American
Working
Conditions
Nicole Maestas, Harvard
Kathleen Mullen, RAND
David Powell, RAND
Till von Wachter, UCLA
Jeffrey Wenger, RAND
October 8-9, 2015
SIEPR Conference on Working Longer and Retirement
Stanford University
Funding gratefully acknowledged from
Alfred P. Sloan Foundation Working Longer Program
Michigan Retirement Research Center (SSA)
Americans Poised for
Longer Work Lives
• Employment rates at older ages have risen since the
mid-1990s
• Recent cohorts of middle-aged workers expect to work
longer than older cohorts
• Gains in longevity and health (Milligan and Wise, 2012)
• Work capacity at older ages is substantial (Cutler et al., 2011)
• Many potential benefits of longer work lives
– Some improvement in government budgets (Smith and Johnson,
2013)
– Personal financial security
– Better health (e.g., Rohwedder and Willis, 2010)
On the Other Hand…
• Median retirement age still 62 (2015 Retirement Confidence Survey)
• More people plan to work at older ages than actually
work (Maestas, 2010)
• Older job seekers less likely to find matches than
younger job seekers (von Wachter et al., 2009; Chan and Stevens 2001;
Maestas and Li 2006)
• Many reasons why actual employment may be below
potential employment
–
–
–
–
Access to pension income facilitates increased leisure
Health shocks to self or family members
Age discrimination (Lahey, 2008)
Social Security policies (e.g., U.S. earnings test)
Another Reason: Job Match Quality
• Workers’ have preferences over job characteristics; may
affect labor supply choices
– Preferences may change with age or focal life events
• Qualitative evidence of a gap between desired and available
jobs (Pitt-Catsouphes et al., 2015)
– Older workers say they desire: flexibility, meaningful work, pay
and benefits, opportunities for advancement, transferable skills,
supportive work environment
• But do these gaps have quantitatively important effects on
labor force participation?
– More so for older older workers than younger?
• What working conditions make work sustainable over a
longer work life?
Hedonic Model of Compensating
Differentials (Rosen 1974; Hwang et al. 1992)
• Jobs characterized by wage and non-wage attributes
• People demand jobs with particular attributes
– Heterogeneous people value jobs according to utility-bearing attributes
– Choose job to maximize utility over consumption, leisure, and job
attributes, subject to budget constraint
– Supply labor if job-specific utility > reservation utility
• Firms supply jobs with particular attributes
– Heterogeneous firms maximize profits
– Cost of “producing” jobs constrained by production technology and
factor markets
• Competitive equilibrium matches people to jobs, gives rise to
observed distribution of job characteristics
– Pareto optimal only under stylized case of no frictions
– Are all firms able to fill all jobs and do all workers have their utilitymaximizing job?
Our Approach
1. Field new survey of working conditions in the U.S.
– American Working Conditions Survey fielded July-Oct 2015
(N≅3000)
– Field on nationally representative RAND American Life Panel (ALP)
– Harmonized with 6th European Working Conditions Survey (EWCS)
2. Conduct “stated preference” experiments in ALP to measure
preferences over job attributes
– Solves key identification issue under certain conditions
– Pilot testing complete, ready to field
3. Compare stated preferences for job attributes with
subsequent (actual) employment transitions
–
In progress
R’s asked
to focus on
“main job”
AWCS Survey Domains
Wage/salary
Hours
Control over
hours
Location of
work
Paid time off
Pace
Autonomy
Stress
Physical
demands
Social
support at
work
Learning on
the job
Meaningful
work
AWCS Results—Selected
Characteristics
• Preliminary Data—95% complete
– Target N=3000
– Response rate 77%
• Note of caution: differences across age groups
reflect
– Actual differences by age
– Selection effect—people with least desirable
working conditions select out of the labor force
earliest
Employment Rates
Table 1. Employment Rates in AWCS and CPS
American Working Current Population
Conditions Survey
Survey
(2015)
(2014)
75.0
72.2
66.4
61.0
10.6
11.6
10.8
7.1
12.7
4.2
15.0
4.9
12.3
12.4
26.3
26.1
42.1
41.2
36.9
36.6
Men
Women
Men
Self-Employment*
Women
Men
% with Multiple Jobs*
Women
Men
% Working PT (<35 hours)*
Women
Men
Average Hours per Week (Main Job)*
Women
Sample: Ages 18-71, N=3000
*Conditional on working for pay
Results weighted using raked sample weights (AWCS) and CPS final weights.
% Working for Pay
Control over Hours
Physical Demands
Physical Demands
Work Intensity
Working with Others
Health at Work
Health at Work
Satisfaction at Work
Effect of Selected Job Attributes on
Job and Life Satisfaction
Standing
Working at very high speed
Low task autonomy
Working to tight deadlines
Carrying or moving heavy loads
Tiring or painful positions
Work 10+ hours for 10+ days/mo
No very close friends at work
Job Satisfaction
Life Satisfaction
0.1
(0.1)
0.2*
(0.1)
-0.4**
(0.1)
-0.1
(0.1)
0.2+
(0.1)
-0.3**
(0.1)
-0.1
(0.1)
-0.4**
(0.1)
-0.3*
(0.1)
0.1
(0.2)
-0.2
(0.2)
-0.4**
(0.2)
0.2
(0.2)
-0.7**
(0.2)
-0.7**
(0.2)
-0.4*
(0.2)
Controls include race, ethnicity, age, sex, education, self reported health status, and quartile of family income.
Measuring Value of Job Attributes
• Observed job matches reveal how much people
value particular job attributes
• Regress wages on job attributes to find implicit
value or “price” of each attribute
• Identification issue: observational relationship
biased by unobserved productivity differences
(Hwang et al., 1992)
• Stated preference experiments are one
approach to solve the identification issue
Creating Realistic Choice Sets
• Define baseline job for each respondent based on
current, most recent, or default job
– Jobs have offered wage and 10 attributes, each taking
multiple values
• Create hypothetical job pairs
– Starting from baseline job, randomly select 2 attributes to
vary plus the wage
– Randomly vary values on selected attributes within each
pair
• Respondent indicates the job they prefer
• Each respondent evaluates 10 choice scenarios
Stated Preferences Pilot Estimates
Table 1. Effect of Job Attribute on Predicted Probability of Job Acceptance (Relative to Reference Attribute)
Ages 18-49
Ages 50-71
Set Own Schedule
0.093
0.116***
(v. Schedule set by manager)
(0.048)
(0.085)
0.023
Telecommute Option? Yes
0.205**
(v. No)
(0.049)
(0.096)
0.044
Moderate Physical Activity
0.140
(v. Mostly sitting)
(0.074)
(0.141)
-0.275***
Intensive Physical Activity
-0.012
(v. Mostly sitting)
(0.052)
(0.143)
0.135***
Relaxed Work Environment
0.036
(v. Fast-paced)
(0.050)
(0.091)
-0.116***
Tasks Well-defined
0.011
(v. You choose how to do the work)
(0.042)
(0.086)
0.164***
10 days PTO
0.019
(v. 0 days PTO)
(0.065)
(0.147)
0.379***
20 days PTO
0.305***
(v. 0 days PTO)
(0.052)
(0.111)
-0.173***
Team-Based, Evaluate by Team
0.153
(v. Work alone)
(0.063)
(0.136)
Team-Based, Evaluate Own
0.359***
0.065
(v. Work alone)
(0.143)
(0.075)
Thank you!
Appendix A.
Stated Preference Methodology
Design Choices
• Which job attributes to feature?
• How to create realistic “jobs”?
Ten Attributes
1. Wage/Salary
– Hourly
– Salaried
– Expressed as % of last wage/salary [prefilled]
2. Full-Time vs. Part-Time (no hours specified)
3. Control over Hours
– Little control over weekly hours
– A lot of control over weekly hours
4. Location of Work
– Must work on-site
– Opportunities to work remotely
Ten Attributes
5. Physical Demands
– Primarily sitting throughout work day
– Job requires moderate physical demands (e.g., standing for periods of
time, walking)
– Job is physically-demanding (e.g., lifting, stooping)
6. Meaningful work
– Mission-oriented
– Personally satisfying
7. Stress
– Job is fast-paced with externally-imposed goals
– Relaxed environment with externally-imposed goals
– Relaxed environment, opportunities for self-initiated work
Ten Attributes
8. Paid Time Off
– Generous paid time off (sick days, vacation) plus availability of
additional unpaid sick leave
– Some paid time off (sick days, vacation) plus availability of
additional unpaid sick leave
– Unpaid sick leave availability
9. Working with others
– Primarily work by yourself
– Frequently work within teams
– Frequently work within teams in a friendly/social environment
10. Learning on the job
– Firm offers opportunities to learn new skills
Creating Realistic “Jobs”
• Define “baseline” job attribute values for each R
based on current or recent job
– 10 attributes, each taking multiple values
• Create hypothetical job pairs
– Starting from baseline job, randomly select 2 attributes to
vary plus the wage
– Randomly vary values on selected attributes within pair
• Re-randomize if procedure yields identical jobs
• Some restrictions to ensure feasible attribute combinations
– Specify common background attributes (e.g., “Both jobs
offer the same benefits.”)
Evaluating Job Pairs
• For each pair, R indicates if
–
–
–
–
“Strongly Prefer Job A”
“Prefer Job A”
“Prefer Job B”
“Strongly Prefer Job B”
• Each R evaluates 10 job pairs
– 1 profile test question where one job clearly dominates
– 7 profiles centered on current job
– 2 profiles centered on jobs commonly preferred by older
workers
Analysis of SP Data
• We interpret individual choices as reflecting a
comparison of indirect utility under each choice
• Logit estimation of the probability of choosing a job
as a function of job attributes, wage
• Relate stated preferences to subsequent job transitions
and associated changes in job attributes
Appendix B: Selected American
Working Conditions Survey Questions
Compensation
• Looking at this list, please select the category or categories
which apply to your main job?
–
–
–
–
–
–
–
–
Sole director of own business
Operating (or a partner in) a business or professional practice
Working for yourself
Working as a subcontractor
Doing freelance work
Paid a salary or a wage by an agency
Other
Don’t know
Hours
• How many hours do you usually work per week in your main
paid job?
• How many days per week do you work in your main paid job?
• Besides your main paid job, do you have any other paid jobs?
Average hours in other jobs?
• Provided that you could make a free choice regarding your
working hours and taking into account the need to earn a
living: how many hours per week would you prefer to work in
TOTAL?
• Plus: Overtime, Shift work, Night work, Variation in weekly
hours (and notice)
Control over Hours
• How are your working arrangements set?
– They are set by the company/organization with no possibility for
changes
– You can choose between several fixed working schedules determined
by the company/organization
– You can adapt your working hours within certain limits
– Your working hours are entirely determined by yourself
• Do changes to your work schedule occur regularly? If so, how
long before are you informed about these changes?
• In general, do your working hours fit in with your family or
social commitments outside work very well, well, not very
well or not at all well?
Pace of Work
• Does your job involve…
– Working at high speed?
– Working to tight deadlines?
• Is your pace of work dependent on…
– The work done by colleagues
– Direct demands from people such as customers, passengers, pupils,
patients, etc.
– Numerical production targets or performance targets
– Automatic speed of a machine or movement of a product
– The direct control of your boss
Working with Others
• Do you work in a group or team that has common tasks and
can plan its work?
–
–
–
–
Yes, always in the same one
Yes, in more than one team at the same time
Yes, in more than one team over the course of a year
No, I do not work in such a team or group
• For the team in which you work mostly, do the members
decide by themselves…?
– …on the division of tasks
– …who will be head of the team
– …the timetable of the work
Autonomy
• Are you able to choose or change... ?
– Your order of tasks
– Your methods of work
– Your speed or rate of work
• Generally, does your main job involve…
–
–
–
–
–
–
Meeting precise quality standards
Assessing yourself the quality of your own work
Solving unforeseen problems on your own
Monotonous tasks
Complex tasks
Learning new things
Work Location
• During the last 12 months how often have you
worked in each of the following locations?
– My employer’s/my own business’s premises (office,
factory, shop, school, etc.)
– Clients’ premises
– A car or another vehicle
– An outside site (construction site, agricultural field, streets
of a city)
– My own home
– Other
Physical Conditions
• Are you bothered by any of the following in the place you
spend most of your working time?
– Noise from coworkers; background noise (e.g., music, machines,
outside noise, etc.)
– Lack of cleanliness
– Poor lighting (too bright or dim)
– Lack of natural light
– Too hot or humid; too cold
– Unpleasant scents, odors or vapors
– Poor ventilation or air flow
– Inadequate furniture; outdated equipment
– Inadequate toilet facilities, eating or break facilities
– Inadequate parking
– Unsafe surrounding area
Exposures
• Are you exposed at work to…?
–
–
–
–
–
–
–
–
–
Vibrations from hand tools, machinery, etc.
Noise so loud that you would have to raise your voice to talk to people
High temperatures which make you perspire even when not moving
Low temperatures whether indoors or outdoors
Breathing in smoke, fumes (such as welding or exhaust fumes), powder
or dust (such as wood dust or mineral dust) etc.
Breathing in vapors such as solvents and thinners
Handling or being in skin contact with chemical products or substances
Tobacco smoke from other people
Handling or being in direct contact with materials which can be
infectious, such as waste, bodily fluids, laboratory materials, etc.
Physical Demands
• Does your main job involve…
–
–
–
–
–
–
Tiring or painful positions
Lifting or moving people
Carrying or moving heavy loads
Sitting
Repetitive hand or arm movements
Dealing directly with people who are not employees at your workplace
such as customers, passengers, pupils, patients, etc.
– Working with portable computing devices (such as laptops, tablets or
smartphones)
– Standing
– Working with computers
Meaningful Work
• In general how often does your work provide you with the
following:
–
–
–
–
–
–
–
–
Opportunities to fully use my talents
Ways to fulfill my potential
A positive effect on my community and society
A sense of personal accomplishment
Goals that I aspire to
Opportunities to develop good judgment and decision making
The satisfaction of work well done
The feeling of doing useful work
Learning on the Job
• Which of the following statements best describes your skills at
work?
– I need further training to cope well with my duties
– My present skills correspond well with my duties
– I have the skills to cope with more demanding duties
• Over the past 12 months, have you undergone any of the
following types of training to improve your skills?
– Training paid for or provided by your employer
– Training done on your own initiative outside your workplace
– On-the-job training (by co-workers, supervisors)
Presenteeism/Work Productivity
• Thinking about the last time you worked while sick or ill, how
much did your illness affect your work productivity (e.g., the
amount or kind of work you were able to do, or whether you
worked as carefully as usual).
Percent reduction in productivity due to illness:
0 10 20 30 40 50 60 70 80 90 100
Modification of Work Productivity and Activity Impairment Questionnaire
Work Outside of the Main Job
• Apart from your main job, do you earn income from any of the
following?
–
–
–
–
–
–
–
–
Regular part-time work
Temporary work (e.g., Manpower, Kelly, other temp agency)
Independent contracting or consulting (e.g., fixed fee for service)
On-demand services (e.g., Uber, Lyft, Handy, TaskRabbit, Medicast,
Axiom, Eden McCallum, Instacart, etc.)
Internet-based sales of goods (e.g., Etsy, eBay, KRRB, etc.)
Online labor markets (e.g., ODesk, MTurk, Freelancer.com, etc.)
Home-based sales of goods or services (e.g., cosmetics, crafts,
childcare, handyman, etc.)
Day labor (e.g., gardening, construction, other tasks; finds new work
each day but not through an internet service)
Appendix C. Additional Slides
for Longer Presentation
Ample Scope for Frictions
• Workers may have difficulty assessing match quality ex ante
– Multidimensional jobs hard to evaluate (complexity)
– Match quality tends to be revealed with experience
– Shocks to job attributes, productivity, worker preferences, wealth
• Bundling of job attributes may limit spectrum of combinations
– May lead to thin/incomplete markets for some desired combinations
– Although reduces complexity
• Switching costs may inhibit transitions to better matches
– Job lock due to pay and benefits
– Search costs, risk of prolonged unemployment
• Firms may have imperfect information about the productivity of
older workers
– Limited understanding of age-related cognitive heterogeneity
– Firms may underinvest in labor-enhancing technologies if don’t
account for social value of employing older workers
AWCS Survey Structure
Screener of
Employment Status
Employed
Unemployed/NILF
Why left last job?
American Working
Conditions Survey
Open to the right
job?
Future job qualities
Barriers
AWCS Harmonized with the 6th
European Working Conditions Survey
• Face-to-face interviews of random sample of 41,000
workers in 35 countries (1,000-3,300 per country)
– 28 EU countries
– 5 EU candidate countries (Albania, the former Yugoslav
Republic of Macedonia, Montenegro, Serbia, and Turkey)
– Switzerland and Norway
• Fieldwork began in Spring, now ending
• “First findings” in November 2015
• Closely harmonized efforts in the U.S., Korea,
possibly Brazil and China
Physical Demands
Work Intensity
Health at Work
Work Ability
% Unable to Do the Same
Job Physically or Mentally in
10 years*
Results weighted using raked sample weights
Physically
Mentally
Men
Women
Men
Women
40-49
12.6
8.6
6.7
6.6
50-59
15.9
18.2
6.5
10.1
Work Intentions
Stated Percent Chance of
Working after Age 62*
No College
Degree
College
Degree
Men
Women
Men
Women
25-39
57.1
58.5
61.5
62.0
40-49
64.9
64.9
76.2
68.2
50-61
67.2
62.2
76.6
69.4
Results weighted using raked sample weights
Those who report a 50 percent chance and then indicated that this meant they were "unsure" are dropped from the
sample.
* Those 62 years old and older are asked about the probability of working 12 months in the future.