Contingent Worker Supplement” (Current Population Survey Staff, 2018). 

2Available: https://www.bls.gov/osmr/response-rates.

3Available: https://www.census.gov/programs-surveys/cps/technical-documentation/methodology.

html.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 55

depending on whether the individual in question is identified in the basic 

monthly CPS as an employee or as self-employed. 

In addition to characterizing whether jobs are temporary, the CWS classifies the respondent’s main job into one of several largely exclusive work 

arrangements (although they are not entirely exclusive, as on-call workers 

also can be contract company workers):

•	 Temporary help agency work

•	 On-call work

•	 Day laborer

•	 Contract company work

•	 Independent contractor

In principle, independent contractors are by definition self-employed, 

but the survey’s questions about independent contractor work are asked 

in the basic monthly CPS both of those who are coded as employees 

and those who are coded as self-employed (although the questions are 

worded somewhat differently). For each category, if the respondent (or 

other household member4) is reported to be in the given type of work 

arrangement, a series of follow-up questions is asked about it. Workers not 

assigned to one of the alternative work arrangements can be categorized 

either as employees not in an alternative arrangement or as self-employed 

but not an independent contractor. Questions were added to the 2017 edition of the supplement to collect information on whether any job (not just 

the main job) held in the reference period was intermediated by a mobile 

app or online platform.

After asking about a person’s current job, the CWS asks about the 

pathway taken into that job. Depending on the person’s job, these can be 

pathways into independent contractor/self-employment work, into other 

AWAs, or from AWAs into a current (regular) job. The CWS also includes a 

set of job satisfaction questions. For the most part, these are cast as “work 

preferences” and focus on an indicated characteristic of the respondent’s 

job.5 Understanding workers’ motivations is valuable for understanding 

the implications of AWAs for worker well-being, specifically understanding whether workers are engaged in AWAs as a fallback because standard 

4The CPS allows proxy reports for other members of the household.

5For example, question PES25a, administered to people whose jobs were characterized as 

contingent, asks, “Would (you/NAME) prefer to have a job that is permanent rather than 

temporary?” And question PES25aR follows up with: “People have temporary jobs for a 

variety of reasons. For example, some people have temporary jobs because it is the only type 

of work they could find. Others have temporary jobs because they enjoy the flexibility or for 

other personal reasons. What is the MAIN reason (you/NAME) (have/has) a temporary job?” 

Available: https://www2.census.gov/programs-surveys/cps/techdocs/cpsmay17.pdf.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

56 MEASURING ALTERNATIVE WORK ARRANGEMENTS

employer work is unavailable or because the flexible job characteristics of 

the contract (or other kind of) work are attractive to them.

Finally, the CWS includes detailed CPS-type questions about whether 

respondents are looking for other work and what has been done to find 

other employment. It also asks about other characteristics of their jobs, 

including employee benefits (health insurance, retirement accounts), earnings, hours, and membership in labor unions/associations. 

The supplement interview averages 3 minutes, 38 seconds in length 

for each person who completes it, and 5 minutes, 42 seconds in length for 

households with at least one person who completes it. An intended 10-minute 

maximum was exceeded by 12.5 percent of households. 

As a supplement to the CPS, the CWS has a number of important 

strengths. The sample is carefully designed to be representative of the U.S. 

population, the data collection is undertaken by well-trained interviewers, 

it has a relatively high survey response rate, and a significant amount of 

demographic information is obtained about survey participants as part 

of the basic monthly survey. The fact that the CWS is a survey means that 

it can be used to collect information about how people feel about their 

jobs and the reasons for working under particular arrangements, something 

that cannot be learned from administrative or financial records data. As 

such, the CWS is well suited to collecting information on important policyrelevant features of jobs and job characteristics, as described in Chapter 2 

(section 2.3). 

Like any data source, the CWS also has limitations. There are some 

concerns about the use of household survey data generally, including data 

from high-quality federal surveys such as the CPS and its supplements. One 

of these concerns is over the use of proxy reporting. For the CPS, this is 

a practical necessity, because CPS responses must be obtained during the 

10 days following the survey reference week, and it would be difficult if not 

impossible to interview all household members directly on that schedule. 

The BLS acknowledges this and notes that, ideally, all respondents would 

be self-reporters, but given the data collection environment and constraints, 

eliminating proxy responses simply is not feasible. 

Proxy reporters can provide high-quality information about others’ 

activities and behaviors if they are visible and known to the proxies 

(Moore, 1988). This may not always be the case, however, with occasional 

or irregular work. Even when a proxy reporter knows about it, another 

person’s work activities may be less salient to the proxy reporter than to 

the person doing the work, so stronger cues may be required to prompt 

accurate reporting (Abraham and Amaya, 2019). Katz and Krueger (2019) 

found that in the 1995 and 2005 versions of the CWS, reported participation in AWAs was about 2 percentage points lower among proxy reports 

than among self-reports. This difference widened to about 2.9 percentage 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 57

points lower in 2017. Although these differences could reflect real differences between the people for whom proxy and self-reports were obtained, 

the fact that they persist even after controlling for respondents’ educational 

attainment, experience, race, and sex may suggest that proxy reporters 

have been failing to report some AWA work. All of this suggests that it 

would be worthwhile for BLS to carry out additional cognitive testing on 

the ability of proxy respondents to report about AWAs for other members 

of their households and on the best way to pose questions about this to 

proxy reporters. 

Another factor that may be affecting the accuracy of estimates from the 

CPS and CPS supplements such as the CWS are the above-noted waning 

response rates. Falling response rates raise concerns about the representativeness of the CWS sample, because nonresponders are not likely to be 

randomly distributed throughout the population.6 Through 2010, nonresponse rates for the basic CPS were consistently under 10 percent, but 

that figure has risen substantially in the last 10 years. Even among those 

who respond to the basic CPS questions, some do not respond to supplements such as the CWS, and supplement nonresponse has grown. In 2005, 

the overall nonresponse rate to the CWS supplement was 15.5 percent, 

taking into account both nonresponse to the basic CPS and nonresponse to 

the additional supplement; in 2017, using the same measure, nonresponse 

was 23.0 percent.7 All of this raises concerns about bias as well as lack of 

precision in estimates. The CWS response rates are still much higher than 

those for most other surveys, especially nongovernment surveys, but falling 

response rates do create a compelling motivation for thinking about ways 

to complement the CWS with data from other sources. 

Issues related to proxy reporting and generally falling household survey 

response rates across the statistical system are largely beyond the control of 

the BLS, and they are far from unique to the CWS. Much has been written 

about both issues in other contexts. In the next section of this chapter, we 

focus on concerns that are specific to the CWS measurements of AWAs 

and ways in which those can be addressed. These issues include (1) the 

short reference period (the prior week), which leads to the strong likelihood that work, especially sporadic work, is missed; (2) the near-exclusive 

focus on respondents’ main jobs; and (3) uncertainty over whether people 

can reliably answer some types of questions, such as about the nature of 

the employment arrangement (e.g., when the employment arrangement is 

mediated by another party as in the use of temporary help or contract com6The U.S. Census Bureau routinely publishes nonresponse rates, but typically only for a 

recent 12-month period. Available: https://www.census.gov/programs-surveys/cps/technicaldocumentation/methodology/non-response-rates.html.

7See http://data.nber.org/cps/cpsfeb05.pdf and http://data.nber.org/cps/cpsmay2017.pdf.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

58 MEASURING ALTERNATIVE WORK ARRANGEMENTS

pany work). These characteristics of the CWS limit its capacity to measure 

alternative work in a way that is satisfactorily comprehensive for informing 

employment policy. 

3.2. CWS SCOPE: UNIVERSE OF WORKERS 

AND WORK ACTIVITIES

Before workers and work can be categorized, job characteristics identified, and trends in work arrangements measured, the universe of respondents (workers) and work activities for which information is requested must 

be determined. The CWS measures work arrangements concerning the main 

job of each person who reports having worked during the survey reference 

period in the basic monthly CPS. By design, it does not capture any work 

a person may do to generate income that is not reported in response to the 

core CPS employment questions. 

In this section, we consider whether the universe of workers and work 

activities is appropriately defined in the CWS to capture the information 

on work in contingent and alternative work arrangements that is needed 

for policy and research. Specifically, we discuss issues related to the survey 

reference week, work activities that may not be reported in the main CPS, 

and secondary work activities. 

CWS Universe: Survey Reference Period and 

Difficult-to-Identify Work Activities

In considering whether the universe of respondents to the CWS is 

appropriate, two issues deserve discussion. First, we consider whether the 

survey reference period of 1 week is too short to provide the data needed 

to understand the role of contingent and alternative work arrangements in 

Americans’ lives. Second, we consider whether the CWS should allow for 

the possibility that some work done during the survey reference period is 

missed in the main CPS—work that is likely to be disproportionately in a 

contingent or alternative work arrangement. 

With regard to the first issue, the designation of the reference period—

typically the week that includes the 12th of the month (data collection 

occurs the following week)—is perhaps the most obvious survey design 

feature in the CWS affecting the way respondents are sorted by work status. 

Unlike the work status of people who work a regular weekly schedule or 

who do not work at all, the work status of a person who, for example, 

works sporadically throughout the year will depend on the timing of work 

performed in relation to the reference period.

The issue is that people who report being unemployed or not in the 

labor force may nonetheless periodically engage in work activities to sup-
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 59

plement their household income. Even if respondents always accurately 

report their work activities during the reference week, this type of periodic 

work may be missed because of its timing. There is evidence of the potential 

importance of such supplemental income in both survey data and proprietary sources. The Survey of Household Economics and Decisionmaking 

(SHED), sponsored by the Federal Reserve Board, asks respondents about 

their primary work status during the prior month.8 All respondents, including those who report “not in the labor force” or “unemployed” as their 

primary status during the previous month, are asked whether they have 

worked in any of a variety of side jobs during that month. Estimates from 

the SHED suggest that holding such side jobs is very common among these 

two groups: in 2016 and 2017, 20 percent of those who were not in the 

labor force and 42 percent of those who were unemployed reported having 

at least some informal work activity or side job during the prior month 

(Abraham and Houseman, 2019). 

Analyses of financial account data indicate that most individuals participating in platform work do so for just 3 months or fewer out of the year, 

so that the number of platform participants in any particular month is considerably below the number who participate over the course of a year (e.g., 

Farrell, Greig, and Hamoudi, 2018). Similarly, participation in platform 

work in any given week is apt to be notably lower than participation over a 

month or longer period. Again, using financial account data, Farrell, Greig, 

and Hamoudi (2018) also find a spike in work done for online platforms 

among those who recently became unemployed, as determined by receipt 

of unemployment checks. Although such work is often sporadic, it can be 

an important source of income, particularly for households experiencing 

financial hardship (Abraham and Houseman, 2019). 

Additionally, even if such work is done during the reference week, it 

may be missed in the CWS. Under the current CWS design, other than a 

single question asked of unemployed and discouraged workers, the questions on the supplement about current work arrangements are asked only 

8The SHED was administered by GfK, an online consumer research company. In order to 

create a nationally representative probability-based sample, the survey methodology selects 

respondents based on both random-digit dialing and address-based sampling. The cumulative 

response rate for the survey was approximately 4.0 percent for the SHED in 2016, 2017, and 

2018. A post-stratification process was used to adjust for any survey nonresponse as well as 

any noncoverage or under- or over-sampling resulting from the study’s specific sample design. 

The variables employed in the adjustment of weights for that study comprised gender, age, 

race/ethnicity, education, Census region, residence in a metropolitan area, household income, 

and access to the Internet. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

60 MEASURING ALTERNATIVE WORK ARRANGEMENTS

of those who are identified as employed in the basic monthly CPS.9 Recent 

research suggests that the basic CPS employment questions may miss certain types of work that are in scope for the survey. Evidence of uncaptured 

market work done by individuals who may not be categorized as employed 

in the monthly CPS pertains primarily to what is sometimes termed “side” 

or “gig” jobs and other informal, nonemployee work activities. In the CWS, 

this type of work would fall under the category of independent contractor work, broadly defined. Examples of such work could include driving 

for Uber, tutoring students on the side, doing housekeeping or yard work, 

providing child care, eldercare, or dog-walking services, or earning income 

from YouTube video postings. 

Robles and McGee (2016), analyzing data from the Enterprising and 

Informal Work Activities (EIWA) survey fielded by the Federal Reserve 

Board, report that during the 6 months prior to the survey in 2015, 36 percent of the adult population had participated in informal work that involved 

either selling or renting property or providing services. Abraham and Amaya 

(2019) report the results of a study in which a nonrepresentative sample of 

respondents recruited through Amazon’s Mechanical Turk platform were 

asked the standard CPS employment questions followed by additional questions about their engagement in various types of independent contractor or 

nonemployee work. Depending on how the latter questions were phrased, 

including those who reported such work raised the estimated employment 

rate by 3 to 5 percentage points. Similarly, results from two waves of the 

Federal Reserve Bank of Boston Survey of Informal Work Participation 

(SIWP)—which replicates the basic CPS questions to determine whether a 

person is employed and also asks separately about participation in informal work activity—show that accounting for informal work raised the 

employment rate estimated for those age 21 and older from 65.1 percent to 

69.6 percent, a 4.5 percentage point increase (Bracha and Burke, 2018).10

In an analysis of the American Time Use Survey (ATUS), which provides a detailed accounting of individuals’ daily activities, Allard and 

Polivka (2018) examine the incidence of “income-generating activities” 

that are not part of any main or secondary job reported. Although they do 

not find evidence of growth in such activities over time, on average, about 

9The question for those who were unemployed or laid off is about what type of work these 

people were looking for. Specifically, the survey introduction asks: “I have a question about the 

type of employment you looked for in the last 4 weeks . . . Were you looking for temporary, 

short-term employment or more long-term employment?” (with the option of the answer being 

coded as “either/anything I can find”). There is also a question for discouraged and marginally 

attached workers, but they do not figure in the weighting scheme and thus a weighted estimate 

cannot be derived for them.

10The SIWP attempts to account for informal paid activity or side jobs, exclusive of selling 

property, renting property, or responding to surveys.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 61

1 percent of the population reported doing such income-generating activities on a given day from 2012 to 2016. Under the assumption that selected 

categories of these income-generating activities were in fact “work,” they 

estimate that correctly classifying as employed individuals who were coded 

as unemployed or not in the labor force but who engaged in such labor 

income-generating activities would raise the employment rate for those 

age 15 and older 0.3 to 1.8 percentage points.11

A possible explanation for these findings from various surveys is that 

people engaged in nonemployee work or other AWA may think of themselves as unemployed or not in the labor force, especially if they have held 

a standard employer-provided job in the past. In the existing CWS, however, if such work is not reported in response to the basic CPS employment 

question respondents are not asked about the arrangements under which 

it occurs. 

The CWS could address these issues—a short reference period and 

potential underreporting of certain AWAs—by asking CPS respondents who 

did not report any work in the main CPS a set of initial screener questions. 

RECOMMENDATION 3.1: At the beginning of the CWS supplement, 

screener questions should be asked of those who did not report any 

work in the basic monthly CPS. The questions should probe into work 

activities for pay that individuals sometimes do to supplement household income when they are unemployed and looking for a steady job 

or when they are retired or otherwise not steadily employed. The questions should ask about such work over a longer reference period, such 

as 1 month, as well as during the CPS reference period (the prior week). 

Secondary Work Activities

The scope of the CWS is limited by the fact that it has been concerned 

only with a respondent’s main job. As discussed in detail in Chapter 2, 

it would be useful to know about all the work activity of those reporting work, not just about the work associated with one job. Often, secondary work activities are in contract or other AWAs, or they may be held by 

workers whose main job is in an AWA (Abraham and Houseman, 2019). 

For various policy-related reasons, it is important to understand when and 

why people engage in secondary work activities. Particularly important is 

understanding the circumstances in which people take on second jobs to 

supplement household income and make ends meet. 

CPS data indicate that the share of workers who held more than one 

job averaged about 5 percent during 2017, the year of the most recent 

11These results are based on data presented in Allard and Polivka (2018), Table 3. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

62 MEASURING ALTERNATIVE WORK ARRANGEMENTS

CWS. In the study described above, Allard and Polivka (2018) also use the 

ATUS to examine the possibility that the CPS underestimates the prevalence of multiple job holding. Allard and Polivka find evidence of a significant understatement of multiple job holding, concluding that “if workers 

misclassified as single jobholders were classified correctly, the estimate of 

multiple jobholders would be between 3.0 percent and 20.7 percent higher 

in 2012–16 than the current figure.” It is also notable that the base level 

of multiple job holding in the ATUS is about double that estimated in the 

basic CPS.

Research based on other sources has generated additional evidence suggesting that secondary work activities are far more common than suggested 

by the CPS/CWS data and that much of this work takes the form of AWAs. 

Moreover, the same evidence suggests that income from these activities can 

be important to households experiencing a reduction in income from a 

main job, unusually high expenses, or some other type of financial distress. 

Data from the above-referenced SIWP produced an estimate of the 

multiple-job-holding rate that was 11 percentage points higher than the 

survey’s baseline estimate of 19 percent (Bracha and Burke, 2018). Estimates based on data from the 2016 and 2017 SHED, which included 

similar questions, were that 28 percent of adults had earned money from 

informal work or side jobs outside of a main job during the month prior 

to the survey. Among those adult respondents, roughly one-third, or about 

11 percent of the employed, reported that money from their side job was an 

important source of household income (Abraham and Houseman, 2019). 

Consistent with those findings, in data collected using a survey module on 

the nightly Gallup telephone survey, responses to questions designed to capture all work activity, including work involving very low hours, indicated 

that about 20 percent of workers held multiple jobs (Abraham, Hershbein, 

and Houseman, 2019). 

The results from these surveys suggest that probing for other incomegenerating work activities substantially increases estimates of multiple job 

holding. This is a significant finding about the U.S. labor market and, if 

confirmed in a larger, more representative survey, such as the CWS, is 

something that would be desirable to have reflected in official economic 

statistics.

RECOMMENDATION 3.2: For respondents reporting only one job 

in the basic CPS, the CWS should begin with a set of questions about 

additional work activity. Respondents would first be asked if they 

did anything for pay (to supplement income) beyond what they have 

already reported for their main job. The questions would ask about 

such work over a longer reference period, such as 1 month, as well as 

about the CPS reference period (the prior week).
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 63

Although the evidence from other surveys showing high rates of secondary work activities is compelling, it is possible that the same result 

might not hold in the CPS sample. Although they were designed to be 

representative of the population as a whole, several of the surveys cited 

earlier were administered through an online panel, and people willing to 

participate in such panels could be more likely than other people to participate in secondary work activities as well. Nonetheless, cognitive testing 

for the 2017 CWS uncovered a similar problem. Specifically, the cognitive 

testing for electronically mediated work indicated that there were multiple 

paid activities that respondents did not think of as “jobs,” leading the 

CWS to revise questions for electronically mediated work to include “any 

work” (Kopp and Edgar, 2016). Thus, the 2017 implementation of the 

CWS already asked respondents with only one job about additional work 

for pay using electronic means. The recommendation above simply expands 

this line of inquiry to include other kinds of work.

Querying respondents about work activity over two time horizons will 

yield a new estimate of the rate of secondary job holding during the reference week, one that captures second jobs missed in the basic CPS, and an 

estimate of the rate of secondary job holding over a longer time horizon. 

As was the case with the employment rate, the estimated rate of secondary 

job holding over the longer time horizon should be higher than the rate 

computed in the basic CPS, both because it captures work that is sporadic 

or interrupted and because the question wording will be designed to better 

capture work activity that is sometimes missed by standard household 

survey questions.

A subset (at least) of the work-arrangement questions asked about primary jobs also should be asked about secondary jobs, whether identified in 

the basic monthly CPS or in response to the new questions about additional 

work asked on the CWS.

RECOMMENDATION 3.3: It would be desirable to ask the full battery of CWS questions about all secondary jobs held either during the 

reference week or during the longer 1-month time frame. At a minimum, 

the CWS should collect information, where applicable, on selected characteristics of one secondary job (when there is more than one secondary 

job, selecting the one with the most hours worked). These characteristics 

should include: whether the job is a self-employment or independent 

contractor arrangement, hours variability, and main reason for holding 

the secondary job. If not already collected in the basic monthly CPS, 

information on hours, earnings, industry, and occupation also should 

be collected. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

64 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Cognitive Testing of Screener Questions

Implementing the previous recommendations will require the development of screener questions to identify work activity that may have been 

missed in the basic CPS interviews. As is always the case when new questions are added to the CPS or its supplements, careful cognitive testing 

will be required, in this case to determine the optimal reference period and 

wording to solicit work that was not reported in response to the standard 

monthly CPS employment questions. 

RECOMMENDATION 3.4: Implementation of the new questions proposed for the CWS (in recommendations 3.1 through 3.3) will require 

extensive cognitive testing to determine the optimal reference period 

and wording to solicit responses about work that was not reported in 

the main CPS. 

Regarding the reference period, the panel acknowledges that there may 

be risks in deviating from the standard reference period for a subset of the 

CWS questions. In testing new questions for the survey, potential risks will 

have to be weighed against the value of questions about a longer reference 

period for providing a more complete picture of employment activities. 

Another concern is that questions about a longer period may be more 

subject to recall bias. For these reasons, it will be important to pilot the 

approach recommended above. 

Testing can be guided by two hypotheses regarding underreported 

AWAs. One hypothesis is that AWAs are common but sporadic, so the 

CWS reports about respondents’ main jobs are correct for the reference 

week in question. The other hypothesis is that some people engaged in 

an AWA misreport it (or do not report it). Much of the other work measuring AWAs has used longer reference periods and also has provided 

respondents with more specific examples of different types of work activity 

that might be performed under an AWA. This means there are multiple 

factors that might account for the higher rates of AWA participation in 

those surveys, making it difficult to directly evaluate the likely impact 

of asking about a longer reference period. If people are reporting accurately but their work is infrequent or sporadic, then it would be better 

to ask about the recent week first, and then expand to the 1-month time 

frame. On the other hand, if there are concerns that revising the survey questions to encourage more complete reporting of AWAs may lead 

to “telescoping”—unintentionally including in their report activity that 

occurred prior to the reference period—it will be preferable to start with 

the longer period and then ask about the shorter period. Asking in this 

latter order (longer period first, then shorter) puts a boundary around the 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 65

answers and reduces the chance that people will misreport activity in 

the last week when it really occurred earlier. 

Aside from the choice of reference period, testing also will need to 

address how best to obtain complete reporting of primary or secondary 

work activities not reported in the main CPS. One strategy would be to 

include examples of the types of work that prior research indicates may 

be missed in the basic CPS, such as the provision of personal services to 

households and work obtained online. In addition, it may be worth emphasizing that “even one hour” of work constitutes work for pay. For instance, 

the American Community Survey asks, “LAST WEEK, did this person do 

ANY work for pay, even for as little as one hour?”12 The Gallup survey 

discussed in Abraham, Hershbein, and Houseman (2019) uses the phrasing, 

“Thinking about your WORK SITUATION over the past seven days, have 

you been employed by an employer—even minimally like for an hour or 

more—from whom you receive money or goods?” 

The goal of providing examples is to better convey to respondents 

the kinds of income-generating work activities about which users of the 

data would like to know. Following this strategy, the SHED asks about 

being paid for specific activities, including “child or elder care services; 

dog walking, feeding pets, or house sitting, house cleaning, yard work, or 

other property maintenance work” and so on.13 Jensen, Tickamyer, and 

Slack (2019) ask about “additional kinds of work—other than the more 

formal types of employment we’ve already discussed—that many people do 

to make ends meet” and list 19 different activities. Abraham and Amaya 

(2019) test questions about informal work that provide detailed examples 

compared to a simpler question without examples; they find that among 

those reporting for others in their household, providing detailed examples 

produced a larger number of reports of that sort of work. 

Given budget and time constraints, any examples given in the CWS 

will need to be more limited than those found in other surveys such as the 

SHED, which probes participation in about a dozen different work activities. While mentioning some specific company names, such as the names 

of platform companies, could help to jog respondents’ memories, the relevant company names can be expected to change over time, making that 

an unattractive strategy for a survey intended to provide information that 

can be compared over time. For that reason, examples should be framed 

in terms of the types of work involved (e.g., “ride share work”) and not in 

terms of specific employers (e.g., Uber or Lyft). 

12Available: https://www2.census.gov/programs-surveys/acs/methodology/questionnaires/2019/

quest19.pdf.

13Available: https://www.federalreserve.gov/consumerscommunities/files/SHED_2018codebook.

pdf.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

66 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Finally, while using examples in surveys may improve data quality (e.g., 

Tourangeau et al., 2014), there are many outstanding issues regarding the 

selection and presentation of examples in survey questions (see Schaeffer 

and Dykema, 2020). Therefore, as with the other survey changes proposed 

in this chapter, the inclusion of examples to help define the constructs under 

consideration and facilitate recall should be thoroughly tested, because the 

examples chosen can broaden or narrow what respondents consider in 

unintended ways.

The BLS naturally may be concerned about asking questions that might 

affect the CPS responses in subsequent waves. The agency has recognized 

that some kinds of work may be missed in the basic CPS, and it considered 

expanding the universe for the questions about electronically mediated 

employment (EME) arrangements to include unemployed respondents. In 

the end, the BLS did not modify the survey this way, partly out of concerns 

that doing so could be seen as challenging people about whether they were 

really unemployed, potentially affecting reports of unemployment in subsequent waves and causing some disruption to the time series of statistics on 

employment and unemployment.14 The BLS also was concerned that asking 

such questions might appear redundant and frustrate people who thought 

they already had answered the questions.

There are ways to frame questions about additional work to capture 

activity that the basic monthly CPS might have missed while mitigating any 

impacts on subsequent responses to the standard CPS employment questions. For example, in the main CPS a question asked of people who are 

coded as unemployed or not in the labor force might note that sometimes 

people do some work on the side to supplement their income (or “while 

looking for work” if the person is unemployed) and give examples of such 

work. Similarly, in querying people who report only one job in the main 

CPS, questions could first note that sometimes people do some work on 

the side to supplement their income from a primary job, giving examples. 

Respondents then could be asked if they had done this type of work over 

the indicated reference period(s). 

Particularly for people who report being unemployed or not in the 

labor force in the main CPS, there is the possibility that the screener questions would capture a primary job held before the individual entered this 

job status. This possibility could be minimized by wording the question 

to ask about a job that supplements household income. Further, for those 

indicating that they held such a job, a follow-up question could directly 

ask if the job was a primary job that they lost or left prior to becoming 

unemployed or leaving the labor force. 

14“Question universe” section, available: https://www.bls.gov/opub/mlr/2018/article/

electronically-mediated-work-new-questions-in-the-contingent-worker-supplement.htm.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 67

Before committing to adding questions about additional work on the 

CWS, the BLS may wish to test how much additional work activity such a 

question is likely to uncover. This applies to new questions asked of both 

those reporting no work and those reporting a single job. The BLS could 

perform such a test by asking those in the outgoing CPS rotation groups—

month-in-sample (MIS) 4 and 8—about work activity not already reported 

in answering the basic CPS employment questions. Restricting the sample 

for this test to those in MIS4 and MIS8 would greatly reduce if not eliminate the risk of contaminating later CPS responses while still informing the 

decision about whether the work activity in question is significant enough 

to warrant asking about it in the CWS. If additional work activity turned 

out to be relatively unimportant among CPS respondents, that would create a solid justification for deciding not to ask about it on the CWS. If, on 

the other hand, consistent with evidence from other sources, a significant 

number of people report other work activity that the CPS is not currently 

capturing, that would create a compelling rationale for including questions 

about that work and the arrangements under which it occurs on the CWS.15

While the potential to disrupt the historical continuity of the responses to 

the basic CPS is a legitimate concern, it is critical for policy purposes that BLS 

endeavor to capture all market work activity. Moreover, as already noted, 

there are ways to eliminate or minimize any impacts that further probing 

in the CWS might have on CPS responses in subsequent waves. It is worth 

disrupting the CWS (and perhaps the CPS) in the ways recommended above, 

given that the survey addresses profound policy questions about modern 

employment and how people are piecing together their income. The CWS 

revision will set a standard for work in this area for a long time to come. 

3.3. CATEGORIZING WORK AND WORKERS

All six waves of the CWS measured the contingency of employment—

that is, whether a person’s job is temporary in nature—and selected types 

of AWAs, including independent contractors, temporary agency workers, 

on-call workers, day laborers, and contract company workers. For all 

but on-call workers, these AWAs are defined as being mutually exclusive. 

This section focuses on these mutually exclusive categories, which capture 

15One caveat to drawing conclusions based on questions asked in MIS4 and MIS8 is that 

possible month-in-sample bias may affect reports of employment in the CPS in those waves. 

For instance, Halpern-Manners and Warren (2012) found that there were significantly lower 

reports of having a second job among self-reports in the second month-in-sample than there 

were in the first month-in-sample, for every single first versus second month-in-sample comparison between January 2007 and July 2010. The finding holds even after accounting for 

changes in mode of interview (see their Figures 6 and 8). If month-in-sample bias is material, 

then the universe for the CWS questions should be everyone.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

68 MEASURING ALTERNATIVE WORK ARRANGEMENTS

instances where a worker is not an employee of the organization for whom 

he or she is performing work. 

The set of AWAs that follows distinguishes between those who are 

not employees (independent contractors) and those who are in an intermediated arrangement (temporary agency workers and contract company 

workers). In the latter, workers are employees of a temporary help agency 

or other type of company that contracts their services to other organizations. Day laborers, hired on a daily or very-short-term basis, most likely 

are independent contractors. On-demand platform work, captured only 

in the 2017 CWS, is a hybrid of these two types; while payments to these 

workers are mediated by the platform company, the workers are usually 

classified as independent contractors and so may be thought of as a subset 

of that category. 

It is important that a revised CWS continue to collect information 

on independent contractors, including platform workers, although the 

panel has some recommendations for modifying the questions that query 

respondents about these work arrangements. It is also important to collect 

information on temporary help workers and contract company workers, 

even though the value of surveying workers about such intermediated 

arrangements in the CWS is less clear. As discussed in the next section (3.4), 

rather than attempting to attach a label to on-call and other workers with 

unpredictable schedules, we recommend collecting information on these job 

characteristics, which would allow data users to categorize work arrangements as appropriate for their needs. 

Independent Contractors

As discussed in Chapter 2, there is strong policy and research interest in 

distinguishing between those who are W-2 employees and those in various 

self-employment or nonemployee arrangements. The latter are not covered 

by employment and labor laws, such as wage and hours laws and laws 

giving workers the right to form a union and collectively bargain. They 

generally are not covered by social insurance programs, such as unemployment insurance and workers’ compensation. Finally, they do not have access 

to benefits that many employers provide their employees, such as paid 

sick leave, health insurance, and retirement benefits. The large number of 

people in nonemployee work arrangements and the possible growth in these 

arrangements’ prevalence has raised concerns about the adequacy of social 

protections in the United States. It is therefore critical that the CWS try to 

distinguish between those who are W-2 employees and those in independent 

contractor and other self-employment arrangements. 

Among those identified as self-employed, the basic CPS differentiates 

only between the incorporated and the unincorporated self-employed. The 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 69

CWS also differentiates between those who are independent contractors, 

independent consultants, or freelance workers and other self-employed 

individuals. A challenge in household surveys in measuring self-employment 

and subcategories of self-employment such as independent contractors is 

that respondents may have quite different understandings of what these 

terms mean. For example, while some respondents may understand that 

self-employment means that they are not employees of an organization, 

others may understand self-employment to mean that they own and operate 

their own business. Those who work for an organization but are not a W-2 

employee may not think of themselves as self-employed, and in common 

parlance may still refer to themselves as employees. Similarly, usage of the 

term “independent contractor” may carry different connotations and vary 

across occupations. In some occupations, for instance, distinctions are made 

among nonemployees between independent contractors and subcontractors.

Idiosyncratic differences in the use and understanding of such terms may 

significantly affect how people respond to questions in household surveys 

about their independent contractor status.16

In the current CWS, respondents who identified both as self-employed 

and as employees in the main CPS are asked whether they are an “independent contractor, independent consultant, or freelance worker” on 

their main job. Those who identify as working for an organization in 

the main CPS (and hence are coded as employees) are also told that 

independent contractors, independent consultants, and freelance workers 

obtain customers on their own to provide a product or service. Although 

independent contractors should not be identified as employees in the CPS, 

recent research evidence provides compelling evidence that many likely 

are, which is consistent with the widespread confusion over these terms. 

Whereas the share in self-employment has not grown in the CPS, research 

using administrative data shows a sizable growth in the share of individuals with self-employment income as reported to the tax authorities 

and higher levels of self-employment than found in the CPS (Abraham et 

al., 2020; Abraham et al., forthcoming; Jackson, Looney, and Ramnath, 

2017; Katz and Krueger, 2019; Lim et al., 2019). Some of this reflects 

work activity that is not mentioned in household survey responses, but 

some of it reflects self-employment work activity that is miscoded as wage 

and salary work. 

One potential reason for the undercount of self-employment in the CPS 

is that the survey may be prone to misidentifying independent contractors 

as employees (Abraham, Hershbein, and Houseman, 2019). In the CPS, 

individuals who indicate that they did work for pay are asked: “Were you 

16Abraham, Hershbein, and Houseman (2019) provide a thorough discussion of definitional 

issues in measuring independent contracting. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

70 MEASURING ALTERNATIVE WORK ARRANGEMENTS

employed by government, by a private company, a nonprofit organization, 

or were you self-employed or [if applicable] working in the family business?” Individuals responding that they are employed by the government, 

a private company, or a nonprofit organization are coded as employees. It 

would be reasonable and accurate for a respondent working on a contract 

basis for a company or organization to report being employed by that 

entity, particularly if the term self-employment carries certain connotations, 

such as running one’s own business. 

In a Gallup survey module on contract work, Abraham, Hershbein, and 

Houseman (2019) found that a sizable share (about 10%) of Gallup respondents who reported being employed by an employer, and so were coded 

as employees, also indicated upon further probing that they were an independent contractor, independent consultant, or freelance worker. Linking 

tax records to data from the Annual Social and Economic (ASEC) supplement to the CPS for the period from 1996 through 2015, Abraham et 

al. (2020) and Abraham et al. (forthcoming) find substantial growth in 

self-employment in the tax data that is not reported in the CPS-ASEC. 

Their findings are similar to those from other research using administrative data. Consistent with the findings reported by Abraham, Hershbein, 

and Houseman (2019), about a third of this growth was accounted for by 

people who reported only employee work in the CPS-ASEC and only selfemployment work in the tax data. 

Given this evidence, a broad approach is needed for measuring independent contract work. Questions pertaining to independent contractor 

work in the CWS should be designed to capture individuals who (a) are not 

employees of an organization and (b) do not own or operate a business or 

have significant capital investment in their business. Currently, no definition 

of independent contractors, who are also commonly referred to as consultants or freelance workers, is provided for those identified as self-employed 

in the CWS. Many of those who are in informal work arrangements—such 

as providing child care, elder care, cleaning, or maintenance services directly 

to households or providing services through online platforms or mobile 

apps—also should be captured in the independent contractor category. 

Moreover, the definition of independent contractors given to those 

identified as wage and salary workers in the CWS—“someone who obtains 

customers on their own to provide a product or service”—may be misleading because this is not a defining characteristic of independent contractor 

work. Many who work as independent contractors do so primarily for one 

organization and are commonly termed “dependent” contractors to reflect 

that reliance on a single client. Individuals in this arrangement might not 

think of themselves as obtaining customers on their own in the same way 

as, say, a self-employed business owner might. Those who report being 

employed by an organization in the main CPS but say in the CWS that they 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 71

are independent contractors—between 1 and 2 percent of those identified as 

an employee in the main CPS—may be especially likely to work primarily 

for a single client. This may mean that the CWS data understate the share 

of CPS employees who are in fact independent contractors. We recommend 

removing the definition of independent contractors as people who obtain 

customers on their own from the question.

RECOMMENDATION 3.5: The CWS should continue to ask those 

identified both as self-employed and as employees in the main CPS 

about their status as independent contractors. A broad definition of 

independent contractor should be given in both questions, and the current definition of independent contractor used for those identified as 

wage and salary workers should be replaced. 

For those who are identified as self-employed in the main CPS, the goal 

of the question is to identify those who do not own or operate a business 

or who do not have a significant capital investment in their business. The 

goal of the question asked of those identified as wage and salary workers in 

the main CPS is to distinguish between W-2 employees and nonemployees; 

the measure for independent contractor work should include the types of 

informal work activities captured in the SHED and other recent surveys in 

which the individual is not an employee. 

RECOMMENDATION 3.6: Cognitive testing should, among other 

things, determine how well respondents distinguish between employee 

and nonemployee concepts and explore ways to improve the accuracy 

of responses. To this end, BLS might clarify for respondents that independent contractors are not employees of the organization or customers 

for whom they provide a good or service and/or do not have any taxes 

taken from their pay. 

The first step in testing is for BLS to evaluate how respondents 

understand the CWS questions about independent contracting, especially 

for proxy reports. Errors may arise, either because respondents do not 

understand the questions as written or because the nature of independent 

contracting or freelance work has changed over time and respondents cannot easily align their work into these categories. Even someone who has 

reported their work activity in the basic monthly CPS—someone who sells 

jewelry on Etsy and at the local flea market, for example—might not think 

of him- or herself as an “independent contractor” or “freelance worker.” 

As noted above, people who work on a nonemployee basis for a single firm 

may be an especially problematic group. Another possible source of error 

is interviewers who do not administer a question as intended. Initial work 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

72 MEASURING ALTERNATIVE WORK ARRANGEMENTS

on the administration of these questions in the 1995 CWS indicated that 

interviewers often changed the question wording during administration, 

especially in households with multiple adults (Polivka, 1996). All of these 

potential issues should be evaluated. 

For those identified as wage and salary workers in the main CPS, one 

option, tested by Abraham, Hershbein, and Houseman (2019), is to ask 

respondents if their employer withheld taxes from their pay. At a minimum, 

payroll taxes should be withheld for everyone who is a wage and salary 

worker, but firms do not withhold taxes from payments to independent 

contractors. BLS could perform cognitive testing on the approach used by 

Abraham, Hershbein, and Houseman as one way of distinguishing between 

employee and nonemployee work. 

Platform Workers (subset of independent contractors)

Work mediated by web platforms still represents a small percentage 

of independent contracting, but its rapid growth has raised the profile of 

policy issues that more generally concern independent contractors. As discussed in Chapter 2, some people engage in web-platform work to supplement their income, but others rely on it as their main source of income. 

This raises concerns about workers’ ability to access basic benefits such as 

medical care and retirement savings. Additionally, Internet intermediary 

companies have formalized many work arrangements previously considered informal, and there is some evidence that web- mediated options are 

displacing more traditional job arrangements. One example is Jitjatjo, a 

“human powered contingent labor platform and staffing marketplace” 

that seeks to intermediate between businesses in the service and hospitality 

industry (primarily restaurants) needing to hire on short notice and stopgap 

workers willing to step in.17 Another example is Pared, an app used by 

restaurants (including many high-end establishments) to make on-demand 

hires of chefs and other culinary professionals.18

Such developments have spillover effects on wages in employer-provided 

jobs. So, even if these platform companies account for only a small share 

of jobs, these new ways of engaging with workers can lead to outsized impacts 

in the broader labor market. For these and other reasons, BLS has prioritized 

improved measurement of web-platform work. As noted earlier, new questions introduced in the 2017 CWS were designed to capture work obtained 

through platforms and mobile apps where payment was coordinated by these 

17Available: https://www.jitjatjo.com/index.

18Available: https://www.washingtonpost.com/lifestyle/food/apps-have-turned-restaurantwork-into-a-gig-economy-hustle-heres-how-one-cook-chases-a-paycheck/2020/02/24/1f02ee5c54a8-11ea-9e47-59804be1dcfb_story.html.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 73

companies. However, the new questions did not work as intended and resulted 

in unrealistically high estimates of the number engaged in this type of work. 

Following a detailed examination of the data, the BLS recoded many of the 

answers to these questions that were deemed likely to have been wrong. 

RECOMMENDATION 3.7: The CWS should continue to ask about 

work mediated by platforms/apps. These questions will require extensive modification and further testing. 

Additionally, a decision must be made about what kinds of webmediated activity to consider within the scope of the CWS. One key distinction that is often drawn is that between “work-based” income and 

income derived from a combination of work and capital. This distinction 

is somewhat blurry, however, as many web-mediated jobs combine capital 

and labor inputs. An illustrative example, described in Chapter 2, is renting 

out rooms through Airbnb, which entails both labor and nonlabor inputs. 

Although renting out an Airbnb home is typically thought of as a capitalbased income-generating activity, a person operating several properties may 

spend substantial time in the enterprise. How far apart Airbnb and Uber 

are on the labor/capital continuum is an open question. 

RECOMMENDATION 3.8: For purposes of measuring web-platform 

work, BLS should test the option of not making a capital/labor distinction. The survey could simply ask self-identified platform workers 

which company (or companies) they work with, and then allow the 

data to be sorted depending on the question at hand. If the concern is 

over what motivates people’s efforts to generate income, the distinction 

regarding the extent to which income is a return on labor or capital 

may not be crucial.

Another point is that respondents may have difficulty differentiating 

between platform work that is capital-based and that which is labor-based, 

or where on the spectrum their activity falls. An advantage of simply including all income-generating activities, whether they are slightly more laborbased (Uber) or slightly more capital-based (Airbnb), is that doing so avoids 

requiring respondents to make this difficult, subjective call.

Another distinction that may be important to make in order to meet 

future measurement needs is between work that is provider/client-based 

and work that is mediated through another company. In some cases, the 

two arrangements may involve an almost identical type of work. Consider, 

for example, a person who walks and boards dogs through his or her own 

neighborhood business, dealing directly with customers, while another 

person provides the same services but does so through the Rover.com app. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

74 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Again, the distinction is between serving a customer (final demand) and 

working through an intermediary business such as a platform company. 

The CWS should aim to provide data to help researchers and policy makers 

understand where—in what sectors, locations, and so on—platform work 

is expanding and how this work may be changing labor market patterns.

Finally, given the difficulty that respondents had in understanding questions pertaining to platform work on the 2017 CWS, these questions should 

undergo much cognitive testing. Having the name of the platform company 

will potentially be valuable for conducting a quality check on data from 

these questions in a future survey. 

Temporary Help Agency Employment and Contract Company Work

Some questions in the current CWS have proven less useful than others, 

either because evidence indicates the quality of the resultant data is poor 

or because for other reasons the data are little used. Such cases present 

an opportunity to create survey space by streamlining parts of the survey. 

The temporary help agency component of the survey is one such candidate. While tracking temporary help agency employment is important, the 

incidence measured in the CWS is well below that indicated by employer 

surveys and administrative data (Polivka, 1996). Respondents appear to 

confuse their employer, which is the temporary help agency, with the client 

for whom they are performing work. 

Another candidate for CWS streamlining pertains to information on 

contract company workers—those who perform work for a client on or 

off the client’s worksite. Although information about contract work is 

needed, household surveys may not be the best vehicle for collecting it. 

Partly because BLS determined that respondents cannot reliably report on 

the contract arrangements of their employer, the CWS focuses on measuring 

a narrow subset of contract company work: individuals who work primarily for one client company at the client’s worksite. This narrow definition 

misses a lot of contract work that is relevant for policy, such as contract 

workers who work remotely. Further, BLS reports that its contract company 

worker measure is little used. For these reasons, measuring this category of 

AWA is not a comparative advantage of the CWS.

RECOMMENDATION 3.9: BLS should consider dropping questions 

on temporary help agency employment and on contract company work 

from the CWS to make room for other, higher-priority questions. 

If the BLS opts to continue to ask about temporary help agency employment in a future CWS, it should consider revising the question wording to 

use terms like staffing agency in lieu of, or in addition to, temporary help 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 75

agency. The industry has long used the terms staffing firm and staffing 

agency instead of temporary help agency; use of the older term may contribute to the undercount of these workers in the CWS. 

Data supplied by businesses are largely complementary to those 

captured in household surveys and can fill in some information needs. 

Establishment- and firm-level surveys are an underexplored source of data 

on alternative work arrangements, especially subcontracted work, that have 

the potential to yield vital information about the prevalence and nature of 

firms’ contracting-out activities. 

On-call Workers and Day Laborers

The current version of the CWS asks respondents if they are on-call 

workers. A key attribute of both on-call and day laborer work is that hours 

are unpredictable—the person works only when he or she is called in or 

someone offers them work. The predictability of hours is an important 

dimension of a person’s work activity that the CWS should ask about. As 

described in the next section, however, the panel recommends that this be 

done by asking directly about work scheduling and the predictability of 

hours, within the context of inquiring more generally about the characteristic of the person’s job or jobs, as opposed to asking whether the person 

identifies as an on-call worker or day laborer.19 Depending on the arrangement, a day laborer also may be identified through questions pertaining to 

independent contractors or temporary help workers.

3.4. INSECURITY IN HOURS, JOBS, AND EARNINGS

Capturing the security of workers’ jobs has been a primary focus of 

the CWS over its history. The concept of contingency in the CWS measures 

whether a worker’s job is temporary because the position is expected to 

last for a limited time. This concept of contingency captures job insecurity 

that, in cases where loss of the job results in employment gaps, may lead to 

19Early testing of the CWS indicated that the questions for on-call workers, contract workers, 

and independent contractors/consultants/free-lance workers were “too long,” resulting in a 

notable number of interruptions and, in some cases, failure of interviewers to read definitions 

to the respondents (BLS, 1995). In the current questionnaire, the information defining these 

job categories is in parentheses, presumably indicating that it is not to be read to persons in 

the household beyond the first respondent. This questionnaire structure is notably difficult 

for interviewers to deal with, however, as each one must decide how to implement the parenthetical information. This may lead to increased interviewer-driven variation in answers and 

potentially different distributions of answers for those who are exposed versus not exposed 

to information in the parenthetical statements (Dykema et al., 2016; Olson, Smyth, and 

Cochran, 2018).
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

76 MEASURING ALTERNATIVE WORK ARRANGEMENTS

employment and earnings instability. Job insecurity is one factor that may 

result in earnings insecurity. 

Even if the job itself is not temporary, the hours and hence a worker’s 

earnings may be variable. In addition to on-call work, other types of scheduling practices also may be associated with unpredictable hours and earnings insecurity. While the alternative work arrangements described in the 

preceding section are mutually exclusive, job contingency and unpredictable 

schedules are characteristics of jobs that may be present in all or most work 

arrangements, including when workers are employees of the organization 

for which they perform work. 

Schedule Variability and Predictability

As noted above, the CWS asks wage and salary workers whether they 

work on an on-call basis or whether they work as day laborers. These forms 

of on-demand work are associated with variable hours and unpredictable 

schedules that may result in earnings insecurity. 

RECOMMENDATION 3.10: As opposed to the current approach 

of classifying workers into the categories of on-call workers or day 

laborers, the CWS should focus on simply describing the characteristics 

of these and other work arrangements with variable hours. 

Subsequently, analysts can sort workers by scheduling arrangement, 

but respondents do not need to be asked directly to label the category into 

which their employment falls. This job-characteristics-based approach will 

mitigate confusion over terminology and hence potential misreporting on 

the survey. For example, an individual may not think of herself as being an 

“on-call worker” even if she must report to work when called.

While the current version of the CWS only asks about hours variability and uncertainty as they pertain to on-call and day laborer work, 

because they represent an issue of growing importance variability in hours 

and scheduling uncertainty need to be measured more comprehensively. 

As noted in Chapter 2, the widespread adoption of scheduling algorithms 

in the retail sector and other services industries has meant that firms are 

better able to match workers’ hours to the company’s needs. The resulting variability and unpredictability in work hours shifts scheduling and 

income risk from the firm onto the workers. Even if the total number of 

hours a worker is offered remains constant, if a worker’s schedule is so 

erratic that she does not know when she will have to come in to work 

that in itself can take a toll—for example, by making it difficult to arrange 

child care. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 77

Research on work scheduling issues20 provides ample justification for 

adding question about scheduling in the CWS. National surveys are typically limited in capturing this dimension of work; since question wording is 

often about “usual or typical hours,” by design, the resultant data smooth 

rather than reveal variations in work hours. 

By contrast, some specialized surveys have allowed researchers to estimate the magnitude and direction of fluctuations in weekly work hours. 

For example, looking at scheduling variability in the National Longitudinal 

Survey, Lambert and colleagues (2014) find that 83 percent of respondents 

age 26 to 32 who are hourly part-time workers give a different number for 

the greatest and fewest hours they worked in a week. The average difference between those two is 13 hours, which amounts to 37 percent of their 

reported usual hours. For these estimates, the researchers developed a survey, the Work Scheduling Study, which asks: “In the last month (past three 

months), what is the greatest number of hours you’ve worked in a week 

at this job? Please consider all hours, including any extra hours, overtime, 

work you did at home, and so forth” and “In the last month (past three 

months), what is the fewest number of hours you’ve worked in a week at 

this job? . . . Please consider all hours, including any extra hours, overtime, 

work you did at home for your job, and time you spent on work that may 

not have been directly billable or compensated.” These analyses provide 

models of how to move forward on measuring work schedule variability.21

High schedule variability often brings with it a lack of predictability, 

which can create additional problems for a household and should therefore 

be tracked. Using data from the SHED and the 2016 General Social Survey 

(GSS),22 Fugiel and Lambert (2019) find that the number of workers reporting that they receive less than 7 days’ notice regarding their work schedule 

is 15 percent. For those receiving less than a day’s notice, the figures for the 

two surveys are 6.4 percent (GSS) and 5.1 percent (SHED). 

Although surveys such as the SHED and the GSS have measured hours 

or schedule variability, they rely on small samples. Given the prevalence 

of erratic and unpredictable worker schedules, this aspect of employment 

and earnings instability should be measured with a much larger, nationally 

representative survey. 

20See, for example, Henley and Lambert (2014) and Schneider and Harknett (2019). Another 

article by Miller (2019), “How Unpredictable Work Hours Turn Families Upside Down,” provides case studies.

21Lambert et al. (2019) provides a full set of statistics on the prevalence of schedule instability, 

unpredictability and lack of schedule control using data from the General Social Survey. 

22Available: https://gss.norc.org/.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

78 MEASURING ALTERNATIVE WORK ARRANGEMENTS

RECOMMENDATION 3.11: For employees, the CWS should inquire 

into the following aspects of schedules and hours:

• Usual hours worked and hours worked last week (on primary and 

secondary jobs);

• Schedule autonomy—who determines the schedule, the employer 

or the worker?

• Schedule predictability—whether the schedule is generally the same 

from week-to-week or, if it varies, how much notice the worker 

typically receives;

• The amount by which weekly hours vary; and

• Whether a worker must be available if called (here, BLS can model 

its questions on those from other surveys where testing on similar 

questions has already been done). 

In addition to questions attempting to get at workers’ lack of control 

over when and how much they work, it may also be worth asking about 

more favorable work arrangements, such as whether the worker is allowed 

flexibility in his or her hours. 

As stated in Recommendation 3-10, with this kind of detailed information about workers’ schedules it should not be necessary to ask respondents 

to self-identify their work category. Appropriately identified characteristics 

capture the aspects of being, say, an on-call worker that are most salient to 

workers’ well-being and to the policies designed to safeguard it. Likewise, 

“on-call” workers may have regular work, or they may not be called in to 

work very often or very predictably. Some workers, for example those in 

retail, may be called in to work and then given no hours. The key policy 

question is, “which (primary) jobs are providing insufficient income, or 

highly unpredictable income?” Including a set of scheduling questions 

(restricted to people working for employers)23 focused on hours and earnings variability at the core of the new CWS would get at the kind of variability that is likely a common motivation for pursuing a second job.24

A number of surveys offer options for question wording related to 

characteristics of jobs rather than labels of AWAs. For example, the 2017 

American Time Use Survey Annual Leave Module asked respondents about 

the availability of a flexible work schedule, since sometimes an inconsistent—though probably not unpredictable—work schedule is what a worker 

23Ideally, in order to generate information on how schedule instability and unpredictability 

vary across today’s employment arrangements, one would like to measure scheduling patterns 

of independent workers as well. Asking nonemployee workers about scheduling and hours, 

however, would require another battery of questions—an expansion of the CWS that, while 

desirable, may not be feasible. 

24Asking about variability in hours (and not earnings) may be sufficient for the wage and 

salary group.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 79

needs or prefers. The module also asked about the reasons for being in a 

flexible work schedule, about days usually worked (including an “it varies” 

answer), and about working from home. Cognitive testing revealed issues 

with respondents’ answering that yielded changes in the question wording 

for the implemented module (Mockovak and Kaplan, 2015).

Contingency

The current CWS focuses on measuring contingency—that is, whether 

the job is temporary in nature. Indeed, concerns that temporary, or contingent, jobs were a growing share of employment motivated the initial 

development of the CWS in the 1990s. A high percentage of questions in 

the current version of the CWS are devoted to measuring the contingency 

of work, and the BLS publishes three measures of contingency based on 

the survey results. In the May 2017 CWS, BLS reported that 5.9 million 

people, or 3.8 percent of the employed, held contingent jobs, according to 

the broadest measure of contingency.25

Over its history, the CWS has uncovered no growth trend in contingent 

jobs. Instead, there has been a small but steady decline over time in the 

estimated percentage of the employed holding contingent jobs, and BLS’s 

measures of contingency have not gained currency among policy makers 

and researchers (see, for example, the wide-ranging definitions of contingency used in U.S. Government Accountability Office, 2015). Moreover, 

the BLS definitions sometimes relied on people’s expectations about future 

employment, which BLS’s own cognitive testing found to be problematic. 

Respondents struggled to answer how long they expected their job (or the 

job held by another household member) to last, which resulted in data 

that were likely of low quality. Quality assessment research on the CWS 

indicated that respondents did not know how to answer the questions, 

“How much longer do you expect to work in your current job/to be selfemployed?” and “Do you think it will be more than a year?,” resulting in 

nonspecific answers, such as, “Well, I don’t know” or “It depends on the 

economy and GM’s future hiring plans” (BLS, 1995, p. 5). In addition, 

there was notable interviewer variation in addressing these difficulties. 

Although there are options to select “something else,” including “Until I 

retire” or “As long as I want,” interviewers did not appear to select these 

to summarize respondents’ answers very often.

In the U.S. economy, many jobs are temporary in some sense. The 

country has an “employment at will” doctrine such that, except for certain 

reasons and protected classes, workers can be fired by their employer at any 

25Available: https://www.bls.gov/opub/ted/2018/3-point-8-percent-of-workers-were-contingentin-may-2017.htm?view_full.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

80 MEASURING ALTERNATIVE WORK ARRANGEMENTS

time for any reason. Unlike many other economically advanced countries, 

the United States does not have a strong legal system of employment protections. Key exceptions are that employers cannot fire workers on the basis of 

gender, religion, ethnicity or race, or age. In this employment environment, 

many workers might view their jobs as temporary. 

Seasonal work may or may not be considered temporary by respondents, especially if they return to the job each season. Similarly, many 

people work from project to project and, while projects end, people may 

be reasonably assured of a pipeline of work going forward. It is therefore 

unclear (including to respondents) what the concept of temporary means 

in the modern labor market. These concerns argue for deprioritizing the 

contingency questions in the CWS. 

RECOMMENDATION 3.12: While the temporary nature of some jobs 

is a key characteristic that should continue to be measured in future 

CWS surveys, the number of questions on contingency should be pared 

back and the questions that remain should be simplified.

In summary, the panel recommends against classifying workers as oncall workers or day laborers and instead recommends expanding questioning about job characteristics to include a broader set of arrangements 

associated with unpredictable work schedules. Some questions pertaining 

to contingent work should be maintained, although the panel recommends 

paring and simplifying these questions.

3.5. OTHER INFORMATION NEEDED FOR 

UNDERSTANDING ALTERNATIVE WORK ARRANGEMENTS 

AND THEIR IMPLICATIONS FOR WORKERS 

Key goals of the CWS involve not only measuring the number of people 

in contingent and alternative work arrangements but also facilitating an 

understanding of the relationship between specific work arrangements, 

worker characteristics, and worker outcomes. Because the CWS is a supplement to the CPS, detailed information about the demographic characteristics of respondents is available. The CWS adds measures of key worker 

outcomes that are not collected in the main CPS: earnings26 and benefits 

as well as indicators of individuals’ preference for or satisfaction with their 

work arrangements. The CWS also collects information on workers’ job 

histories and their transitions into and out of selected work arrangements. 

26The main CPS collects information on earnings for the outgoing rotation groups (MIS4 

and MIS8). The CWS collects information on earnings for other individuals, primarily for 

those who indicate being in a contingent or alternative work arrangement. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 81

Wages and Benefits

The linkage between people’s income and their well-being is clear; 

for this reason, it is essential to include questions about earnings in the 

CPS/CWS. As discussed in Chapter 2, researchers and policy makers have 

been keen to understand how changing work arrangements, including the 

expansion of AWAs, may relate to the flat earnings growth experienced by 

workers over recent decades. The CWS collects information on earnings 

from those identified as being in a contingent or alternative work arrangement and selected other workers. These data may be supplemented with 

earnings data collected in the main CPS for those in the outgoing rotation 

groups (MIS4 and MIS8). So that the earnings of those in alternative work 

arrangements may be compared to those in traditional arrangements, it is 

important that the sample for the latter be representative of that population; the BLS should provide weights appropriate for use in analyses of 

earnings, including analyses that compare the earnings of those in alternative work arrangements with the earnings of other workers. 

The interaction of an employer-delivered worker benefits system and 

emerging AWAs with limited or no access to employer-provided retirement 

plans, medical care plans, and other benefits is also of great concern. The 

possible link between contingent and nonstandard work, wages, and access 

to critical benefits such as health insurance and retirement benefits is of strong 

policy interest. The onset of a global pandemic has underscored the need for 

policy makers to be more aware of the economic vulnerabilities present in 

the labor market. The CWS will continue to shed light on these trends since 

it includes questions that ask about wages and benefits. Additional information will be obtained by asking about the wages and hours associated with 

respondents’ second jobs (as proposed in recommendations 3.2 and 3.3). 

Capturing net earnings—gross revenues less costs—is important for 

independent contractors. In a study of earnings from driving for Uber and 

Lyft in the Denver area, for example, Henao and Marshall (2019) find that, 

whereas gross hourly earnings averaged $15.87, earnings less costs ranged 

from $5.72 to $10.46, and most drivers earned less than the minimum 

wage. For independent contractors, asking about earnings on an annual 

basis may be most practical, because expenses tend to accrue unevenly 

over the course of the year. Questions about earnings posed to independent 

contractors should clearly instruct them to report net rather than gross 

earnings, to the best of their ability. 

Job Satisfaction and Reasons for Choosing a Work Arrangement

The CWS includes a set of questions about workers’ preferences for 

specific job characteristics in Section 2, “Worker Satisfaction with their 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

82 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Current Employment Arrangement.” The questionnaire is structured 

such that workers with particular arrangements—temporary help agency 

workers, on-call workers, day laborers, and self-employed/independent 

contractors—are first asked a tailored question about whether they would 

prefer a job with a different arrangement (e.g., on-call workers are asked 

if they would prefer a job with regularly scheduled hours). Next, workers 

are asked for their main and secondary reasons (if their main reason is 

“for the money”) for working in their current job arrangement. Temporary 

workers are also asked if they would prefer a job where they could stay as 

long as they want. These questions for different categories are summarized 

in Table 3-1.

Measuring the degree to which workers are satisfied with AWAs is 

important for understanding the extent to which people take alternative 

jobs by choice or out of necessity. It is unclear, however, how the current 

set of job preference questions should be interpreted. It can be difficult for 

respondents to specify preferences unless a set of tradeoffs is provided. For 

example, if a survey interviewer asked a person if they “would prefer to not 

work most nights and weekends?”, many would reply, “Yes.” But it also 

may be the case that most of these respondents would not want to change 

careers, so the more informative answer is no, given the tradeoffs (Mas 

and Pallais, 2017). In the context of the CWS, most respondents who are 

in on-call arrangements report that they would prefer regularly scheduled 

hours. Yet, these individuals may nonetheless prefer this arrangement if, for 

example, it pays a relatively high wage. 

Moreover, the wording of the preference questions varies across contingent and alternative work arrangements, and job preference questions are 

not asked of those in traditional wage and salary arrangements. To provide 

a basis for comparison, it is desirable to use the same question wording to 

measure how workers across various work arrangements view their jobs. 

Instead of asking the current set of job preference questions for workers in 

selected arrangements, the CWS could ask all respondents a question about 

their overall satisfaction with their job. For example, the General Social 

Survey’s Quality of Working Life Module asks, “All things considered, how 

satisfied are you with your (main) job?”27

The existing line of questions on the reasons individuals work in alternative arrangements provides potentially valuable information, but the 

fact that they are “field coded” makes these questions problematic as well. 

For a field-coded question, the respondent is asked to provide a narrative 

response that the interviewer codes using a set of predefined, categorical 

options. A number of studies indicate interviewers vary in their ability to 

27Available: http://gss.norc.org/Documents/codebook/QWL%20Codebook.pdf.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 83

code these types of responses accurately (see review in West and Blom, 

2016). For example, Smyth and Olson (2020) find that in one national 

telephone survey, interviewers accurately coded only 49 percent of answers 

into nominal categories. The challenge of accurately classifying respondents’ narrative responses is likely compounded when the categories are not 

comprehensive (when they do not include the range of possible categories) 

or when the labels for the categories are difficult for interviewers to use. 

Cognitive testing of field-coded questions can help ensure that the labels for 

the categories included in the questionnaire accurately reflect the range of 

likely responses and use appropriate language. An alternative to field coding 

the questions is to narrow the options to a short list of possible reasons and 

ask the respondent to select the most important. 

As discussed throughout this report, it is also important to know 

why people are engaging in multiple jobs—including why they are doing 

web-mediated work on the side. Questions on job satisfaction and on the 

motivation of individuals to work a second job/work activity would be 

extremely useful for understanding people’s work patterns.

TABLE 3-1 Structure of CWS Job Preference Question

Temporary 

Workers

Temporary 

Agency 

Workers

On-call 

Workers Day Laborer

Self-employed/

Independent 

Contractor

Prefer job that 

is permanent 

rather than 

temporary

Prefer job with 

different type 

of employer

Prefer job 

with regularly 

scheduled 

hours

Prefer job 

with regularly 

scheduled 

hours

Prefer to work 

for someone

Main reason 

for having 

temporary job

Main reason 

work for 

temporary help 

agency

Main reason 

for being an 

on-call worker

Main reason 

for being a day 

laborer

Main reason 

for being selfemployed /

independent 

contractor

Main reason 

other than “for 

the money”

Main reason 

other than “for 

the money”

Main reason 

other than “for 

the money”

Main reason 

other than “for 

the money”

Main reason 

other than “for 

the money”

Prefer job 

where could 

stay as long as 

wished

SOURCE: Current Population Survey (2017). Available: https://www2.census.gov/programssurveys/cps/techdocs/cpsmay17.pdf.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

84 MEASURING ALTERNATIVE WORK ARRANGEMENTS

RECOMMENDATION 3.13: BLS should ask questions on job satisfaction for all workers in lieu of asking job preference questions for 

selected workers. The BLS should continue to ask about reasons 

for working in selected alternative work arrangements, but it should 

consider moving away from field coding the responses and instead provide a preset list of reasons and ask respondents to identify the most 

important. In addition, for those with a second job or work activity, 

BLS should ask about their motivations for holding multiple jobs. 

Job History and Work Transitions

The CWS asks a series of questions about people’s history in their 

main job. The primary item collected concerns job tenure, with the question wording differing according to the reported employment arrangement. 

Information on job tenure can be useful for some research and policy purposes. If retained in a future CWS, the structure of the questions could be 

simplified to ask about tenure on the primary and, if applicable, secondary 

job, regardless of whether the job is in self-employment or as an employee. 

One could make an argument for dropping the job tenure questions. 

Early cognitive work on the CWS indicated that the questions about how 

long an individual has worked for their current or former employer yielded 

highly imprecise answers from respondents: More than 35 percent of 

respondents answered with a qualified answer, or with an answer that did 

not match the question task (inadequate), or else said they did not know. 

Most of these imprecise answers were given when this retrospective question was proxy-reported (discussed further below).28 On balance, however, 

even if respondents find it difficult to give a precise answer to the job tenure 

question, the responses are likely to contain valuable information.

Asking about other aspects of respondents’ job histories, however, 

seems both more problematic and less likely to be valuable. The current version of the CWS asks those who report working for an employer 

whether they previously worked for the employer under a different work 

arrangement. Although this information potentially provides interesting 

background, the question is retrospective in nature and subject to recall 

bias; data quality is likely to be particularly poor for proxies. For this 

reason, and because the information collected in prior years has been 

rarely used, these questions are candidates for dropping in future iterations of the CWS. 

Another set of questions in the CWS asks respondents about transitions 

into their current employment arrangement; specifically, what they or other 

household members were doing prior to becoming an independent contrac28Quality Assessment Research on the CWS, 1995, p. 8.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF THE CONTINGENT WORKER SUPPLEMENT 85

tor, a temporary agency worker, or an on-call worker or contract company 

worker. These questions also are likely to be subject to recall bias and have 

been little used, and thus are candidates for dropping as well. 

An additional section of the CWS asks respondents in AWAs or 

contingent/temporary jobs if they have looked for other types of work in 

the last couple of months (since the beginning of December for the CWSs 

conducted in February and since the beginning of March for the May 2017 

CWS). If they answer yes, respondents are asked for details on their job 

search. Searching for another type of job may be a good indicator that 

workers in alternative or temporary arrangements are dissatisfied with the 

job. The line of questioning in this section, however, is not a high priority, and BLS should consider dropping these questions as well. Also, since 

only the people in AWAs are asked these questions, there is no benchmark 

against which to compare their responses. One could imagine that it would 

be useful to know whether the share of people engaged in on-the-job job 

searching is higher among those in AWAs than among those in other types 

of jobs. Perhaps this could be asked without then going into detail about 

exactly how they had searched.

RECOMMENDATION 3.14: BLS should consider dropping questions 

on respondents’ job history (except, possibly, those concerning job 

tenure), on their transitions into their current employment arrangements, and on whether they have looked for employment in another 

type of job.

Researchers have effectively exploited the longitudinal structure of the 

CPS to study transitions into and out of the contingent and alternative work 

arrangements (Addison and Surfield, 2006, 2009; Farber, 1999; Houseman 

and Polivka, 2000; Katz and Krueger, 2017). In general, as discussed in 

Chapter 4, there are panel datasets that are better at characterizing people’s 

job histories. Also, every 2 years, BLS fields a Job Tenure Supplement of the 

CPS (also known as the Employee Tenure and Occupational Mobility Supplement) that includes questions about respondents’ type of work, industry, 

and occupation from 1 year earlier and on how long respondents have 

worked for their current employer.29 This supplement, therefore, duplicates 

coverage on some aspects of job history. Hyatt and Spletzer (2016) use these 

data to show the distribution of jobs in terms of duration held. Likewise, 

the CPS Displaced Workers and Job Tenure Supplement may provide a 

home for some question areas. The stated goal of that supplement is to 

“measure the severity of job displacements and assess employment stability 

29Available: https://cps.ipums.org/cps/jt_sample_notes.shtml.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

86 MEASURING ALTERNATIVE WORK ARRANGEMENTS

during a period of downsizing at many firms, and increased use of temporary and contract labor.”30

In summary, in addition to basic information on wages and benefits, 

BLS should ask CWS respondents a question on job satisfaction. The 

question should be asked of all workers, including those who do not fall 

into any alternative work, contingent work, or unpredictable scheduling 

arrangement. Understanding the degree to which workers are satisfied with 

(or prefer) their arrangement is important, but a comparison is needed to 

assess whether workers in various alternative arrangements are more or 

less satisfied than those in regular employment. Other surveys could be 

consulted to guide question wording. Questions about main and secondary 

reasons for having a job would be retained but revised as appropriate for 

the work characteristic. Questions on respondents’ job history and employment transitions could be eliminated or cut back to create survey space for 

the new questions.

30Available: https://catalog.data.gov/dataset/current-population-survey-displaced-workersjobtenure-supplement.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

No single source can meet all demands for data needed to describe, 

monitor, and analyze alternative work arrangements (AWAs) in the U.S. 

labor market. Chapter 3 cited selected evidence, based on a wide range of 

data sources, to support recommendations for designing future iterations 

of the Contingent Worker Supplement (CWS). In this closing chapter, we 

give a brief overview of how other data sources have added to our understanding of the prevalence and characteristics of AWAs and the workers 

who engage in them—sometimes in ways that would not be possible or 

practical for a Current Population Survey (CPS) supplement. 

The range of other data sources from which insights can be drawn 

includes household and business surveys, government administrative 

records, and commercial data. In some cases, these data sources allow 

researchers to measure dimensions of AWAs that are beyond the scope of 

the CWS, such as the relationship between work arrangements and health 

outcomes. In other cases, data sources such as administrative and commercial data may allow more accurate or detailed measurement of some aspects 

of AWAs, such as the prevalence of some forms of on-demand platforms. 

Over the long term, there may be potential for linking the CWS with 

other data sources to enhance our understanding of AWAs. Continued 

exploration of this broader ecosystem of data sources will be an important 

strategy if we are to generate the most comprehensive statistical information about AWAs possible given budgetary constraints.

4

The Role of Other Data Sources 

in Measuring Alternative 

Work Arrangements

87
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

88 MEASURING ALTERNATIVE WORK ARRANGEMENTS

4.1. OTHER HOUSEHOLD SURVEYS

Chapter 3 already identified specific questions from non-CWS surveys 

that could be adapted for the CWS or at least provide insights into how 

to improve the CWS. Comparing results based on data from different 

household surveys can generate insights into the ways definitions, question wording, and respondent interpretations may affect estimates. In this 

section, we provide some examples of household surveys that can inform 

research on AWAs as well as others that, while focused on topics largely 

beyond the scope of the CWS, can complement our understanding of the 

nature of work. The goal here is to illustrate the importance to research 

and policy of being able to draw from multiple data sources; it is not to 

comprehensively catalog the data that could be used for this purpose. 

For example, although worker safety is of significant policy interest 

because of its direct link to job quality and worker well-being, the CWS 

is not positioned to collect data on this outcome. One instrument that 

provides rich information on workplace safety is the Occupational Health 

Supplement to the National Health Interview Survey (NHIS), a major 

data collection program of the National Center for Health Statistics of 

the Centers for Disease Control and Prevention (CDC). This supplement, 

which so far has been fielded in 1988, 2010, and 2015, generates evidence 

of the impact of work schedules on health, among other things. The most 

obvious effects are on sleep quality and quantity, which in turn are linked 

to a wide range of outcomes. In addition, impacts on exercise, diet, smoking, substance use, and work-life balance and conflict are also important 

considerations. An example of a finding from this survey is the distinctly 

higher injury rates found among temporary help agency workers relative 

to direct-hire employees; after adjusting for occupational differences, the 

injury rates of temp agency workers have been estimated to be about twice 

as high. Temp agency workers actually tend to have less frequent exposure 

to workplace health and safety hazards, but on average they also have less 

safety training and less experience for the jobs to which they are assigned 

(Fabiano et al., 2008).1

Another reason data sources beyond the CWS are needed is that some 

research questions require longitudinal estimates. Longitudinal datasets 

are needed, for example, to accurately measure people’s transitions into 

and out of different kinds of work, which is important for understanding 

the implications of these work arrangements and the underlying reasons 

people engage in them. Despite the strengths of longitudinal analysis, the 

opportunity to employ it is limited in the CPS. Household members are 

1See, also, the Appendix B summary of a presentation to the panel by Tim Bushnell and Toni 

Alterman of the National Institute for Occupational Safety and Health, who covered this issue.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF OTHER DATA SOURCES 89

observed for only 8 months over a 16-month period. Although the CWS 

has asked retrospective questions about workers’ entry into and exit from 

AWAs, as discussed in Chapter 3, there are concerns about the ability of 

respondents to answer such questions accurately. For data that span longer 

time periods, researchers typically rely on longitudinal surveys, such as the 

National Longitudinal Surveys (NLS), which are sponsored by the BLS.

The NLS have gathered information at regular time intervals on the 

labor market experiences and other significant life events of several nationally representative cohorts of men and women. For the past four decades, 

the NLS79 has collected labor force information for a cohort of individuals 

who were ages 14 to 22 when they were first surveyed in 1979. These individuals, currently ages 54 to 62, were interviewed annually through 1994 

and have been interviewed biennially since then.2 The NLS97 has collected 

labor force information since 1997 for a cohort currently ages 34 to 39; this 

group, containing individuals who were ages 14 to 22 when they were first 

surveyed, was interviewed annually through 2011 and has been interviewed 

biennially since then.3

From the beginning, the NLS interviews have attempted to identify 

whether workers are self-employed. The precise question sequence has varied 

somewhat over time, but since 2006 in the NLS97, if workers do not say they 

are self-employed, they are asked if they are independent contractors, freelancers, or independent consultants. Wage and salary workers who are not 

independent contractors, freelancers, or independent consultants are asked 

if they are temporary help workers, on-call workers, or contract company 

workers (with questions akin to those in the CWS). Similar changes were 

made beginning in 2002 in the NLS79 to better identify workers who are not 

in traditional wage and salary jobs.4 The longitudinal structure of the survey 

makes it possible for researchers to analyze transitions into and out of different employment arrangements—for example, when studying topics such as 

determinants of women’s entry into self employment (Taniguchi, 2002) or the 

“relative importance of family financial and human capital in the transition 

into self-employment” (Dunn and Holtz-Eakin, 2000).

2Available: https://www.bls.gov/nls/nlsy79.htm.

3Available: https://www.bls.gov/nls/nlsy97.htm.

4Changes included a clarification of what defines self-employment: “On the basis of answers 

to the job classification questions, the respondent is classified as self-employed if he or she 

owned at least 50 percent of the business, was the chief executive officer or principal managing 

partner of the business, or was supposed to file a form SE for federal income taxes. Respondents also are classified as self-employed if they identify themselves as independent contractors, 

independent consultants, or freelancers. A job is classified as nontraditional employment if the 

respondent is paid by a temp employment agency.” Available: https://www.nlsinfo.org/content/

cohorts/nlsy79/topical-guide/employment/class-worker.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

90 MEASURING ALTERNATIVE WORK ARRANGEMENTS

The Survey of Income and Program Participation (SIPP), the statistical 

system’s premier source of information on individuals participating in government assistance programs, is another example of a dataset that allows 

career histories to be followed—something that, again, is largely outside the 

scope of the CWS. Beginning in 2014, the interview structure of the SIPP 

was changed so that households were now to be interviewed annually for 

4 consecutive years. 

The SIPP asks several questions of those who identify as employed 

and, in particular, collects information about what might be considered 

“informal” work. The 2014 SIPP asks people who reported performing 

work for pay the following: “Was that for an employer, self-employed or 

did you have some other arrangement? Other arrangements include odd 

jobs, on-call work, day labor, one-time jobs and informal arrangements 

like babysitting, lawn mowing or leaf raking for neighbors.” Answers are 

recorded as self-employed, employee, or other arrangement. Drawbacks 

to this question include its 1-year reference period, which again is likely 

to result in recall error, as well as the lack of detail regarding both selfemployment and “other” arrangements. 

A final example of a complementary household survey data source is the 

Quality of Worklife module, included in the 2002, 2006, 2010, and 2014 

editions of the General Social Survey (GSS). The GSS is a biennial, nationally 

representative, personal interview survey of U.S. households conducted by 

the National Opinion Research Center and funded by the National Science 

Foundation. In addition to questions about earnings and benefits, the GSS 

module asks respondents how often they are allowed to change schedules 

and how often they are allowed to change their starting and quitting times 

on a daily basis.5 As discussed in Henley and Lambert (2014),6 the GSS also 

includes questions about unpredictable and unstable scheduling. Instead 

of asking about usual hours, the GSS asks how many hours respondents 

worked during the week prior to the survey. These questions have allowed 

researchers to study the impacts of these job characteristics on such outcomes as work-family conflict and work stress (Golden, 2015). 

4.2. ESTABLISHMENT AND OTHER BUSINESS SURVEYS

Data supplied by businesses can provide important information for 

policy makers and researchers that is largely complementary to that captured in household surveys such as the CPS and CWS. Key areas where 

business data may be called on to fill gaps include capturing contract 

5Available: http://gss.norc.org/Pages/quality-of-worklife.aspx.

6See also, in Appendix B, the summary of the presentation given to the panel by Susan 

Lambert. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF OTHER DATA SOURCES 91

company work, including use of temporary help services. These work 

categories were identified in Chapter 3 as areas where household surveys 

are deficient because respondents have difficulty reporting reliably on the 

contract arrangements of their employers. 

Experience from various household surveys suggests that additional 

probing may be needed so that independent contractors can correctly identify their status. Reporting about subcontracting relationships may be especially difficult for household survey respondents. Bernhardt, Spiller, and 

Theodore (2013) attempted to identify subcontracted jobs in their in-depth, 

long-form survey of low-wage workers, but they abandoned the effort 

because of workers’ inability to accurately identify whether their employer 

was a contractor or not. As discussed in Chapter 3, the CWS currently 

attempts to measure only a subset of subcontracted work (on-site, for one 

client), but the potential universe of subcontracted work arrangements is 

much broader and more varied. Subcontracted workers may work off-site, 

at multiple sites, for multiple clients, or with names on their paychecks that 

they do not recognize or that do not match who they think their employer is. 

Establishment and firm-level surveys can provide an important source 

for measuring complex AWAs, such as subcontracting, that workers understandably have a difficult time identifying correctly. Firm-to-firm contracting arrangements for services within the United States—variously called 

subcontracting, fissuring, or domestic outsourcing—appear to be increasingly common in a wide range of industries. These arrangements likely 

affect many more workers than has been recognized, ranging from lowwage service workers such as janitors, security guards, warehouse workers, 

and hotel housekeepers to professional and technical workers such as 

programmers, health care technicians, and accountants (Bernhardt et al., 

2016; Weil, 2014).

In response, researchers have harnessed a variety of datasets that 

include establishment- and firm-level data to begin to measure the prevalence of subcontracting (Dorn, Schmieder, and Spletzer, 2018; Goldschmidt 

and Schmieder, 2017). For example, the share of payroll employment in 

professional and business services, a sector composed primarily of contractor companies, nearly doubled from 1980 to 2016, rising from 7.3 to 

13.9 percent (Bernhardt et al., 2016). Similarly, Yuskavage, Strassner, and 

Medeiros (2008) report that the share of gross domestic product (GDP) 

accounted for by domestic providers of outsourcing services—which they 

defined as purchased services excluding telecommunications and financial services—rose from 7 to 12 percent between 1982 and 2006. And 

Goldschmidt and Schmieder (2017) show that the outsourcing of cleaning, food, security, and logistics services accounts for a sizable share of 

the growth in wage inequality in Germany since the 1980s. Because subcontracting inherently involves two (or more) firms, the long-term promise 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

92 MEASURING ALTERNATIVE WORK ARRANGEMENTS

of this emerging research is the ability to identify and link the industry and 

firm characteristics of both user firms and contractor firms in order to study 

the impact of contracting on job quality outcomes such as wages, benefits, 

and other working conditions.

Bernhardt and Houseman (2017), Dey, Houseman, and Polivka (2010), 

and Foster and others (2019) provide detailed overviews and analysis 

of firm- and establishment-level surveys and potential measures of subcontracting. A comprehensive menu of surveys and recommendations for 

each lies beyond the scope of this chapter; here we briefly highlight several 

key opportunities afforded by existing business surveys.

Many of the efforts within the federal statistical system to collect 

data from U.S. businesses are spearheaded by the Census Bureau, which 

conducts a wide range of business surveys, including the quinquennial 

economic censuses, annual economic surveys, and quarterly and monthly 

indicator surveys. The full suite of annual surveys is currently being 

reengineered, which may create opportunities to implement changes that 

better capture trends and motivations regarding AWAs from the employer’s 

perspective.7

For example, as suggested by a recent CNSTAT panel, the annual 

surveys could be expanded to more fully capture firms’ expenditures on, 

and use of, contracted services. Currently only aggregate categories are 

used, such as transportation and warehousing services, or professional and 

technical services. But these are the areas where growth in contracting out 

is concentrated (Yuskavage, Strassner, and Medeiros, 2008). Berlingieri 

(2014) finds that sectoral reallocation toward the outsourcing of professional and business services accounts for a very high percentage of increases 

in service sector employment and a corresponding decrease in manufacturing employment. Greater detail in expenditure data would allow better estimation and tracking of the scale, scope, and growth of contracting out as a 

firm-level practice, especially since Economic Census data are the primary 

source of BEA’s input-output tables, which could be leveraged to measure 

inter-firm contracting (see Bernhardt and Houseman, 2017). 

7See National Academies of Sciences, Engineering, and Medicine (NASEM) (2018), which 

covers the scope, operation, and major uses of the following economic surveys conducted by 

the Census Bureau, listed here by topic area. Manufacturing: Annual Survey of Manufactures 

(ASM); Manufacturers’ Unfilled Orders Survey (M3UFO); Management and Organizational 

Practices Survey (MOPS). Trade: Annual Retail Trade Survey (ARTS); Annual Wholesale 

Trade Survey (AWTS). Services: Service Annual Survey (SAS). Multisector: Annual Capital 

Expenditures Survey (ACES); Information and Communication Technology Survey (ICTS). 

Demographic: Annual Survey of Entrepreneurs (ASE). Other surveys related to the Business 

Register (Sampling Frame): Business and Professional Classification Survey (SQ-CLASS); 

Company Organization Survey (COS). The NASEM (2018) report also provides a framework 

for redesign of the annual surveys.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF OTHER DATA SOURCES 93

The Annual Survey of Entrepreneurs (ASE) and the Annual Business 

Survey (ABS) are examples of Census firm-level surveys that shed light on 

businesses’ use of various work arrangements. The ASE, which was administered in 2014 through 2016, and the ABS, which has been administered 

annually since 2017, ask firms if they use each of six categories of workers: 

full-time employees; part-time employees; temporary agency workers; day 

laborers; workers from professional employer organizations (PEOs); and 

contract, subcontracted, independent contractors, or outside consultants. A 

2015 module to the ASE also asked firms to report the percentage of their 

workforce in each of these arrangements and the functions performed by 

each type of worker. Brown, Earle, and Lee (2019) use evidence from the 

employer-provided data to ask, “Who hires nonstandard labor?” with nonstandard defined as workers who are not on the firm’s payroll. The resulting 

firm-based data allowed these researchers to determine, for example, that 

contract work is the most common type of nonstandard work; that the fraction of firms using contract workers is around 30 percent; that young firms 

are more likely to use nonstandard workers; and that larger firms tend to 

hire more temporary workers and contractors than do smaller firms. These 

types of insights into the use of AWAs require employer-based data. The 

types of questions on the 2015 ASE module could be collected in future 

business surveys. 

The BLS also produces relevant statistics collected through employer 

surveys. In addition to the payroll employment statistics already mentioned, 

the BLS conducts the Survey of Occupational Injuries and Illnesses (SOII), 

which produces workforce health and safety measures. Although the injuries and illnesses suffered by subcontracted workers should in principle 

be counted in the survey, they unfortunately are not separately identified 

in the data.8 Since 2011, however, the Census of Fatal Occupational Injuries (CFOI) has collected information on contractor status, including the 

industry of the firm for which a job was performed and the industry of the 

contractor firm. Although these data are limited to the most serious safety 

incidents faced by subcontracted workers, they could be used to investigate 

long-standing concerns that outsourcing, on average, may lead to higher 

rates of workplace death.

8The information reported on the SOII is drawn from OSHA Form 300. The OSHA form 

states: “The employer must also record injuries and illnesses that occur to workers who 

are not on the employer’s payroll if the employer supervises these workers on a day-to-day 

basis (including employees of temporary help services, employee leasing services, personnel 

supply services and contractors).” There is evidence that employers are often confused by 

these instructions and do not report correctly. See, for example, the September 2016 issue 

of Monthly Labor Review at https://www.bls.gov/opub/mlr/2016/article/an-update-on-soiiundercount-research-activities.htm.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

94 MEASURING ALTERNATIVE WORK ARRANGEMENTS

An example of a nongovernment survey that illuminates an aspect of 

contract company work is the American Staffing Association (ASA) Staffing 

Employment and Sales Survey (SESS). This survey,9 conducted on a quarterly basis since 1992, collects information from staffing firms to estimate 

temporary and contract staffing industry employment, sales, and payroll. 

In a presentation to the panel (described in Appendix B to this report), 

Steve Berchem defined staffing companies as those that are employers of 

temporary and contract workers. A key indicator derived from the survey 

is the ASA Staffing Index, a weekly measure of changes in employment by 

staffing firms. Berchem reports that the index closely tracks and serves as 

a leading indicator of GDP. For example, in July 2009, at the end of the 

recession, the staffing index began to tick up, revealing the beginning of 

the subsequent expansion ahead of many other indicators. 

In sum, establishment- and firm-level surveys are an underexplored 

source of data on AWAs. Especially in the case of subcontracted work, these 

surveys have the potential to yield vital information about the prevalence 

and nature of firms’ contracting-out activities. Similarly, as discussed next, 

tax data are an important complementary data source to the CWS.

4.3 GOVERNMENT ADMINISTRATIVE AND COMMERCIAL DATA

While household and business surveys will continue to provide critical 

information on the changing nature of employment arrangements in the 

U.S. economy, surveys are limited to questions to which respondents know 

the answer and that they can answer relatively easily. Moreover, survey 

response rates, including in government surveys, have been falling, raising 

concerns about costs and the ability of the statistical system to rely solely on 

survey data in the future. In this context, nonsurvey data sources are being 

increasingly called on to fill the void. As has been documented in numerous 

reports—most recently and prominently by the Commission on EvidenceBased Policymaking (2017)—the use of administrative data can improve 

the overall efficiency of data programs by reducing agency expenditures, 

lowering respondent burden, encouraging the sharing of information across 

agencies, and potentially increasing the accuracy of the information col9The SESS is a stratified sample of about 100 companies of various sizes (encompassing 

about 10,000 establishments) that uses the Economic Census as a benchmark. The survey 

is now a web-based instrument of no more than seven questions; employment, sales, and 

payroll are measured from quarter to quarter within each company size strata. The length of 

the SESS used to be about 20-25 minutes, but the number of questions has been reduced so 

that in now takes about 10 to 12 minutes to complete. The SESS is based on the methods of 

the BLS’s establishment surveys—for example, even collecting data for the week containing 

the 12th day of the month.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF OTHER DATA SOURCES 95

lected. In some cases, administrative data may be used to replace survey 

data (NASEM, 2019).10

Tax Data

Government administrative tax data are a key example of sources of 

information on AWAs that can complement the CWS. Researchers have 

recently focused on using tax data for measuring and tracking the scale and 

scope of independent contracting, including the use of on-demand labor 

platforms (Collins et al., 2019; Jackson, Looney, and Ramnath, 2017; Lim 

et al., 2019).

Tax data feature several advantages over survey data. They offer a relatively clear delineation between employees (measured by W-2 income) and 

independent contractors (measured by sole proprietor income and/or 1099 

income). The 1099-K form can be used to identify work for on-demand 

labor platforms, which is of particular public policy interest. And tax data 

also can capture sources of income that some workers might not report 

through surveys such as the CWS.11 As a result, tax data are valuable for 

estimating the prevalence of all sources of paid income and, importantly, 

how these income sources (including from on-demand labor platforms) are 

combined by workers. 

The above-described features of tax data have allowed researchers to 

generate novel findings that would be difficult to generate using household 

survey data alone. For example, Lim and colleagues (2019) use tax data to 

study trends in independent contracting. They define independent contractors as tax filers who earned income reported on a form 1099-MISC or 

1099-K and had less than $10,000 in non-car, non-travel-expense deductions (if filing as an individual) or less than $10,000 in total deductions (if 

filing as a business). Although the largest share of independent contractors 

are people whose Form 1099 earnings supplement their wage and salary 

incomes, until quite recently the rate of growth in independent contracting 

has been most rapid among those for whom those earnings are the primary 

source of labor income. 

10The Evidence-Based Policymaking Commission Act of 2016 defines administrative data as 

data that are “(1) held by an agency or contractor or grantee of an agency (including a State or 

unit of local government); and (2) collected for other than statistical purposes” (Commission 

on Evidence-Based Policymaking, 2017, p. 9). Unlike survey data collected specifically for 

statistical purposes, administrative data are typically collected in support of an agency’s or 

other organization’s routine program operations.

11Presentations to the panel by Dmitri Koustas and by Mike Udell and Diane Lim, summarized in Appendix B, include a detailed description of the use of tax data in research—for 

example, to capture payments by firms to unincorporated individuals for nonemployee 

services. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

96 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Collins and colleagues (2019) examine the universe of tax returns “to 

reconcile seemingly contradictory facts about the rise of alternative work 

arrangements in the United States.” They find that, among the tax-paying 

workforce—defined as workers who get a W-2 or a form 1099 and file a 

form 1040, or get a W-2 and do not file—expansion of 1099 work since 

2013 has been driven almost exclusively by online platform work.12 They 

also find that, for most people engaged in online platform work, that work 

is secondary, generating income that is supplementary to primary W-2 

jobs.13 Other findings show that, although most people who engage in this 

work do it as a secondary job, most of the work for platform companies is 

accounted for by people who do it full-time and as their primary source of 

income. While the research of Lim and colleagues emphasizes results for a 

longer post-2000 period, the focus of Collins and colleagues is on the past 

few years, during which patterns of independent contracting work have 

changed significantly.

Accurate information of this kind is difficult to attain using a household survey, where W-2 workers often neglect to report supplementary 

independent contractor income (Abraham et al., 2020; Abraham et al., 

forthcoming). Thus, even these early tax-based studies are contributing 

significantly to our understanding of trends in independent contracting, 

and online platform work in particular. Going forward, there is significant 

potential to learn more about how workers use independent contracting—

for example, whether over the life course or to manage career disruptions. 

There is also potential to learn about how firms use independent contracting, for example, whether it is to supplement or substitute for their W-2 

workforce, and how firms’ use varies over the business cycle. 

That said, tax data have their own shortcomings. While tax data may 

better measure the prevalence of independent contracting, they still do not 

capture the full universe of such activity. For example, they do not measure 

the presence of off-the-books and other informal work. Nor is measurement 

of sole proprietor income using tax data free from error, due to underreporting of income and/or overreporting of expenses (IRS, 2019; Slemrod, 

2018). Additionally, the 1099-K form will likely be an unstable source for 

measuring on-demand platform work because of the current high reporting 

12They find that “the share of the workforce with income from alternative, non-employee 

work arrangements has grown by 1.9 percentage points of the workforce from 2000 to 2016. 

More than half of this increase occurred over 2013 to 2016 and can be attributed almost 

entirely to dramatic growth in work mediated through online labor platforms.”

13Collins et al. (2019) find that approximately 44 percent of the overall growth in the 1099 

economy comes from people who do not file self-employment taxes. Examining the relationship between 1099s and self-employment tax records more generally, we find that the previously documented increases in self-employment tax filings since 2007 are largely driven by 

workers without 1099s.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF OTHER DATA SOURCES 97

threshold of $20,000 in annual gross income and 200 transactions.14 In 

addition, tax data are available only on an annual basis, and when multiple 

sources of income are reported in tax filings, one cannot tell if work relationships were held at the same time (and so reflect multiple job holding) 

or were held sequentially.

In conclusion, recent research has demonstrated the utility of access to 

confidential tax data for measuring the prevalence of independent contracting activity, and in particular how that activity is combined with W-2 work. 

As such, tax data should be considered an important complementary data 

source to the CWS for AWA measurement purposes; it can also serve as an 

external source of information to help in the refining of CWS questions in 

the future. However, the quality and therefore value of tax data is determined by tax rules and by the extent of taxpayer compliance. An important 

example is the 1099-K form, which could serve as an accurate source of 

data on the prevalence of on-demand platform work over time were its 

filing threshold significantly lowered, but at the existing filing threshold it 

provides incomplete information and thus an imperfect picture. 

Commercial Data

In addition to tax data, a number of researchers have begun using 

financial and other commercial data to reveal different aspects of AWA that 

are not often well understood. Koustas (2019) analyzes the income, spending, and liquid assets of rideshare drivers using personal financial service 

data;15 Hall and Krueger (2018) study pricing in the ride-share industry 

using Uber data; and Parrott and Reich (2018) use Uber data to determine, 

among other things, that about two-thirds of ride-share drivers in New 

York City do this work full time.

Recent work from the JPMorgan Chase Institute (JPMCI) illustrates 

how administrative (commercial) datasets can contribute value in measuring labor market trends. Using JPMCI financial accounts data, Farrell, 

Greig, and Hamoudi (2018) estimate platform participation among all 

families regardless of labor force status, and expose the fact that people are 

particularly likely to turn to platforms for income when they are between 

jobs or when their income from other sources dips. The researchers find 

that platform work is a supplementary source of income for most people, 

suggesting that many workers engaged in this form of AWA may also hold 

more traditional jobs. Indeed, it is the flexible nature of contingent work 

14For a detailed discussion of the use (and shortcomings of) 1099 data, see the summary of 

the presentation to the panel by Mike Udell and Diane Lim in Appendix B.

15A summary of research presented by Koustas to the panel can be found in Appendix B 

of this report.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

98 MEASURING ALTERNATIVE WORK ARRANGEMENTS

that may make it possible for individuals to fit it in around their traditional 

work schedules. Some student-age (18 to 24 years) and older adults (65+), 

who might self-identify as not in the labor force, nevertheless generate 

income on platforms. Put differently, certain forms of work, such as platform work, might not fit into traditional concepts of labor force participation. Thus, conditioning our understanding on labor force participation 

might underestimate the share of the population engaged in contingent and 

alternative work arrangements. 

As discussed in Chapter 3, defining the reference period as a week may 

miss many who sporadically engage in work activities and result in undercounting of contingent and alternative work arrangements. The JPMCI 

data reveal that most individuals who participate in platforms do so for no 

more than 3 months of the year. As a result, estimated platform participation rates are much lower if they are examined during a particular month 

(e.g., 1.6% in March of 2018) than when they are measured to include 

any point in the prior year (e.g., 4.5% for the 12 months leading up to 

March 2018). Another benefit of a quarterly or annual time frame, which 

some commercial data make possible, is the ability to make comparisons 

with government administrative datasets, such as unemployment insurance 

wage records or tax data, which are also collected on a quarterly or annual 

basis. Commercial data can provide alternative reference periods and more 

granular data with which to analyze work activity.

Sources such as the JPMCI Online Platform Economy dataset, which 

passively captures information from daily administrative operations used 

to manage customer accounts, offer some advantages as compared to existing survey datasets. First, these datasets are very large. The example from 

Farrell, Greig, and Hamoudi (2018) leverages a sample size of 2.3 million 

families who received income from 128 on-line platforms, allowing the 

construction of narrow confidence intervals around estimates over time. 

These data also permit analysis of differences across demographic and 

geographic subgroups, as well as subcategories of work, such as transportation platforms versus nontransport work. Second, they offer a continuous 

high-frequency lens over the observed period, such that trends can be ascertained on a weekly or monthly basis rather than only for a specific reference 

period. This is critical in the case of contingent work, since their research 

revealed just how sporadic work is in the online platform economy. In addition, the continuous lens paired with the large sample size is particularly 

valuable in picking up new trends and forms of work in their infancy when 

the prevalence of the activity may be very low. 

Third, because commercial data are based on real transactions or 

operations, they offer an unfiltered perspective unaffected by low (and 

falling) survey response rates, by the respondents’ interpretations, by recall 

bias, or by proxy reporting when answering survey questions. As described 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF OTHER DATA SOURCES 99

above, respondents’ varying interpretations of a question pose a particularly vexing measurement challenge when the question relates to new and 

rapidly changing concepts, such as electronically mediated work. Most 

recent attempts to measure electronically mediated work have yielded an 

unrealistically high level of participation due to affirmative responses that 

the BLS subsequently deemed to be false positives. Finally, administrative 

data often offer a view into a range of other outcomes and attributes. In the 

case of the banking data, Farrell, Greig, and Hamoudi (2018) are able to 

observe all income deposited to an account and thus measure how reliant 

families are on platforms. 

For all of the promise of nonsurvey data sources, caution must be taken 

when interpreting them. The potential sources of measurement error and 

approaches to addressing error are very different in administrative (commercial or government) data compared to survey data. For example, rarely 

will commercial data sources be representative of the full target population. Reweighting can make them more closely approximate the general 

population, but it cannot assist in representing subgroups that are missing 

entirely. In the case of the JPMCI data, for example, the unbanked and 

those who chose not to bank with Chase will always be absent. Additionally, while the unit of observation often becomes a design choice of how 

to aggregate the data rather than how to ask the survey question, there are 

practical challenges in delineating concepts such as an individual, family, or 

household within the context of administrative data. In the case of banking 

data, Farrell, Greig, and Hamoudi (2018) aggregated linked accounts to 

approximate platform participation for an entire family, but we know that 

accounts held by family members are not always linked nor do individuals 

always funnel all their income through a single financial institution. 

Similarly, while users of administrative data do not have to wrestle 

with ensuring that a question will be (or has been) interpreted correctly by 

a respondent, another critical design choice is which operations within an 

account to include as contingent or nonstandard work. The set of platforms 

included within the JPMCI Online Platform Economy data has expanded 

from 30 to 128 over time as new platforms have emerged, allowing for a 

window into not only labor platforms but also capital platforms. While 

these design choices can be applied uniformly across all accounts (families, 

if you will), there are judgment calls and practical challenges in defining 

and effecting such inclusion criteria. For instance, researchers will need 

to ask: Which platforms should we include? Can we identify transactions 

associated with such platforms? 

Finally, while surveys are created for the purposes of measurement and 

designed to make observations comparable, commercial administrative data 

are a byproduct of operations that can change in ways that distort the perspective over time. For example, if online platforms change or expand the 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

100 MEASURING ALTERNATIVE WORK ARRANGEMENTS

ways in which they pay participants, measurements of participation solely 

based on direct deposits into checking accounts may miss an increasingly 

larger share of the activity. 

These shortcomings underscore the value of commercial administrative data as a complementary source of information even while, for the 

foreseeable future, government surveys will remain an important part of 

the data collection infrastructure of statistical agencies. That said, there 

may be some domains where private sector data are intrinsically superior 

or where government data collection would be impractically expensive. In 

those cases, presumably, private sector data could even serve as a substitute 

for government surveys. 

The contribution of commercial and administrative data is in providing not just additional estimates with which to triangulate measures of 

contingent work and AWAs, but also an additional perspective that can 

reveal the ways in which each lens, from surveys to administrative data, is 

filtering the information. The exercise in reconciling not just estimates but 

also lenses can help inform efforts to improve the design of government 

surveys. For example, Farrell, Greig, and Hamoudi (2018) note that, all 

told, the JPMCI and BLS estimates for participation in labor platforms 

were remarkably similar, both estimating that 1.0 percent of respondents 

were earning income from labor platforms through electronically mediated 

work in May 2017. The fact that the two estimates were so close gives us 

confidence that they are in the right ballpark, even while their similarity is 

striking in light of the very different approaches taken by JPMCI and BLS 

to measuring electronically mediated work. These differences in approaches 

reveal opportunities for improvement in measuring contingent and alternative work arrangements.

4.4. THE LONGER-TERM PROMISE OF 

COMBINING DATA SOURCES

Declining response rates—even for federal surveys with historically high 

response rates—and the multitude of data sources now available are leading 

to broad-based efforts to expand the statistical system beyond the surveycentric approach developed during the 20th century. The Commission for 

Evidence-Based Policymaking16 advocated for expanded use of administrative data and improved data linkage across federal statistical and regula16The Commission was a 15-member group of experts charged by the U.S. Congress and the 

President with examining how government could better use its existing data sources to provide high-quality evidence for policy and government decision-making. The Commission was 

created in March 2016 by the Evidence-Based Policymaking Commission Act (P.L. 114-140), 

legislation jointly filed by Speaker of the House Paul Ryan (R-WI) and Senator Patty Murray 

(D-WA). Available: https://www.congress.gov/bill/114th-congress/house-bill/1831.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

THE ROLE OF OTHER DATA SOURCES 101

tory agency sources to help guide decision making. That work created a 

climate in which movement to this new paradigm may have the opportunity 

to flourish, including through legislative changes. Of course, policies and 

procedures are needed to ensure that access to restricted data is limited 

to qualified researchers and policy makers while protecting the privacy 

of people’s records.17 The capacity to improve measurement of social and 

economic phenomena, including trends in employment and work arrangements, will be largely driven by how effectively multiple data sources—

survey and nonsurvey, national and local, public and private—can be drawn 

from and combined (NASEM, 2019). Redesigns of surveys increasingly will 

presume that these instruments will need to be linked to other data sources.

The emergence of a multiple-data-source paradigm will no doubt influence the way employment and other labor market statistics are generated 

going forward. Research is already being conducted in cooperation with 

the U.S. Census Bureau that successfully links survey and administrative 

microdata (e.g., Abraham et al., 2020; Abraham et al., forthcoming). One 

finding, among many, is that CPS-based and administrative data-based 

employment estimates, such as those for wage and salary employment, 

multiple job holding, and self-employment, differ, and some of these differences have grown over time.18

Even though this panel strongly supports ongoing statistical agency 

work of this kind, at this time we do not recommend linking CWS data to 

tax (or other administrative) data as a priority for the BLS. One reason for 

this is that the single-week reference period for most of the CWS questions 

cannot easily be compared to the annual reference period for tax data. In 

addition, there would be technical and legal barriers to carrying out such 

linkages.19 We do, however, endorse the long-term goal of leveraging multiple data sources to better measure and understand the evolving nature of 

alternative work arrangements in the United States.

17One model for accomplishing this is provided by the Federal Statistical Research Data 

Centers (FSRDCs)—a partnership between federal statistical agencies and leading research 

institutions in which secure facilities provide authorized access to restricted-use microdata 

for statistical purposes only. FSRDCs (coupled with legislation) have allowed agencies and 

outside researchers to combine IRS data with existing statistical agency surveys, available: 

https://www.census.gov/fsrdc.

18For details, see the Appendix B summary of a presentation to the panel by James Spletzer. 

19As described by Spletzer, CPS supplement data have been linked with tax data for various projects, but the personal identifier code needed to link the data are collected only in the 

March Annual Social and Economic Supplement and so would not be available for all CWS 

respondents since the CWS has been fielded in February and May. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

Abraham, K.G., and A. Amaya. (2019). Probing for informal work activity. Journal of Official 

Statistics 35(3): 487–508.

Abraham, K.G., and S.N. Houseman. (2019). Making ends meet: The role of informal work 

in supplementing Americans’ income. RSF: The Russell Sage Foundation Journal of the 

Social Sciences 5(5): 110–131. doi: 10.7758/RSF.2019.5.5.06.

Abraham, K.G., B. Hershbein, and S.N. Houseman. (2019, June). Independent Contract, 

Informal, and Online Intermediary Work: Preliminary Evidence on Developing Better 

Measures in Household Surveys. Unpublished working paper. Available: http://conference.

iza.org/conference_files/Statistic_2019/abraham_k16798.pdf.

Abraham, K.G., J.C. Haltiwanger, K. Sandusky, and J.R. Splezter. (2013, April). Exploring 

differences in household vs. establishment measures of employment. Journal of Labor 

Economics 31(S1): S129–S172.

______. (2018). Driving the Gig Economy. Unpublished paper, National Bureau of Economic 

Research. Available: http://papers.nber.org/conf_papers/f110357/f110357.pdf.

______. (2020). Measuring the Gig Economy: Current Knowledge and Open Issues. In Measuring and Accounting for Innovation in the 21st Century, edited by C. Corrado, J. Haskel, 

J. Miranda, and D. Sichel. Chicago: University of Chicago Press.

Abraham, K.G., J.C. Haltiwanger, C. Hou, K. Sandusky, and J.R. Spletzer (Forthcoming). 

Reconciling Survey and Administrative Measures of Self-Employment. Journal of Labor 

Economics. 10.7758/RSF.2019.5.5.06.

Addison, J.T., and C.J. Surfield. (2006). The use of alternative work arrangements by the jobless. Journal of Labor Research 27(2): 149–162.

_____. (2009). Atypical work and employment continuity. Industrial Relations 48(4): 655–683.

Allard, M.D., and A.E. Polivka. (2018, November). Measuring labor market activity today: 

Are the words work and job too limiting for surveys? Monthly Labor Review, U.S. 

Bureau of Labor Statistics. doi: 10.21916/mlr.2018.26.

Appelbaum, E., and R. Batt. (2014). Private Equity at Work: When Wall Street Manages Main 

Street. New York: Russell Sage Foundation.

References

103
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

104 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Autor, D., D. Dorn, L. F. Katz, C. Patterson, and J. Van Reenen. (2017). Concentrating on the 

fall of the labor share. American Economic Review 107(5): 180–185.

Barley, S., and G. Kunda. (2006). Gurus, hired guns, and warm bodies: Itinerant experts in a 

knowledge economy. Industrial & Labor Relations Review 59(2): 326–329.

Barth, E., A. Bryson, J. Davis, and R. Freeman. (2016). It’s where you work: Increases in 

earnings dispersion across establishments and individuals in the US. Journal of Labor 

Economics 34: S67–S97.

Berlingieri, G. (2014). Outsourcing and the Rise of Services. Working Paper No. 1199. London: 

London School of Economics and Political Science, Centre for Economic Performance.

Berlinski, S. (2008). Wages and contracting out: Does the law of one price hold? British 

Journal of Industrial Relations 46(1): 59–75.

Bernhardt, A., and S.N. Houseman. (2017). Memorandum—Data Needs for Research on 

Domestic Outsourcing in the United States. Working Paper, W.E. Upjohn Institute. 

Bernhardt, A., M.W. Spiller, and N. Theodore. (2013, July). Employers gone rogue: Explaining 

industry variation in violations of workplace laws. ILR Review 66(4): 808–832 (Cornell 

University, ILR School).

Bernhardt, A., E. Appelbaum, S.N. Houseman, and R. Batt. (2016). Domestic Outsourcing 

in the United States: A Research Agenda to Assess Trends and Effects on Job Quality. 

Working Paper #102-16. University of California Berkeley: Institute for Research on 

Labor and Employment (IRLE). Available: http://irle.berkeley.edu/domestic-outsourcingin-the-u-s-a-research-agenda-to-assess-trends-and-effects-onjob-quality.

BLS (U.S. Bureau of Labor Statistics). (1995, June). Quality Assessment Research on the 

Contingent Work Supplement to the Current Population Survey. Unpublished memo, 

Washington, DC.

______. (2018, June). The Economics Daily: 3.8 Percent of Workers Were Contingent in May 

2017. Washington, DC. Available: https://www.bls.gov/opub/ted/2018/3-point-8-percentof-workers-were-contingent-in-may-2017.htm.

______. (2018, November). Measuring labor market activity today. Are the words work and 

job too limiting for surveys? Monthly Labor Review. Washington, DC. Available: https://

www.bls.gov/opub/mlr/2018/article/measuring-labor-market-activity-today.htm.

Board of Governors of the Federal Reserve System. (2018). Codebook for 2018 Survey of 

Household Economics and Decision-making. Washington, DC. Available: https://www.

federalreserve.gov/consumerscommunities/files/SHED_2018codebook.pdf.

Bollinger, C.R., B.T. Hirsch, C.M. Hokayem, and J.P. Ziliak. (2019). Trouble in the tails? What 

we know about earnings nonresponse 30 years after Lillard, Smith, and Welch. Journal 

of Political Economy 127(5).

Bracha, A., and M.A. Burke. (2017, November). How Big Is the Gig? Federal Reserve Bank 

of Boston. Unpublished Working Paper. Available: https://www.researchgate.net/publication/321228231_How_Big_is_the_Gig.

______. (2018). Wage inflation and informal work. Current Policy Perspectives, 18(2). Available: https://www.bostonfed.org/publications/current-policy-perspectives/2018/wageinflation-and-informal-work.aspx.

Brown, J.D., J.S. Earle, and K.M. Lee. (2019). Who Hires Non-Standard Labor? Evidence 

from Employers. Available: http://conference.iza.org/conference_files/Statistic_2019/

lee_k26929.pdf.

Collins, B., A. Garin, E. Jackson, D. Koustas, and M. Payne. (2019, March). Is Gig Work 

Replacing Traditional Employment? Evidence from Two Decades of Tax Returns. IRS 

SOI Working Paper. Washington, DC: Internal Revenue Service. Available: https://www.

irs.gov/pub/irs-soi/19rpgigworkreplacingtraditionalemployment.pdf.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

REFERENCES 105

Commission on Evidence-Based Policymaking. (2017). The Promise of Evidence-Based Policymaking: Report of the Commission on Evidence-Based Policymaking. Washington, DC. 

Available: https://www.cep.gov/content/dam/cep/report/cep-final-report.pdf.

Current Population Survey Staff. (2018). Electronically mediated work: New questions in the 

Contingent Worker Supplement. Monthly Labor Review, September. Washington, DC: 

U.S. Bureau of Labor Statistics. 

Davis, S.J., and J. Haltiwanger. (2014). Labor market fluidity and economic performance. 

In Re-Evaluating Labor Market Dynamics. Federal Reserve Bank of Kansas City. Also 

available as NBER Working Paper No. 20479.

Dey, M., S.N. Houseman, and A. Polivka. (2010). What do we know about contracting out in 

the United States? Evidence from household and establishment surveys. Pages 267–304 

in Labor in the New Economy, edited by K.G. Abraham, J.R. Spletzer, and M.J. Harper. 

Chicago: University of Chicago Press.

Dorn, D., J.F. Schmieder, and J.R. Spletzer. (2018). Domestic Outsourcing in the United States. 

Technical Report. Washington, DC: U.S. Department of Labor.

Dube, A., and E. Kaplan. (2010). Does outsourcing reduce wages in the low-wage service 

occupations? Evidence from janitors and guards. Industrial and Labor Relations Review 

63(2): 287–306.

Dunn, T., and D. Holtz-Eakin. (2000). Financial capital, human capital, and the transition 

to self-employment: Evidence from intergenerational links. Journal of Labor Economics 

18(2): 282–305.

Dykema, J., N.C. Schaeffer, D. Garbarski, E.V. Nordheim, M. Banghart, and K. Cyffka. 

(2016). The impact of parenthetical phrases on interviewers’ and respondents’ processing 

of survey questions. Survey Practice 9(2).

Fabiano, B., F. Currò, A.P. Reverberi, and R. Pastorino. (2008). A statistical study on temporary work and occupational accidents: Specific risk factors and risk management strategies. Safety Science 46(3): 535–544.

Farber, H. (1999). Alternative and part-time employment arrangements as a response to job 

loss. Journal of Labor Economics 17(4, pt. 2): S142–S169.

______. (2017). The role of unemployment in the rise in alternative work arrangements. 

American Economic Review: Papers and Proceedings 107(5): 388–392.

Farrell, D., F. Greig, and A. Hamoudi. (2018). The Online Platform Economy in 2018: Drivers, 

Workers, Sellers, Lessors. JPMorgan Chase & Co. Institute. Washington, DC. Available: 

https://www.jpmorganchase.com/corporate/institute/document/institute-ope-2018.pdf.

Foster, L., C. Grim, J. Haltiwanger, and Z. Wolf. (2019). Innovation, productivity dispersion, 

and productivity growth. In Measuring and Accounting for Innovation in the 21st Century, edited by C. Corrado, J. Haskel, J. Miranda, and D. Sichel. Chicago: University 

of Chicago Press.

Fugiel, P.J., and S.J. Lambert. (2019). On-demand and on-call work in the United States. 

Chapter 6 in Zero Hours and On-Call Work in Anglo-Saxon Countries, edited by M. 

O’Sullivan, J. Lavelle, J. McMahon, L. Ryan, C. Murphy, T. Turner, and P. Gunnigle. 

Springer Publishing.

Furman, J., and P. Orszag. (2018). A firm-level perspective on the role of rents in the rise in 

inequality. In Toward a Just Society: Joseph Stiglitz and Twenty-First Century Economics, 

edited by M. Guzman. New York: Columbia University Press.

GAO (U.S. Government Accountability Office). (2015). Contingent Workforce: Size, Characteristics, Earnings, and Benefits. GAO-15-168R. Washington, DC. Available: http://www.

gao.gov/products/GAO-15-168R.

Golden, L. (2015, April). Irregular Work Scheduling and Its Consequences. Briefing Paper No. 

394, Economic Policy Institute. Available: https://ssrn.com/abstract=2597172 or http://

dx.doi.org/10.2139/ssrn.2597172.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

106 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Goldschmidt, D., and J.F. Schmieder. (2017). The rise of domestic outsourcing and the 

evolution of the German wage structure. The Quarterly Journal of Economics 132(3): 

1165–1217. 

Grabell, M., J. Larson, and O. Pierce. (2013). Temporary work, lasting harm. Online 

article published on the ProPublica Website, December 18. Available: https://www.

propublica.org/article/temporary-work-lasting-harm?utm_campaign=get-involved&utm_

source=youtube&utm_medium=video&utm_term=temp-land.

Hall, J.V., and A.B. Krueger. (2018). An analysis of the labor market for Uber’s driver-partners 

in the United States. ILR Review 71(3): 705–732.

Halpern-Manners, A., and J.R. Warren. (2012). Panel conditioning in longitudinal studies: 

Evidence from labor force items in the Current Population Survey. Demography 49(4): 

1499–1519. doi: 10.1007/s13524-012-0124-x.

Henao, A., and W.E. Marshall. (2019). An analysis of the individual economics of ride-hailing 

drivers. Transportation Research 130: 440–451. 

Henly, J.R., and S.J. Lambert. (2014). Unpredictable work timing in retail jobs: Implications for employee work-life outcomes. Industrial and Labor Relations Review 67(3): 

986–1016.

Houseman, S.N., and A. Polivka. (2000). The implications of flexible staffing arrangements 

for job stability. In On the Job: Is Long-Term Employment a Thing of the Past?, edited 

by D. Neumark (pp. 427–462). New York: Russell Sage Foundation.

Howell, D.R., and A. Kalleberg. (2019). Declining job quality in the United States: Explanations and evidence. The Russell Sage Foundation Journal of the Social Sciences 5(4): 

1–53. doi: 10.7758/RSF.2019.5.4.01.

Hyatt, H., and J. Spletzer. (2016). The shifting job tenure distribution. Labour Economics 

41(1): 363–377.

IRS (U.S. Internal Revenue Service) Research. (2019). Applied Analytics & Statistics Federal 

Tax Compliance Research: Tax Gap Estimates for Tax Years 2011–2013. Publication 

1415 (Rev. 9-2019). Washington, DC.

Jackson, E., A. Looney, and S. Ramnath. (2017). The Rise of Alternative Work Arrangements: Evidence and Implications for Tax Filing and Benefit Coverage. Working Paper 

No. 114. Washington, DC: Office of Tax Analysis, U.S. Department of the Treasury. 

Available: https://www.treasury.gov/resource-center/tax-policy/tax-analysis/Documents/

WP-114.pdf.

Jamieson, D. (2014). Walmart warehouse contractor to pay $21 million to settle wage 

theft allegations. Huffington Post, May 14. Available: https://www.huffingtonpost.

com/2014/05/14/walmart-warehouse-wage-theft_n_5324021.html.

Japec, L., F. Kreuter, M. Berg, P. Biemer, P. Decker, C. Lampe, J. Lane, C. O’Neil, and A. 

Usher. (2015). Big data in survey research: AAPOR task force report. Public Opinion 

Quarterly 79: 839–880.

Jensen, L., G.T. Cornwell, and J.L. Findeis. (1995). Informal work in nonmetropolitan 

Pennsylvania. Rural Sociology 60: 91–107.

Jensen, L., A.R. Tickamyer, and T. Slack. (2019). Rural-urban variation in informal work 

activities in the United States. Journal of Rural Studies, 68: 276–284.

Ji, M., and D. Weil. (2015). Does ownership structure influence regulatory behavior? The 

impact of franchising on labor standards compliance. Industrial and Labor Relations 

Review 68(5): 977–1006. 

Kalleberg, A.L. (2011). Good Jobs, Bad Jobs: The Rise of Polarized and Precarious Employment Systems in the United States, 1970s-2000s. New York: Russell Sage Foundation.

Kalleberg, A.L., B.F. Reskin, and K. Hudson. (2000). Bad jobs in America: Standard and 

nonstandard employment relations and job quality in the United States. American 

Sociological Review 65(2): 256–278.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

REFERENCES 107

Katz, L.F., and A. Krueger. (2017). The role of unemployment in the rise in alternative work 

arrangements. American Economic Review: Papers and Proceedings 107(5): 388–392.

______. (2019, December). Understanding trends in alternative work arrangements in the 

United States. The Russell Sage Foundation Journal of the Social Sciences 5(5): 132–146. 

doi.org/10.7758/RSF.2019.5.5.07.

Kopp, B., and J. Edgar. (2016, September). Current Population Survey Program: Electronic 

Mediation of Contingent Work Question Cognitive Testing. Technical Documentation. 

Washington, DC: Bureau of Labor Statistics.

Koustas, D. (2019). What do big data tell us about why people take gig economy jobs? AEA 

Papers and Proceedings 109: 367–371.

Lambert, S.J., P.J. Fugiel, and J.R. Henly. (2014). Precarious Work Schedules among EarlyCareer Employees in the US: A National Snapshot. Research brief issued by EINet 

(Employment Instability, Family Well-being, and Social Policy Network) at the University of Chicago. Available: http://ssascholars.uchicago.edu/einet/announcements/scheduleunpredictability-among-early-career-workers-us-labor-market-national-sn.

Lambert, S.J. J.R. Henly, and J. Kim. (2019). Precarious work schedules as a source of economic insecurity and institutional distrust. RSF: The Russell Sage Foundation Journal of 

the Social Sciences 5(4): 218–257. Available: https://www.rsfjournal.org/content/5/4/218.

full. 

Lim, K., A. Miller, M. Risch, and E. Wilking. (2019, July). Independent Contractors in the 

U.S.: New Trends from 15 Years of Administrative Tax Data. IRS, Washington, DC. 

Available: https://www.irs.gov/pub/irs-soi/19rpindcontractorinus.pdf.

Litwin, A., A. Avgar, and E. Becker. (2017). Superbugs versus outsourced cleaners: Employment arrangements and the spread of health care-associated infections. ILR Review 

70(3): 610–641.

Mas, A., and A. Pallais. (2017). Valuing alternative work arrangements. American Economic 

Review 107(12): 3722–3759. 

Miller, C.C. (2019). How unpredictable work hours turn families upside down. New York 

Times, October 16. 

Mockovak, W., and R. Kaplan. (2015). Comparing results from telephone reinterview with 

unmoderated, online cognitive interviewing. In Proceedings of the American Association 

for Public Opinion Research Annual Conference. Washington, DC: Bureau of Labor 

Statistics. Available: http://www.asasrms.org/Proceedings/y2015/files/234247.pdf.

Moore, J.C. (1988). Self-proxy response status and survey response quality: A review of literature. Journal of Official Statistics 4(2): 155–172.

NASEM (National Academies of Sciences, Engineering, and Medicine). (2017). Information 

Technology and the U.S. Workforce: Where Are We and Where Do We Go from Here? 

Washington, DC: The National Academies Press. doi.org/10.17226/24649.

______. (2018). Reengineering the Census Bureau’s Annual Economic Surveys. Washington, 

DC: The National Academies Press. doi: https://doi.org/10.17226/25098.

______. (2019). Improving Data Collection and Measurement of Complex Farms. Washington, 

DC: The National Academies Press. doi.org/10.17226/25260.

Olson, K., J. Smyth, and B. Cochran. (2018). Item location, the interviewer-respondent 

interaction, and responses to battery questions in telephone surveys. Sociological Methodology 48(1): 225–268.

Osterman, P. (1999). Securing Prosperity: The American Labor Market: How it has Changed 

and What to Do about It. Princeton: Princeton University Press. 

Parrott, J.A., and M. Reich. (2018). An Earnings Standard for New York City’s App-Based 

Drivers Economic Analysis and Policy Assessment. The New School, Center for New 

York City Affairs.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

108 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Pegula, S., and M. Gunter. (2019). Fatal occupational injuries to independent workers. Beyond 

the Numbers: Workplace Injuries 8(10). U.S. Bureau of Labor Statistics. Available: 

https://www.bls.gov/opub/btn/volume-8/fatal-occupational-injuries-to-independentworkers.htm?view_full.

Polivka, A.E. (1996). Contingent and alternative work arrangements, defined. Monthly Labor 

Review 119(10): 3–9.

Polivka, A.E., and T. Nardone. (1989). On the definition of ‘contingent work’. Monthly Labor 

Review 112(12): 9–16.

Robles, B., and M. McGee. (2016). Exploring Online and Offline Informal Work: Findings 

from the Enterprising and Informal Work Activities (EIWA) Survey. Washington, DC: 

Board of Governors of the Federal Reserve System. Available: https://www.federalreserve.

gov/econresdata/feds/2016/files/2016089pap.pdf.

Schaeffer, N.C., and J. Dykema. (2020). Advances in the science of asking questions. Annual 

Review of Sociology 46.

Schneider, D., and K. Harknett. (2019). Consequences of routine work-schedule instability for 

worker health and well-being. American Sociological Review 84(1): 85–114.

Slack, T. (2007). The contours and correlates of informal work in rural Pennsylvania. Rural 

Sociology, 72(1): 69–89.

Slemrod, J. (2018). Tax Compliance and Enforcement. NBER Working Paper No. 24799. 

Cambridge, MA: National Bureau of Economic Research.

Smyth, J.D., and K. Olson. (2020). How well do interviewers record responses to numeric, 

interviewer field-code, and open-ended narrative questions in telephone surveys? Field 

Methods 32(1): 89–104.

Song, J., D.J. Price, F. Guvenen, N. Bloom, and T. Von Wachter. (2019). Firming up inequality. 

The Quarterly Journal of Economics 134(1): 1–50.

Taniguchi, H. (2002, September). Determinants of women’s entry into self-employment. Social 

Science Quarterly 83(3): 875–894.

Telles, R. (2016). Digital Matching Firms: A New Definition in the “Sharing Economy” 

Space. ESA Issue Brief #01-16. Washington, DC: U.S. Department of Commerce, Office 

of the Chief Economist. Available: https://permanent.access.gpo.gov/gpo94038/digitalmatching-firms-new-definition-sharing-economy-space.pdf.

Tickamyer, A., and T. Wood. (1998). Identifying participation in the informal economy using 

survey research methods. Rural Sociology 63(2): 323–339.

______. (2003). The social and economic context in informal work. Chapter 17 in Communities of Work: Rural Restructuring in Local and Global Context, edited by W.W. Falk, 

M. Shulman, and A.R. Tickamyer. Athens: Ohio University Press.

Tourangeau, R., F.G. Conrad, M.P. Couper, and C. Ye. (2014). The effects of providing 

examples in survey questions. Public Opinion Quarterly 78(1): 100–125. 

U.S. Census Bureau. (2015). Non-response Rates. Available: https://www.census.gov/programssurveys/cps/technical-documentation/methodology/non-response-rates.html.

U.S. Congress. (2017). H.R. 4174 - Foundations for Evidence-based Policymaking Act of 

2018. 115th Congress (2017–2018). Washington, DC. Available: https://www.congress.

gov/bill/115th-congress/house-bill/4174/text.

U.S. Department of Commerce. (2019). The American Community Survey. Questionnaire 

booklet. Washington, DC. Available: https://www2.census.gov/programs-surveys/acs/

methodology/questionnaires/2019/quest19.pdf.

U.S. Department of Labor. (2015, July). Administrator’s Interpretation No. 2015-1.

Washington, DC: U.S. Department of Labor, Wage and Hour Division. Available: https://

www.blr.com/html_email/AI2015-1.pdf.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

REFERENCES 109

______. (2020, January). Fact Sheet: Final Rule on Joint Employee Status under the Fair 

Labor Standards Act. Washington, DC: U.S. Department of Labor, Wage and Hour 

Division. Available: https://www.dol.gov/sites/dolgov/files/WHD/publications/flsa-frjoint-employer-fs.pdf.

Vernon, D. (2018). UPS, FDX: A deep-dive on Amazon Flex and the threat from crowdsourced 

delivery. A/B Bernstein Analysts 5: 6–7.

Warren, E. (2020). A Fair Workweek for America’s Part-time Workers. Statement published 

on the Warren Democrats Website. Available: https://elizabethwarren.com/plans/parttime-workers.

Weil, D. (2014). The Fissured Workplace. Cambridge, MA: Harvard University Press.

______. (2019). Understanding the present and future of work in the fissured workplace context. RSF: The Russell Sage Foundation Journal of the Social Sciences 5(5): 147–165. 

doi: 10.7758/RSF.2019.5.5.08.

West, B.T., and A.G. Blom. (2016). Explaining interviewer effects: A research synthesis. 

Journal of Survey Statistics and Methodology 5(2): 1–37. doi: 10.1093/jssam/smw024.

Yuskavage, R.E., E.H. Strassner, and G.W. Medeiros. (2008). Outsourcing and imported 

services in BEA’s industry accounts. Pages 247–288 in International Flows of Invisibles: 

Trade in Services and Intangibles in the Era of Globalization, edited by M. Reinsdorf 

and M. Slaughter. Chicago: University of Chicago Press.

Zaleski, O. (2018, November 1). Amazon raises minimum pay for everyone: Except these 

workers. Bloomberg. Available: https://www.bloomberg.com/news/features/2018-11-01/

amazon-flex-workers-are-left-out-of-minimum-pay-raises.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

SUSAN N. HOUSEMAN (Chair) is vice president and director of research 

at the W.E. Upjohn Institute for Employment Research. She also serves as 

research fellow at the Institute of Labor Economics (IZA), an international 

research organization based in Bonn, Germany, and as a member of the 

National Bureau of Economic Research, Conference on Research in Income 

and Wealth. Houseman is chair of the U.S. Bureau of Labor Statistics (Technical Advisory Committee), member of the American Economic Association 

(Committee on Government Relations), co-chair of the Labor and Employment Relations Association (ASSA Program Committee), and co-director of 

the IZA Program on Labor Statistics. An expert on temporary-help employment, outsourcing, and nonstandard work arrangements, her research has 

examined trends in employers’ use of these arrangements and their implications for workers’ wages, benefits, and employment stability. Houseman’s 

research interests also include outsourcing, offshoring, older workers and 

retirement issues, and comparative labor market policies. She has written 

extensively on such topics as employment, worker compensation, and offshoring. She has a Ph.D. in economics from Harvard University.

KATHARINE G. ABRAHAM is professor of economics and survey 

methodology at the University of Maryland, College Park. She is also chair 

of the Conference on Research in Income and Wealth and coordinator of 

the Program on Labor Market Statistics at IZA. Abraham serves as a member of the Federal Reserve Bank of Chicago’s Academic Advisory Committee, the Congressional Budget Office Panel of Economic Advisers, and the 

Bureau of Economic Analysis Advisory Committee. She formerly served as 

Appendix A

Biographical Sketches of 

Committee Members

111
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

112 MEASURING ALTERNATIVE WORK ARRANGEMENTS

chair of the Commission on Evidence-Based Policymaking, as a member of 

the President’s Council of Economic Advisers, and as commissioner of the 

Bureau of Labor Statistics. Abraham is a fellow of the American Statistical 

Association and the Society of Labor Economists. Her published research 

includes papers on the contingent workforce, domestic outsourcing, 

work and retirement decisions of older Americans, student financial aid, 

unemployment and job vacancies, and the measurement of economic activity. She has a Ph.D. in economics from Harvard University.

ANNETTE BERNHARDT is director of the Low-wage Work Program 

at the UC Berkeley Center for Labor Research and Education, and senior 

researcher at the UC Berkeley Institute for Research on Labor and Employment. She sits on numerous advisory committees and boards for nonprofits, 

research projects, and foundation initiatives. Bernhardt was one of the 

principal investigators in the National Employment Law Project’s landmark 

2009 study documenting high rates of minimum wage, overtime, and other 

workplace violations in the low-wage labor market. Her current research 

focuses on domestic outsourcing, the gig economy, and the impact of new 

technologies on low-wage work. She is widely published in journals in the 

fields of sociology and labor economics. Bernhardt has a Ph.D. in sociology 

from the University of Chicago.

JENNIFER DYKEMA is distinguished scientist and senior survey methodologist at the University of Wisconsin Survey Center at the University of 

Wisconsin–Madison. Dykema’s research focuses on issues related to questionnaire design, interviewer effects, interaction in the survey interview, and 

methods to increase response rates. Her research has appeared in numerous 

journals in the fields of sociology, survey methodology, and statistics, as 

well as major edited volumes on survey research, questionnaire design, and 

evaluation and testing. Dykema is on the American Association for Public 

Opinion Research (AAPOR) advisory committee for Public Opinion Quarterly, and holds memberships in the American Sociological Association, 

American Association for Public Opinion Research, Center for Demography 

and Ecology, and Midwest Association for Public Opinion Research. She 

has a Ph.D. in sociology from the University of Wisconsin–Madison.

DIANA FARRELL is founding president and chief executive officer of 

the JPMorgan Chase Institute. Prior to holding that position, she was a 

senior partner at McKinsey & Company, where she was global head of 

the McKinsey Center for Government and the McKinsey Global Institute. 

Farrell served in the White House as deputy director of the National Economic Council and as deputy assistant to the President on economic policy 

(2009–2011). During her White House tenure, she led interagency processes 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX A 113

and stakeholder management of a broad portfolio of economic initiatives, 

including financial reform, housing, and innovation. She currently serves 

on the boards of directors for eBay, The Urban Institute, and the National 

Bureau of Economic Research, and is a trustee emeritus of Wesleyan University. In addition, Farrell is a trustee of the Trilateral Commission and 

served as a co-chair of the World Economic Forum’s Council on Economic 

Progress. She is also a member of the Council on Foreign Relations, the 

Economic Club of New York, the Aspen Strategy Group, and the Bretton 

Woods Committee. She has an M.B.A. from Harvard Business School and 

a B.A. from Wesleyan University.

ARNE L. KALLEBERG is Kenan distinguished professor of sociology at 

the University of North Carolina at Chapel Hill, where he is also chair of 

the curriculum in global studies and adjunct professor of public policy and 

management. Kalleberg also serves as distinguished research fellow in the 

Center for Strategy and Leadership at the Foundation for Research in Economics and Business Administration in Bergen, Norway. He has published 

extensively in the areas of the sociology of work, occupations, and organizations; economy and society; and social stratification and inequality. He is 

editor in chief of Social Forces, an international journal of social research, 

as well as serving on the editorial boards of numerous publications. His 

research has been supported by numerous foundations in the United States 

and abroad. Kalleberg is an elected fellow of the American Association for 

the Advancement of Science, the Labor and Employment Relations Association, the Association for Psychological Science, and The Royal Norwegian 

Society of Sciences and Letters. He has a Ph.D. in sociology from the University of Wisconsin–Madison.

KRISTEN M. OLSON is Leland J. and Dorothy H. Olson professor in 

sociology and vice chair in the Department of Sociology at the University of 

Nebraska–Lincoln. Olson’s research includes examining interviewer effects, 

paradata, the intersection of nonresponse and measurement errors, withinhousehold selection in self-administered surveys, and questionnaire design. 

Her work has appeared in numerous journals in the fields of statistics, public opinion research, and survey and other research methods in the social 

sciences. She serves on the editorial board of several publications, including Sociological Methodology and The Sociological Quarterly, and holds 

memberships in several organizations, including the American Sociological 

Association. Olson has been elected as conference chair for the American 

Association for Public Opinion Research and is an elected fellow of the 

American Statistical Association. She has a Ph.D. in survey methodology 

from the University of Michigan. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

114 MEASURING ALTERNATIVE WORK ARRANGEMENTS

BARBARA R. ROBLES is principal economist in the Consumer and Community Research Unit for the Federal Reserve Board in Washington, DC. 

Her research interests include monetary policy, community economic development, Internet research, and regional economic development. Her professional affiliations include the American Economic Association, American 

Statistical Association, Urban Economics Association, and American Association of Public Opinion Researchers. Robles has served as referee for 

numerous publications, including American Economic Review; Journal of 

Family and Economic Issues; Journal of Consumer Education; Sociological Quarterly; International Migration Review; and Journal of Consumer 

Affairs. She has written and presented extensively on such topics as Latino 

employment and entrepreneurship, the gig economy, and low-income communities. Robles has a Ph.D. in economics from the University of Maryland, 

College Park.

MICHAEL R. STRAIN is Arthur F. Burns scholar in political economy and 

director of economic policy studies at the American Enterprise Institute in 

Washington, DC. He also serves as a research fellow at the Institute for 

Labor Economics. His research, which focuses on labor economics, public 

finance, and social policy, has been published in peer-reviewed academic 

journals and in policy journals. He is the author or editor of several books 

on the subjects of public policy and its effects on the U.S. labor market, 

political philosophy and economic freedom, and the American dream. 

Strain has a Ph.D. in economics from Cornell University. 

DAVID WEIL is dean and professor at The Heller School for Social Policy 

and Management at Brandeis University. Prior to joining the Heller School, 

he served as administrator of the Wage and Hour Division at the U.S. 

Department of Labor under President Obama. Weil is an internationally 

recognized expert in employment and labor market policy as well as regulation, transparency policy, and the impacts of industry restructuring on 

employment and work outcomes and business performance. He has advised 

both international organizations and U.S. agencies at the state and federal 

levels on employment, labor, and workplace policies. He cofounded and 

codirects the Transparency Policy Project at the Harvard Kennedy School 

of Government, and he is the author of more than 125 articles and 5 books. 

He has received many awards, including the fall 2019 Frances Perkins 

Intelligence and Courage Award. Weil has a Ph.D. in public policy from 

Harvard University.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

On June 10, 2019, the Panel on Measuring Alternative Work Arrangements for Research and Policy held an open workshop to highlight perspectives of data users and policy makers related to the modern economy’s 

changing work arrangements. This workshop complemented information 

learned during the panel’s first meeting, which featured presentations by U.S. 

Bureau of Labor Statistics (BLS) experts about the history, measurement 

objectives, and past performance of the Contingent Worker Supplement 

(CWS) of the Current Population Survey (CPS). The CWS is designed to 

shed light on individuals working in nonstandard jobs.

The June 10 workshop covered several topics central to the panel’s 

charge to review the CWS and other data sources, as well as methods 

surrounding the measurement of alternative work arrangements (AWAs). 

Workshop sessions included presentations on (1) the policy context for measuring alternative work, (2) measures of worker well-being, (3) employer 

and broader market issues, (4) insights about alternative work from other 

(non-BLS) surveys, and (5) use of administrative data that may substitute 

for or complement survey data. The sections of this summary correspond 

to the workshop sessions, in the same order as they were conducted. 

B.1. THE POLICY CONTEXT FOR 

MEASURING ALTERNATIVE WORK

Following an overview of the study charge by the panel chair, Susan 

Houseman, Session 1 examined the policy context for measuring alternative 

work. Houseman reminded meeting participants that the CWS was created 

Appendix B

Summary of June 10, 2019, Workshop

115
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

116 MEASURING ALTERNATIVE WORK ARRANGEMENTS

in response to concerns during the 1980s about the changing nature of 

employment and its implications for workers and public policy. This means 

that concerns today about the changing nature of employment are not new, 

although the characteristics of AWAs have evolved, raising new issues.

During this opening session, presenters offered perspectives on what 

information policy makers need to know and what questions remain unanswered—for example, how many people engage in supplemental work and 

what their motivations are. Methodological considerations that allow data 

to be translated into policy (for example, collecting data that is representative at the state level) were also addressed; and definitions and boundaries 

for different categories of work were discussed, such as the categories of 

“contingent,” “independent,” and “web-mediated.” 

Carolina F. Young, policy advisor, Office of U.S. Senator Mark R. 

Warner, kicked off the session, discussing legislative developments relating to alternative work. Senator Warner is honorary co-chair of the Aspen 

Institute’s Future of Work Initiative, and his office has been active on 

issues pertaining to gig work. Young updated the panel on her work in 

Senator Warner’s office on relevant initiatives—such as proposed legislation 

that would direct the U.S. Treasury to study tax issues for gig economy 

workers—and the kinds of data needed to inform this work. 

Young noted that Senator Warner has been actively engaged with 

such issues as the changing nature of work and the relationship between 

employers and workers for a long time. Recently, the senator’s office has 

been focused on the rise of the gig economy, the impact of platform-based 

companies on flexible work arrangements, the opportunity for people to 

subsidize W-2 employment, and other issues related to the future of work 

in the 21st century economy. Warner has also expressed concern about the 

access that gig workers and other independent workers have to basic benefits, which are more typical of regular W-2 employment. 

Young described three initiatives by Senator Warner’s office of particular relevance to the panel’s charge. The first stemmed from the fact that 

when the senator started working on these issues in 2015, the most recent 

CWS data were from 2005. Tax data, if accessible, would offer the potential 

for better year-to-year information about trends in wages and numbers of 

workers in nonemployer work. To explore this idea, the senator introduced 

legislation in 2018 to direct the U.S. Department of the Treasury to conduct 

a study of nonemployer business income.1 The study was not to be limited 

to the gig economy or platform-based work but would look at a much 

broader universe of employment. The senator directed Treasury to include, 

1The U.S. Census Bureau defines nonemployer businesses as businesses with no paid 

employees, having annual business receipts of $1,000 or more ($1.00 or more in the construction industries) and subject to federal income taxes.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 117

in this study, a report for the Senate Committee on Finance and the House 

Committee on Ways and Means, to evaluate the following:

— Tax compliance from nonemployer business income, including 

whether there is significant overreporting of nonemployer business 

income from underutilizing allowable deductions and other tax 

benefits (if feasible, the study would break out the same information for income earned through online and mobile platforms); 

— The current tax withholding reporting and tax-filing systems to 

identify how they should be updated to reflect the growing number 

of workers earning nonemployer business income; and

— How the earnings of wage income and nonemployer business 

income had changed over time, specifically dividing by income 

decile, and analyzing at least the most recent 10 years of available 

tax filing information.

The above-described kinds of information are not typically available 

to policy makers, Young noted, and this legislation was introduced to remedy that, providing insight into these different income streams. Moreover, 

policy makers would often prefer to work with federal agency data instead 

of having to rely on private proprietary data.

The second initiative by Senator Warner was a request that the U.S. 

Government Accountability Office (GAO) undertake a study of the platform workforce and how it deals with tax issues. Young noted that, for 

the workers engaged in this part of the labor force, complying with tax 

requirements or even understanding how to do so can be daunting. Senator Warner’s office also wanted the study to address how employers and 

organizations, which include independent contractors, comply with the 

tax system. Complications may be especially acute for form 1099-K earnings (introduced through the 2008 Housing and Economic Recovery Act) 

which involve third-party payment or service processors such as PayPal, for 

example. To alleviate the burden of requirements for companies, the threshold for reporting on 1099-K forms was set at over 200 transactions and 

over $20,000 in sales over the course of a year. Since many people engage 

in platform or other kinds of contract work on an ad hoc basis, sometimes 

to supplement W-2 wages, many do not meet the $20,000 a year threshold, 

and these workers typically do not get a tax form for that work.

The requested GAO study would address several core issues. It would 

analyze the available information on tax compliance of the platform workforce to help understand the level of underreporting and overreporting 

from workers earning income through platforms. It was also hoped that the 

paper would analyze the reporting regimes for tax withholding, tax filing, 

and current taxation to identify how they could be updated to reflect the 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

118 MEASURING ALTERNATIVE WORK ARRANGEMENTS

growing size of the platform workforce and any additional challenges and 

costs faced by the platform companies in complying with potential updates. 

Young reported that GAO has accepted this study request and is moving 

forward. 

The third initiative from Senator Warner’s office seeks to address 

broader trends in the economy, such as how market forces encourage 

companies to prioritize short-term returns and, potentially, to have less 

loyal relationships with workers. Policy makers at the federal level are now 

trying to figure out what can be done about benefits such as workers’ compensation, paid leave, and retirement accounts for people engaged in jobs 

ranging from Uber drivers, to freelancers, to domestic workers. According 

to Young, the senator is broadening the scope of his thinking to include 

ways policy can help the entire contingent of workers in the nonemployee 

workforce. He has introduced legislation to create an innovation seed fund 

at the U.S. Department of Labor that would award grants to states, cities, 

and nonprofits interested in experimenting with the delivery of worker benefits to the alternative workforce. This would allow the current patchwork 

system of benefits at the state level to encourage more innovation at the 

local level that, in turn, could be adopted and scaled as federal solutions. 

However, it is currently difficult for policy makers to know how best to 

proceed without the data needed to understand the issues. 

Young concluded her presentation with this summary take-away: Policy 

makers are, in fact, engaged on this topic, and they will be moving forward 

with legislation and advocacy of various kinds. As they do this they are 

making a series of assumptions about what the alternative worker population looks like, either through a tax lens, a worker-benefits lens, or an 

employer classification lens. The data piece is particularly important for 

these policy makers, she believes, as they attempt to build a consensus on 

how to move forward in a way that is helpful to this population of workers. 

Following Young’s presentation, BLS Commissioner William Beach

pointed out that his agency is fully engaged on this issue and would do all it 

could to be good partners in finding the necessary data to support research 

and policy. He asked Young which Senate committees would be dealing 

with the issues she discussed. She explained that finance questions around 

tax and compliance would be handled by the Senate Finance Committee, 

while benefits would fall within the purview of the Senate Committee on 

Health, Education, Labor, and Pensions.

Next, Alastair Fitzpayne, executive director of the Aspen Institute’s 

Future of Work Initiative, and Shelly Steward, research manager for the 

initiative, updated the workshop on their initiative’s plans. The Future of 

Work Initiative, which seeks to identify policy solutions to the challenges 

facing workers in the 21st century, has produced and maintains the Gig 

Economy Data Hub, in partnership with the New York State School of 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 119

Industrial and Labor Relations (ILR) at Cornell. This hub is an online 

resource that provides accessible summaries of data sources on independent 

and nontraditional work. 

The initiative’s taxonomy of “nontraditional work”—identified in 

terms of employment classification, U.S. Internal Revenue Service (IRS) 

and BLS designations, and a set of job characteristics—is summarized in 

Figure B-1. Within this taxonomy, it is apparent that nontraditional work 

includes a wide variety of job types and occupations. They fall under 

five BLS categories: part-time, on-call, temporary help agency, contract 

employee, and independent contractor. Recently, in order to address worker 

issues that arise, the institute’s team has focused on portable benefits, tax 

simplification for independent workers, and worker training tax credits. 

They recently released a report on this subject, Designing Portable Benefits: 

A Resource Guide for Policymakers.

Fitzpayne noted that the Future of Work Initiative, which is nonpartisan, has been analyzing what changes in the nature of work could 

mean for our economy and labor market and what policies may be needed 

to prepare for the transitions. The project has focused on three trends: 

first, the fracturing relationship between workers and employers; second, 

the increased importance of access to skills and education as new technologies and increased automation change the world of work; and third, 

the market-based pressures that companies face to produce short-term 

profits rather than long-term value. Because the social contract between 

workers and employers has weakened, the initiative has proposed policy 

solutions aimed at improving economic security for both traditional and 

nontraditional workers. 

Fitzpayne pointed out that well-designed policies require a better understanding of how our workforce is changing. With both the 2017 CWS data 

and recent academic research, more is known now than several years ago, 

but there are still unanswered questions and confusion among policy makers and the general public about how work arrangements are changing. 

Different sources, including those from government, academia, and the 

private sector, ask different questions and apply different definitions to the 

category of nontraditional work, and that makes it difficult to understand 

trends and identify solutions. 

Echoing Young’s remarks, Fitzpayne noted that one central challenge 

for nontraditional workers is their ability to access workplace benefits 

and protections. Given the instability inherent in much of their work, 

nontraditional workers have a great need for workplace benefits, yet they 

have some of the lowest rates of coverage. BLS’s National Compensation 

Survey, conducted quarterly to collect information from establishments 

on pay and benefits provided to employees, has shown an overall decline 

in employer-provided benefits over the past two decades, most notably in 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

120

FIGURE B-1 The nontraditional work landscape.SOURCE: Fitzpayne and Steward presentation.

3

IRS designation W-2 1099 Employment classification Employee Independent 

contractor 

Bureau of Labor Statistics designation

Part-time On-call Temporary 

help agency Contract firm Independent 

contractor Full-time

Representative occupations

• Retail cashier• Bartender• Adjunct 

professor

• Fitness instructor

• Substitute 

teacher

• Farm laborer• Construction 

worker

• Security guard• Janitor• Software 

developer

• Receptionist• Warehouse 

associate

• HR specialist

• Real estate agent• Massage therapist• Rideshare driver• Musician• Hair stylist

• Office clerk• Machine operator• Physician 

assistant

• Flight attendant

N

O

N

-

T

R

A

DITIO

N

A

L W

O

R

K L

A

N

D

S

C

A

P

E

Does worksite entity pay worker? Yes, worker paid directly No, worker employed and paid 

by intermediary Varies 

Access to benefits Some benefits mandated by law; few benefits typically voluntarily provided by employers

Few benefits 

mandated by law or 

voluntarily provided

A range of benefits 

mandated by law; 

others voluntarily 

provided

Non-traditional work

FIGURE B-1 The nontraditional work landscape.SOURCE: Fitzpayne and Steward presentation.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 121

health insurance and retirement. This trend means workers today are facing more economic insecurity than prior generations of workers. Available 

data suggests to Fitzpayne that these challenges have been felt particularly 

acutely by nontraditional workers, including temps, subcontracted workers, 

and independent contractors. This problem might be addressed by several 

approaches, including one put forward by the Future of Work Initiative 

as a promising solution in today’s labor market: portable benefits that 

can be taken from job to job. Effective portable benefits policies, though, 

depend on a solid understanding of how people are working and what their 

needs are.

Shelly Steward, research manager for the Future of Work Initiative, 

spoke about the project’s efforts to connect policy makers with relevant 

data sources. She described the initiative’s Gig Economy Data Hub, created 

to provide an accessible and comprehensive summary of available data 

and research on gig, independent, and nontraditional work in the United 

States. The data hub seeks to provide summary answers to basic questions 

of interest to a range of stakeholders, including policy makers, journalists, 

students, and the general public. Among the key questions of interest are 

these: How many nontraditional workers are there? How many of them do 

this work to supplement other employment? What industries do they work 

in, and what is their demographic makeup? And, what are the motivations 

for nontraditional work, especially supplemental work, and how does that 

vary across income levels and other demographics? The initiative has partnered with Carnegie Mellon University to add interactive data visualizations on the site as well, using the 2017 CWS numbers, to allow people to 

look at these data in new ways. 

Steward reiterated a point made by Young: that there are very different policy implications if people need benefits attached to nontraditional 

work because that is their primary source of income, as compared to when 

they are seeking supplemental work because reliance on a traditional job 

alone does not provide adequate financial security and benefits. Informal 

or under-the-table work, which is not well captured in official statistics, 

may be disproportionately performed by the most vulnerable segments of 

the population. Data, including at the state and local level, are needed to 

quantify this assertion and to assess variations among regions and cities 

and between rural and urban areas. Toward this end, Steward reported, 

the National Governors Association has a consortium (currently involving 

10 states) working to improve knowledge within their states about ondemand and nontraditional workforces

Steward concluded with an overview of the ways better data could be 

helpful to policy makers working on portable benefits, which are defined 

by these characteristics:
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

122 MEASURING ALTERNATIVE WORK ARRANGEMENTS

— Portability: Benefits are connected to an individual, rather than to 

a single employer, and can be taken from job to job;

— Prorated: Benefits are provided in proportion to work performed 

and can be funded from multiple sources; and

— Universal: Benefits are accessible by all workers, regardless of work 

arrangement.

Several states have introduced bills to create portable plans, and also 

to make existing programs, such as a state paid-leave program or a state 

auto-enrollment retirement account, more accessible to a wider range of 

workers. Key questions that remain to be sorted out include: What benefits 

will be included in a new plan? Who would be eligible for these benefits? 

How will the benefits be funded? And, who will administer them? 

Panel member Michael Strain, who led the open discussion, pointed 

out that a number of state-level policies have already been enacted, or an 

attempt was made to enact them, to redefine who is an employee and who is 

an independent contractor. The ground is shifting, as players at various levels 

of government are using different models with different built-in assumptions 

about how workers should be categorized, and this is complicating the measurement of phenomena, especially across time. Fitzpayne confirmed that 

this is the case, with work being done by different states that is moving in 

different directions concerning the definition of nontraditional work.

Steward agreed and noted that this points to the need to have data 

that do not rely on formal, established categories of employment, which 

are constantly shifting. Instead, the focus should be on job characteristics: 

Do these workers have access to benefits? Do they have channels through 

which they can access workplace protections or take action should they run 

into a problem? These questions, Steward suggested, are more about the 

job experience than about formal categories that can change. Panel member 

Annette Bernhardt stated that California is deep in policy design discussions concerning independent contractors, and one factor blocking progress 

there is that people do not understand how varied the set of independent 

contractors is—across the income spectrum, by industry, by demographic 

group, and by age.

Strain argued that some balance was needed when identifying key 

measurement objectives. He pointed out that, along with the challenges 

created by emerging AWAs, there are also positives: For example, people 

value the flexibility, and people value being their own boss. When thinking about measurement objectives, those considerations should be part of 

the overall picture. Strain agreed that worker benefits and tax compliance 

are important measurement objectives, along with wages, but he urged the 

committee to also consider the perspectives of businesses, both platform 

companies and businesses that employ contractors and contingent workers. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 123

Other questions that he urged be looked into: How does the growth of 

contingent work affect traditional W-2 employers? What sorts of measures 

from their perspective would policy makers need to know? 

Strain also posed several fundamental questions about the workforce 

that current surveys fail to adequately get at: Are workers satisfied with 

their jobs? Are they working part time for economic reasons? Are those 

who are working part time satisfied with the hours they are getting? Are 

the jobs that workers are currently holding perceived to be part of their 

longer-term career goals? Answering worker satisfaction questions of this 

type could be an important measurement objective as well.

Julie Hatch Maxfield, assistant commissioner for current employment 

analysis, noted that the CWS does ask workers about preferences and 

benefits—health care and retirement being the two topics on which BLS has 

traditionally focused. BLS commissioner William Beach noted the importance of not confining research on AWAs to any one statistical agency, and 

argued that the CWS is an ideal project to view through the lens of the 

Commission on Evidence-Based Policymaking (2017), calling for greater 

collaboration among the statistical agencies. He was optimistic that recommendations from the Commission’s report, The Promise of Evidence-Based 

Policymaking, would spur progress among the principal statistical agencies 

to improve measurement by combining data sources. Beach reported that 

the agencies were trying to design the right kind of guidance language and 

inspirational vision statement to do this. 

Panel member David Weil raised an additional issue affecting data 

needs. The employment categories, particularly the representative occupations identified in Figure B-1, are constantly shifting, even within different 

types of employment structures. Even when one is able to determine which 

category a job is in, the wage structures in the nontraditional sector will 

increasingly affect wage structures in the traditional sector. Ultimately, the 

concern should be with broader phenomenon in the labor market—such as 

employment volatility, earnings, and benefit coverage—not with how jobs 

are labeled. Someone employed in the same occupation or the same industry 

may affect the wages and benefits of other people even if they are working 

under different employment models. How one thinks about this classification issue ultimately affects questions about the outcomes and questions the 

data are being used to answer.

B.2. MEASURES OF WORKER WELL-BEING

A discussion of policy issues affecting worker well-being continued with 

a presentation by Susan Lambert (University of Chicago, School of Social 

Service Administration). Among the broad spectrum of public policy issues 

associated with different types of worker arrangements is the problem of 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

124 MEASURING ALTERNATIVE WORK ARRANGEMENTS

unpredictable work schedules. This particularly affects the well-being and 

security of low-income and low-skill workers. Lambert discussed measurement challenges and the need to inform public policy around work-hour 

standards. She advocated the benefits of a multidimensional approach to 

estimating the prevalence of different types of work arrangements, especially those common at the lower end of the labor market. She also spoke 

about new items in the National Longitudinal Survey of Youth-97 and 2016 

General Social Survey (GSS) to capture information about problematic 

scheduling practices. 

Lambert’s comments focused on questions related to the timing of 

work—when people work, how much they work, and who controls the 

outcomes. She noted that, even when hired directly by firms, workers’ 

hours can be unpredictable, unstable, and scheduled on call. U.S. employers 

do not need to have special job categories or tax arrangements to provide 

workers with what is essentially temporary employment and demanddriven work hours. 

To improve measurement, Lambert discussed the potential value of 

asking more detailed questions about work schedules in the CWS so that 

it would be possible to differentiate the form of employment arrangements 

from their functions. One goal would be to facilitate comparisons across 

standard and nonstandard alternatives even when jobs are not categorized 

consistently (either through time or across states or countries).

Lambert and colleagues have been studying the nature of work time 

and evaluating new “fair work week” legislation, which many cities now 

have. They have examined the different dimensions of working time and 

attempted to devise some core measures. The three dimensions of working 

time they identify are:

— Quantity: the number of weekly hours where, at one end, the 

worker is underemployed and at the other end, the employee is 

overworked;

— Timing: which may be either standard or nonstandard, where the 

majority of hours fall outside the hours of 9 to 5, Monday through 

Friday; and

— Stability: characterized by consistency in the number of hours, days 

of the week, and times of day; also, by consistency in the magnitude and direction of variation in the number of hours.

These dimensions of work can have serious ramifications for a worker’s 

economic security; as can predictability—the ability of workers to anticipate when they will and will not work—and the amount of input employees 

have in setting the number and timing of the hours. Lambert summarized what is known about the relationships of these different dimensions 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 125

to worker well-being and performance. Key among her findings are the 

following:

— Schedule unpredictability and instability are related to higher levels 

of stress, work-to-family conflict, and interferences with nonwork 

activities; 

— For parents, schedule unpredictability makes it difficult to arrange 

reliable child care and to participate in family routines important 

to child development; 

— An unpredictable and unstable schedule can mean unpredictable 

and unstable earnings; too few hours leads to too little income, and 

to economic insecurity;

— Evidence from a retail firm case study by Lambert and colleagues 

suggested that improving schedule stability and predictability can 

improve labor productivity.

In terms of survey measurement, a key observation is that national 

surveys are limited in capturing dimensions of working time. Surveys typically focus on “usual or typical hours” and are designed intentionally to 

smooth rather than reveal variations in work hours. Recently, items have 

been added to the NLSY-97 and the 2016 GSS that allow researchers to 

partly identify the magnitude and direction of fluctuations in weekly work 

hours, the extent of advance notice, and input into the number of hours. 

Respondents are asked, for example: What are the greatest number of hours 

you worked in a week in the last month, and what are the fewest number 

of hours you worked (not counting illness and vacation)? Or, How far in 

advance do you usually know what days and hours you’ll need to work? 

The 2016 GSS hourly data indicate that 82 percent of respondents 

give a different number of hours for the greatest and fewest hours they 

worked in a week. The average difference between those two is 13 hours, 

which amounts to 37 percent of their reported usual hours. Fifty percent of 

respondents reported a difference of 8 or more hours, which is more than 

a full day of pay. This indicates how irregular hours are for some workers. 

Additionally, about 50 percent of people reported that their employer 

controls the timing of their work, meaning they have little or no input into 

their number of hours. 

By looking at constellations of work-scheduling practices, Lambert 

and colleagues attempted to translate these responses into categories of 

employment. They found that on-call and on-demand workers display two 

qualities: There is variation in either the number or the timing of hours 

worked; and the hours are not controlled by the employee, but rather by 

the employer. In addition, hours are often set with only short notice. The 

researchers then compared this kind of multidimensional definition to the 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

126 MEASURING ALTERNATIVE WORK ARRANGEMENTS

direct approach used in the CWS question that attempts to measure on-call 

work. The CWS asks each respondent if they were an “on-call worker last 

week?” Beginning in 1997, a follow-up question was added that asks if 

hours are “regularly scheduled?” 

As indicated in Table B-1, the 2017 CWS identifies 1.9 percent of 

respondents to be on-call workers. If the additional restriction—of having 

no regularly scheduled hours reported—is included, the figure drops to less 

than 1 percent. This means that half of the people who said they only work 

as needed also reported that they have some regularly scheduled hours.

In Lambert’s multidimensional approach to defining on-call workers, 

which they used in the GSS and which has also been used in the Federal 

Reserve’s Survey of Household Economics and Decisionmaking (SHED), 

the figure for the number of workers reporting less than 7 days’ notice 

jumps to about 15 percent. For less than 1 day’s notice, the figures for 

the two surveys are 6.4 percent (GSS) and 5.1 percent (SHED). Almost a 

quarter of workers reported that volatility that was at least 25 percent of 

their usual hours; about 11 percent reported that their hours varied in the 

last month by more than 50 percent of their usual hours. This means that 

the majority of people in the labor market effectively performing on-call 

or on-demand work are in a so-called conventional standard employment 

TABLE B-1 Alternative Methods for Counting On-call or On-demand 

Workers

CWS (2017) GSS (2016) SHED (2017)

On-call Work (form/category)

Only work as needed (%) 1.9

No ‘regularly scheduled’ hours

(zero hours contract) (%) 0.8

Multidimensional

On-call Work (unstable hours/

no EE input/short notice)

Notice < 7 days (%) 14.9 14.9

Notice ≤ 1 day (%) 6.4 5.1

On-demand Work (unstable hours/

no EE input/considerable volatility in hours)

Volatility ≥ 0.25 usual hours (%) 22.7

Volatility > 0.50 usual hours (%) 10.7

N 41,722 493 5,120

SOURCE: Fugiel and Lambert (2019).
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 127

relationship. There is a blurring of lines in terms of what is standard and 

what is not standard.

Lambert suggested that if the CWS were to look at different dimensions 

of work schedules, it would offer a way to start teasing out the unique features of different kinds of employment relationships. It would also provide 

a way to make comparisons internationally to other countries that have 

even more different titles for the kinds of jobs people hold. 

The workshop focus turned next to worker safety. The National Institute for Occupational Safety and Health (NIOSH) has led efforts to develop 

a taxonomy of work arrangements to examine their relationships with 

worker safety, health, and well-being. NIOSH is a prominent user of CWS/

CPS data for its work identifying high-risk categories of workers, including 

those in industries and occupations with a high prevalence of AWAs. 

Tim Bushnell, Economic Research and Support Office, and Toni 

Alterman, Division of Surveillance, Hazard Evaluations and Field Studies, 

represented NIOSH during this session. Bushnell’s talk covered NIOSH programmatic interests in work arrangements, including its Healthy Work Design 

and Well-Being Program; its work defining specific dimensions of work 

arrangements; the value of adding new questions to existing surveys concerning job dissatisfaction and reasons for quitting; and the role of the CWS and 

other data sources for NIOSH research related to work arrangements. 

In addition to tracking patterns in occupational injuries and illnesses 

and the hazards and exposures related to them, NIOSH also devotes attention to organizational and managerial risk factors. The agency is interested 

in characteristics of work arrangements, not just because of their potential 

relationships with poor pay, benefits, and job security, but because of possible links to health and safety and other aspects of well-being. 

The Healthy Work Design and Well-Being Program, still in formation, 

is the agency’s central vehicle for addressing concerns about work arrangements. Bushnell described the well-being outcomes connected to work 

design as including not only the traditional concerns with illness and injury 

but levels of physical, cognitive, and behavioral function, economic wellbeing, work/life fit and conflict, positive social experience, fair treatment at 

work in various forms, and intrinsic work rewards.

The Healthy Work Design and Well-Being Program defines standard 

work arrangements as fulfilling specific job conditions for the worker. These 

are employee status; secure, career oriented; adequate and stable pay; inclusion of health insurance and retirement benefits; regular, full-time schedule; 

adequate schedule flexibility; and paid leave. A nonstandard work arrangement is one that deviates from this standard arrangement definition.

Bushnell echoed Lambert’s point that examining the dimensions or 

characteristics of work, and not the formal categories, is most useful for 

their analyses. In addition to pay, benefits, and job security, he identified 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

128 MEASURING ALTERNATIVE WORK ARRANGEMENTS

the key work schedule dimensions: total work hours; shift type (e.g., day, 

evening, night, rotating, split); predictability of work hours; and work flexibility (e.g., sick leave, number and choice of days, and hours off). Bushnell 

cited evidence of the impact of work schedules on health. The effects on 

sleep quality and quantity, which are linked to a wide range of outcomes, 

are most obvious, but exercise, diet, smoking, substance use, and impact on 

work/life fit and conflict are also important considerations.

Bushnell pointed to evidence that NIOSH has observed distinctly 

higher injury rates among temp agency workers relative to their permanent 

counterparts. After adjusting for occupational differences, the injury rates 

of temp workers are about twice as high, he said. Temp workers actually tend to have less frequent exposure to job hazards but, on average, 

have less safety training and less selection for their jobs based on their 

experience.

Bushnell also discussed the distinction between employee and selfemployed status, as well as the distinction between different forms of 

self-employment, noting that the agency is interested in obtaining better 

data on the number of employees misclassified as independent contractors, 

and about which industries and occupations they work in. These employers 

do not carry workers’ compensation insurance, they have less incentive to 

emphasize safety, and they lack other standard benefits and protections. 

Bushnell reported that the self-employed generally express a high degree 

of satisfaction with their work arrangement, but they also experience a 

work-related fatality rate that is four times as high as the conventionally 

employed. To better track these trends, NIOSH supports the idea of including on surveys a question on receipt of 1099-K tax forms or other means to 

identify misclassified workers, or simply to identify workers who consider 

themselves employees but are paid as independent contractors. 

Bushnell also raised the possibility of surveying respondents about other 

key dimensions of AWAs, including split or shared responsibility for supervision, and form of compensation. Split responsibility for supervision may 

be present for contract workers placed under the management of a company that is a client of the worker’s direct employer, or workers who are 

supervised in part by other parties such as a customer, supplier, franchisor, 

software platform, or other contractors on the same worksite. The concerns 

with split or shared responsibility for supervision are about potential for 

lack of coordination of supervision, lack of understanding of supervising 

parties of all of the risks to workers, or failure to take sufficient responsibility for worker safety, health, and well-being. A general question on split 

supervision might ask workers whether, besides the employer who pays 

them, there is any other company or organization that also supervises or 

directs how they do their job. The form of compensation (as opposed to its 

amount) can affect safety, health, and well-being because it has the potential 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 129

to create incentives that undervalue safety and health as compared to speed 

and productivity or lead to stress and overwork.

Bushnell also described questions that could be added to surveys about 

workers’ job dissatisfaction—including reasons for leaving a job or looking for another job—which would be useful in indicating negative working 

conditions associated with all work arrangements. Such questions could 

also provide information about unfair treatment, excessive work demands, 

the physical and social work environment, schedule flexibility, and the 

safety and health risks of work. The complexity of job acceptance and 

quit decisions also allows multiple factors related to working conditions to 

be identified by respondents. Bushnell believes it would be useful to elicit 

salient information about dissatisfactions with current jobs from workers 

who are not planning to leave their jobs, since many aspects of discontent 

do not get expressed in job change. 

Next, Bushnell turned to the role of the CWS and other data sources 

in NIOSH Work Arrangement Research. The CWS is useful for estimating 

the potential magnitude of work arrangement risks and the industry and 

occupation “location” of specific work arrangements. The CWS currently 

asks respondents if they are “registered with more than one temporary help 

agency last week?” Bushnell suggested a follow-up question—“How many 

temporary help agencies were you registered with last week?”—would 

potentially be valuable to NIOSH, since the nature of employment relationships changes with the number of agencies worked for.

One key initiative of the agency is its sponsorship of the Occupational 

Health Supplement to the National Health Interview Survey, one of the 

major data collection programs of the National Center for Health Statistics 

of the U.S. Centers for Disease Control and Prevention (CDC). This supplement was fielded in 1988, 2010, and 2015. The plan going forward is to 

ask at least 6 or 7 questions about work arrangements in 2020 or 2021. 

Bushnell’s colleague, Toni Alterman, listed and described the measurement constructs proposed by NIOSH for 2020/2021 as follows: (1) selfemployment; (2) working for temporary help or staffing agency; (3) job 

insecurity; (4) organizational justice, distributive justice/effort-reward; 

(5) shiftwork (usual shift); (6) mandatory overtime; (7) schedule flexibility; 

(8) income variability; (9) presenteeism (working while physically ill); and 

(10) schedule predictability. 

Questions of interest for the future would address additional matters: 

(1) extra shift on short notice; (2) desired hours of work (more or less); 

(3) method of payment (salary, hourly wage, tips, commission, etc.); 

(4) financial stress (adequacy); (5) supervisors from multiple organizations; 

(6) presenteeism (working while having mental health problems); (7) work 

engagement (vitality); (8) type of employer or self-employment; and (9) use 

of electronic monitoring by supervisors. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

130 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Bushnell concluded with a discussion of the Quality of Work Life 

Survey module of the GSS (2002, 2006, 2010, 2014, and 2018). He noted 

that what is especially valuable to NIOSH is knowing the industry and 

occupation location where different kinds of work arrangements prevail. 

This project began through an interagency agreement with the National 

Science Foundation to add a special module assessing the quality of work 

life in America to the 2002 GSS. Because the GSS is a relatively small 

sample survey, it does not produce industry and occupation detail, but it 

does contain rich descriptions of working conditions that uncover national 

trends. As with the CWS, the GSS module showed a flat trend in the growth 

of explicitly named nonstandard categories of work arrangements.

B.3. EMPLOYER AND BROADER MARKET POLICY ISSUES

The new economy requires policies designed to make new employment 

models work well not just for employees, but also employers who hire them 

and for the markets in which they operate. Kicking off this session, Gene 

Zaino, founder and executive chairman of MBO Partners, spoke about his 

organization’s work on key policy issues shaping the independent workforce movement that need to be informed by data collections, as well as 

about how to think about different categories of workers (e.g., part time 

and full time) within this movement. 

MBO Partners provides an end-to-end business management platform 

for independent workers and the enterprises with which they engage. Collaborating with the firms Emergent Research and Rockbridge Associates, 

MBO Partners has been conducting research on the independent workforce 

for about 9 years. The firm’s top-level findings, as summarized by Zaino:

— Independent work is a vibrant source of economic growth; 

— Independent work satisfaction is high (most independent workers 

choose to work independently); and 

— Measuring all segments of employment is important for effective 

policy.

MBO Partners estimates that, in 2018, full-time independent workers 

generated $1.28 trillion of revenue for the U.S. economy, more than 6 percent of gross domestic product (GDP). The organization estimates that about 

15 million workers are “occasional independents” (e.g., doing “side gigs”), 

about 10.8 million workers are part-time independents (working regularly, 

but fewer than 15 hours per week), and about 15.3 million workers are 

full-time independents (working regularly, greater than 15 hours per week).

Zaino discussed four features distinguishing regular employees from 

independent workers:
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 131

— Relationship with the firm where they work: The regular employee 

has an extended or permanent relationship; the independent worker 

is project-limited;

— Risk: The regular employee does not realize profit or loss; the independent worker incurs profit or loss from a project;

— Control of work process: A regular employee’s manager has control 

over work; the independent worker’s manager does not control the 

work process; and

— Integration: The regular worker is part of the company’s regular business; the independent worker is outside the company’s 

regular business.

Among full-time independent workers, MBO Partners surveys find that 

21 percent earn more than $100,000 per year. This subgroup, unsurprisingly, reports high levels of job satisfaction. A high percentage of full-time 

independent workers also report that they engage in independent work 

by choice (81%) and that working on their own is better for their health 

(68%). Zaino emphasized that, in his interpretation of MBO Partners 

research, people are engaging in independent work in large part because 

there is a positive side to it.

Zaino also addressed the business perspective. He cited the Deloitte 

Global Human Trends Survey (2018), in which 84 percent of surveyed 

businesses reported anticipating the use of independent professionals to 

increase or stay the same by 2020. Similarly, Mercer’s 2019 Global Talent 

Trends Study indicated that 79 percent of executives expect that contingent and freelance workers will substantially replace full-time employees 

in the coming years. Zaino’s view was that companies are using independent workers not just for cost reasons, but also for agility and for 

competitive advantage.

The MBO Partners perspective is that policies are needed that reflect 

economic realities and that do not restrain independent workers and the 

global advantage of U.S. firms that engage them. One goal, Zaino suggested, should be to protect the lower-paid, routine commodity workers 

who are vulnerable to abuse as part of a “race to the bottom,” while 

enabling on-shore economic growth for the higher-paid, nonroutine work 

where workers have choices.

To inform this policy area, Zaino advocated that BLS collect data 

on businesses’ use of independent workers and on various workforce 

segments. He believes information is needed in three areas: (1) workforce configuration—full time vs. part time and occasional, serving consumers vs. businesses, routine microprojects vs. skilled; (2) motivation for 

independence—reluctant, forced vs. chosen, primary income vs. supplementing other work income; and (3) hourly income levels associated with 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

132 MEASURING ALTERNATIVE WORK ARRANGEMENTS

different jobs. Zaino also spoke about the need to simplify and harmonize 

worker classification, a theme echoed by many of the speakers.

During open discussion of the Lambert, Bushnell, and Zaino presentations, panel member Arne Kalleberg reiterated the point that looking 

at the work categories themselves is not as useful as one would think, 

because they are ever-changing. Since there are good jobs and bad jobs 

even in “standard employment,” he argued, the discussion of contingent 

or nonstandard work is tangential to what the real issues are: the nature 

of work, how the nature of work is changing, and which aspects of work 

affect people’s lives in terms of health, stress, and family life. It is these 

characteristics, rather than the type of work arrangement, that should shape 

the measurement objectives, Kalleberg argued.

Panel Chair Susan Houseman asked Lambert, who had made a compelling argument for collecting data on irregular, unpredictable work schedules, if there was value-added to including such questions on the CWS, 

given that the information is collected on various other surveys such as the 

GSS and the NLSY. Lambert responded that researchers do use the CWS 

and the CPS to try to get at this issue, and the supplement should be more 

focused on these types of jobs than a broader, nonemployment-specific 

survey would be. For example, the CWS already identifies on-call workers, 

which would not be done in the NLSY or for most other datasets. Adding 

such a question in the context of the CWS would allow users to look at the 

similarities and differences across the range of employment arrangements. 

Panel member David Weil followed up with Zaino to ask about the 

respective roles of worker and employer (or establishment) surveys. He 

referred to the Mercer’s 2019 Global Talent Trends study, discussed by 

Zaino, which reported that CEOs planned on moving aggressively to 

increase their use of contingent and freelance workers. In fulfilling measurement needs in this area, Weil felt it was clear that household surveys would 

not suffice to answer all the questions, such as how businesses are making 

decisions. Zaino agreed that business surveys are needed to understanding 

staffing decisions to use nontraditional workers which, again, he suggested 

are cost-based but also, in some cases, about accessing talent. Some types 

of workers, such as those in creative technology fields, are in high demand 

and do not necessarily want to be restricted to arrangements with only one 

company.

Panel member Kristen Olson asked Lambert if, in her surveys of hourly 

workers, she has been able to check the accuracy of responses regarding 

number of hours worked against payroll or other records. Lambert replied 

that her team had established that workers’ responses were accurate—even 

accessing information on the actual times when workers clock in and out 

every day—which helped them convince BLS to add questions about fluctuating hours to their surveys. Lambert implied that people’s perceptions of 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 133

how much their hours vary were less consistent, although they correlated 

closely with the actual variation.

B.4. INSIGHTS ABOUT ALTERNATIVE WORK 

FROM OTHER (NON-BLS) SURVEYS

Building on what was learned from BLS experts during the panel’s 

first meeting, this session included presentations intended to help the panel 

assess the range of questions that can best be answered using household 

surveys and to identify which questions require other kinds of data, such 

as those derived from employer surveys, administrative/tax records, and 

commercial sources. 

Panel member Barbara Robles began the session with an overview 

of the Federal Reserve Board surveys, focusing on results from the 2018 

SHED. The Division of Consumer & Community Affairs at the Federal 

Reserve Board has fielded the SHED for 3 straight years in an attempt to 

measure the extent of and reasons for engagement in alternative, enterprising, and informal work activities.

Ipsos, a private consumer research firm, administers the SHED survey 

using its KnowledgePanel, a nationally representative probability-based 

online panel. Ipsos selects respondents for this panel based on address 

sampling, and SHED selects respondents from this panel. The respondent 

sample for the 2018 survey’s “gig work” module was 3,152, from a total 

sample of 11,316 respondents, with a cumulative response rate of 4.3 percent. SHED attempts to be as inclusive as possible concerning categories of 

employment. The 2018 version of the module evolved from an exploratory 

stand-alone survey fielded in 2015, called the Enterprising and Informal 

Work Activity Survey, designed to pick up enterprising activity—that is, 

when people generate jobs for themselves. This survey had estimated that 

a high percentage of workers (36% in 2015) take part in freelance work.

Robles noted that some of the SHED questions on gig work were 

revised from those asked in 2016 and 2017, so time-series comparability is 

limited. Five percent of the survey’s screener respondents2 reported engaging in gig work providing child or elder care services; 3 percent engaged in 

dog walking, feeding pets, or home sitting; and 6 percent reported doing 

house cleaning or yard work. Driving or ride sharing, reported in a standalone question introduced in 2017, was reported by about 3 percent of 

respondents. Activities done online—any kind of paid online task—were 

reported by 4 percent. Selling goods at flea markets and garage sales was 

indicated by 5 percent of respondents; selling goods at consignment by 

3 percent; and selling goods online (such as on eBay) by 10 percent. Four 

2The screener questions were asked of the full SHED sample.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

134 MEASURING ALTERNATIVE WORK ARRANGEMENTS

percent reported renting property. Among the subgroup of respondents 

reporting they had engaged in gig work, a high percentage of the activities 

appear to have involved selling items they no longer had use for. The other 

large response category, accounting for 22 percent, was house cleaning, 

yard work, and property maintenance.

Strain raised the point that it is important to differentiate between 

income and labor earnings. Income can result from selling an old bicycle 

on eBay, yet that is not generally the kind of economic activity that official 

statistics try to capture. Strain added that asking questions about why 

people engage in alternative work is very useful for understanding the labor 

market, and also because the variety of reasons have very different policy 

implications.

The survey also asked why respondents engaged in the gig work. This 

was done using two separate types of questions: One allows gig respondents to provide a reason why they are motivated, using an open-ended 

format; the other provides a checklist for all that apply. The survey also 

asks respondents for a main reason for engaging in gig work. About 

50 percent of respondents reported that they were motivated to supplement income; 35 percent reported that they wanted to sell items they 

no longer needed; and a substantial 21 percent reported that the money 

earned was their main source of income. When respondents were asked 

to indicate only one reason, the “main source of income” motivation 

dropped from 21 percent to 18 percent, and the answer, “to earn money 

supplementally,” dropped from 50 percent to 37 percent. Motivating factors varied somewhat by income category—40K and under, 40K–100K, 

100K and over—and by ethnicity and race as well. Earning money to help 

family members was the most frequent response among the under-40K 

income group.

To conclude, Robles posed a set of questions for further research to 

guide design of the SHED. Are the right questions being asked and in ways 

such that respondents can convey how they see themselves: as workers, 

income generators, or both? If individuals are engaged in multiple forms of 

AWAs, how do we assign them “one” category? 

The use of online probability panels remains a much-discussed issue 

among survey methodologists, researchers, and statistical agencies. Given 

the declining response rates in many paper and phone survey collection 

efforts, and given budgetary constraints, online surveys have increased in 

recent years as respondent pools have also become more adapted to internet 

and smartphone use. Robles pointed out that the digital divide remains an 

area of concern, both for respondent representation (do such respondents 

accurately represent the populations with no connectivity?) and for the 

acculturation of respondents presumably representing the “unconnected” 

populations. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 135

Cynthia Davidson and Steve Berchem of the American Staffing Association (ASA) presented next on survey and policy work at their organization, which is headlined by the ASA Staffing Employment and Sales Survey 

(SESS). This survey, conducted on a quarterly basis since 1992, collects 

information from staffing firms to estimate temporary and contract staffing 

industry employment, sales, and payroll. 

Berchem defined staffing companies as those that employ temporary and 

contract workers. In 2018, sales for the industry—which includes temporary 

and contract staffing as well as permanent placement services—amounted 

to around $167 billion. Temporary and contract staffing employees account 

for about 2 percent of the nation’s nonfarm workforce, or about 3 million 

people per day or per week. Over the course of the year, however, because 

turnover is around 400 percent, the industry employs about 17 million 

people. Berchem noted that, for those employed by staffing agencies, around 

80 percent of temporary and contract workers work full time, and the majority are W-2 employees (meaning they are typically not platform employees 

for example). A similar proportion of temporary and contract workers come 

to staffing companies as a way to transition into a permanent job. Most 

assignments are 10 to 12 weeks, and most staffing employees come to work 

for a staffing company for one assignment with one staffing firm, and then 

they leave, presumably to go take the job permanently. Echoing a point 

made by Zaino when discussing firms hiring independent workers, Berchem 

stated that clients use staffing firms primarily to gain access to talent that 

they would not have otherwise; cost reduction is typically a secondary factor. 

According to Berchem, the impetus for ASA developing the quarterly 

SESS occurred when BLS temporarily suspended its measuring of the staffing industry in 1990. (BLS resumed measuring it in 2000, reconstructing 

and publishing a series for the 1990s.) Meanwhile, ASA had already established its survey, which was created for it by DRI McGraw Hill.3 Having 

data collected by a third party is important for the purpose of keeping 

information provided by the staffing companies secure and private; ASA 

staff do not see information for individual companies.

The SESS is a stratified sample of about 100 companies of various sizes 

(encompassing about 10,000 establishments) drawn from the U.S. Census 

of Business. The survey is now a web-based instrument of no more than 

seven questions; employment, sales, and payroll are measured from quarter 

to quarter within each company-size stratum. The length of the SESS used 

to be about 20 to 25 minutes, but the number of questions has been reduced 

so that in now takes about 10 to 12 minutes to complete.

A key project derived from the survey is the ASA Staffing Index, a 

weekly measure of changes in employment by staffing firms. Berchem 

3The company was later renamed Global Insight and then IHS Market.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

136 MEASURING ALTERNATIVE WORK ARRANGEMENTS

reported that the index tends to track closely with GDP. For example, in 

July 2009, at the end of the recession, the staffing index began to tick up, 

revealing the beginning of the subsequent expansion before many other 

indicators did.

Berchem closed by pointing out some differences between the SESS and 

the BLS surveys. The SESS is based on the methods of the BLS’s establishment surveys—for example, even collecting data for the week containing 

the 12th day of the month. However, the ASA survey includes temporary 

and contract workers only and does not include the corporate employees 

of staffing companies themselves, unlike the BLS. Berchem believes that the 

BLS surveys miss some contract employment, and pointed to two pieces 

of evidence: First, BLS estimates that the temporary help services industry employs about 2.5 million workers while ASA estimates a little over 

3 million, even though BLS includes the corporate employees of staffing 

companies. Second, the BLS may miss some contract employment because, 

in some cases, the agency classifies temporarily placed computer programmers and other IT professionals under the category of “computer business 

professionals.” 

Davidson expanded on Berchem’s presentation to discuss additional 

aspects of the SESS and differences relative to the CWS. The ASA survey, 

she pointed out, differs from the CWS in frequency, in its identification and 

classification of employees, and in survey length. As noted earlier, the SESS 

is quarterly, whereas the CWS has been done on a periodic basis. Because 

ASA is more narrowly focused on temporary and contract workers for 

staffing companies, its task is somewhat easier than the BLS’s task with the 

CWS, since the BLS seeks to measure all “contingent” work, a wider set 

of employment arrangements. The SESS screener questions ask whether or 

not a worker works for a staffing company and in what capacity. Terms are 

important, and ASA is careful not to call temporary workers “part-time” 

workers since, as pointed out earlier, they are more often working full time 

than not. The key distinction is temporary versus permanent. 

The ASA data dashboard, which is used by industry leaders, economists, analysts, and journalists, includes four metrics: changes in ASAmeasured staffing jobs (which can be compared by firm size); changes in 

BLS-measured temporary help jobs; changes in the ASA Staffing Index 

(described above); and changes in the GDP projections made by Wall Street 

Journal economists. Census data on turnover and overall annual employment, drawn from the quarterly survey and sector-level information, are 

added to provide dashboard users with extra layers of information. Statistics are available at a variety of geographic and sectoral levels.

During open discussion, panel member Arne Kalleberg asked the ASA 

why estimates of people working in the staffing industry were so much 

higher than those estimated by the BLS. Davidson responded that the main 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 137

difference between the ASA’s number and the BLS’s stems from the fact 

that in the BLS’s monthly jobs report contractors are often classified under 

other industries and not as temporary help. She said that after BLS revises 

its numbers, the two sets of estimates become closer. 

Houseman questioned whether household surveys such as the CWS 

should continue asking whether respondents work for a temporary help 

agency, since staffing companies now call themselves just that and the old 

wording may no longer resonate. She also pointed out that there is considerable evidence from the CPS and CWS that people in temporary help 

jobs, for example, are often confused about their status and often report 

the client as their employer. This mix-up is revealed in the CWS responses 

and with further probing about whom they are being paid by (e.g., a client 

or a staffing agency). 

Next, Leif Jensen of Penn State University presented survey-based 

research exploring urban-rural variation in informal work activities. He 

addressed definitional questions, differentiating between unpaid and paid 

(off-the-books) work, and discussed his research team’s measurement strategy for capturing informal work activities. He discussed a national survey 

of informal work conducted with colleagues Ann Tickamyer (Penn State) 

and Tim Slack (Louisiana State University) and identified possible implications for the panel’s study and its recommendations about the CWS. 

Jensen noted that the term “informal economy” was historically associated with self-employment and small-scale family enterprise, but also with 

poverty and underemployment. An implication was that informal economic 

activity was endemic to underdeveloped countries and that its significance 

would decrease with economic growth. However, it has become clear that 

this is not the case—the informal economy retains importance in modern 

and rich societies, and indeed it has perhaps become more important with 

recent trends in work arrangements. 

For the purposes of his presentation, Jensen used the following definition from Jensen, Tickamyer, and Slack (2019): Informal work includes 

“household work activities that generate cash or in-kind income or reduce 

expenditures that operate outside the scope of state regulation in contexts 

where [they otherwise would be].” 

Jensen described qualitative evidence indicating that informal work is 

more common in rural than in urban areas. He cited several attributes of 

rural areas as reasons for this pattern: (1) formal sources of goods and services may be lacking; (2) networks of family and friends tend to be stronger; 

(3) there is greater deprivation; and (4) there is greater proximity to natural 

resources, which facilitates certain informal activities. 

Jensen cited the lack of representative quantitative data to study informal work as his motivation for engaging in survey research on the topic. 

Building on earlier survey research (Jensen, Cornwell, Findeis, 1995; Slack, 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

138 MEASURING ALTERNATIVE WORK ARRANGEMENTS

2007; and Tickamyer and Wood, 1998, 2003), Jensen and colleagues initiated a national-level household survey of informal work using computer 

assisted telephone interviewing conducted by Penn State’s Survey Research 

Center. The sample was about 1,800 households, with a cooperation rate of 

about 50 percent, and low-income and rural households were oversampled. 

The content of the survey included questions on:

— Household roster with demographic information;

— Formal employment circumstances;

— Formal self-employment / business ownership;

— Informal economic activities (“things that you and other members 

of your household do to help economically by earning money, saving money, or getting other items of value through barter or trade, 

as opposed to formal employment”);

— Income sources; and

— Social capital and community involvement.

Respondents were asked 18 closed-ended questions regarding the engagement of household members in a list of informal economic activities. They 

were asked, “In the past year did you or any other members of your 

household engage in X?” and whether that X was any one of 18 different 

activities. 

The overall fraction of households recording any kind of informal work 

done for any form of return was about two-thirds. When the definition was 

restricted to those who engaged in formal work only to earn money (as 

opposed to those also motivated to barter, save, or volunteer), the fraction 

shrank to closer to one-third. Table B-2 indicates the percentages of households reporting various categories of informal work performed; households 

could report more than one. Growing or producing food products and 

home repair and improvement were the most reported categories. For most 

categories, the rate of informal work was higher in nonmetro areas than 

in metro areas. In nonmetro areas, activities such as growing or producing 

food, hunting, and fishing were more common, while in metro areas personal services, accounting, and computer work were more typical activities.

Jensen has also explored the reasons motivating households to engage 

in informal work. The top reasons cited in the survey were to help out 

relatives and neighbors (77.6% reporting “somewhat important” or “very 

important”); to be able to set one’s own hours (58.7%); to make ends 

meet (58%); to be one’s own boss (55.2%); and to work at home (50.9%). 

Responses such as “to make ends meet” and “there aren’t enough good 

jobs around here” were more common motivating factors in rural areas.

Multivariate models using the data confirmed the higher prevalence of 

informal work in nonmetro areas. While the residential differences could 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

139

TABLE B-2 Percentage Engaging in Informal Work by Type and Residence

Total Sample Metro

Non-MetroTotal Micro Non-core

Any Informal Work 67.0 66.0** 72.1 73.4 70.4

Grow or produce food products 26.4 25.1** 32.5 32.7 32.2

Home repair or improvement 24.0 23.2 27.9 30.2 24.6

Repair vehicles, appliances, or other mechanical work 18.6 17.9 22.0 22.9 20.8

Personnel service 17.3 17.4 17.1 18.5 14.9

Hold or contribute to garage sale/flea market 17.2 16.3* 21.4 22.9 19.3

Reuse/fix things others had discarded 17.3 17.0 18.5 18.9 17.8

Sell or trade clothes, makeup, scrap metal, etc. 15.5 14.5** 20.4 23.3 16.1

Hunt, fish, or gather from land 15.0 12.5** 26.8 25.2 29.2

Landscaping, snow removal, etc. 12.7 11.9** 16.9 18.1 15.1

Provide blood or blood products (e.g., plasma) 12.6 12.7 12.3 12.7 11.8

Crafts, collectibles, or sew/do alterations 8.9 8.8 9.2 10.4 7.6

Other informal work not mentioned 8.3 8.4 7.4 8.1 6.4

Accounting or computer work 7.4 7.5 6.7 7.8 5.1

Give lessons(e.g., music, language, sports) 7.0 7.0 7.0 6.8 7.2

Breed, board, or tend non-farm animals 4.6 4.6 4.4 4.7 4.1

Clerical work (e.g., typing) 4.4 4.2 5.4 6.0 4.4

Take in boarders 2.1 2.1 2.5 2.4 2.7

Bartending or catering 1.5 1.5 1.9 2.1 1.6

Street vending/roadside sales 1.4 1.3 1.6 2.0 1.1

Number of Activities Reported

Mean overall 2.2 2.1** 2.6 2.7 2.4

Mean among those engaged in 1 or more 3.3 3.2* 3.6 3.7 3.4

Maximum 16.0 16.0 15.0 15.0 13.0

NOTES: *Metro/nonmetro difference significant at p < .05.**Metro/nonmetro difference significant at p < .01.SOURCE: Jensen, Tickamyer, and Slack (2019). 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

140 MEASURING ALTERNATIVE WORK ARRANGEMENTS

not be fully explained, they are partly accounted for by race/ethnic composition and the strength of social networks. However, other factors, such 

as lower levels of education in rural areas, suppress the residential effect.

Jensen concluded by summarizing the implications of his work for 

the panel’s study: Respondents’ location is an important factor influencing levels and types of informal work as an AWA. Definitional lines are 

blurry—it is difficult to know where to draw the line when defining informal activities (e.g., should barter and self-provisioning be included?). In a 

survey, listing specific types of informal work activities is effective but may 

not seem practical. However, if a respondent is asked if he or she engages in 

the informal economy, blank stares will follow! Summarizing, Jensen stated 

that rural America is important, different, and diverse; clearly, in his view, 

there is value in retaining the ability to identify rural populations and being 

attentive to their circumstances.

Next, panel chair Susan Houseman and panel member Katharine 

Abraham provided an update on their work (with Brad Hershbein of the 

Upjohn Institute) developing a survey module for the Gallup Education 

Consumer Pulse Survey, which consists of 14 questions asking respondents 

about the nature of their work arrangements. The goals of this research are 

to assess how well household surveys capture various types of contract and 

informal work and to inform ways in which household surveys might be 

improved to better measure these activities. 

Houseman’s comments focused on a subset of objectives for fielding the Gallup module: to uncover the potential for miscoding workers’ 

employment status as “employees” in surveys such as the CPS and CWS; 

to capture all forms of work for pay—including informal work that may 

not be reported in government surveys, especially when not associated with 

a primary job; to measure contract company work; and to better measure 

work secured through online platforms or mobile apps.

In the Gallup survey, once a respondent has self-identified as an employee, 

one of the following question versions was asked in the added module:

— (Version 1): “Were you an employee on this job or were you 

an independent contractor, independent consultant or freelance 

worker?” Or,

— (Version 2): “Did this employer take any taxes out of your pay?”

Since an individual working as an independent contractor for an organization might respond that he or she is employed by that organization, the 

first follow-up question was designed to tease out cases where respondents 

are coded as employees when in fact they are not. The second version of the 

question catches miscoding as well, since respondents who are employees 

should have Social Security taxes taken out of their pay. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 141

Findings revealed through the addition of one of the probing questions (summarized in Abraham and Amaya, 2019) indicate that some 

respondents do in fact get miscoded as employees when relying on their 

self-reported classification. The incidence of miscoding was 10.8 percent for 

the first follow-up question version and 8.9 percent for the second version. 

Employee miscoding was strongly (positively) associated with the number 

of employers the respondent had (i.e., multiple job holders), and also with 

low work hours, older workers, and gender (males). 

The inference here, Houseman said, is that CPS question wording may 

suffer from similar problems of interpretation. As with the Gallup question, 

the CPS also attempts to distinguish the self-employed from those employed 

by government, by a private company, or by a nonprofit organization. The 

CWS itself provides some evidence of employee miscoding in the CPS, as 

15 percent of independent contractors reported being employees on their 

main job (and 1–2 percent of all workers were coded as employees on their 

main job).

Another goal of the research highlighted by Houseman was to capture 

all sources of work activity, not just primary jobs. The Gallup survey, 

particularly in the work supplement module, may be better designed to 

capture work activity than other household surveys, like the CPS, because 

all respondents are asked both whether they were employed by an employer 

and whether they were self-employed. Additionally, question wording in 

the standard Gallup survey is designed to capture low work hours by asking about work for an employer or self-employment that occurs “even 

minimally like for an hour or more.” The Gallup self-employment question 

provides a more expansive definition of self-employment than is used in 

most household surveys.4

Houseman reported that their survey module also revealed a striking level of multiple job holdings—that is, of working for more than one 

employer in the prior 7 days. Multiple job holding includes cases where 

respondents worked for more than one employer and cases when work for 

an employer was combined with self-employment activity. Among those 

with some employment, the multiple-job-holding rate was 18.7 percent. 

Table B-3 summarizes the incidence of secondary work by worker category. 

The figures in the second column indicate that the incidence of secondary 

work is much higher among those coded as employees and—at between 

37 and 38 percent—especially high among those that are miscoded as 

employees; and considerably higher than those whose main job is reported 

to be in self-employment activities. Among those who are self-employed, 

4Self-employment “means working for yourself, freelancing, or doing contract work, OR 

working for your own or your family’s business. Self-employment also includes fishing, doing 

farm work, or raising livestock for either your own or your family’s ranch.”
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

142 MEASURING ALTERNATIVE WORK ARRANGEMENTS

secondary work is somewhat higher for independent contractors than it is 

for those who are not independent contractors.

The third part of the module discussed by Houseman explored contract company work. Here, respondents who reported being employed by 

an employer were randomly assigned to one of two sets of questions, as 

follows:

— (Version 1): “In the last 7 days, did your employer contract you or 

your services out? On this job, are you usually assigned to more 

than one client or customer? Do you usually work at the client’s or 

customer’s worksite?”

— (Version 2): “In the last 7 days, were you doing work for a business 

or organization that was different from the business or organization that paid you?”

The first version, while not identical to what was asked in the 2017 CWS, 

is very close to it. The second version attempts to get at respondents’ understanding of what it means to have their services contracted out—specifically 

whether the business where they are working is the same as the business 

that pays them.

The key finding here was that, using the narrow (version 1) definition similar to that used in the CWS, the percentage of contract company 

workers was estimated to be 2.0 percent. For version 2, the percentage was 

1.4 percent, a statistically significant difference. The estimate based on the 

May 2017 CWS was 0.7 percent, but that only reflected respondents’ main 

wage and salary job. The incidence was higher among those saying they 

were “employed by an employer” but also (with further probing) reported 

TABLE B-3 Incidence of Secondary Work by Type of Work Arrangement 

and Main Job Among Those in Indicated Main Job, Percentage with 

Secondary Employment Arrangement

Percentage 

of All 

Respondents 

by Main Job

Any 

Secondary 

Work

Work for 

Employer

Selfemployed

Other, 

Informal 

Work

Employee, not miscoded 50.77 19.81 6.94 12.91 2.14

Miscoded employee 4.43 37.80 21.71 18.85 5.92

Self-employed, not IC 5.34 7.65 3.76 n/a 4.94

Self-employed, IC 5.35 10.51 3.17 n/a 8.59

Informal work only 0.71 n/a n/a n/a n/a

SOURCE: Houseman presentation.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 143

not being employees (possibly independent contractors); they had a higher 

incidence of also reporting being contracted out by their employer. Using 

the above definition, 4.4 percent of these respondents were miscoded, versus 1.5 percent of the others.

The final task of the Gallup module was to try to capture online intermediary work. As in the case of the CWS, the authors found evidence of 

substantial respondent confusion regarding this question. All respondents 

were randomly assigned to one of two question versions:

— (Version 1): “For any of the work you did in the past seven days, 

did you connect directly with new customers or clients through a 

mobile app or online platform?”

— (Version 2): (Repeats above question and adds examples): “For 

example, you might have given rides to people using a ridesharing 

app; used an app to find people looking for cleaning, delivery or 

handyman services; or used an online platform where people can 

bid on data entry or other tasks.”

Findings from the first two waves of the module indicated that adding the examples led to significantly lower measured incidence or reported 

online intermediary work. Examples appear to help individuals better 

understand the question and not misclassify work as mediated by a mobile 

app or online platform when it was not. Both versions of the question, 

however, yielded higher estimates than Houseman and colleagues expected.

For waves 3 and 4 of the survey, those who responded “yes” to either 

question version were also asked, “Did the customers pay you directly, or 

did they pay the mobile app or online platform which then pays you?” 

Houseman reported that unpacking content in this way reduced the measured incidence of online intermediary work by more than half, to about 

3 percent. This finding is consistent with the hypothesis that the CWS 

questions are getting at a complex concept and that breaking out this information across questions would be helpful. 

Houseman offered some preliminary conclusions. First, she cautioned 

against interpreting the levels of employee miscoding and multiple job holding as representative of the population, since the Gallup sample is weighted 

to be representative of the population based on observable characteristics. 

Many people may differ in unobserved ways that affect responses. Second, 

the findings from this research illustrate the potential of question wording to affect responses and support certain concerns about household 

surveys like CPS and CWS. Specifically, individuals working in contract 

arrangements may be miscoded as employees; surveys may miss some work 

activity, especially secondary jobs; measuring online intermediated work is 

difficult; and there is substantial confusion over payments coordinated by 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

144 MEASURING ALTERNATIVE WORK ARRANGEMENTS

intermediaries. However, according to Houseman, there is no evidence that 

the wording of questions in the CWS to identify independent contractors 

and contract company workers results in lower estimates of incidence than 

would the alternative wording, which was studied. 

B.5. ADMINISTRATIVE DATA ALTERNATIVES/COMPLEMENTS 

TO SURVEY DATA

Building on the presentation by Diana Farrell about commercial banking data during meeting #1, this session explored what can be learned 

from nonsurvey data sources, on their own or in combination with surveys. Dmitri Koustas, University of Chicago, led off the session, presenting his research exploring what can be learned about alternative work 

arrangements from tax data. He also commented on his analyses, using 

personal financial service data, of the income, spending, and liquid assets 

of rideshare drivers. In considering the size and scope of the gig economy, 

Koustas is concerned not only with the jobs mediated through online platforms but also with how their emergence affects more traditional forms of 

alternative work arrangements. Specifically, there are clear implications for 

workers, since in the United States many social programs are administered 

through employers and many legal protections apply exclusively to traditional employees. 

Koustas’ presentation focused on two different datasets that he and 

his coauthors have used in their research: financial accounts data capturing microtransactions and IRS information derived from returns, including 

individual tax returns. The financial accounts data derive from a financial 

aggregator and bill-paying application for smartphones and computers. 

The dataset used by Koustas and colleagues includes comprehensive coverage across financial providers for over 2.1 million workers covering the 

period 2012 to 2016, a time frame characterized by growth in the online 

platform economy. The researchers had access to anonymized data tracking 

microtransactions from linked credit cards and bank accounts that accrued 

through workers’ use of the app.

While there are concerns with datasets like these—for example, regarding the representativeness of people who use the app (for example, they 

might be more financially sophisticated than others, on average)—there are 

also distinct advantages. One important feature identified by Koustas is the 

administrative-level quality for measures of income, spending, and liquid 

assets all linked in one place. Also, the data are high-frequency, posting 

transactions daily. For measuring gig income, the microdata reveal transactions associated with major online platforms. Using these detailed personal 

financial app data allowed Koustas and his coauthors, for example, to 

determine that growth in the number of active Uber drivers, as reported by 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 145

Hall and Krueger (2018), tracked growth in gig work financial transactions 

very closely over the study period.

Next, Koustas discussed insights gleaned from his research5 using IRS 

tax records. The IRS records capture payments made by firms to unincorporated individuals for nonemployee services. Nonemployee compensation 

is reported on 1099-Miscellaneous forms, which allows the universe of 

firm-facing independent contractor relationships to be examined. Similar to 

the method using the microtransactions data from financial accounts, online 

platform firm names can be identified with the tax information.

Using the IRS data on business filings, it is possible to link to information about firms—e.g., industry and business expenses in broad categories 

such as legal/professional services and contract labor—that are issuing the 

1099. On the individual tax side, 1040 returns capture information about 

the type of self-employment work people are doing. For workers who file a 

Schedule C, there is a self-reported industry, a description of business activity, and information on expenses. From W-2 forms, a panel of other work 

that people are doing can be constructed. Retirement and health benefits 

can be added using information from 5500 or 1095 forms.

By linking these data sources, Koustas and colleagues have produced 

several findings. One is that, for the tax workforce—defined as people who 

get a W-2 and file a form 1040 or a form 1099, or get a W-2 and don’t 

file—expansion of 1099 work in recent years has been driven almost exclusively by work in the online platform economy. A second finding is that 

most 1099 work and almost all online platform work supplement primary 

W-2 jobs. In other words, most people receiving a Form 1099 receive the 

majority of their earnings from wages, not from their independent contracting. They find much less growth in 1099 work among people who are 

primarily self-employed.

A third finding from Koustas and colleagues’ work is that the geography 

of the more traditional 1099 work and the online platform economy differs. The top five urban areas, measured as the percentage of the workforce 

engaged in online platform economy work, are San Francisco/Oakland 

CA (2.9%), Miami, FL (2.7%), Las Vegas, NV (2.6%), Washington, DC 

(2.5%), and Los Angeles, CA (2.5%). Because tax data are comprehensive, 

they pick up some geographic areas that do not show up in commercial data 

sources—for example, because the commercial entity such as a bank does 

not have a presence in that area—which are not necessarily representative 

of the broader population.

A fourth finding is that much of the online platform economy is missing from self-employment filings. Roughly 40 percent of people receiving 

5Joint research with Andrew Garin at the University of Illinois, Urbana-Champaign, Emilie 

Jackson at Stanford University, and two IRS partners, Brett Collins and Mark Payne.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

146 MEASURING ALTERNATIVE WORK ARRANGEMENTS

a 1099 from an online platform did not file a Schedule C or Schedule SE, 

which is how self-employment filing in the tax data has been traditionally 

thought of. A final finding discussed by Koustas concerns the relationship 

between the 1099 independent contracting and self-employment filing in 

the tax data more broadly. Independent contracting is a subset of selfemployment. Nearly all of the growth in self-employment has been coming 

from people without 1099s. 

Koustas also addressed limits in the accuracy of tax data—specifically, 

that the reliability of those data depends on consistent reporting, which 

is not always the case. Of particular concern is that the typical reporting 

threshold for 1099-K companies is $20,000 and 200 transactions, compared with $600 for the 1099-MISC firms. Until 2016, some gig companies voluntarily reported at $1 of earnings. However, some of the largest 

gig companies have publicly announced they will increase their reporting 

thresholds, which would reduce the value for measurement of the resulting 

tax data. Policy can fix this problem. A current proposal, H.R. 594, would 

eliminate or lower the $20K threshold for the 1099-K filing (but increase 

the 1099-MISC threshold to $1,500). Some states (Massachusetts and 

Vermont) already require reporting at the $600 threshold, although they 

do not share these data with the IRS.

Mike Udell and Diane Lim, from the District Economics Group, continued the discussion of the role of tax data in measuring alternative work 

arrangements. They identified advantages and limitations of using tax data 

to measure various categories of alternative employment, including the 

size and scope of the platform economy, as well as the data’s potential to 

inform tax policy. Udell built on Koustas’ discussion of tax code deficiencies in regard to 1099-K workers, clarifying that his comments were about 

taxable income, not all income. Udell discussed workers who provide labor 

as contractors and the kind of tax information reporting that occurs in 

conjunction with those payments. 

Information in tax systems serves several important purposes, in Udell’s 

view. It informs taxpayers about amounts of income earned, gross proceeds, 

and situations qualifying for special tax treatment. Having such information speeds up the ability of tax administrators to verify the accuracy of a 

tax return, and ideally it also supports policy making in areas ranging from 

unemployment and Social Security to student loans. 

In an income tax system, liability is determined by income—e.g., wages, 

interest income, dividend income, and state and local income tax refunds—

subject to tax less allowable deductions. If these were the only categories of 

income, tax returns would not be needed, because the tax administration 

has information on these sources and can precisely determine liability. But, 

Udell pointed out, some income is not fully subject to tax and requires 

additional time and cost on the part of individuals and tax administrators 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 147

to ascertain the taxable portion. One major example is Social Security 

income. Even though some recipients receive a 1099-SSA form, it does not 

tell the tax administrator what the taxable amount of that income is; other 

information is required for that determination. The same is true with pensions and annuities. 

Another example where additional information is needed to determine 

tax liability is reporting about gross proceeds from the sale of goods and 

services. Gross proceeds, as Udell explained, are not subject to tax. Rather, 

it is income that is taxed, and income is equal to gross proceeds minus the 

cost of goods sold minus general, sales, and administrative costs.

As Udell framed the issue, one might wonder what this has to do with 

contingent and other alternative work arrangements. In the federal tax 

reporting system for, say, a platform worker such as an Uber driver, gross 

proceeds are documented using a form 1099-K. But, again, gross proceeds 

are not income. In almost all cases, taxpayers self-identify the cost of 

goods sold. This is why the largest part of the tax gap has to do with selfemployed sole proprietors. It is not only because of unreported income, but 

because these workers control what the cost of goods sold is.

The measurement problem with the 1099-K arises when the cost of 

goods sold is larger than the gross proceeds received. Sometimes this is 

legitimate, but other times it is not, and when it is not, Udell emphasized, 

that turns out to be a big problem in the tax system. According to rules 

contained in section 6050W of the Internal Revenue Code, payments in any 

amount made to a business by a customer using a payment card, such as a 

VISA, MC, AMEX, or Diners Club card, are reported to the business (and 

to the tax administrator) at the end of the year by the payment card company. However—as pointed out by Koustas earlier—only payments made to 

persons providing goods and/or services on a third-party payment network 

in amounts greater than $20,000 and with more than 200 transactions 

during a year are reported to the seller by the payment network provider, 

such as Uber, Lyft, Airbnb, Etsy, and eBay.

When the 6050W legislation was drafted, third-party payment networks for service providers were not yet in existence (some, notably 

eBay, were providing goods). For a period prior to 2016, there was sufficient legal confusion whether the $20,000 threshold applied to services 

on third-party payment networks that some companies did file the form 

1099-K on all of their service providers; however, others did not. After 

2016, and as the result of a private letter ruling to a third-party payment 

network that provided only services, few if any networks are providing 

gross proceeds reports for service providers with sales less than $20,000 

and 200 transactions per year. The development of section 6050W did not 

anticipate labor services being provided on third-party payment networks. 

(Nevertheless, the iPhone had come out in July of 2008, which is when 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

148 MEASURING ALTERNATIVE WORK ARRANGEMENTS

the app store turned on and therefore the moment when platforms began 

to be created.)

Udell expressed the view that, without new legislation, third-party 

payment networks will continue to use the threshold of $20,000 in gross 

proceeds and 200 transactions. In turn, this will result in very little information being reporting through the federal income tax to the great majority 

of individuals providing goods or services on these platforms. Udell went 

on to suggest two approaches for improving this tax reporting situation. 

First, while the 1099-K data are limited in their capacity to help researchers 

identify platform workers, corporate income tax returns of the companies 

may be more promising, since they do not miss the opportunity to deduct 

the payments made to the service providers. Buried in the details of a corporate income tax return is a dollar amount showing the size of the payments, 

although this is still gross proceeds, not income. The corporate income tax 

returns could be used to view top-level gross proceeds in an industry and 

provide some measure of total economic activity.

Another measurement option would exploit state and local sales tax 

information. Udell noted that a few states—Pennsylvania is one—are using 

a facilitator tax, which requires companies to report how much activity 

takes place inside their state. So, for example, the state taxing agency would 

ask a company like eBay the amount of their sales of goods that were delivered into Pennsylvania. Instead of taxing the seller, the state then taxes the 

facilitator, which has led to an increase in the state’s sales tax receipts. If 

more states follow through in a similar fashion, information on these facilitator taxes could potentially provide an effective way to measure the sale of 

both services and goods (although perhaps mostly goods) being transacted 

on platforms. States could also implement a tax on services provided over 

platforms as well, and then use the same approach. 

During open discussion of the session on administrative data, Abraham 

asked Udell whether there could be modifications to the tax code to gain 

insights into how alternative work activities fit into people’s work lives. 

For that purpose, data on whether people have this type of income would 

be needed, not just covering aggregates but on a person-by-person basis. 

Udell suggested that replacing the threshold of $20,000 and 200 transactions with one set at $1,000 or $2,000 in gross proceeds would largely solve 

the issue. However, doing this would raise the problem of eBay sellers—

1099-Ks being issued to people selling out of their attic—and that would 

undermine administrative record-matching programs. Separating goods and 

services in the 1099-K could address this problem. 

The final presentation of the day, by Jim Spletzer (Center for Economic 

Studies, U.S. Census Bureau), was on work by the Census Bureau combining data sources. Spletzer addressed three topics: (1) The possibility of 

linking CPS microdata, specifically the CPS contingent worker supplement 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 149

microdata, to administrative data—specifically tax data—housed at the 

Census Bureau; (2) how this kind of data linkage is done; and (3) what can 

be learned using this approach.

Regarding the first topic, Spletzer reported that, as demonstrated 

through several projects,6 person records in the CPS can be linked to 

their information in administrative data. He then discussed three reasons 

for linking CPS and administrative data: (1) to understand differences in 

the measurement of various concepts—income is an example—between 

administrative records and household survey data (including those created 

by measurement error and nonresponse bias); (2) to improve imputations; 

and (3) to reduce respondent burden.

After walking workshop participants through the technique whereby 

the Census Bureau links records using a protected identification key (PIK)—

a confidentiality-protected version of the Social Security number—Spletzer 

discussed the CWS. His understanding is that respondents who answer the 

May 2017 CWS and who also participate in CPS ASEC will be assigned a 

PIK. Spletzer said his own informal calculations suggest that based on this 

rule, perhaps 60 to 70 percent of the records in the May 2017 CWS should 

be linkable to administrative data housed at the Census Bureau, such as 

unemployment insurance (UI) wage records, Social Security Administration 

Detailed Earnings records, and nonemployer records. 

Next, Spletzer provided a summary of what has been learned from previous exercises matching CPS microdata to administrative data. Abraham et 

al. (2013), for example, were able to compare employment status and multiple job holdings in the CPS with those estimated from UI wage records. 

Their findings included that 6.4 percent of UI employed—people who 

have a wage record—did not report being employed in the CPS; meanwhile, 17.6 percent of the CPS employed are not employed according to 

the UI wage records. Likewise, close to 70 percent of multiple job holders 

in the UI records show up as single-job holders in the CPS, while almost 

45 percent of multiple job holders in the CPS appear as single-job holders 

in the UI records. Since the authors went to great pains to examine the 

same types of workers—e.g., those in nonfederal government and nonagriculture sectors—Spletzer admitted that he found it disconcerting to see 

such differences. 

In another research project, Abraham et al. (2020) sought to understand 

why self-employment levels and trends in administrative data are higher 

than those revealed by household surveys. As reproduced in Figure B-2, 

6For example, monthly CPS to UI wage records are linked in Abraham et al. (2013). CPS 

ASEC records are linked to SSA’s Detailed Earnings Records (DER) in Abraham et al. (2018) 

and in Bollinger et al. (2019). CPS ASEC records are linked to nonemployer records (sourced 

from IRS Schedule Cs) in Abraham et al. (2020). 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

150

FIGURE B-2 Levels of unincorporated self-employed as measured by different sources.SOURCE: Analysis by K. Abraham, J. Haltiwanger, J. Spletzer, and K. Sandusky, based on data from U.S. Census Bureau, U.S. Department of the Treasury, CPS data, BLS website, and CPSASEC.

6,000,000

24,000,00018,000,00012,000,000

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

CPS Monthly, Main Job Last Week ACS, Main Job Last WeekCPS ASEC, Longest Job Last Year CPS ASEC, All Jobs Last YearNonemployers Nonemployer Sole Proprietors1099-MISC, Individuals 1099-MISC, Indiv + BusinessDER Self Employed

FIGURE B-2 Levels of unincorporated self-employed as measured by different sources.SOURCE: Analysis by K. Abraham, J. Haltiwanger, J. Spletzer, and K. Sandusky, based on datafrom U.S. Census Bureau, U.S. Department of the Treasury, CPS data, BLS website, and CPSASEC.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 151

levels of unincorporated self-employed varied substantially by source. The 

bottom four lines are based on data from household surveys: the Monthly 

CPS, the Census Bureau’s American Community Survey, and the Annual 

Social and Economic Supplement of the CPS (often referred to as the March 

supplement). The top five lines capture administrative sources: Social Security’s detailed earnings records, the 1099-MISC, and the Schedule SEs from 

the SSA. Each administrative data source indicates that the number of 

unincorporated self-employed is rising over time and substantially higher 

than the number of unincorporated self-employed measured in household 

surveys. 

The paper examines what is driving this difference by source in measured self-employment by linking the CPC ASEC to the SSA’s detailed 

earnings records. An attractive feature of this approach is that the CPS 

ASEC and the administrative tax data sources have the same annual reference frame. Spletzer also acknowledged minor differences, such as that 

self-employment is only reported on Schedule SE if earnings exceed $433. 

Again, findings based on administrative tax data were very different from 

those based on the CPS-ASEC. More than 50 percent of the CPS-ASEC 

respondents who identified as self-employed are not self-employed based 

on reporting to tax authorities. Conversely, 65 percent reporting to the tax 

authorities as self-employed are not showing up as self-employed in the 

CPS-ASEC—and that figure has increased over time.

Spletzer concluded with a few summary statements. He said research 

conducted at the Census Bureau that links CPS and administrative microdata has found that CPS-based and administrative data-based employment 

measures (such as wage and salary employment, multiple job holding, and 

self-employment) do differ, and some of these differences have grown over 

time. Spletzer asked why we would want to link the CWS to administrative 

data—is it to better understand measurement error or nonresponse bias, 

to improve imputations, or to reduce burden? In Spletzer’s view, research 

would need to overcome comparability issues, such as the use of different 

reference periods (e.g., “last week” versus quarterly or annually) and the 

problems arising from different concepts, such as the fact that administrative 

data do not measure “contingent work” or “electronically mediated work.”

During open discussion, potential problems with survey instruments 

were raised. Lim pointed out that a lot of people responding to a survey 

(such as the CPS) in which the first question is about the respondent’s main 

job will then have trouble shifting to accurately report self-employment 

(1099-K) income. Spletzer pointed out that the ASEC is a long survey, and 

that most of the income and earnings questions are placed at the end, so 

that by the time respondents reach them survey fatigue may have kicked 

in. Abraham added that the monthly CPS, which asks people about their 

work “last week,” is very different from the CPS-ASEC, which asks them 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

152 MEASURING ALTERNATIVE WORK ARRANGEMENTS

about their earnings over the whole prior year; answering these questions 

involves very different cognitive processes.

Robles raised the issue of how self-employment is categorized and 

measured given how diversely it manifests itself. For example, Schedule F 

employees are often overlooked even though they are in many ways similar 

to Schedule C workers. Partnerships, she suggested, were also important to 

capture, especially since, based on IRS data, they appear to have recently 

proliferated. Spletzer responded that the Census Bureau does publish nonemployer statistics by the legal form of organization. Eighty-seven percent 

of non-employers, he reported, are unincorporated sole proprietors. This, 

he suggested, is why he focuses on that group and calls them self-employed, 

which is what the Census Bureau does in their own publications. There are 

22 million of these unincorporated self-employed.

Strain added that, even if a respondent earns $10,000 or $20,000 of selfemployment income and it amounts to perhaps 10 percent of total income, 

that person could reasonably respond he or she is not self-employed. This 

speaks to the issue of how to design the survey question. 

Olson argued that the mismatch between the household survey data 

and the tax data is partially due to measurement error, in that people are 

not classifying things appropriately. She added that specifying the right 

probing questions would be helpful, but there is also a more fundamental 

issue about whether or not people see the work that they are doing, regardless of the source of payment, as being under the umbrella of what they 

consider to be their job. And this is very important when thinking about 

contingent and temporary work and understanding payment mechanisms 

that help survey designers write better questions. An example would be a 

university professor being paid her university salary for the year, but receiving a grant covering 3 of those months. In such a case one could reasonably say that she was paid by, say, the National Science Foundation or the 

National Institutes of Health, even though all the grant money was paid 

to her through the university. Even a reasonably informed person could 

become confused about that kind of question. 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 153

Panel on Measuring Contingent Work and Alternative Work Arrangements

Second Meeting—June 10, 2019

The National Academy of Sciences Building

The Board Room/Room 120

2100 Constitution Ave. NW

Washington, DC 20418

AGENDA

MEETING GOALS: During its first meeting, the panel heard from BLS 

experts about the history, measurement objectives, and past performance 

of the Contingent Worker Supplement (CWS) of the Current Population 

Survey (CPS). Working with BLS, the panel also sharpened the statement 

of task for the project. During this second meeting, the panel will continue 

information gathering by hearing presentations from data users and policy 

makers dealing with changing worker and employer dynamics. Sessions 

will include presentations and discussion of measurement objectives and 

policy needs, the measurement capabilities of household and other kinds 

of surveys, and the complementary (or possibly, in some cases, substitute) 

role of nonsurvey data such as administrative (e.g., tax) or commercial data.

OPEN PUBLIC SESSION

9:00 AM Welcome, Introductions, Agenda, and Reminder of the Study 

Charge

— Susan Houseman, Panel Chair

9:15 SESSION 1: POLICY CONTEXT FOR MEASURING ALTERNATIVE WORK. This session features presentations to help 

the panel round out its thinking about measurement objectives. 

Presenters will offer perspectives on (1) what information policy 

makers need to know and what questions remain unanswered 

(for example, how many people engage in supplemental work 

and what their motivations are), and (2) methodological and 

other considerations that allow data to be translated into policy. 

Definitions and boundaries for different categories of work—

contingent, independent (many of whom do not consider themselves as “contingent” or temporary), web-mediated, etc.—will 

be discussed.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

154 MEASURING ALTERNATIVE WORK ARRANGEMENTS

Legislative developments relating to alternative work. U.S. 

Senator Mark Warner is honorary co-chair of the Aspen Institute “Future of Work Initiative,” and his office has been active 

on issues pertaining to gig work. Carolina Young will update 

the panel on her work in Senator Warner’s office on relevant 

initiatives—such as proposed legislation that would direct the 

U.S. Treasury to study tax issues for gig economy workers—

and the kinds of data needed to inform this work. 

— Carolina F. Young, Policy Advisor, Office of U.S. Senator 

Mark R. Warner

Update on Future of Work Initiative projects and plans. The 

Aspen Institute’s Future of Work Initiative seeks to identify 

policy solutions to the challenges facing workers in the 21st 

century. The Initiative, along with Cornell’s ILR School, produced and maintains the Gig Economy Data Hub, an online 

resource that provides accessible summaries of data sources on 

independent and nontraditional work. Recently, the team has 

written on portable benefits, tax simplification for independent 

workers, and worker training tax credits. The Institute has 

recently released the report, “Designing Portable Benefits: A 

Resource Guide for Policymakers.”

— Alastair Fitzpayne, Executive Director of the Aspen Institute 

Future of Work Initiative; Shelly Steward, Research Manager, 

Future of Work Initiative

Open discussion

10:30 SESSION 1 (continued)

Worker well-being measurement issues. Unpredictable work 

schedules, particularly for low-income/low-skill workers, affect 

the well-being and security of those involved. Susan will discuss measurement challenges and needs for informing public 

policy around work hour standards and the benefits of a multidimensional approach to estimating the prevalence of different 

types of work hour arrangements.

— Susan Lambert, University of Chicago, School of Social 

Service Administration

Health and safety. The National Institute for Occupational 

Safety and Health is a federal research agency that has made 

work arrangements a key focus of its recently established 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 155

program on Healthy Work Design and Well-Being. Tim will 

describe this program and its recent attempts to define those 

work arrangements of greatest concern. He will also discuss 

the value of CWS data for NIOSH research, and suggest some 

ways in which expanded details on work arrangements could 

be of value.

— Tim Bushnell, Economic Research and Support Office, 

NIOSH; Toni Alterman, Division of Surveillance, Hazard 

Evaluations and Field Studies, NIOSH 

Employer and broader market policy issues. The new economy 

requires polices designed to make new employment models 

work well not just for employees, but also employers who hire 

them and for the markets in which they operate. Gene will 

speak about his organization’s work on policy issues shaping 

the independent workforce movement, as well as about how 

to think about different categories of workers.

— Gene Zaino, Chief Executive of MBO Partners

Open discussion

1:15 PM SESSION 2: INSIGHTS ABOUT ALTERNATIVE WORK 

FROM OTHER (NON-BLS) SURVEYS. Building on what was 

learned during meeting #1, this session includes presentations 

to help assess the range of questions that can best be answered 

using household surveys, and which questions require other 

kinds of data (whether stand-alone or linked to survey data), 

such as those derived from employer surveys, tax records, and 

commercial sources. 

Federal Reserve Board surveys. Barbara will review results for 

2018 from the Survey of Household Economics and Decisionmaking (SHED) and provide information about the survey’s 

questions. She may also comment on findings from the Enterprising and Informal Work Activities (EIWA) Survey, which 

estimates that a high percentage of workers (36 percent in 

2015) take part in freelance work.

— Barbara Robles, Panel member

Survey and policy work at the American Staffing Association. 

The ASA Staffing Employment and Sales Survey generates 

insights about intermediary employment arrangements. The 

survey collects information from staffing firms to estimate tem-
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

156 MEASURING ALTERNATIVE WORK ARRANGEMENTS

porary and contract staffing industry employment, sales, and 

payroll. Cynthia and Steve will describe the survey’s general 

methodology, how employment and payroll information differs from that generated from the CWS, what research is done 

using the survey, and what policy questions it helps to address. 

— Cynthia Davidson and Steve Berchem, American Staffing 

Association

Urban-rural variation in informal work activities. Leif will 

describe the background, methods, and findings of his collaborative research using a survey measuring geographic variation 

in informal work. He will address definitional questions about 

the types of informal work including unpaid and paid (off the 

books) work, the measurement strategy used to capture informal work, as well as (briefly) their findings on the prevalence 

of, reasons for, returns to, and correlates of informal work.

— Leif Jensen, Penn State University

Gallup Education Consumer Pulse Survey. Susan and Katharine 

will provide an update on their work developing a survey module for this Gallup survey consisting of 13 questions on respondents’ employment and the nature of their work arrangements. 

Goals of this work include assessing how well household surveys capture various types of contract and informal work and 

informing ways in which household surveys might be improved 

to better measure these types of work. Data collection is now 

complete, as is some initial analysis.

— Susan Houseman and Katharine Abraham, Panel members

Open discussion

3:15 SESSION 3: ADMINISTRATIVE (TAX) DATA ALTERNATIVES/

COMPLEMENTS TO SURVEY DATA. Building on the presentation by Diana Farrell on the use of commercial banking data 

during meeting #1, this session will further explore what can be 

learned from non-survey data sources, on their own or in combination with surveys, about alternative employment. The focus 

here will be on administrative data (as opposed to commercial 

data), specifically the benefits and limitations of using tax data. 

What can be learned about alternative work arrangements 

from tax data? (1). Dmitri may also comment on his analyses 

of rideshare drivers using personal financial service data 
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

APPENDIX B 157

containing information on rideshare income, outside income, 

spending, and liquid assets.

— Dmitri Koustas, University of Chicago

What can be learned about alternative work arrangements 

from tax data? (2). Mike and Diane will discuss the advantages 

and limitation of using tax data to measure various categories 

of alternative employment (including the size and scope of 

the platform economy), and how it can be used to inform tax 

policy. 

— Mike Udell and Diane Lim, District Economics Group

Census Bureau work combining data sources. Federal Research 

Data Centers (coupled with legislation) have allowed agencies 

and outside researchers to combine IRS data with existing 

Census surveys. Jim will discuss linking survey and tax data 

(in the context of LEHD or other programs) for the purpose of 

measuring independent contractor/self-employment work, and 

any implications that this might have for optimal design of the 

Contingent Worker Supplement.

— Jim Spletzer, Center for Economic Studies, U.S. Census Bureau

Open discussion

4:45 PM ADJOURN
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.

COMMITTEE ON NATIONAL STATISTICS

The Committee on National Statistics was established in 1972 at the 

National Academies of Sciences, Engineering, and Medicine to improve 

the statistical methods and information on which public policy decisions are 

based. The committee carries out studies, workshops, and other activities to 

foster better measures and fuller understanding of the economy, the environment, public health, crime, education, immigration, poverty, welfare, 

and other public policy issues. It also evaluates ongoing statistical programs 

and tracks the statistical policy and coordinating activities of the federal 

government, serving a unique role at the intersection of statistics and public 

policy. The committee’s work is supported by a consortium of federal agencies through a National Science Foundation grant, a National Agricultural 

Statistics Service cooperative agreement, and several individual contracts.
Measuring Alternative Work Arrangements for Research and Policy

Copyright National Academy of Sciences. All rights reserved.