Tag Archives: Employment Situation

What is “Benchmarking” of Bureau of Labor Statistics Employment Data?

August 21, 2019BLS Commissioner

BLS has released the “preliminary benchmark” information for the Current Employment Statistics (CES) survey, the source of monthly information on jobs.

You know what a bench is

Image of a park bench

and you know what a mark is,

Image of a checkmark

but what pray tell is a benchmark? And what does this preliminary benchmark tell us?

So as not to bury the lead, I’ll let you know that this year’s preliminary estimate of the benchmark revision is a bit bigger than it has been in the last few years. Our preliminary estimate indicates a downward adjustment to March 2019 total nonfarm employment of 501,000. Still, that estimated revision is only -0.3 percent of nonfarm employment. In most years our monthly employment survey has done a good job at estimating the total number of payroll jobs. More details on that below. This year our survey estimates are off more than we would like. Our goal is to provide estimates that are excellent and not just good or pretty good, and that’s why we benchmark the survey data each year.

What is benchmarking and why do we do it?

The CES is a monthly survey of approximately 142,000 businesses and government agencies composed of approximately 689,000 individual worksites. As with all sample-based surveys, CES estimates are subject to sampling error. This means that while we work hard to ensure those 689,000 worksites represent all 10 million worksites in the country, sometimes our sample may not perfectly reflect all worksites. So the monthly CES estimates aren’t exactly the same as if we had counted employment from all 10 million worksites each month. To fix this problem, we “benchmark” the CES data to an actual count of all employees, information that’s only available several months after the initial CES data are published.

In essence, we produce employment information really quickly from a sample of employers, then anchor that information to a complete count of employment once a year.

The primary source of the CES sample is the BLS Quarterly Census of Employment and Wages (QCEW) program, which collects employment and wage data from states’ unemployment insurance tax systems. This is also the main source of the complete count of employment used in the benchmark process. QCEW data are typically available about 5 months after the end of each quarter.

Each year, we re-anchor the sample-based employment estimates to these full population counts for March of the prior year. This process—which we call benchmarking—improves the accuracy of the CES data. That’s because the population counts are not subject to the sampling and modeling errors that may occur with the CES monthly estimates. Since the CES data are re-anchored to March of the last year, CES estimates are typically revised from April of the year prior up to the March benchmark. Then estimates from the benchmark forward to December are revised to reflect the new March employment level.

We will publish the final benchmark revision in February 2020 and will incorporate revisions to data from April 2018 to December 2019. (Thus, we’re not showing a 2019 number in graph and table below). On August 21, BLS released a first look at what this revision will be—what we call the “preliminary benchmark.” This preliminary benchmark gives us an idea of what the revised nonfarm employment estimates for March 2019 will be.

The size of the national benchmark revision is a measure of the accuracy of the CES estimates, and we take pride that these revisions are typically small.

Chart showing differences in nonfarm employment after benchmarking, 2009–18

For total employment nationwide, the absolute annual benchmark revision has averaged about 0.2 percent over the past decade, with a range from −0.7 percent to +0.3 percent.

The following table shows the total payroll employment estimated from the CES before and after the benchmark over the past 10 years. For example, pre-benchmark employment for 2018 was 147.4 million; post-benchmark employment was also 147.4 million.

Nonfarm employment estimates before and after benchmarking, March 2009–March 2018
Year	Level before benchmark	Level after benchmark	Difference	Percent difference
2009	132,077,000	131,175,000	-902,000	–0.7
2010	128,958,000	128,584,000	-374,000	–0.3
2011	129,899,000	130,061,000	162,000	0.1
2012	132,081,000	132,505,000	424,000	0.3
2013	134,570,000	134,917,000	347,000	0.3
2014	137,147,000	137,214,000	67,000	<0.05
2015	140,298,000	140,099,000	-199,000	–0.1
2016	142,895,000	142,814,000	-81,000	–0.1
2017	144,940,000	145,078,000	138,000	0.1
2018	147,384,000	147,368,000	-16,000	<-0.05

The 2019 preliminary benchmark revision is following the same pattern, with an estimated difference of -0.3 percent. We provide this first look at the benchmark revision to give data users a sense of what we are seeing in the data. The final benchmark may be a little different—could be higher, could be lower. But based on recent experience, we are confident the benchmark released next February will show only a moderate difference from what we’ve been publishing each month and will validate the accuracy of our monthly CES estimates.

Want to know more? See our Current Employment Statistics webpage, send us an email, or call (202) 691-6555.

Tags: Employment Situation, Labor market trends, Methodology, Statistics awareness

BLS Local Data App Now Available for Android Devices

April 17, 2019BLS Commissioner

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.

Tags: BLS products and services, Data visualization, Employment Situation, Labor market trends, New tools, Regions and states, Statistics awareness, Unemployment

Greetings and a Meditation on Alan Krueger

April 9, 2019BLS Commissioner

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.

Topics: BLS Management | Earnings and Wages | U.S. Statistical System

Tags: BLS staff, Employment Situation, Statistics awareness

Tracking the Changing Nature of Work: the Process Continues

February 12, 2019BLS Commissioner

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

Tags: Contingent workers, Contract workers, Employment Situation, Independent contractors, Interviews, Labor market trends, New tools, On-call workers, Statistics awareness, Temporary workers

What Do We Know about Mega Metros?

January 23, 2019BLS Commissioner

Not only does BLS produce nationwide economic indicators, but we also have a treasure trove of data for metropolitan areas across the country.

According to the U.S. Census Bureau, 62.9 percent of our country’s 325.7 million people live in incorporated places. To celebrate our metro areas, we looked at the data for our six largest ones. We started with five but expanded to six, and you’ll soon see why.

Just a little history

You can track our march west as a nation, and, later, to the Sun Belt, in this list of the six most populous U.S. cities:

New York City: Since the first census in 1790, New York has been our most populous city. Its population of 8.6 million makes it more than twice as large as the next largest city, Los Angeles.
Los Angeles City: With a population of about 4 million, Los Angeles first showed up on the top-five list with the 1930 Census.
Chicago City: Even with little population growth over the last several years, Chicago remains the third-largest city, with a population of 2.7 million. Chicago first showed up on the top-five city list in 1870.
Houston City: And now we get to the Sun Belt, which seems to expand every year. Houston, with a population of 2.3 million, was a top-five city starting in 1980.
Phoenix City: In 2016, Phoenix beat out Philadelphia for the number five spot on the most populous city list. In July 2017, its population was 1.6 million.
Philadelphia City: Since Philadelphia was the second most populous city in 1790 and remained within the top five until Phoenix nudged it out in 2016, we kept it on our list. Philadelphia’s population is almost 1.6 million.

What makes a metro area great?

That’s easy—its people! So what’s happening with the people in each metro area? Are they working? Where do they work? What type of work? What are their earnings? How do they spend their money?

For the rest of this blog, we will use the Office of Management and Budget’s Metropolitan Statistical Areas to define our mega metros:

New York-Newark-Jersey City, NY-NJ-PA Metropolitan Statistical Area
Los Angeles-Long Beach-Anaheim, CA Metropolitan Statistical Area
Chicago- Naperville-Elgin, IL-IN-WI Metropolitan Statistical Area
Houston-The Woodlands-Sugar Land, TX Metropolitan Statistical Area
Phoenix-Mesa-Scottsdale, AZ Metropolitan Statistical Area
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD Metropolitan Statistical Area

We won’t use these long titles, but we will compare the areas listed above.

What’s the unemployment rate?

In November 2018, the national unemployment rate was 3.5 percent. Los Angeles had the highest rate (4.2 percent) among these six areas. Phoenix (3.9 percent), Houston (3.8 percent), Chicago (3.8 percent), Philadelphia (3.6 percent) and New York (3.3 percent) round out our list. New York had the largest over-the-year decrease in their unemployment rate among these six areas from November 2017 to November 2018 (-0.9 percentage point). Los Angeles was the only one of the six metro areas that had an over-the-year increase (+0.2 percentage point) in the unemployment rate.

How about the number of jobs? Has that been going up?

As we walk around our metro areas, we will see more folks going to work than a year ago. Nonfarm payroll employment increased for all of these areas from November 2017 to November 2018. Two showed growth rates above the national average—4.2 percent in Phoenix and 3.7 percent in Houston. The other four areas showed growth rates of 1.5 percent or lower. The national growth rate was 1.6 percent.

Where are people employed? What industries?

What industries employ the most workers? Trade, transportation, and utilities is the biggest industry, with 28.5 million workers nationwide. Education and health services (24.1 million workers) comes in second.

As we walk around each of these metro areas, what industries will we see employing our workers? Basically the same as the nation! In four of the six areas (all but New York and Philadelphia), trade, transportation, and utilities is the biggest industry. For both New York and Philadelphia, the biggest industry is education and health services.

What kind of occupations do people have?

What occupations do these folks have? This might sound like what we just covered, but occupation and industry are different. For example, I’m an economist (occupation) who works in government (public administration industry), but I could be an economist who works in a bank (financial activities industry).

I must admit I was surprised that, for all of our metro areas and the nation, these are the three largest occupational groups for our workers: office and administrative support occupations, sales and related occupations, and food preparation and serving related occupations. So as you walk around these metro areas, you will see people hurrying to work on a computer, sell an item, or cook a meal!

What about earnings? Do they vary much by metro area?

Nationwide, average hourly earnings in November 2018 for all employees were $27.28. Phoenix had the lowest average hourly earnings among these six areas, at $27.22. The highest average hourly earnings were in New York, $32.83. That’s a difference of $5.61 per hour between the highest and lowest averages among these six metro areas.

Where do folks spend their money?

Because of small sample sizes for metro areas, we’ll use an average of 2016–17 data on consumer spending for metro areas and the United States. Consumers in the three largest areas—New York, Los Angeles, and Chicago—all allocate a larger share of their total spending to housing than the national average. The U.S. housing average is 33 percent, while New Yorkers spend about 39 percent on housing. The percentage of households that own their homes also varies in our areas: Philadelphia has the highest homeownership percentage (70 percent), while New York has the lowest (49 percent). But New York residents spend less on transportation, 12 percent, compared to Houston residents, who spend 18 percent.

Want more metro area data?

You might not know about our Economic Summaries, which gather data from many programs. We have information for hundreds of metro areas in all 50 states, plus a couple of territories. We also have geographic definitions for each subject. We update the summaries each month to keep them fresh.

You can use these Economic Summaries to see how your area is doing. If you have questions about this information, feel free to contact one of our BLS Regional Information Offices. We provide these gold-standard data to help you make smart decisions, such as, do you want to stay in your metro area? Or does another catch your eye?!

*A note to our readers that the above data are not seasonally adjusted and some may be subject to revision. Area definitions may differ by subject. For more area summaries and geographic definitions, please see our Economic Summaries.

Tags: BLS products and services, Employment Situation, Labor market trends, Statistics awareness