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Topic Archives: Benefits and Compensation

Brood X Cicadas over the History of BLS Data

For readers around several Eastern and Midwest states, you likely know that “Brood X” is the name of the cohort of 17-year cicadas that have made their appearance known, and heard, starting in mid-May 2021. According to the U.S. Forest Service, scientists have been studying cicadas for a couple of centuries, and there are historical reports going back centuries. In fact, in The Iliad, Homer speaks of two elder sages who were “… too old to fight, but they were fluent orators, and sat on the tower like cicadas that chirrup delicately from the boughs of some high tree in a wood.”

A cicada

We can’t find any record of President Chester A. Arthur (who signed the law to create BLS) nor Carroll Wright (the first BLS Commissioner) speaking of cicadas, but is it a coincidence that Brood X appeared just one year after BLS was founded in 1884? Since BLS has lived through 9 appearances of Brood X, let’s take a look at what we reported during those years.

Year of BLS founding in 1884 and Brood X appearances in 1885, 1902, 1919, 1936, 1953, 1970, 1987, 2004, and 2021

Brood X of 1919 was the first to encounter the BLS Consumer Price Index, which provides information back to 1913. Using the CPI Inflation Calculator, you can look at how buying power has changed over time. As the chart below shows, Brood X from 1919 could spend $6.31 and have buying power equal to their great, great, great, great grandchildren spending $100 today. The 1936 cicadas were affected by the Great Depression, with increasing buying power because of deflation. The 1987 cicadas were affected by high inflation rates that occurred after their 1970 ancestors disappeared.

Purchasing power of $100 in January 2021 compared with January of other Brood X years

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

While BLS has reported on the number of workers on employer payrolls since before the 1919 cicadas came out of the ground, consistent data for all states were not available until the late 1940s. That was in time for the 1953 cicadas, which witnessed about 43 million jobs on private nonfarm payrolls. The 1953 cicadas saw about 45 percent of private sector employment in good-producing industries — mining, construction, and manufacturing. Interestingly, cicadas from the groups that followed saw little change in the number of jobs on good-producing payrolls. The peak number in Brood X years was 23 million in 1987. Goods-producing employment in 2021 is just over 20 million. In contrast, payrolls of service-providing industries have soared over the same period, from nearly 24 million in 1953 to just over 100 million today. These service-providing industries include trade, transportation, financial activities, education and health services, restaurants and other hospitality businesses, and many more. The 2021 cicadas have seen that 83 percent of payroll employment is in service-providing industries.

Private-sector employment in goods-producing and service-providing industries, January of Brood X years

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

BLS has been studying productivity since before Brood X of 1902 emerged. The first such study was of “Hand and Machine Labor” in 1898. Consistent measures of labor productivity in the nonfarm business sector date from 1947, in time for the 1953 cicadas. Over the more than 70-year history of these data, the percent change from the previous quarter, at an annual rate, has been negative about 20 percent of the time (based on the first quarter of each year). But perhaps the sound and fury of Brood X has some influence, as 2 out of 5 (40 percent) of the cicada-year changes have been negative. Yes, it’s a small sample, but let’s not discount the cicada effect.

Annualized percent change in nonfarm business sector labor productivity in the first quarter of Brood X years, compared with the previous quarter

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

Finally, our flying friends have studied BLS data on pay and know about all our measures of worker pay. The longest consistent series on pay began in 1964, in time for the 1970 cicadas to track average hourly earnings for production and nonsupervisory employees. The 1987 cicadas saw pay nearly triple from that of their parents, and future generations saw continued increases as well.

Average hourly earnings of production and nonsupervisory employees in the private sector, January of Brood X years

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

BLS is looking forward to providing the latest in labor statistics in 2038, when the children of the 2021 cicadas check out the latest on www.bls.gov. In the meantime, maybe they’ll follow us on Twitter.

Purchasing power of $100 in January 2021 compared with January of other Brood X years
YearPurchasing power

1919

$6.31

1936

5.28

1953

10.17

1970

14.45

1987

42.51

2004

70.80

2021

100.00
Private-sector employment in goods-producing and service-providing industries, January of Brood X years
YearGoods producingService providing

1953

19,721,00023,629,000

1970

22,726,00035,954,000

1987

23,232,00060,401,000

2004

21,715,00087,516,000

2021

20,221,000100,948,000
Annualized percent change in nonfarm business sector labor productivity in the first quarter of Brood X years, compared with the previous quarter
YearAnnualized percent change

1953

3.5%

1970

1.3

1987

-1.8

2004

-1.3

2021

5.4
Average hourly earnings of production and nonsupervisory employees in the private sector, January of Brood X years
YearAverage hourly earnings

1970

$3.31

1987

9.02

2004

15.51

2021

25.14

The Challenges of Seasonal Adjustment during the COVID-19 Pandemic

In a previous edition of Commissioner’s Corner, we described seasonal adjustment, the process BLS and many others use to smooth out increases and decreases in data series that occur around the same time each year. Seasonal adjustment allows us to focus on the underlying trends in the data. Seasonal adjustment works well when seasonal patterns are pretty consistent from year to year. But what about when there are large shocks to the economy, such as natural disasters and the massive effects of the COVID-19 pandemic and resulting business closures and stay-at-home orders? Today we’ll look at how BLS addressed this issue.

First, a little background on seasonal adjustment. Here’s an example similar to one we have used before, looking at employment in the construction industry. Construction employment varies throughout the year, mostly because of weather. As the chart shows in the “not seasonally adjusted” line, construction adds jobs in the spring and throughout the summer before it starts to lose jobs when the weather turns colder. The large seasonal fluctuations make it hard to see the overall employment trend in the industry. That makes it harder to study other factors that affect the trend, like changes in consumer demand or interest rates. After seasonal adjustment, the construction industry grew by 1.2 million jobs from the beginning of 2015 to the end of 2019.

Construction employment, 2015–19

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

BLS seasonally adjusts data in several of its monthly and quarterly news releases.

Two Approaches to Seasonal Adjustment

BLS uses one of two approaches to seasonally adjust data in these releases—projected factors or concurrent seasonal adjustment. When we project seasonal adjustment factors, we only use historical data in the models. That means we calculate factors in advance, so they are not influenced by the most recent trends. Concurrent seasonal adjustment uses all the data available, including the most recent month or quarter. As a result, the factors are influenced by recent changes.

Regardless of whether the factors are projected or concurrent, the seasonal adjustment models can be additive or multiplicative. We’ll explain more about that below. The COVID-19 pandemic affected the seasonal adjustment process in different ways depending on how the seasonal factors are calculated.

Approach #1

The Consumer Price Index, Producer Price Indexes, and Employment Cost Index use the projected-factor approach and calculate seasonal factors once a year. BLS staff estimated the 2020 seasonal factors at the beginning of 2020 and have used them throughout the year. When new factors for 2021 and revised historical factors are calculated, BLS will examine the effects of the pandemic on the seasonal adjustment models.

Approach #2

We use a concurrent process to calculate the seasonal factors each month for nonfarm employment estimates for the nation, states, and metro areas, unemployment and labor force estimates for the nation, states, and metro areas, and job openings and labor turnover estimates. Each quarter, BLS also uses a similar concurrent process to calculate seasonal factors for productivity measures and business employment dynamics. This helps create the best seasonal factors when seasonality may shift over time. For example, think of schools letting out for summer a little earlier than they usually do each year, or the changing nature of delivery services because of online shopping. Using the most recent data to calculate seasonal factors helps pick up these changes to seasonality faster than the forecasted method. The risk of using the concurrent process is that it may attribute some of the movement in the estimates to a changing seasonal pattern when it really resulted from a nonseasonal event. BLS also annually examines and revises the historical seasonal factors even if the factors were originally calculated using concurrent adjustment. As the saying goes, hindsight is 20/20.

Before the COVID-19 pandemic, the concurrent seasonal adjustment models required limited real-time intervention. Examples of potential reasons for intervention include major events like hurricanes. The COVID-19 pandemic is unusual in its severity and duration, so significant intervention was needed.

BLS intervened in several ways to create the highest quality, real-time seasonal factors. The tool we use most often is called outlier detection. We consider outliers not to represent a normal or typical seasonal movement. When we label an observation as an outlier, we don’t use it to inform the seasonal adjustment model. Since economic activity is still being heavily influenced by COVID-19 and efforts to contain it, BLS has detected more outliers. When this happens, concurrent models behave more like projected-factor models because the most recent data are not used to create seasonal factors.

The Local Area Unemployment Statistics program uses another type of intervention, a technique call a level shift. It is used when there is a sudden change in the level of a data series. In this case, level shifts were used over a series of months.

Additive versus Multiplicative Models

As noted earlier, all BLS programs review their seasonal adjustment models each year. One of the steps during this process is to select a model—either additive or multiplicative. We use an additive model when seasonal movements are stable over time regardless of the level of the series. A multiplicative model is better to use when seasonal movements become larger as the series itself increases—that is, the seasonality is proportional to the level of the series. That means a sudden large change in the level of a series, such as the large increase in the number of unemployed people in April 2020, will be accompanied by a proportionally large seasonal effect. BLS did not want this to occur. When there are large shifts in a measure, multiplicative seasonal adjustment factors can result in adjusting too much or too little. In these cases, additive seasonal adjustment factors usually reflect seasonal movements more accurately and have smaller revisions.

Because of the unusual data patterns beginning in March 2020, both the Current Population Survey, which we use to measure unemployment and the labor force, and the Job Openings and Labor Turnover Survey switched from multiplicative to additive seasonal models for most series and did not wait until the typical yearend model review.

BLS does not produce the weekly data on unemployment insurance. We do, however, compute the seasonal adjustment factors used by the Department of Labor’s Employment and Training Administration for their Unemployment Insurance Weekly Claims data. As we recommended, the Employment and Training Administration recently switched from using multiplicative to additive seasonal adjustments.

Our quarterly Labor Productivity and Costs news release uses input data from the Bureau of Economic Analysis, the U.S. Census Bureau, and several BLS programs. Most of the input data are already seasonally adjusted by the source agencies or programs. The productivity program only seasonally adjusts monthly Current Population Survey data on employment and hours worked for about ten percent of workers, mostly the self-employed, who are not included in the monthly data from the Current Employment Statistics survey on nonfarm employment and hours. The productivity program detected outliers in some of the data beginning at the start of the COVID-19 pandemic in March 2020 and accounted for them in the estimates.

Science and Art

Seasonal adjustment of economic data is a scientific process that involves complex math. But seasonal adjustment also involves some art in addition to science. The art comes in when we use our judgment about outliers in the data or when we decide whether an additive or multiplicative model more closely reflects seasonal variation in economic measures. The art also comes in when we recognize how complicated the world is. During 2020 we have experienced not just a global pandemic but also massive wildfires in several western states, a historic number of hurricanes that made landfall, and other notable events that affect economic activity. Did our seasonal adjustment models properly account for all of these events? I can say we have tried our best with the information we have available. As we gather more data for 2020 and future years, we will continue to examine how we can improve our models to help us distinguish longer-term trends from the seasonal variation in economic activity.

Acknowledgment: Many BLS staff members helped make the technical details in this blog easier to understand, and they all have my gratitude. Three who were especially helpful were Richard Tiller, Thomas Evans, and Brian Monsell.

Construction employment, 2015–19
MonthSeasonally adjustedNot seasonally adjusted

Jan 2015

6,320,0005,953,000

Feb 2015

6,361,0005,962,000

Mar 2015

6,334,0006,051,000

Apr 2015

6,392,0006,300,000

May 2015

6,427,0006,491,000

Jun 2015

6,441,0006,633,000

Jul 2015

6,472,0006,718,000

Aug 2015

6,490,0006,754,000

Sep 2015

6,508,0006,704,000

Oct 2015

6,547,0006,740,000

Nov 2015

6,598,0006,685,000

Dec 2015

6,630,0006,542,000

Jan 2016

6,620,0006,252,000

Feb 2016

6,650,0006,256,000

Mar 2016

6,680,0006,402,000

Apr 2016

6,701,0006,614,000

May 2016

6,691,0006,758,000

Jun 2016

6,702,0006,913,000

Jul 2016

6,736,0006,989,000

Aug 2016

6,737,0006,997,000

Sep 2016

6,768,0006,971,000

Oct 2016

6,798,0006,981,000

Nov 2016

6,819,0006,903,000

Dec 2016

6,821,0006,700,000

Jan 2017

6,847,0006,459,000

Feb 2017

6,889,0006,527,000

Mar 2017

6,909,0006,634,000

Apr 2017

6,916,0006,820,000

May 2017

6,928,0006,998,000

Jun 2017

6,955,0007,169,000

Jul 2017

6,960,0007,212,000

Aug 2017

6,990,0007,248,000

Sep 2017

7,004,0007,201,000

Oct 2017

7,027,0007,208,000

Nov 2017

7,066,0007,147,000

Dec 2017

7,093,0007,004,000

Jan 2018

7,114,0006,729,000

Feb 2018

7,200,0006,840,000

Mar 2018

7,205,0006,933,000

Apr 2018

7,223,0007,129,000

May 2018

7,266,0007,336,000

Jun 2018

7,282,0007,497,000

Jul 2018

7,304,0007,554,000

Aug 2018

7,335,0007,586,000

Sep 2018

7,355,0007,535,000

Oct 2018

7,378,0007,557,000

Nov 2018

7,376,0007,454,000

Dec 2018

7,402,0007,311,000

Jan 2019

7,452,0007,069,000

Feb 2019

7,423,0007,062,000

Mar 2019

7,443,0007,170,000

Apr 2019

7,469,0007,377,000

May 2019

7,478,0007,540,000

Jun 2019

7,497,0007,699,000

Jul 2019

7,504,0007,753,000

Aug 2019

7,508,0007,760,000

Sep 2019

7,524,0007,700,000

Oct 2019

7,541,0007,720,000

Nov 2019

7,539,0007,609,000

Dec 2019

7,555,0007,447,000

Innovations at BLS during the COVID-19 Pandemic

Our work at the Bureau of Labor Statistics is driven by the idea that good measurement leads to better decisions. Good measures of economic and social conditions help public policymakers and private businesses and households assess opportunities and areas for improvement. Measuring these conditions consistently over time helps people who use our data evaluate the impact of public and private decisions.

We also believe we must be completely transparent about the design of our surveys and programs and the methods we use to conduct them. It isn’t enough to publish statistics and expect people simply to trust their quality. We gain this trust by documenting the design and procedures for all our programs in our Handbook of Methods. Our website also explains our policies for ensuring data quality and protecting the confidentiality and privacy of the people and businesses who participate in our surveys and programs. Further, BLS works with the wider U.S. statistical community to ensure and enhance the quality of statistical information.

Good measures are essential in “normal” times, but the global COVID-19 pandemic has made these last few months anything but normal. I am so proud of the work of the career professionals at BLS and our fellow statistical agencies for continuing to produce vital economic statistics. Our entire BLS staff moved to full-time telework in mid-March and didn’t miss a beat. We continue to publish measures of labor market activity, working conditions, price changes, and productivity like BLS has done since its founding in 1884. See our dashboard of key economic indicators in the time of COVID-19.

Publishing these measures hasn’t been easy. The pandemic has raised new questions about how businesses, households, and consumers have changed their behavior. BLS also has had to innovate to find new ways of doing things during the pandemic.

Today I want to tell you about the new data we have been collecting to learn more about the effects of the pandemic. I also want to tell you about some of the ways the BLS staff has innovated to keep producing data that are accurate, objective, relevant, timely, and accessible.

New Data

How businesses have responded to the pandemic

We have collected new data on how U.S. businesses changed their operations and employment from the onset of the pandemic through September 2020. This information, combined with data collected in other BLS surveys, will aid in understanding how businesses responded during the pandemic. Other statistics we have collected and published during the pandemic show changes in employment, job openings and terminations, wages, employer-provided benefits, prices, and more. These new data provide more insights by asking employers directly what they experienced as a result of the pandemic and how they reacted. Data for the Business Response Survey to the Coronavirus Pandemic will be released in early December 2020.

Changes in telework, loss of jobs, and job search

The Current Population Survey is the large monthly survey of U.S. households from which we measure the unemployment rate and other important labor market indicators. We added questions to the survey to help gauge the effects of the pandemic on the labor market. These questions were added in May 2020 and will remain in the survey until further notice. One question asks whether people teleworked or worked from home because of the pandemic.

Percent of employed people who teleworked at some point in the previous 4 weeks because of the COVID-19 pandemic, May through October 2020

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

Other questions ask whether people were unable to work because their employers closed or lost business because of the pandemic; whether they were paid for that missed work; and whether the pandemic prevented them from searching for jobs.

Number of people not in the labor force who did not look for work because of the COVID-19  pandemic, May through October 2020

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

Changes in sick leave plans

We added several questions to the National Compensation Survey to understand the effects of the pandemic on sick leave plans. The questions asked whether private industry establishments changed their leave policies and whether employees used sick leave between March 1 and May 31, 2020.

Receiving and using stimulus payments during the pandemic

BLS is one of several federal agencies that developed questions for the rapid response Household Pulse Survey. The survey is a collaboration among the U.S. Census Bureau, BLS, the U.S. Department of Housing and Urban Development, the National Center for Education Statistics, the National Center for Health Statistics, and the U.S. Department of Agriculture’s Economic Research Service. BLS contributed questions on the receipt and use of Economic Impact Payments and on sources of income used to meet spending needs during the pandemic.

Our staff will continue to publish research on how the pandemic has affected the labor market and markets for goods and services. Check back regularly as we add to this library of research.

Innovations in Data Collection and Training

The COVID-19 pandemic has caused profound changes in the daily lives of Americans. BLS is no exception. As I mentioned earlier, all BLS staff moved to full-time telework in March. The pandemic hasn’t prevented us from continuing to publish high-quality data, but we have had to change some of our data-collection methods and estimation procedures. We will continue to explain those changes so you can understand how they affect the quality of our measures.

Our survey respondents are the heart of everything we do at BLS. Without their generous and voluntary cooperation, we would not be able to publish high-quality data for public and private decision making. Respondents have businesses and households to run, and a pandemic is a challenging time to ask for their help. The data-collection staffs at BLS, the U.S. Census Bureau, and our state partners form great relationships with survey respondents. We must continue to protect the health of data collectors while also training them in a rapidly changing environment. Let me highlight a few of the innovative changes we have made during the pandemic that focus on our relationships with respondents and how we train data collectors.

Using videoconferencing technology for data collection

Several of our surveys have started using videoconferencing tools to speak with respondents and collect data from them. Some of the surveys that now use this technology include the National Compensation Survey, the Occupational Requirements Survey, and the Producer Price Index. Many of our surveys previously relied on interviewers visiting businesses or households to collect data. We suspended all in-person data collection in March to protect the health of data collectors and respondents, so we had to find other ways to collect data. Many of our surveys also use telephone and internet to collect data, but those modes aren’t always ideal for every kind of data. We often need to develop personal relationships with respondents to gain their trust and cooperation and ensure high-quality data. Videoconferencing helps us accomplish what we often can’t do with phones or web survey forms.

The Occupational Requirements Survey is one that has begun using videoconferencing in data collection. The survey provides information about the physical demands; environmental conditions; education, training, and experience; and cognitive and mental requirements for jobs in the U.S. economy. Collecting data for this survey often requires visual aids, hand gestures, and other nonverbal information to understand job characteristics. It often helps to watch jobs as they are performed at a worksite, but that’s not an option during the pandemic. Videoconferencing is the next best alternative.

Many of our data collectors and respondents have mentioned how helpful videoconferencing is for developing a rapport and for sharing screens and other visual information. Videoconferencing also helps us reduce travel and lodging costs, so we likely will continue to rely on videoconferencing at least partly even after the pandemic.

Using videoconferencing technology for training and mentoring

Many of our surveys are complex and require considerable ongoing training for data collectors. For example, before the pandemic, our Consumer Price Index Commodities and Services (C&S) survey involved in-person training at our Washington, DC, headquarters. There were two classroom training courses: a 2-week introductory course and a 1-week advanced course. Each course was followed by on-the-job training held in our regional offices. Even before the pandemic, we were developing videoconference training. The pandemic caused us to accelerate these plans. We now provide C&S survey training through video collaboration tools. We also integrate on-the-job training throughout the classes.

Several other surveys have adopted a similar training approach as the Consumer Price Index. Our data-collection staffs also increasingly use videoconferencing for mentoring and to share ideas about how to make the data-collection experience better for data collectors and respondents.

A final note

Before I conclude, I want to share some sad news about one of the people who played an indispensable leadership role in developing the new survey questions and innovative data-collection and training methods. Jennifer Edgar, our Associate Commissioner for Survey Methods Research, died November 8 in a tragic fall in her home. She leaves behind her husband and two young children, her parents, and her sister. Moreover, she leaves hundreds of BLS colleagues and many more throughout the statistical community and beyond, who will grieve the loss of an exceptionally gifted friend and professional whose great promise was cut suddenly and tragically short. Jennifer was using her considerable energies to move BLS forward. Her passing is a huge blow to her family, loved ones, and the entire statistical community. We are working on ways to ensure Jennifer’s memory and passion is forever present at BLS.

Percent of employed people who teleworked at some point in the previous 4 weeks because of the COVID-19 pandemic
MonthPercent

May 2020

35.4%

Jun 2020

31.3

Jul 2020

26.4

Aug 2020

24.3

Sep 2020

22.7

Oct 2020

21.2
Number of people not in the labor force who did not look for work because of the COVID-19 pandemic
MonthNumber not in the labor force

May 2020

9,740,000

Jun 2020

7,043,000

Jul 2020

6,454,000

Aug 2020

5,200,000

Sep 2020

4,499,000

Oct 2020

3,563,000

Celebrating World Statistics Day 2020

At the Bureau of Labor Statistics, we always enjoy a good celebration. We just finished recognizing Hispanic Heritage Month. We are currently learning how best to protect our online lives during National Cybersecurity Awareness Month. We even track the number of paid holidays available to workers through the National Compensation Survey. Today I want to focus on a celebration that happens once every 5 years — World Statistics Day. While there may not be parades, special meals, or department store sales to honor this day, we at BLS and our colleagues worldwide take time out on October 20, 2020, to recognize the importance of providing accurate, timely, and objective statistics that form the cornerstone of good decisions.

United Nations logo for World Statistics Day 2020

World Statistics Day, organized under the guidance of the United Nations Statistical Commission, was first celebrated in October 2010. This year, the third such event, focuses on “connecting the world with data we can trust.” At BLS, the trustworthy nature of our data and processes has been a hallmark of our work since our founding in 1884. Our first Commissioner, Carroll Wright, described our work then as “conducting judicious investigations and the fearless publication of results.” That credo guides us to this day. As the only noncareer employee in the agency, I am surrounded by a dedicated staff of data experts  whose singular mission is to produce the highest-quality data, without regard to policy or politics. BLS and other statistical agencies throughout the federal government strictly follow Statistical Policy Directives that ensure we produce data that meet precise technical standards and make them available equally to all. For nearly 100 years, we have regularly updated our Handbook of Methods to provide details on data concepts, collection and processing methods, and limitations. Transparency remains a hallmark of our work.

The United States has a decentralized statistical system, with numerous agencies large and small spread throughout the federal government. Despite this decentralization, the agencies work together to improve statistical methods and follow centralized statistical guidance. This partnership was recently strengthened by the Foundations for Evidence-Based Policymaking Act of 2018, which reinforced how the statistical agencies protect the confidentiality of businesses and households that provide data. The Act also designated heads of statistical agencies, like myself, as Statistical Officials for their respective Departments. In my case, my BLS colleagues and I advise other Department of Labor agencies on statistical concepts and processes, while continuing to stay clear of policy discussions and decisions.

World Statistics Day is a global event, so this is a good time to share some examples where BLS participates in statistical activities around the world:

  • We have regular contact with colleagues at statistical organizations around the world. Just recently, I participated in a very long-distance video conference on improvements to the Consumer Price Index. For me, it was 6:00 a.m., and I made sure I had a mug of coffee handy; for my colleagues in Australia, it was 6:00 p.m., and I’m certain their mug had coffee as well.
  • We have a well-established training program for international visitors, focusing on our processes and methods. We hold training sessions at BLS headquarters (or at least we did before the pandemic), we send experts to other countries, and we are exploring virtual training. We are eager to share our expertise and long history.
  • We participate in international panels and study groups, such as those organized by the United Nations, the Organization for Economic Cooperation and Development, and others, with topics ranging from measuring the gig economy to use of social media.
  • We provide BLS data to international databases, highlighting employment, price, productivity and related information to compare with other countries.

And that’s just a taste of how BLS fits into the World of Statistics. As Commissioner, I’ve had the honor to represent the United States in conferences and meetings across the globe. The BLS staff and I also hold regular conversations with statistical officials worldwide. In a recent conversation with colleagues in the United Kingdom, we were eager to learn about each other’s changes in the ways we provide data and analyses to our customers. These interactions expand everyone’s knowledge and keep the worldwide statistical system moving forward.

To celebrate World Statistics Day, I asked some BLS cheerleaders if they would join me in a video message about the importance of quality statistical data. Here’s what they had to say:

In closing, let’s all raise a toast to World Statistics Day, the availability of high-quality and impartial data, and the dedicated staff worldwide who provide new information and analysis every day.

Happy World Statistics Day!

Labor Day 2020 Fast Facts

I have been Commissioner of Labor Statistics for about a year and a half now, and what a time it has been! BLS has faced many challenges throughout its history, but none quite like those from the COVID-19 pandemic. All of our staff moved to full-time telework March 16, and I am so proud of how well they have worked under trying circumstances. In a very short time—days, not weeks—we had to change our data collection processes to eliminate in-person collection and move to a combination of telephone, internet, and video. We recognize how challenging it is for our survey respondents to provide data during the pandemic, and I am very grateful for their cooperation. Response rates have dipped a bit in some programs, but the quality of our samples remains strong across the board. Despite all of the challenges, BLS has been able to produce all of our economic reports without interruption.

The pandemic has taught us there’s an unlimited appetite for data. The U.S. statistical system is working to satisfy that appetite. At BLS, we strive for more and better data to understand the hardships caused by the pandemic. Starting in May we added new questions to our monthly survey of households. The questions ask whether people teleworked or worked from home because of the pandemic; whether people were unable to work because their employers closed or lost business; whether they were paid for that missed work; and whether the pandemic prevented job-seeking activities. We continue to gather new data from those questions.

We collaborated with our partners at other U.S. statistical agencies to find out how many people received payments from the Coronavirus Aid, Relief, and Economic Security (CARES) Act, signed into law on March 27, 2020. For those who received payments, we asked how they used them.

Soon we will have new data about how businesses have responded to the pandemic. These data are from a brand new survey that seeks to identify changes to business operations, employment, workforce flexibilities, and benefits as a result of the pandemic.

These are just a few examples of how our data collection has responded to the pandemic. Good data are essential for identifying problems, guiding policymakers, and gauging whether and how fast conditions improve for workers, jobseekers, families, and businesses.

Labor Day is a good time to reflect on where we are. Despite these difficult times, I hope you are able to enjoy the long holiday weekend. Take a moment to look at some fast facts we’ve compiled on the current picture of our labor market.

Working

Our monthly payroll survey shows that employment had been increasing through February 2020. With March came the pandemic and the job losses related to it. We lost more than 22 million jobs in March and April and then regained about 48 percent of them in May, June, July, and August.

The employment–population ratio was 56.5 percent in August. This ratio is the number of people employed as a percent of the population age 16 and older. The ratio was 61.1 percent in February.

There were 7.6 million people working part time for economic reasons in August 2020. These are people who would have preferred full-time employment but were working part time because their hours had been reduced or they were unable to find full-time jobs. This number was down from 10.9 million in April. The number was 4.3 million in February.

Not Working

The unemployment rate reached 14.7 percent in April 2020. That was the highest rate, and the largest over-the-month increase, in the history of the data back to January 1948. The rate has fallen since then, reaching 8.4 percent in August. The rate was 3.5 percent back in February, the lowest since 1969.

We have noted the challenges of measuring unemployment during this pandemic. The rates we have seen since March likely understate unemployment, but the trend is clear. The rate rose sharply in March and even more sharply in April and has trended down since April.

Among the major worker groups in August 2020, the unemployment rate was 8.4 percent for adult women and 8.0 percent for adult men. The rate for teenagers was 16.1 percent. The unemployment rate was 13.0 percent for Blacks or African Americans, 10.7 percent for Asians, 10.5 percent for Hispanics or Latinos, and 7.3 percent for Whites.

Job Openings

On the last business day of June 2020, the number of nonfarm job openings was 5.9 million. That was a decline of 18 percent from June 2019.

The ratio of unemployed people per job opening was 3.0 in June 2020. Since the most recent peak of 4.6 in April 2020, the ratio of unemployed people per job opening declined in May and June. In February 2020, there was 0.8 unemployment person per job opening.

Pay and Benefits

Civilian compensation (wage and benefit) costs increased 2.7 percent in June 2020 from a year earlier. After adjusting for inflation, real compensation costs rose 2.1 percent over the year.

Paid leave benefits are available to most private industry workers. The access rates in March 2019 were 73 percent for sick leave, 79 percent for vacation, and 79 percent for holidays.

In March 2019, civilian workers with employer-provided medical plans paid 20 percent of the cost of medical care premiums for single coverage and 33 percent for family coverage.

Productivity

Labor productivity—output per hour worked—in the U.S. nonfarm business sector grew 2.8 percent from the second quarter of 2019 to the second quarter of 2020. That increase reflects large pandemic-related declines in output (−11.2 percent) and hours worked (−13.6 percent).

Safety and Health

In 2018, there were 5,250 fatal workplace injuries. That was a 2-percent increase from 2017 and was the highest number of fatal work injuries in a decade. It was, however, below the numbers of workplace deaths in the 1990s, when over 6,000 fatalities occurred per year.

There were about 2.8 million nonfatal workplace injuries and illnesses reported in 2018 by private industry employers. This resulted in an incidence rate of 2.8 cases per 100 full-time workers in 2018. The rate is down from 9.2 cases per 100 full-time workers in 1976.

Unionization

The union membership rate—the percent of wage and salary workers who were members of unions—was 10.3 percent in 2019, down by 0.2 percentage point from 2018. In 1983, the first year for which comparable union data are available, the union membership rate was 20.1 percent.

Total employer compensation costs for private-industry union workers were $48.57 and for nonunion workers $34.16 per employee hour worked in March 2020. The cost of benefits accounted for 40.5 percent of total compensation (or $19.65) for union workers and 28.4 percent (or $9.71) for nonunion workers.

Looking to the Future

We released our latest set of long-term employment projections September 1. We project employment to grow by 6.0 million jobs from 2019 to 2029. That is an annual growth rate of 0.4 percent, slower than the 2009–19 annual growth rate of 1.3 percent. The healthcare and social assistance sector is projected to add the most new jobs, and 6 of the 10 fastest growing occupations are related to healthcare. These projections do not include impacts of the COVID-19 pandemic and response efforts. We develop the projections using models based on historical data. The historical data for this set of projections cover the period through 2019, so all input data precede the pandemic. We will continue to examine the effects of the pandemic as we update our projections next year and the years that follow.

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