Tag Archives: Statistics awareness

New State Data on Labor Productivity and Job Openings and Labor Turnover

While international trade has become increasingly important to our economy over the past 60 years, U.S. households and businesses continue to rely primarily on local markets for most goods and services. The products we create come from all over our country. Workers, businesses, and policymakers care deeply about the economy in our own backyards. That’s why BLS recently began publishing new data on labor productivity by state and, separately, on job openings and labor turnover by state.

State labor productivity

Our measures of labor productivity for states are still experimental, meaning we’re still assessing them and considering ways to improve them. These measures cover the private nonfarm sector for all 50 states and the District of Columbia from 2007 to 2017. They show that labor productivity growth varies a lot from state to state. From 2007 to 2017, labor productivity changes ranged from a gain of 3.1 percent per year in North Dakota to a loss of 0.7 percent per year in Louisiana. In 2017, labor productivity grew fastest in Montana (2.0 percent), West Virginia (1.9 percent), California (1.8 percent), and Hawaii (1.7 percent). You can get the complete dataset from our state labor productivity page.

U.S. map showing productivity growth in the private nonfarm sector in each state from 2007 to 2017

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

We construct these state measures from data published by several BLS programs and by our colleagues at the Bureau of Economic Analysis. A recent Monthly Labor Review article, “BLS publishes experimental state-level labor productivity measures,” explains the data and the methods for putting them all together. The article also highlights how you might use these new state data. We’re happy to have your feedback on these new measures. Just send us an email.

State job openings and labor turnover

We also have new data on job openings, hiring, and separations by state. Data from the Job Openings and Labor Turnover Survey are widely used by economic policymakers and others who want to understand the job flows that lead to net changes in employment. We have these data back to December 2000 and update them every month for the nation and the four broad census regions. Now we have them for all states and the District of Columbia too. These state estimates are available from February 2001 through December 2018 for the total nonfarm sector.

Many of you have told us you want more geographic details about job openings and turnover. To make sense of data on job openings, for example, it helps to know where the jobs are. The survey sample size is designed to estimate job openings and turnover for major industries only at the national and regional levels. For several years we have researched ways to produce model-assisted estimates for states. As with the state productivity data, these estimates are experimental. We plan to update the state estimates each quarter while we assess your feedback on the models and the usefulness of the data. We encourage you to send us your comments.

But wait, there’s more! We’ve updated the BLS Local Data App!

In previous blog posts, we’ve told you about our mobile app for customers who want to know more about local labor markets. This app now includes employment and wage data for detailed industries and occupations. (It doesn’t yet have the new data on state productivity, job openings, and turnover.)

Interested in local data for a particular industry or occupation? The latest version allows you to quickly search or use the built-in industry and occupational lists. Want to know which industry employs the most workers in your area or which occupation pays the highest? The updated app allows you to sort the employment and wage data across groups of industries and occupations. You can still find data on unemployment rates and total employment. You also can find your state, metro area, or county by searching for a zip code or using your device’s current location.

These new data and features result from the continued partnership between BLS and the U.S. Department of Labor’s Office of the Chief Information Officer. Be on the lookout for more new features to be added in future releases.

Download the BLS Local Data app from the App Store or Google Play today!

Annual percent change in labor productivity in the private nonfarm sector, 2007–17
State Annual percent change
North Dakota 3.1
California 1.7
Oregon 1.7
Washington 1.7
Colorado 1.6
Oklahoma 1.6
Maryland 1.5
Montana 1.5
Pennsylvania 1.5
Massachusetts 1.4
New Mexico 1.4
Vermont 1.4
Idaho 1.3
Kansas 1.3
Nebraska 1.1
New Hampshire 1.1
South Carolina 1.1
Tennessee 1.1
Texas 1.1
West Virginia 1.1
Alabama 1.0
Hawaii 1.0
Kentucky 1.0
Minnesota 1.0
New York 1.0
Rhode Island 1.0
South Dakota 1.0
Virginia 1.0
Georgia 0.9
Arkansas 0.8
Missouri 0.8
Ohio 0.8
Utah 0.8
Illinois 0.7
North Carolina 0.7
Delaware 0.6
Florida 0.6
Iowa 0.6
Indiana 0.5
Mississippi 0.5
New Jersey 0.5
Wisconsin 0.5
Alaska 0.4
Arizona 0.4
District of Columbia 0.4
Michigan 0.4
Maine 0.3
Nevada 0.3
Wyoming 0.1
Connecticut -0.5
Louisiana -0.7

Why This Counts: 10 Million U.S. Establishments for the First Time

In the third quarter of 2018, the number of establishments in the U.S. economy reached 10 million. This milestone is based on data from the Quarterly Census of Employment and Wages (QCEW), which uses administrative records to identify the number of establishments in our economy.

What is the QCEW?

The QCEW compiles quarterly reports of the Unemployment Insurance systems in each state, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. Every business with an employee, other than the owner, must register with the state where it has a business location. We call these locations establishments.

 Behind the number

Behind the 10 million establishments are some interesting facts about our labor market.

First, the U.S. labor market is dynamic

Roughly 200,000 establishments are new each quarter. That adds up to almost 800,000 new establishments each year. If we consider that we first hit the 9 million mark in third quarter 2007, you may wonder why we didn’t reach 10 million sooner.

Some establishments continue for long periods, while others close. In 2018, more than half of all private sector establishments were 10 years or older. And while the number of establishments grows in most years, during a recession fewer establishments open and more close. Openings and closings that mostly offset one another result in a pretty stable rate of change in the total number of establishments over time.

Line chart showing the number of establishments each quarter from 2001 to 2018

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

Second, most establishments are small

If we define small establishments as having fewer than 500 employees, 99.8 percent of all establishments in the U.S. economy are small. These employ 82.6 percent of workers and pay 73.5 percent of all wages, including bonuses.

Less than one-tenth of 1 percent of establishments have 1,000 employees or more, yet these establishment have an outsized impact. In first quarter 2018 they accounted for 11.0 percent of employment and 17.8 percent of total wages, far higher than their representation in our economy.

Chart showing the share of establishments, employment, and total wages by establishment size in the first quarter of 2018

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

Slicing the data a different way, we find that 62.5 percent of all establishments in first quarter 2018 had fewer than 5 employees. In fact, the five industries with the most establishments are all dominated by small establishments.

Services for the elderly and disabled is the industry with both the highest number of establishments and the highest number of small establishments. In first quarter 2018, it had 742,364 private establishments, and 97.1 percent of them had fewer than 5 employees. The industry office of physicians, except mental health ranks fifth in the U.S. economy in terms of the number of establishments, and 52.5 percent of them had fewer than 5 employees.

An interesting story about physicians’ offices

The real value of the QCEW data is in its fine level of detail. Drilling down, we find that in first quarter 2018 Los Angeles County had 10,360 establishments in offices of physicians, except mental health, ranking first in the U.S. economy.

However, the highest concentration of physicians’ offices is not in Los Angeles, but in Johnson County, Georgia. We use location quotients to measure the concentration of establishments in a geographic area. A location quotient greater than 1 means the industry has a greater concentration of establishments within the county than in the nation. With a location quotient of 5.0, Johnson County has five times the concentration of physicians’ offices than the nation.

Offices of physicians, except mental health, number of establishments and establishment location quotients in selected counties, first quarter 2018
County Number of Establishments Establishment location quotient
Johnson County, Georgia 14 5.0
Greenup County, Kentucky 40 3.2
Boyd County, Kentucky 103 3.1
Angelina County, Texas 107 2.8
Jefferson County, Texas 359 3.0
Los Angeles County, California 10,360 1.0

 

So, who uses the data?

The detail available in QCEW data is important to a range of users. In the private sector, commercial real estate brokers may use the data when deciding the best location for a new business. Small business owners may compare average weekly wages. Large corporations may use local data to develop geographic profiles and market studies.

In the public sector, local and regional economic development agencies use the data for planning and program development. Understanding the type and size of establishments can help them recruit and retain businesses and support workforce development investment. Disaster relief agencies use information on the size of establishments or the concentration in an area to determine risk and track recovery efforts. State governments and academic institutions use the data to study the health of regional economies.

Want to know more?

For this blog, we use private ownership data from first quarter 2018 to explore QCEW establishment size data. You can explore establishment size data using the QCEW Data Viewer.

For even more information, visit our QCEW page.

Number of establishments, 2001–18
Quarter Number of establishments
Q1 2001 7,925,541
Q2 2001 7,958,077
Q3 2001 8,008,006
Q4 2001 8,046,492
Q1 2002 8,042,613
Q2 2002 8,060,770
Q3 2002 8,124,227
Q4 2002 8,179,879
Q1 2003 8,188,261
Q2 2003 8,206,992
Q3 2003 8,239,152
Q4 2003 8,280,956
Q1 2004 8,298,175
Q2 2004 8,305,907
Q3 2004 8,389,106
Q4 2004 8,465,990
Q1 2005 8,478,533
Q2 2005 8,525,655
Q3 2005 8,613,899
Q4 2005 8,666,489
Q1 2006 8,690,719
Q2 2006 8,726,001
Q3 2006 8,816,751
Q4 2006 8,902,635
Q1 2007 8,862,947
Q2 2007 8,936,111
Q3 2007 9,014,197
Q4 2007 9,074,333
Q1 2008 9,028,884
Q2 2008 9,059,689
Q3 2008 9,108,151
Q4 2008 9,131,473
Q1 2009 8,967,310
Q2 2009 8,984,662
Q3 2009 9,020,598
Q4 2009 9,040,216
Q1 2010 8,925,889
Q2 2010 8,962,280
Q3 2010 9,014,193
Q4 2010 9,070,072
Q1 2011 8,989,800
Q2 2011 9,042,922
Q3 2011 9,104,661
Q4 2011 9,153,801
Q1 2012 9,006,016
Q2 2012 9,179,368
Q3 2012 9,128,346
Q4 2012 9,173,740
Q1 2013 9,107,736
Q2 2013 9,178,547
Q3 2013 9,241,547
Q4 2013 9,295,722
Q1 2014 9,288,442
Q2 2014 9,313,909
Q3 2014 9,380,061
Q4 2014 9,463,005
Q1 2015 9,414,823
Q2 2015 9,470,124
Q3 2015 9,561,224
Q4 2015 9,644,927
Q1 2016 9,601,391
Q2 2016 9,677,672
Q3 2016 9,758,568
Q4 2016 9,828,841
Q1 2017 9,718,391
Q2 2017 9,807,791
Q3 2017 9,871,253
Q4 2017 9,942,980
Q1 2018 9,910,520
Q2 2018 9,988,054
Q3 2018 10,065,152
Q4 2018 10,169,140
Percent of establishments, employment, and total wages by establishment size, first quarter 2018
Number of employees in establishment Percent of total establishments Percent of total employment Percent of total wages
1,000 or more 0.1% 11.0% 17.8%
500 to 999 0.1 6.4 8.7
Fewer than 500 99.8 82.6 73.5

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.