Topic Archives: U.S. Statistical System

Wage Information Yesterday, Today, and Tomorrow

On April 16, BLS reported that median weekly earnings for full-time wage and salary workers rose 2.7 percent over the year.

On April 30, BLS reported that the Employment Cost Index for wages of private industry workers rose 3.0 percent over the year.

On May 2, BLS reported that hourly compensation in the nonfarm business sector rose 2.5 percent over the year.

On May 3, BLS reported that average hourly earnings for private industry workers rose 3.2 percent over the year.

What’s going on here? Why so much wage information? And which one is RIGHT?

At BLS, we get questions like this all the time, and the answer is usually “it depends.” There is no one answer that fits every question on wages; there are just different answers depending on what you want to measure. People come to BLS looking for all kinds of answers, and we want to provide as much information as we can. Thus, we have many measures of wages (and other forms of compensation) — a dozen, to be exact.

Do you want to know about wages for an industry? An occupation? By location? For men and women? Based on education? Adjusted for inflation? Including benefits? How wages relate to spending patterns? How wages relate to worker productivity? BLS has it all, and more.

We have so much wage information that even we get confused. So we developed a tool to make the dozen wage series a little easier to understand. It’s an interactive guide that lists all 12 data sources and 32 key details about each of those sources, like how often it is available.

I can hear you now — that’s 384 pieces of information (12 x 32). I’m just looking for one piece of information, not almost 400. And how do you fit all that information on one page, anyway?

The interactive guide limits the display to 3 sources at a time — you pick the sources you want to see.

A table showing 3 BLS sources of compensation information and data characteristics available from those sources.

Or you can pick one characteristic, like “measures available by occupation” and get an answer for all 12 data sources.

A table showing the occupational information available from several BLS data sources on compensation.

This tool is on the BLS beta site. We want you to give it a try and provide feedback. Check it out and leave us a comment. Want to know even more? Watch this video that helps make sense of BLS wage information.

BLS Local Data App Now Available for Android Devices

The wait is over! The BLS Local Data app — a mobile application that connects users with the data they need to know about local labor markets — is now available for Android devices. Search “BLS Local Data” in Google Play.

The BLS Local Data app, first released for iPhones last fall, uses the BLS API to present local data and national comparisons for unemployment rates, employment, and wages. You can search using your current location, a zip code, or a location name to find relevant data quickly without having to navigate through the huge BLS database. With one click, you can find data for states, metro areas, or counties.

BLS continues to partner with the U.S. Department of Labor’s Office of the Chief Information Officer to expand the features and data in the app. A second version is in development and will be available soon for both iPhone and Android devices. Version 2.0 will include employment and wage data for detailed industries and occupations. It also will have new charting functionality that will allow users to plot the historical unemployment rate time series for their local area of interest.

Check out the app and bring the wealth of local labor market data produced by BLS directly to your mobile devices!

The BLS Local Data App showing employment and wage data for Allegheny County, Pennsylvania.

Greetings and a Meditation on Alan Krueger

William W. Beach became the 15th Commissioner of Labor Statistics in March 2019.

I am a little late with my first blog, but I’m sure readers can appreciate what it means to start this job as Commissioner of Labor Statistics on a week that ends in the publication of the Employment Situation report.

Every moment of my first week at BLS has been highlighted by the unfailing grace and cheerfulness of the career staff.

I felt very strongly that my first blog as BLS Commissioner should be about the late Alan Krueger’s pioneering work, particularly as it relates to both the Department of Labor and the Bureau of Labor Statistics.

A Meditation on Alan Krueger
(1960 – 2019)

I have been thinking a lot about Alan Krueger since his passing on March 16. Thinking about the loss, of course: the shock of losing such a penetrating mind, such a courageous scholar. And thinking about the insights and breakthroughs he could yet have made: at 58, Alan Krueger was striding strongly.

The past three weeks have seen a steady flow of recollections in the popular and professional press. Let me recommend two highly accessible pieces: Ben Casselman and Jim Tankersley’s New York Times essay and Larry Summers’s deeply thoughtful recollection in the Washington Post. There are more out there and more to come.

I’m writing today to remind us of Professor Krueger’s close ties to our daily work. He, indeed, connected in so many ways. First, he was a consummate though sometimes reluctant government economist. Dr. Krueger served as the Department of Labor’s chief economist from 1994 to 1995, returned to the federal government service in 2009 as an assistant secretary in the Treasury Department from 2009 through 2010, and finally served on President Barack Obama’s Council of Economic Advisers from 2011 through 2013.

This service record as a government economist, as important as it is, is not Professor Krueger’s deepest tie to BLS. Rather, and second, he stood out among peers for his leadership as an empirical economist. Starting with his celebrated study of the economic effects of the minimum wage in 1994, when he and David Card pioneered the use of natural experiments in policy analysis, to his recent pathbreaking work on the opioid crisis, Alan Krueger made important contributions to our understanding of work and public policy through innovative use of data.

This is what ties him most to us, in my view. His sometimes controversial conclusions to one side, Professor Krueger looked at the world when he wrote. That may seem an obvious posture for any economist, but too often analysts look elsewhere: for instance, they wrap themselves in strictly theoretical work or confine their own work to the research channels that others have dredged. While theory and replication are essential parts of our profession, they cannot substitute for an active curiosity about the real world and how it is changing. Unless you’re looking out into the world, you may never see the amazing, new developments there that could inspire you to grow beyond the current limits of your economic understanding.

It will take time to define Alan Krueger’s legacy in economics and public policy, but this much is already clear: he left a strong marker of what it means to be a labor economist and a public servant, and he showed two generations of labor researchers that the most fruitful laboratory for economic science is the swirling, crazy world outside our office doors.

Tracking the Changing Nature of Work: the Process Continues

The days of working the same 9-to-5 job for 40 years are a fading memory. Work today may involve multiple part-time jobs, working from home, obtaining work through a mobile device, and changing jobs frequently. The so-called “changing nature of work” is already here, and at the U.S. Bureau of Labor Statistics we are trying to keep up with this new world.

One of our primary sources of information on Americans’ labor market activity is the Current Population Survey (CPS), a monthly survey of households that provides a real-time snapshot of the share of the population who are employed and unemployed. These data are complemented by other BLS programs that focus on labor turnover, how Americans spend their time, details about local labor markets, and other topics.

But how well do these programs track nontraditional forms of employment, including short-term assignments, platform work, temporary help, and jobs so new and different we haven’t even named them yet? BLS has been working on these issues for many years. Let’s consider a few timely questions and see how BLS has responded.

Not all jobs are permanent. What do we know about jobs that are not expected to last?

Throughout its history, BLS has been exploring perceived changes in the nature of work. For example, an article in the October 1996 Monthly Labor Review described “…reports of corporate downsizing, production streamlining, and increasing use of temporary workers…” as raising questions about “…employers’ commitment to long term, stable employment relationships.” This article, and many others in the same issue, went on to introduce the first “Contingent Worker Supplement” (CWS) to the CPS. Supplements such as this are additional questions on specific topics generally asked once (as opposed to every month) of CPS households.

The CWS asks about jobs that are not expected to last, as well as alternative work arrangements, such as working as an independent contractor or through a temporary help agency. While not an ongoing BLS program, we received funding to conduct the supplement in 1995, 1997, 1999, 2001, 2005, and 2017. This allows us to track contingent work over time. In May 2017, there were 5.9 million contingent workers – those who did not expect their job to last. This represented 3.8 percent of the total employed. Twelve years earlier, a slightly higher percentage, 4.1 percent, did not expect their job to last.

Percent of employed in contingent jobs

Editor’s note: Data for this chart are available in the table below.

How many people are in different types of jobs, such as independent contractors?

The CWS also included questions to identify people who were in four types of alternative work arrangements:

  • Independent contractors
  • On-call workers
  • Temporary help agency workers
  • Workers provided by contract firms

The most prevalent of these arrangements was independent contractors. The 10.6 million independent contractors identified in May 2017 represented 6.9 percent of the total employed.

Percent of employed in alternative arrangements

Editor’s note: Data for this chart are available in the table below.

Does BLS have a measure of the “gig” economy?

BLS does not have a definition of the gig economy or gig workers. In fact, researchers use many different definitions when they talk about the gig economy. You may think of a gig as something your high school band played on a Saturday night. Or today you might consider your ride-share driver as performing a gig. Classifying workers as gig could get very confusing. For example:

  • A plumber or electrician may be on the payroll of a contracting company on the weekdays and obtain individual jobs through an app on the weekend. Gig worker?
  • A substitute teacher in one school district may obtain assignments and pay through traditional means, while the neighboring district assigns and pays workers through an app. Is one a gig worker?

Confused? So am I. To repeat, BLS does not have a definition of gig. Definitions developed by others may overlap with contingent workers and some of those in alternative employment arrangements in the CWS. Rather than try to develop such a definition, BLS chose to focus new questions narrowly, as you will see in the next section.

What about work obtained through an app?

In preparing for the 2017 CWS, and knowing the interest in work obtained through an app on a phone or other mobile device, BLS added four questions about short jobs or tasks that workers find through an app or website that both links them with customers and arranges payment. Separate questions asked about in-person work (such as driving for a ride-sharing company or providing dog-walking services) and online-only work (such as coding medical records). At BLS, we call these jobs “electronically mediated employment.”

While BLS conducted some testing of the questions on electronically mediated employment and vetted them with a variety of stakeholders, the results made it clear that people had difficulty understanding the questions. This effort resulted in many false-positive answers, such as a surgeon who said all of his work was obtained through an app. BLS used companion information, where available, to recode responses. To be completely transparent, BLS published both the original and recoded data, but we encourage data users to focus on the recoded information. These results indicate that 1 percent of the employed in May 2017 – about 1.6 million people – held electronically mediated jobs. A slightly higher number of workers (990,000) held in-person jobs than online-only jobs (701,000). Note that some workers indicated they had both types of jobs.

Compared with workers overall, electronically mediated workers were more likely to be ages 25 to 54 and less likely to be age 55 and older.

Percent distribution of workers by age, May 2017

Editor’s note: Data for this chart are available in the table below.

Maybe these “app” jobs are a second job. Do we know how many people hold more than one job?

We get information from the CPS each month on the number of workers who hold more than one job. In 2018, there were 7.8 million multiple jobholders – about 5.0 percent of total employment in 2018. That’s around the same share of employment it has been since 2010, but it was below the rates recorded during the mid-1990s, which were above 6.0 percent.

With all these new types of work, is the BLS monthly employment information missing anyone?

As noted, the CPS is an authoritative source of labor market information and has provided consistent data for over three-quarters of a century. But BLS is always looking to improve its measures, and there are other data sources that can supplement the CPS. For example, the American Time Use Survey obtains information about an individual’s activities during a 24-hour period. Among the categories that may be identified are “income-generating activities,” such as making pottery for pay, playing in a band for pay, and mowing lawns for pay.

Recently, BLS looked at people who were not counted as “employed” but who participate in income-generating activities. The research suggested that between 657,000 and 4.6 million people participated in income-generating activities but were not otherwise counted as employed in the survey. Given that total employment is around 155 million Americans, this undercount ranges from 0.4 to 3.0 percent of the total.

The study also examined the extent that employed people who did informal work in addition to a regular job might not be correctly classified as multiple jobholders. The research found that reclassifying workers misclassified as single jobholders would increase the number of multiple jobholders somewhere between 3.0 percent and 20.7 percent.

What more is BLS doing to improve labor market measures?

So, yes, BLS is doing a lot to improve our labor market measures, and the work continues. We know there is likely a small number of people who are not counted as employed yet perform income-generating activities. We know that definitions and concepts may need to be updated from time to time. We know that some terms, like “gig,” are not well defined and mean different things to different people. And we know it is not easy to define or identify electronically mediated employment.

Given all this, we continue to move forward. BLS has contracted with the Committee on National Statistics, part of the National Academies of Sciences, Engineering, and Medicine, to convene an expert panel to address these issues and provide recommendations to BLS. This work began in late 2018 with a report due in early 2020. BLS will review the recommendations and, resources permitting, develop plans to test any new concepts or questions.

There’s been interest in emerging types of work for many years. It’s also a moving target, as the “changing nature of work” keeps changing. BLS has provided gold-standard data on America’s labor force for many years and will continue to research and refine and improve.

Percent of employed in contingent jobs
Year Percent of employed
February 1995 4.9%
February 1997 4.4
February 1999 4.3
February 2001 4.0
February 2005 4.1
May 2017 3.8
Percent of employed in alternative arrangements
Alternative arrangement May 2017 February 2005 February 2001 February 1999 February 1997 February 1995
Independent contractors 6.9% 7.4% 6.4% 6.3% 6.7% 6.7%
On-call workers 1.7 1.8 1.6 1.5 1.6 1.7
Temporary help agency workers 0.9 0.9 0.9 0.9 1.0 1.0
Workers provided by contract firms 0.6 0.6 0.5 0.6 0.6 0.5
Percent distribution of workers by age, May 2017
Workers 16 to 24 years 25 to 54 years 55 years and older
Total employed 12.4% 64.4% 23.1%
Workers with electronically mediated jobs 10.3 71.2 18.5
Electronically mediated jobs, in-person work 7.4 72.5 20.1
Electronically mediated jobs, online work 15.7 69.6 14.8

Why This Counts: What Types of Jobs Are in the U.S. Labor Market?

Ever wonder how many accountants there are in the United States? Or how much an occupational therapist gets paid? Or maybe you already have a job, but you’re thinking about working somewhere new. What areas or industries have the highest pay for your occupation?

We have the answers to these questions, plus much, much more!

The Occupational Employment Statistics (OES) survey publishes hundreds of thousands of estimates for employment and wages covering around 800 detailed occupations in 600 areas spanning all 50 states, the District of Columbia, and three territories: Guam, Puerto Rico, and the U.S. Virgin Islands.

That sounds impressive, but what does it mean? It means you can see employment and wages for occupations where you live or in the type of business where you work. OES provides specific information on the types of jobs found in each industry or area and their wages.

OES building blocks: occupation and industry

Before we dive into the deep end with data, let’s wade in a little by clarifying some terms. In our everyday lives, occupation and industry may be interchangeable, but in fact occupation refers to the worker and industry refers to the employer.

Occupation refers to what people do and the jobs people have. BLS uses the Standard Occupational Classification system to code workers into more than 800 different occupations based on their job duties. This system is the standard used by federal agencies to classify workers into occupations.

Industry refers to the types of businesses where people work. BLS uses the North American Industry Classification System to code business establishments into industries based on what they produce or sell. This also is the standard used by federal agencies to classify business establishments into industries.

Because we use these federally mandated coding structures, data users can easily compare OES data with other federal statistical programs.

Why does OES data count?

For this blog post, we will only focus on national level data. We’re saving state and area data for a later post. Let’s take a closer look at the occupational data for the United States and in certain industries.

People count on OES data to see employment by occupation

Did you know that the largest occupation in the United States is retail salespersons? This chart shows the 10 largest occupations, which together account for more than one in five jobs in the United States.

Employment in the largest occupations, May 2017

Editor’s note: Data for this chart are available in the table below.

According to May 2017 OES data, there were 4.4 million retail salespersons in the United States, accounting for 3 percent of all jobs. The largest three occupations combined account for 8 percent of all U.S. jobs and also include cashiers and combined food preparation and serving workers (each 3.6 million).

We also have data on some of the smallest occupations in the country, such as geographers, watch repairers, astronomers, fabric menders, and mine shuttle car operators. Each of these occupations has fewer than 5,000 jobs.

People count on OES data for wages by occupation

Eight of the 10 largest occupations in the United States had below-average wages. Retail salespersons ($27,460), combined food preparation and serving workers ($21,230), and cashiers ($22,130) had annual mean wages significantly below the average for all occupations of $50,620.

Registered nurses ($73,550) and general and operations managers ($123,460) were the largest occupations with above-average wages.

Annual mean wages for the largest occupations, May 2017

Editor’s note: Data for this chart are available in the table below.

People count on OES data to compare occupations

Occupational employment and wage information is useful to students and schools making investments in education. They can see which fields have the best prospects for getting a job with good wages.

The pairs of related occupations in the table below show wages are generally higher for the occupation with more education and training requirements. In many cases employment is higher in the occupation with more education or training, and in some cases employment is lower.

 Median wage and employment data by select occupations, May 2017

Occupation Median hourly wage Employment
Mechanical Drafters $26.50 58,190
Mechanical Engineers $41.29 291,290
Cooks, Restaurant $12.10 1,276,510
Chefs and Head Cooks $22.09 131,430
Shampooers $9.77 13,330
Hairdressers, Hairstylists, and Cosmetologists $11.95 351,910
Retail Salespersons $11.16 4,442,090
First-Line Supervisors of Retail Sales Workers $18.54 1,200,180
Bookkeeping, Accounting, and Auditing Clerks $18.87 1,532,340
Accountants and Auditors $33.34 1,241,000
Dental Assistants $18.09 337,160
Dental Hygienists $35.61 211,600
Light Truck or Delivery Services Drivers $15.12 877,670
Heavy and Tractor-Trailer Truck Drivers $20.42 1,748,140

People count on OES data to see the types of jobs in each industry

OES data can complement other BLS data by showing the different types of jobs in each industry. For example, healthcare and social assistance is one of the largest industries in the United States. OES data show the types of jobs in this industry. This chart shows the 10 largest occupations in the health care and social assistance industry.

Largest occupations in health care and social assistance, May 2017

Editor’s note: Data for this chart are available in the table below.

Although many of the largest occupations in health care and social assistance are concentrated in this industry, some of the largest occupations in this sector, such as childcare workers, general office clerks, and receptionists and information clerks, can be found in many other industries as well. Jobseekers or workers wanting to increase their wage can use OES data to see which industries pay more by occupation.

The top paying industries for receptionists and information clerks include utilities ($34,780), construction ($31,070), and manufacturing ($30,900), in addition to health care and social assistance ($30,840). According to the May 2017 OES estimates, the national average annual wage for receptionists and information clerks was $29,640.

Industries with the highest annual mean wages for receptionists and information clerks, May 2017

Editor’s note: Data for this chart are available in the table below.

Who uses OES data?

Employers frequently use OES data for their industry. Business startups and entrepreneurs use the data to help determine typical staffing needs and expenses for businesses similar to theirs. Established businesses use occupational wage distributions to ensure they remain competitive and retain and attract good workers. In addition, OES data are used by students, jobseekers, and career advisors to help with career planning.

You may also encounter OES data in other places, because the data are used by a number of other federal agencies. The BLS Employment Projections program uses industry staffing patterns and wages from OES to produce estimates of future job growth. The U.S. Department of Labor Office of Foreign Labor Certification uses OES data to set prevailing wages for visa applicants. The Bureau of Economic Analysis uses OES wages to estimate social security receipts. The Centers for Medicare and Medicaid Services use the data to set reimbursement rates for health care providers. These are just a few of the ways OES data are used by other government programs and agencies.

 Want to know more?

You can further explore all of the reasons why OES data count at the OES homepage. Read the latest OES news release, get answers to frequently asked questions and check out our maps. Also, contact the OES information staff with questions by email or call (202) 691-6569.

Use these gold-standard data to learn more about your current occupation or to find out about new ones. Whatever your occupational employment question, “We have a stat for that!”

Employment in the largest occupations, May 2017
Occupation Employment
Retail salespersons 4,442,090
Combined food preparation and serving workers, including fast food 3,576,220
Cashiers 3,564,920
Office clerks, general 2,967,620
Registered nurses 2,906,840
Customer service representatives 2,767,790
Laborers and freight, stock, and material movers, hand 2,711,320
Waiters and waitresses 2,584,220
Secretaries and administrative assistants, except legal, medical, and executive 2,254,820
General and operations managers 2,212,200
Annual mean wages for the largest occupations, May 2017
Occupation Annual mean wage
General and operations managers $123,460
Registered nurses 73,550
All Occupations 50,620
Secretaries and administrative assistants, except legal, medical, and executive 36,920
Customer service representatives 35,650
Office clerks, general 33,910
Laborers and freight, stock, and material movers, hand 29,690
Retail salespersons 27,460
Waiters and waitresses 25,280
Cashiers 22,130
Combined food preparation and serving workers, including fast food 21,230
Largest occupations in health care and social assistance, May 2017
Occupation Employment
Registered nurses 2,557,530
Personal care aides 1,944,270
Nursing assistants 1,344,390
Home health aides 783,910
Medical assistants 614,180
Licensed practical and licensed vocational nurses 608,080
Medical secretaries 539,680
Receptionists and information clerks 478,800
Office clerks, general 364,060
Childcare workers 330,090
Industries with the highest annual mean wages for receptionists and information clerks, May 2017
Industry Annual mean wage
Utilities $34,780
Management of companies and enterprises 31,970
Finance and insurance 31,180
Transportation and warehousing 31,110
Wholesale trade 31,080
Construction 31,070
Manufacturing 30,900
Health care and social assistance 30,840
Federal, state, and local government, excluding state and local schools and hospitals and the U.S. Postal Service 30,710
Mining, quarrying, and oil and gas extraction 30,710