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Tag Archives: Interviews

A New Tool at BLS: Video Data Collection Interview

The pandemic that has gripped the world for over a year has resulted in many challenges for BLS, notably in collecting key economic data from employers and households. It has also brought about innovation, as we were forced to find new ways to do things. We’ve gotten rid of many paper forms; we’ve learned to “sign” documents electronically; and we’ve done our best to remember to unmute in video meetings. Data collection is now almost entirely paperless. It involves more email and web-based interactions, and the latest BLS innovation—the video data collection interview.

Pretend with me that you are peeking in on a recent video interview. BLS Philadelphia Region Field Economist Joseph Wright is the star of this video show. His mission today is to interview a representative from a business for the Producer Price Index (PPI). The PPI measures the average change over time in the selling prices received by domestic producers for their output. To do that, Joe and his colleagues talk to domestic producers (businesses) to identify products and track selling prices.

Earlier, Joe contacted this business and got permission for video collection. As the scene opens, both Joe and the official at this company (we call these individuals “respondents”) are working from home. Joe has done video collection several times before, and that experience is evident. After he shows his credentials to verify he is legit, he shares his screen to point to information about BLS confidentiality protections and to highlight some PPI data.

View of the webpage on Confidentiality Pledge and Laws at https://www.bls.gov/bls/confidentiality.htm

Thinking about this process, it seems like sharing a few highlights on a screen is much easier than shuffling a bunch of papers while meeting with the respondent in person. Advantage—video.

Next, Joe starts the actual data collection process. He begins with some questions and examples designed to verify the firm’s industry classification. Then the conversation pivots to information about the products produced, where Joe and the respondent clarify things like new formulations, quantities in metric tons, and shipping lingo such as free-on-board. Fortunately, Joe and the respondent speak the same language. In fact, one of the hallmarks of BLS data collection is familiarity with detailed industries, occupations, work processes, and more. We are talking to experts, so it’s best to know our stuff. And Joe clearly does.

The goal of an initial PPI interview like this one is to select a sample of products sold by the business. We also want to get a detailed description of the products so we can follow the correct selling price. Finally, we want to set up the process for the business to easily report updated selling prices each month. From information provided by the respondent, Joe did some quick math and identified a random selection of products to follow, based on sales volume. He confirmed product descriptions, which will be provided back to the respondent when it’s time to update the selling prices. Clearly Joe is a pro, as he made quick work of the entire process.

This respondent’s data will eventually be part of the monthly PPI release, which provides considerable detail on changes in selling prices for a wide range of industries and products. Here’s a look at 12-month changes in the PPI over the past decade. More charts and more details are available on the BLS website.

Chart on Producer Price Index for final demand, 12-month percent changes

Data collection is a tough job. This particular respondent was comfortable with the video process and willing to provide information. It helps that the respondent said more than once that “we use these [BLS data] in our contracts” and that he was “glad to be part of this [since we] use a lot of these indexes.” While many respondents are indeed cooperative, and familiar with BLS data, others are not. Fortunately, BLS field economists are equipped with a marketing toolbox, which includes training in how to work with small and large companies; factsheets and related material that highlight how businesses can use BLS data, for example, in contract escalation; and details on BLS procedures to protect the confidentiality of respondent data. The video data collection interview is the latest tool.

BLS confidentiality procedures deserve extra emphasis. While our goal is to give respondents various data collection options, to make the process as convenient as possible, we never introduce a new collection option without a thorough confidentiality vetting. In the case of video collection, that vetting led to the development of strict standards and detailed procedures. These efforts are designed to ensure respondents of the value of their participation, and the care with which BLS handles their data. Enough said.

At BLS, we see the value in building relationships with respondents, and thus in-person data collection will continue to be part of our toolbox. But we also want to limit respondent burden and be good stewards of the taxpayer’s money. As Joe’s example demonstrates, the video data collection interview is an effective option to limit burden and expense while obtaining quality information to support key economic indicators. Even in a post-pandemic world, BLS video data collection is here to stay.

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.

From an American worker’s first job to retirement and everything in between, BLS has a stat for that! Want to learn more? Follow us on Twitter @BLS_gov.

New Recommendations on Improving Data on Contingent and Alternative Work Arrangements

The workplace is changing. We have seen more evidence of that in recent months as workplaces have adapted to the COVID-19 pandemic. Even before the pandemic, many of us wanted to learn more about telework, flexible work hours, and independent contracting. We also wanted to know more about intermittent or short-term work found through mobile devices, unpredictable work schedules, and other employment relationships we might not think of as traditional. It’s our job at BLS to keep up with these new work relationships and figure out how to measure them.

In 2018, we released data collected in 2017 about people in contingent and alternative work arrangements. Contingent workers are people who do not expect their jobs to last or who report their jobs are temporary. Alternative work arrangements include independent contractors, on-call workers, temporary help agency workers, and workers provided by contract firms. We also published data in 2018 about electronically mediated work. All of these data reflect the rapidly changing workplace.

Those reports received a lot of attention, but policymakers, employers, researchers, and others told us they want to know more about these nontraditional workers. We need to understand people in jobs that often involve doing short-term tasks, such as ridesharing or data-entry services. Our 2017 survey included a few questions about these arrangements, but this work can be complex and varied. That makes it hard to measure nontraditional work arrangements with just a few questions.

To effectively analyze these hard-to-measure work arrangement, BLS sought out experts on nontraditional work. In 2019, we contracted with the Committee on National Statistics to explore what we should measure if we had the funding to collect and publish more data about these workers. We asked the committee not to recommend changes to the main Current Population Survey, the large monthly survey of U.S. households from which we measure the unemployment rate and other important labor market measures. The committee had free rein, however, to recommend topics we should examine in any future edition of the Contingent Worker Supplement to the Current Population Survey. We also asked the committee to recommend changes to the survey design and methods of data collection if we were to conduct the supplement again.

The Committee on National Statistics is a federally supported independent organization whose mission is to improve the statistical methods and information that guide public policies. The committee moved quickly to form a group of experts on the relevant topics. I asked these experts to review the Contingent Worker Supplement and consider other sources of information on nontraditional work arrangements. The group was impressive and included a former BLS Commissioner, a former Administrator of the U.S. Department of Labor Wage and Hour Division, and several experts in economics and survey methods. They all volunteered their time to help us improve the Contingent Worker Supplement.

The group held public meetings and a workshop, hearing from experts, data users, and policymakers to understand what data would be the most valuable. At the end of their year-long review, they produced a report with specific recommendations in July of 2020 about measurement objectives and data collection.

BLS thanks the Committee on National Statistics and the expert panel for the time and effort they put into the report. Their recommendations thoughtfully balanced the desire to measure everything about this important topic with the limited time and information survey respondents can give us. In the coming months, we will study the report. It will guide us as we consider how to update the Contingent Worker Supplement to reflect the variety of work arrangements in the U.S. labor market.

Update on the Misclassification that Affected the Unemployment Rate

How hard can it be to figure out whether a person is employed or unemployed? Turns out, it can be hard. When BLS put out the employment and unemployment numbers for March, April, and May 2020, we also provided information about misclassification of some people. I want to spend some time to explain this issue, how it affected the data, and how we are addressing it.

In the monthly Current Population Survey of U.S. households, people age 16 and older are placed into one of three categories:

  • Employed — they worked at least one hour “for pay or profit” during the past week.
  • Unemployed — they did not work but actively looked for work during the past 4 weeks OR they were on temporary layoff and expect to return to work.
  • Not in the labor force — everyone else (including students, retirees, those who have given up their job search, and others).

Again, how hard can this be? It starts to get tricky when we talk to people who say they have a steady job but did not work any hours during the past week. In normal times, this might include people on vacation, home sick, or on jury duty. And we would continue to count them as employed. But during the COVID-19 pandemic, the collapse of labor markets created challenges the likes of which BLS has never encountered. People who reported zero hours of work offered such explanations as “I work at a sports arena and everything is postponed” or “the restaurant I work at is closed.” These people should be counted as unemployed on temporary layoff. As it turns out, a large number of people—we estimate about 4.9 million in May—were misclassified.

With the onset of the COVID-19 pandemic, the unemployment rate—at a 50-year low of 3.5 percent in February—rose sharply to 4.4 percent in March and to 14.7 percent in April, before easing to 13.3 percent in May. Despite the stark difference from February, we believe the unemployment rate likely was higher than reported in March, April, and May. As stated in our Employment Situation news releases for each of those months, some people in the Current Population Survey (also known as the CPS or household survey) were classified as employed but probably should have been classified as unemployed.

How did the misclassification happen?

We uncovered the misclassification because we saw a sharp rise in the number of people who were employed but were absent from their jobs for the entire reference week for “other reasons.” The misclassification hinges on how survey interviewers record answers to a question on why people who had a job were absent from work the previous week.

According to special pandemic-related interviewer instructions for this question, answers from people who said they were absent because of pandemic-related business closures should have been recorded as “on layoff (temporary or indefinite).” Instead, many of these answers were recorded as “other reasons.” Recording these answers as “on layoff (temporary or indefinite)” ensures that people are asked the follow-up questions needed to classify them as unemployed. It does not necessarily mean they would be classified as unemployed on temporary layoff, but I’ll get into that in a moment.

When interviewers record a response of “other reasons” to this question, they also add a few words describing that other reason. BLS reviewed these descriptions to better understand the large increase in the number of people absent from work for “other reasons.” Our analysis suggests this group of people included many who were on layoff because of the pandemic. They would have been classified as unemployed on temporary layoff had their answers been recorded correctly.

What are BLS and the Census Bureau doing to address the misclassification?

BLS and our partners at the U.S. Census Bureau take misclassification very seriously. We’re taking more steps to fix this problem. (The Census Bureau is responsible for collecting the household survey data, and BLS is responsible for analyzing and publishing the labor market data from the survey.) Both agencies are continuing to investigate why the misclassification occurred.

Before the March data collection, we anticipated some issues with certain questions in the survey because of the unprecedented nature of this national crisis. As a result, interviewers received special instructions on how to answer the temporarily absent question if a person said they had a job but did not work because of the pandemic. Nevertheless, we determined that not all of the responses to this question in March were coded according to the special instructions. Therefore, before the April data collection, all interviewers received an email that included instructions with more detailed examples, along with a reference table to help them code responses to this question. However, the misclassification was still evident in the April data. Before the May data collection, every field supervisor had a conference call with the interviewers they manage. In these conference calls, the supervisors reviewed the detailed instructions, provided examples to clarify the instructions, and answered interviewers’ questions.

Although we noticed some improvement for May, the misclassification persisted. Therefore, we have taken more steps to correct the problem. Before the June collection, the Census Bureau provided more training to review the guidance to the interviewers. The interviewers also received extra training aids. The electronic survey questionnaire also now has new special instructions that will be more accessible during survey interviews.

Why doesn’t BLS adjust the unemployment rate to account for the misclassification?

As I explained above, we know some workers classified as absent from work for “other reasons” are misclassified. People have asked why we just don’t reclassify these people from employed to unemployed. The answer is there is no easy correction we could have made. Changing a person’s labor force classification would involve more than changing the response to the question about why people were absent from their jobs.

Although we believe many responses to the question on why people were absent from their jobs appear to have been incorrectly recorded, we do not have enough information to reclassify each person’s labor force status. To begin with, we don’t know the exact information provided by the person responding to the survey. We know the brief descriptions included in the “other reasons” category often appear to go against the guidance provided to the survey interviewers. But we don’t have all of the information the respondent might have provided during the interview.

Also, we don’t know the answers to the questions respondents would have been asked if their answers to the question on the reason not at work had been coded differently. This is because people whose answers were recorded as absent from work for “other reasons” were not asked the follow-up questions needed to determine whether they should be classified as unemployed. Specifically, we don’t know whether they expected to be recalled to work and whether they could return to work if recalled. Therefore, shifting people’s answers from “other reasons” to “on layoff (temporary or indefinite)” would not have been enough to change their classification from employed to unemployed. We would have had to assume how they would have responded to the follow-up questions. Had we changed answers based on wrong assumptions, we would have introduced more error.

In addition, our usual practice is to accept data from the household survey as recorded. In the 80-year history of the household survey, we do not know of any actions taken on an ad hoc basis to change respondents’ answers to the labor force questions. Any ad hoc adjustment we could have made would have relied on assumptions instead of data. If BLS were to make ad hoc changes, it could also appear we were manipulating the data. That’s something we’ll never do.

How much did the misclassification affect the unemployment rate?

We don’t know the exact extent of this misclassification. To figure out what the unemployment rate might have been if there were no misclassification, we have to make some assumptions. These assumptions involve deciding (1) how many people in the “other reasons” category actually were misclassified, (2) how many people who were misclassified expected to be recalled, and (3) how many people who were misclassified were available to return to work.

In the material that accompanied our Employment Situation news releases for March, April, and May, we provided an estimate of the potential size of the misclassification and its impact on the unemployment rate. Here we assumed all of the increase in the number of employed people who were not at work for “other reasons,” when compared with the average for recent years, was due solely to misclassification. We also assumed all of these people expected to be recalled and were available to return to work.

For example, there were 5.4 million workers with a job but not at work who were included in the “other reasons” category in May 2020. That was about 4.9 million higher than the average for May 2016–19. If we assume this 4.9 million increase was entirely due to misclassification and all of these misclassified workers expected to be recalled and were available for work, the unemployment rate for May would have been 16.4 percent. (For more information about this, see items 12 and 13 in our note for May. We made similar calculations for March and April.)

These broad assumptions represent the upper bound of our estimate of misclassification. These assumptions result in the largest number of people being classified as unemployed and the largest increase in the unemployment rate. However, these assumptions probably overstate the size of the misclassification. It is unlikely that everyone who was misclassified expected to be recalled and was available to return to work. It is also unlikely that all of the increase in the number of employed people not at work for “other reasons” was due to misclassification. People may be correctly classified in the “other reasons” category. For example, someone who owns a business (and does not have another job) is classified as employed in the household survey. Business owners who are absent from work due to labor market downturns (or in this case, pandemic-related business closures) should be classified as employed but absent from work for “other reasons.”

Regardless of the assumptions we might make about misclassification, the trend in the unemployment rate over the period in question is the same; the rate increased in March and April and eased in May. BLS will continue to investigate the issue, attempting both to ensure that data are correctly recorded in future months and to provide more information about the effect of misclassification on the unemployment rate.

When Worlds Converge: Statistics Agencies Learning from Each Other during the Pandemic

We never know when our worlds are going to converge. I have used this blog to tell you about how BLS operations are continuing—and changing—due to the COVID-19 pandemic. I also plan to tell you about our international activities and will continue writing about the BLS Consumer Price Index (CPI) and other programs. Today, all three of these topics converge into one.

The COVID-19 pandemic has compelled BLS and statistical agencies worldwide to examine our processes and concepts to ensure the information we collect and publish reflects current conditions. For BLS, this means suspending all in-person data collection and relying on other methods, including telephone, internet, and email. Adding to our toolbox, BLS is now piloting video data collection. To be flexible, we have changed some collection procedures to accommodate current conditions. For example, we are now doing all of our work at home instead of in our offices. We are learning more every day about teleworking more effectively, and we are training our staff as we learn.

Once we collect the data, we are examining how we need to adapt our processing and publication. Will our typical procedures to account for missing data still apply? Will seasonal patterns in the data change due to COVID-19? Will we be able to publish the level of detail our data users have come to expect? These and more are open questions. We will make informed decisions as we learn more about the pandemic’s impact on our data and operations. What I do know is that BLS has a long practice of sharing its procedures and methods, including any changes. We already have extensive information about COVID-19 on the BLS website, and we continue to update that information. We also provide program-specific information with each data release to alert users to any unique circumstances in the data.

Since BLS has long been known for producing gold-standard data, information about our procedures and methods is also of great interest to our international colleagues. In fact, BLS has helped statistical organizations throughout the world with the collection, processing, analysis, publishing, and use of economic and labor statistics for more than 70 years. We provide this assistance primarily by our Division of International Technical Cooperation. They strengthen statistical development by organizing seminars, consultations, and meetings for international visitors with BLS staff. This division also serves as the main point of contact for the many international statistical organizations that compile information, publish comparable statistics worldwide, share concepts and definitions, and work to incorporate improvements and innovations.

A hallmark of our international activities has been onsite seminars at BLS, often attended by a multinational group of statistical experts and those working to become experts. At these seminars, BLS technical staff present details on every aspect of statistical programs, including concept development, sampling, data collection, estimation procedures, publishing, and more. In recent years, funding, travel restrictions, and other limitations have reduced the number of in-person events, replaced to some extent by virtual events. And of course, the current COVID-19 pandemic and related travel restrictions mean all such events are now being held virtually. But they still go on.

Recently, our international operations converged with our COVID-19 response when the International Technical Cooperation staff set up a virtual meeting between BLS staff primarily from our Consumer Price Index program and their counterparts at India’s Ministry of Statistics and Programme Implementation (MOSPI). They met to discuss challenges in producing consumer price data during the ongoing pandemic. The discussion was largely about methodology: what to do with missing prices and how to adjust weights to reflect real-time shifts in spending that consumers are making in response to the pandemic. It is helpful to hear from worldwide colleagues who are facing similar challenges. These issues are unprecedented, and we know the potential solutions for one country may not be ideal for the nuanced conditions in another country.

In India, for instance, commerce has been limited to essential commodities—food, fuel, and medicine. This will likely leave them unable to publish some indexes. While this is unfortunate in the present time, it is fairly straightforward; they can’t publish what they don’t have. It gets more complicated a year from now. What does it mean to have an annual price change when the denominator is missing? The CPI deals with this by having a fairly robust imputation system—basically “borrowing” price change from similar areas and items—but we will be monitoring the situation closely to make sure our assumptions about what is similar remain valid.

One advantage BLS has over MOSPI is that we are able to collect data by telephone, email, or on the web. MOSPI has traditionally only done in-person collection. Both agencies are transitioning to different modes of collection, but we have significantly greater experience.

Sharing information with our international colleagues, about the CPI and other programs, and about our COVID-19 experience, is a key part of the BLS mission. These worlds continue to converge, not just during organized meetings but also on websites and wikis maintained by statistical organizations and through participation in expert groups and conferences. For example, the United Nations Economic Commission for Europe hosts a ”statswiki” that currently has pages dedicated to COVID-19 and Official Statistics. It is a small world after all, and the worldwide social distancing we are all experiencing makes it clear that we are all in this together. And together, BLS and our international colleagues, reacting to COVID-19 and making adjustments to consumer price indexes and other statistics, will continue to provide vital information that tracks changes in the world economy.