Tag Archives: Statistics awareness

Why This Counts: Breaking Down Multifactor Productivity

Productivity measures tell us how much better we are at using available resources today compared to years past. All of us probably think about our own productivity levels every day, either in the workplace or at home. I find my own productivity is best in the morning, right after that first cup of coffee!

On a larger scale, here at the U.S. Bureau of Labor Statistics, we produce two types of productivity measures: labor productivity and multifactor productivity, which we will call “MFP” for short. An earlier Why This Counts blog post focused on labor productivity and its impact on our lives. In this blog we will focus on why MFP measures matter to you.

Why do we need two types of productivity measures?

Labor productivity compares the amount of goods and services produced—what we call output—to the number of labor hours used to produce those goods and services.

Multifactor productivity differs from labor productivity by comparing output not just to hours worked, but to a combination of inputs.

What are these combined inputs?

For any given industry, the combined inputs include labor, capital, energy, materials, and purchased services. MFP tells us how much more output can be produced without increasing any of these inputs. The more efficiently an industry uses its combination of inputs to create output, the faster MFP will grow. MFP gives us a broader understanding of how we are all able to do more with less.

Does MFP tell us anything about the impact of technology?

It does. But we cannot untangle the impact of technology from other factors. MFP describes the growth in output that is not a result of using more of the inputs that we can measure. In other words, MFP represents what is left, the sources of growth that we cannot measure. These include not just technology improvements but also changes in factors such as management practices and the scale or organization of production. Put simply, MFP uses what we do know to learn more about what we want to know.

What can MFP tell us about labor productivity?

Labor productivity goes up when output grows faster than hours. But what exactly causes output to grow faster than hours? Labor productivity can grow because workers have more capital or other inputs or their job skills have improved. Labor productivity also may grow because technology has advanced, management practices have improved, or there have been returns to scale or other unmeasured influences on production. MFP statistics help us capture these influences and measure their impact on labor productivity growth.

How are MFP statistics used?

We can identify the sources of economic growth by comparing MFP with the inputs of production. This is true for individual industries and the nation as a whole.

For example, a lot has been written about the decline of manufacturing in the United States. MFP increased between 1992 and 2004 by an average of 2.0 percent per year. In contrast, MFP declined from 2004 through 2016 by an average of 0.3 percent per year. A recently published article uses detailed industry data to analyze sources of this productivity slowdown.

MFP is a valuable tool for exploring historical growth patterns, setting policies, and charting the potential for future economic growth. Businesses, industry analysts, and government policymakers use MFP statistics to make better decisions.

Where can I go to learn more?

Check out the most recent annual news release to see the data firsthand!

If you have a specific question, you might find it answered in our Frequently Asked Questions. Or you can always contact MFP staff through email or call (202) 691-5606.

Just like your own productivity at work and at home, the productivity growth of our nation can lead to improvements in the standard of living and the economic well-being of the country. Productivity is an important economic indicator that is often overlooked. We hope this blog has helped you to learn more about the value of the MFP!

Topics: Industries | Productivity | Students (K-12) | U.S. Statistical System | Why This Counts
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BLS Measures Electronically Mediated Work

Are you a ride-share driver using a mobile app (like Uber or Lyft) to find customers? Maybe you do household chores or yardwork for others by finding short-term jobs through a website (such as TaskRabbit or Handy) that arranges the payment for your work. Or perhaps you perform online tasks, like taking surveys or adding descriptive keywords to photos or documents through a platform (like Amazon Mechanical Turk or Clickworker). If so, you are an electronically mediated worker. That’s a term BLS uses to identify people who do short jobs or tasks they find through websites or mobile apps that connect them with customers and arrange payment for the tasks. Have you ever wondered how many people do this kind of work?

BLS decided to find out. In the May 2017 Contingent Worker Supplement to the Current Population Survey, we asked people four new questions designed to measure electronically mediated employment.

Measuring electronically mediated work is difficult

After studying respondents’ answers to the new questions and other information we collected about them, we realized the new questions didn’t work as intended. Most people who responded “yes” to the questions clearly had not found their work through a website or app. For example, a vice president of a major bank, a local police officer, and a surgeon at a large hospital all said they had done electronically mediated work on their main job. Many people seemed to think we were asking whether they used a computer or mobile app on their job. That could apply to many jobs that aren’t electronically mediated.

But it wasn’t all for naught. After extensive evaluation, we concluded we could use the other information in the survey about respondents’ jobs to identify and recode erroneous answers. That allowed us to produce meaningful estimates of electronically mediated employment.

So, who does electronically mediated work?

Based on our recoded data, we found that 1.6 million people did electronically mediated work in May 2017. These workers accounted for 1.0 percent of total employment. Compared with workers overall, electronically mediated workers were more likely to be ages 25 to 54 and less likely to be age 55 or older. Electronically mediated workers also were slightly more likely to be Black, and slightly less likely to be White, than workers in general. In addition, electronically mediated workers were more likely than workers overall to work part time (28 percent versus 18 percent).

Workers in the transportation and utilities industry were the most likely to have done electronically mediated work, with 5 percent of workers in this industry having done such work. Self-employed workers were more likely than wage and salary workers to do electronically mediated work (4 percent versus 1 percent).

What’s next?

We currently don’t have plans to collect information on electronically mediated work again. And even if we did, we wouldn’t want to use the same four questions. At the least, we would need to substantially revise the questions so they are easier for people to understand and answer correctly.

Taking a broader look, we are working with the Committee on National Statistics to learn more about what we should measure if we field the survey again. The committee is a federally supported independent organization whose mission is to improve the statistical methods and information on which public policies are based.

How can I get more information?

The data are available on our website, along with an article that details how we developed the questions, evaluated the responses, recoded erroneous answers, and analyzed the final estimates.

If you have a specific question, you might find it in our Frequently Asked Questions. Or you can contact our staff.

Topics: Employment | Industries | Labor Force Characteristics | Monthly Labor Review | Survey Respondents
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The Griswold Family Vacation through the Lens of BLS Data

We have a guest blogger for this edition of Commissioner’s Corner. Joy Langston is a budget analyst at the U.S. Bureau of Labor Statistics. She enjoys watching classic movies when she’s not working.

As summer wraps up, let’s slow the transition into cooler weather to explore the dream American summer vacation of the Griswold family. America first met the Griswolds in the cult classic National Lampoon’s Vacation. We’ll relive their vacation through the lens of our gold-standard data. Clark Griswold, the easygoing and optimistic patriarch of the family, wants a fun vacation with his wife, Ellen, and adolescent son and daughter, Rusty and Audrey, before the kids grow up. For the past 15 years, Clark has worked as a food scientist creating “new and better food additives.” Data from the 2017 Employee Benefits Survey show that after 10 years of service, full-time workers like Clark receive on average 18 days of vacation, or almost 4 weeks.

Since he has the time, Clark decides to lead the family on a cross-country expedition from the Chicago suburbs to Walley World — “America’s Favorite Family Fun Park” in Southern California. Ellen agrees to the destination but wants to fly, as it will be less of a hassle. However, data from the Consumer Expenditure Surveys suggest driving may not be a bad idea. The average amount a household spent on vacations was $2,076 in 2017, with $684 for transportation costs, so flying from Chicago to Southern California was likely not in the Griswolds’ budget. To jumpstart this trip, Clark ordered the new “Antarctic Blue Super Sports Wagon with the Rally Fun Pack” from the local car dealership. He is scammed into buying the far less appealing, but now iconic, metallic pea, wood grained trimmed station wagon instead. Nevertheless, Clark is determined to make this the best family vacation ever.

Eventually, Ellen gives in to her husband’s enthusiasm and the Griswolds embark on their adventure, but not before stopping for their first tank of gas. You may remember that Clark struggled to find the gas tank, which was ridiculously located under the hood, by the engine, on the passenger’s side. The average household spent $109 in 2017 on gas for out-of-town trips and $1,797 for all uses. In July 2018, the national average price of gas was $2.93 per gallon, according to the Consumer Price Index. Although America has traded in station wagons for SUVs, neither are gas efficient and the Griswolds probably had to fuel up frequently on the 2,460-mile drive.

The family’s first misstep includes taking the wrong exit in St. Louis, Missouri, where they lose a couple of car parts while stopping to ask for directions in a questionable neighborhood. Despite this portrayal of St. Louis, the Occupational Employment Statistics data show this metro area had about 1.4 million jobs in 2017. About 16 percent of them were in office and administrative support occupations, with an average wage of $37,720 per year. Another 10 percent of jobs were in sales and related occupations, and 7 percent were in healthcare practitioners and technical occupations.

Driving through Kansas, they stop in Dodge City to experience life in the Wild West and order drinks in a saloon. According to the Current Employment Statistics survey, stops like these, including historical sites and other historical institutions, provide an average of 69,000 jobs from May to August nationwide.

The Griswolds make it to Coolidge, Kansas, where Ellen’s cousins live. The cousins pressure Clark and Ellen into dropping off cantankerous Aunt Edna — and her equally feisty dog — at her son’s home in Phoenix, Arizona. According to the American Time Use Survey Americans spend an average of 39 minutes a day — or about 237 hours a year — socializing and communicating in person. The survey also shows that Americans spend an average 4 minutes a day caring for and helping nonhousehold adults. The Griswold family gets a concentrated dose of this social activity by adding Aunt Edna to their road trip party.

For lunch, they stop off at rest stop to enjoy some homemade sandwiches. The average American household spent $56 in 2017 on food prepared for out-of-town trips, and $3,365 on food away from home (including fast food establishments and full service restaurants). The Griswolds’ enjoyment is cut short when they realize there is more to their soggy baloney cheese sandwiches than they bargained for. As it turns out, Aunt Edna’s spiteful dog used the picnic basket as a bathroom during the car ride. If you’re driving with a pet and want to avoid this mishap, Kansas has more than 4,600 restaurants and eating places to choose from, according to the Quarterly Census of Employment and Wages.

They spend the night in one of Colorado’s 98 campgrounds in three large, smelly tents. Despite their positive attitudes the next morning, the Griswolds meet with more misfortunes, including being pulled over by a state trooper, Ellen losing her bag with the credit cards, quarrels over their dwindling cash supply, and crashing in the Arizona desert while trying to find a shortcut to the Grand Canyon. After they are rescued and towed to a service station, Clark haggles with the local mechanic, who doubles as the local sheriff, and takes the rest of Clark’s cash. The average American household spent $954 on car maintenance and repairs in 2017, although costs usually are spread throughout the year and not on vacation misadventures.

By the time they drop off Aunt Edna in Phoenix, Ellen and the kids are begging Clark to buy plane tickets to go back home. However, Clark’s enthusiasm hasn’t waned, and he declares this road trip a pilgrimage.

When they finally arrive at Walley World, they discover it is closed for the next two weeks for repairs. Exasperated, Clark demands the security guard open the gates and let the family into the park. After a couple rollercoaster rides, the SWAT team and owner of the park, Roy Walley, arrive. As the police put handcuffs on Clark’s family, Clark begs Roy not to press charges. Clark persuades Roy not only to drop the charges but to allow the family to stay and enjoy all the rides! Americans do love their theme parks. There were nearly 1,000 theme parks in the United States in 2017, with 87 of them in California. These parks provided 185,000 jobs nationwide. This industry increased its labor productivity 13.7 percent in 2017, as theme parks reported higher output while hours worked by employees decreased.

Over the course of their trip, the Griswolds share a number of experiences, many of which either hit a little too close to home, or we hope to never experience for ourselves. After a long and tiresome trip, we hope Ellen finally has her way and Clark doesn’t force the Griswolds to spend another two weeks driving back to Chicago, which would deplete all his vacation days! This classic summer movie shows that BLS really does have a stat for that!

Topics: Benefits and Compensation | Career Outlook | Consumer Spending | Earnings and Wages | Employment | Geographic Information | Industries | Inflation and Prices | Labor Force Characteristics | Occupational Outlook Handbook | Occupations | Productivity | Time Use
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Labor Day 2018 Fast Facts

About 92 percent of civilian workers with access to paid holidays receive Labor Day as a paid holiday. Before you set out for that long holiday weekend, take a moment to look at some fast facts we’ve compiled that show the current picture of our labor market.

Working

Working or Looking for Work

  • The civilian labor force participation rate—the share of the population working or looking for work—was 62.9 percent in July. The rate had trended down from the 2000s through the early 2010s, but it has remained fairly steady since 2014.

Not Working

  • The unemployment rate was 3.9 percent in July. After 6 months at 4.1 percent, the rate has had offsetting movements in recent months. In May, the rate hit its lowest point, 3.8 percent, since April 2000.
  • In July, there were 1.4 million long-term unemployed (those jobless for 27 weeks or more). This represented 22.7 percent of the unemployed, down from a peak of 45.5 percent in April 2010 but still above the 16-percent share seen in late 2006.
  • Among the major worker groups, the unemployment rate for teenagers was 13.1 percent in July, while the rates were 3.4 percent for adult men and 3.7 percent for adult women. The unemployment rate was 6.6 percent for Blacks or African Americans, 4.5 percent for Hispanics or Latinos, 3.1 percent for Asians, and 3.4 percent for Whites.

Job Openings

Pay and Benefits

  • Average weekly earnings rose by 3.0 percent between July 2017 and July 2018; adjusted for inflation, real average weekly earnings are up 0.1 percent during this period.
  • Civilian compensation (wage and benefit) costs increased 2.8 percent between June 2017 and June 2018; adjusted for inflation, real compensation costs decreased 0.1 percent during this period.
  • Paid leave benefits are available to most private industry workers. The access rates in March 2018 were 71 percent for sick leave, 77 percent for vacation, and 78 percent for holidays.
  • In March 2018, civilian workers paid 20 percent of the cost of medical care premiums for single coverage and 32 percent for family coverage.

Productivity

  • Labor productivity—output per hour worked—in the U.S. nonfarm business sector grew 1.1 percent in 2017, continuing the historically below-average pace seen since the Great Recession. Some industries had impressive growth, however, including wireless telecommunications carriers (11.1 percent) and electronics and appliance stores (9 percent).
  • Multifactor productivity growth in the private nonfarm business sector recovered in 2017, rising 0.9 percent after falling 0.6 percent in 2016. Labor input for multifactor productivity—measured using the combined effects of hours worked and labor composition—grew 2.0 percent in 2017, outpacing the long-term 1987–2017 growth for labor input by 0.5 percentage points.

Safety and Health

  • In 2017, 14.3 percent of all workers were exposed to hazardous contaminants. The use of personal protective equipment was required for 11.8 percent of workers.

Education

  • Occupations that typically require a bachelor’s degree for entry made up 21.5 percent of employment. This educational category includes registered nurses, teachers at the kindergarten through secondary levels, and many management, business and financial operations, computer, and engineering occupations.
  • For 18 of the 30 occupations projected to grow the fastest between 2016 and 2026, some postsecondary education is typically required for entry.

Unionization

  • The union membership rate—the percent of wage and salary workers who were members of unions—was 10.7 percent in 2017, unchanged from 2016. 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 union workers were $47.65 and for nonunion workers $32.87 per employee hour worked. The cost of benefits accounted for 40.4 percent of total compensation or $19.23 for union workers and 29.1 percent or $9.56 for nonunion workers.

Work Stoppages

  • In the first 7 months of 2018, there were 445,000 workers involved in work stoppages that began this year. This is the largest number of workers involved in stoppages since 2000, when 394,000 workers were involved. There have been 12 stoppages beginning this year, which surpassed the 7 recorded in all of 2017.

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.

Topics: Benefits and Compensation | Beyond the Numbers | Earnings and Wages | Educational Attainment | Employment | Employment Projections | Geographic Information | Industries | Job Openings, Hires, and Separations | Labor Force Characteristics | Occupations | Productivity | The Economics Daily | U.S. Statistical System | Unemployment | Union Membership | Workplace Injuries and Illnesses
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A Clearer Look at Response Rates in BLS Surveys

Hands holding a tablet computer and completing a surveyPeople know BLS for our high-quality data on employment, unemployment, price trends, pay and benefits, workplace safety, productivity, and other topics. We strive to be transparent in how we produce those data. We provide detailed information on our methods for collecting and publishing the data. This allows businesses, policymakers, workers, jobseekers, students, investors, and others to make informed decisions about how to use and interpret the data.

We couldn’t produce any of these statistics without the generous cooperation of the people and businesses who voluntarily respond to our surveys. We are so grateful for the public service they provide.

To improve transparency about the quality of our data, we recently added a new webpage on response rates to our surveys and programs. We previously published response rates for many of our surveys in different places on our website. Until now there hasn’t been a way to view those response rates together in one location.

What is a response rate, and why should I care?

A response rate is the percent of potential respondents who completed the survey. We account for the total number of people, households, or businesses we tried to survey (the sample) and the number that weren’t eligible (for example, houses that were vacant or businesses that had closed). Response rates are an important measure for survey data. High response rates mean most of the sample completed the survey, and we can be confident the statistics represent the target population. Low response rates mean the opposite, and data users may want to consider other sources of information.

Do response rates tell the whole story?

A low response rate may mean the data don’t represent the target population well, but not necessarily. How much a low response rate affects how well the estimates represent the population is called nonresponse bias. Some important research by Robert M. Groves and Emilia Peytcheva published in the January 2008 issue of Public Opinion Quarterly looked at the connection between response rates and nonresponse bias in 59 studies. The authors found that high response rates can reduce the risk of bias, but there is not a strong correlation between response rate and nonresponse bias. Some surveys had a very low response rate but did not have evidence of high nonresponse bias. Other surveys had high nonresponse bias despite high response rates.

This means we should look at response rates with other measures of data quality and bias. BLS has studied nonresponse bias for many years. We have links to many of those studies in our library of statistical working papers.

What should I be looking for on the new page?

With response rates from multiple surveys in a single place, you can look for patterns across surveys and across time. For example, across every graph we see that response rates are declining over time. This is happening for nearly all surveys, government and private, on economic and other topics. It is simply getting harder to persuade respondents to answer our surveys.

Individual survey response rates are also interesting compared with other BLS surveys. We see that some surveys have higher response rates than others. To understand why this might be, we’ll want to look at the differences between the surveys. Each survey has specific collection procedures that affect response rates. For example, the high response rate for the Annual Refiling Survey (shown as ARS in the second chart) may catch your eye. When you see that it has a 12-month collection period and is mandatory in 26 states, the rate makes more sense.

We also can see how survey-specific changes have affected a survey’s response rate. For example, we see a drop in the response rate for the Telephone Point of Purchase Survey around 2012. This drop likely resulted from a change in sample design, as the survey moved from a sample of landline telephones to a dual-frame sample with both landlines and cell phones. Because the response rate for this survey continues to decline, we are developing a different approach for collecting the needed data.

What should I know before jumping into the new page?

There’s a lot of information! We’ve tried to make it as user friendly as possible, including a glossary page with definitions of terms and a page to show how each survey calculates their response rates. On the graphs, you can isolate a single survey by hovering over each of the lines. You can also download the data shown in each graph to examine it more closely.

We hope you will find this page helpful for understanding the quality of BLS data. Please let us know how you like it!

Topics: Benefits and Compensation | Consumer Spending | Earnings and Wages | Employment | Employment Projections | Geographic Information | Inflation and Prices | Labor Force Characteristics | Productivity | Survey Respondents | U.S. Statistical System | Unemployment | Workplace Injuries and Illnesses
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