Topic Archives: Industries

Ensuring Gold-Standard Data in the Eye of a Storm

“Hurricanes Harvey, Irma and Maria were the most notable storms of 2017, leaving paths of death and destruction in their wake.”
Colorado State University’s Tropical Meteorology Project 2017 summary report

Colorado State University’s Tropical Meteorology Project is forecasting the 2018 hurricane season activity (as of May 31) to be average, with 13 named storms, 6 hurricanes, and 2 major hurricanes expected. Is BLS ready?

How does BLS deal with hurricanes?

Since June starts hurricane season, we want to share with you one example of how last year’s storms affected our data. We present a case study using our national employment survey, the Current Employment Statistics program. This program provides monthly estimates we publish in The Employment Situation—sometimes called the “jobs report.”

We have procedures to address natural disasters. We highlight some of our challenges and how we address them. We do everything possible to provide you with gold-standard data to help you make smart decisions!

2017 Hurricane Destruction

Two major hurricanes—Harvey and Irma—blasted the U.S. mainland in August and September 2017. Hurricane Maria devastated Puerto Rico and the U.S. Virgin Islands later in September.

  • Harvey first made landfall in Texas on August 25. The Federal Emergency Management Agency (FEMA) declared 39 Texas counties eligible for federal disaster assistance after Harvey. Harvey also caused heavy damage in Louisiana.
  • Irma hit the Florida Keys on September 10 and then later hit Florida’s southern coast. FEMA declared 48 Florida counties eligible for federal disaster assistance. Before Irma hit the lower Florida Keys, the hurricane already had caused severe damage in St. Thomas and St. John in the U.S. Virgin Islands and in Puerto Rico.
  • Hurricane Maria made landfall in St. Croix in the U.S. Virgin Islands and in Puerto Rico on Wednesday, September 20, causing catastrophic damage. These areas already had suffered damage from Hurricane Irma earlier in the month.

Some things to know about the monthly employment survey

The monthly employment survey is a sample of nonfarm businesses and government agencies. The reference period is the pay period that includes the 12th of the month. The sample has just over 23,000 active reporting units in the disaster areas, representing about 6 percent of the entire active sample.

What does it mean to be employed? If the employer pays someone for any part of the reference pay period, that person is counted as employed.

How did BLS collect data in these disaster areas?

Our biggest challenge is to collect representative sample data so we publish high-quality estimates. In the “old days,” the survey was a mail survey (yes, I mean snail mail), but no more! Now we collect data electronically by several different methods. These are the most common:

  • About half the total sample uses electronic data interchange. That’s a centralized electronic data reporting system for multi-establishment firms. The firm provides an electronic file directly from their payroll system to BLS for all establishments included in the report. Most of the firms reporting are outside of the hurricane-affected areas, although they may report on establishments within the affected areas.
  • About 23 percent of establishments use computer-assisted telephone interviews.
  • Another 16 percent report using our Internet Data Collection Facility.

Using these methods, we were able to collect data from most sampled businesses in these areas using normal procedures.

What about the emergency workers working in the disaster areas? How are they counted?

  • We count emergency workers where their employer is located, not where they are working.
  • We don’t count volunteers as employed because they are not paid.
  • Activated National Guard troops are considered active duty military and are outside the scope of the survey.

Did the estimation procedures change?

Once we collect the data from businesses in the affected areas, we consider whether we need to change our estimation procedures to adjust for missing data. The survey staff determined that we didn’t need to change our methods because the collection rates in the affected areas were within normal ranges.

How did the hurricanes affect national employment data for September 2017?

Hurricanes Harvey and Irma reduced the estimate of national payroll employment for September 2017. We can’t measure the effects precisely because the survey is not designed to isolate the effects of catastrophic events. National nonfarm employment changed little (+14,000) in September 2017, after increasing by an average of 189,000 per month over the prior 12 months. A steep employment decline in food services and drinking places and below-trend growth in some industries likely reflected the impact of Hurricanes Harvey and Irma.

What about Puerto Rico and the U.S. Virgin Islands?

National nonfarm employment estimates do not include Puerto Rico or the U.S. Virgin Islands.

Because of the devastation caused by Hurricanes Irma and Maria, Puerto Rico and the U.S. Virgin Islands could not conduct normal data collection for their establishment surveys. The September estimates for Puerto Rico and the Virgin Islands were delayed. The October and November estimates for the Virgin Islands also were delayed. Puerto Rico and the Virgin Islands eventually were able to produce estimates for September, October, and November 2017.

Want more information?

For more information on the impact of Harvey, Irma, and Maria, check out these pages:

What else does BLS know about hurricanes?

The Quarterly Census of Employment and Wages produces maps of businesses and employment in flood zones for states on the Atlantic and Gulf Coasts that are vulnerable to hurricanes and tropical storm. You can read more about those maps in another recent blog.

We hope the 2018 hurricane season won’t bring the loss of life and destruction of property that we saw in 2017. Regardless of what the season brings, BLS will be ready to continue providing gold-standard data about the labor market and economy.

BLS Big Data Delivers Hurricane Flood Zone Maps

Information is key to preparing for a natural disaster. That’s why we have updated our maps of businesses and employment in flood zones for states on the Atlantic and Gulf Coasts that are vulnerable to hurricanes and tropical storms.

These maps combine data from the Quarterly Census of Employment and Wages with the most up-to-date information from the U.S. Census Bureau and U.S. Geological Survey. The result is high-resolution graphics for every county with hurricane flood zones along or inland from the Atlantic and Gulf Coasts.

The Quarterly Census of Employment and Wages is our “Big Data” program. It gathers data from 9.9 million reports that almost every employer in the United States, Puerto Rico, and the U.S. Virgin Islands files each quarter. We have been producing maps of businesses and employment in disaster areas since 2001, when we created zip code maps and tables of Lower Manhattan. We began mapping hurricane zones in 2014, combining BLS data with flood zones created by the U.S. Army Corps of Engineers and state emergency management agencies.

These maps are one way we use Big Data to create new products without increasing the burden on our respondents. Within BLS, we use these maps for research into the data collection and economic effects of a storm. We also provide these maps to state labor market information offices to use for their statistical analysis and emergency response.

Hurricane maps highlight how we use emerging technologies. We create these maps with open source mapping software, part of our open data practices that make it easier for decision makers to get and use the data.

This isn’t our only example of matching Quarterly Census of Employment and Wages data with data from other federal agencies to deliver new insights. We have matched our data with publicly available Internal Revenue Service data to measure employment and wages in nonprofit organizations. We also are working with our colleagues at the Bureau of Economic Analysis to improve understanding of foreign direct investment in the United States. When these data become available, users can analyze employment and wages by industry and occupation in firms with and without foreign direct investment.

All of these efforts improve the quality and breadth of information available for decision makers. If you have ideas about other partnerships with our Big Data team, please send us a message or give us a call!

Using Seasonally Adjusted Data or Not: a Case Study

The Current Employment Statistics survey helps us track employment trends in the economy. The headline figures, such as the 164,000 increase in payroll employment in April, are seasonally adjusted. Seasonal adjustment smooths out increases or decreases that occur around the same time each year to make it easier to see the underlying movements in the data.

Consider the construction industry, where employment varies throughout the year, often because of the weather. The chart below shows employment each month in 2017, both seasonally adjusted and not seasonally adjusted. The not seasonally adjusted level ranged from about 6.4 million to 7.2 million jobs, but it is hard to see a trend. The seasonally adjusted level was consistently between 6.8 million and 7.1 million jobs. When we remove the seasonal variation, we can see a slight increase in construction employment over the year.

Construction employment in 2017, seasonally adjusted and not seasonally adjusted

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

While seasonally adjusted data help us see long-term trends, there are times when short-term trends can provide some insight. One example is holiday-season hiring. Certain industries, such as retail trade and parcel delivery services, ramp up hiring in the fall to prepare for increased business during the holiday season. We can see this holiday-related employment buildup with data that are not seasonally adjusted. For example, employment growth in selected retail trade industries increased by 609,000 from October to December 2017, less than the 650,000 jobs gained in the same months of 2016.

Note: Selected retail trade industries include furniture and home furnishings stores; electronics and appliance stores; health and personal care stores; clothing and clothing accessories stores; sporting goods, hobby, book and music stores; general merchandise stores; miscellaneous store retailers; and nonstore retailers.

Seasonal holiday employment buildup in selected retail trade industries, 2012–17 (not seasonally adjusted)

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

We have to be careful when we use data that are not seasonally adjusted. For example, sometimes there are 4 weeks between monthly surveys and sometimes there are 5 weeks. Seasonal adjustment accounts for these differences. When using not seasonally adjusted data, users must be aware that an extra week between surveys can exaggerate seasonal employment increases or decreases. For example, in 2017, there were 5 weeks between surveys in November, just as there were in 2012 and 2013.

Looking across the October-to-December period, the seasonal employment buildup in retail trade slowed each year following a large increase from 2012 to 2013. In each of the next four holiday seasons, job gains over the 3-month (13-week) period were less than the prior year. But 2017 included some anomalies – a strong November (72 percent of the seasonal total), followed by a weak December (7 percent of the seasonal total).

Share of seasonal holiday employment buildup in each month, selected retail trade industries, 2012–17 (not seasonally adjusted)

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

Examining the not seasonally adjusted data may provide some insights into changing hiring patterns, especially in seasonal industries. The 2017 retail trade data suggest declining holiday employment buildup but also earlier holiday employment buildup. Will this pattern continue? We’ll know more when Current Employment Statistics data come out later this year.

We can analyze other industries with seasonal patterns in a similar way. One industry is transportation, and specifically couriers and messengers, which includes parcel delivery services. As the trend in online shopping continues, employment in parcel delivery services has increased, especially during the holiday season. Other seasonal industries include ski resorts in the winter, gardening shops in the spring, and amusement parks in the summer. We can also use not seasonally adjusted data to look at layoff patterns in seasonal industries, such as certain retail industries after the holiday season.

All these data are available from the Current Employment Statistics program.

Construction employment in 2017
Month Seasonally adjusted Not seasonally adjusted
Jan 6,873,000 6,459,000
Feb 6,919,000 6,527,000
Mar 6,922,000 6,634,000
Apr 6,917,000 6,816,000
May 6,924,000 6,990,000
Jun 6,940,000 7,157,000
Jul 6,934,000 7,197,000
Aug 6,962,000 7,228,000
Sep 6,971,000 7,177,000
Oct 6,988,000 7,182,000
Nov 7,030,000 7,117,000
Dec 7,072,000 6,970,000
Seasonal holiday employment buildup in selected retail trade industries, 2012–17 (not seasonally adjusted)
Year October November December
2012 132,000 456,000 103,000
2013 142,000 435,000 184,000
2014 169,000 392,000 158,000
2015 175,000 389,000 127,000
2016 148,000 358,000 144,000
2017 128,000 438,000 43,000
Share of seasonal holiday employment buildup in each month, selected retail trade industries, 2012–17 (not seasonally adjusted)
Year October November December
2012 19.1% 66.0% 14.9%
2013 18.7 57.2 24.2
2014 23.5 54.5 22.0
2015 25.3 56.3 18.4
2016 22.8 55.1 22.2
2017 21.0 71.9 7.1

Small Businesses: This is for YOU!

This week is National Small Business Week, which recognizes the critical contributions of America’s small business owners and workers to our economy. The U.S. economy is fueled by small businesses, which employ about 69 million workers!

Here at the U.S. Bureau of Labor Statistics, we work closely with small businesses every day in two main ways:

  • Small businesses participate in our voluntary statistical surveys, so thanks for your cooperation!
  • BLS data help small businesses make smart decisions.

To celebrate Small Business Week, this blog shares some information about small businesses in our current economy and some testimonials from small business owners who use BLS data.

“As the owner of All Things Career Consulting (and a self-proclaimed data geek), I spend a lot of time working with organizations to develop recruiting programs. I also provide individual coaching on navigating career change, especially military transitions. What I like about BLS data is that they help me tell my clients a story about the labor force. It’s important for both employers and employees to understand what jobs are growing and how things such as the unemployment rate impact the job market. So many times people run with a myth that they have heard without digging into the data to find the truth. BLS data help them to set realistic expectations about job prospects, as well as salaries and benefits.” --Lisa Parrott, Owner (Overland Park, Kansas)

 

What is a small business?

We define small establishments as establishments with fewer than 100 workers. What is an establishment? It’s the physical location of an economic activity—for example, a factory, mine, store, or office. An establishment is not necessarily a firm; it may be a branch plant, for example, or a warehouse. Thus, small establishments may include a “mom and pop” grocery store or a small storage facility.“My company, Cornerstone Macro, provides timely analysis of macroeconomic trends to institutional investors. The Bureau’s comprehensive, reliable, and objective statistics – from employment, to inflation, to productivity – are essential to our understanding of the cyclical and secular forces shaping the investment landscape. Without these data, we would not be able to provide best-in-class research to our customers.” --Nancy R. Lazar, Co-Founder (New York, New York)

What is the source of these data?

Each quarter we publish counts of employment and wages reported by employers. These counts, from the Quarterly Census of Employment and Wages, cover more than 97 percent of U.S. jobs. We have detail available at the county, metropolitan area, state, and national levels by industry.

So the quarterly census doesn’t cover every worker in the United States, but it is very close!

How many small businesses are there and how many people do they employ?

Percent distribution of establishments and employment by size of establishment, private sector, March 2017

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

Highlights:

  • About 69 million workers—57 percent of all private sector workers—were employed in over 9 million small establishments during March 2017.
  • Small establishments make up over 97 percent of all establishments in the nation. The remaining establishments (181,000), those with 100 or more workers, employed over 51 million workers.
  • A whopping 62 percent of establishments fall within the smallest size class, fewer than 5 employees.

“My company, Piedmont Grocery Co., has been a family owned independent purveyor of fine foods and spirits in Oakland, CA since 1902. We use the Bureau’s consumer price indexes to calculate inflation rates that are used to determine incremental rent increases. Without these timely and objective stats, we could potentially be paying more for our rent than is necessary.” --Amy Pence, Vice President (Oakland, California)

In what industries do we find small businesses?

Percentage of private employment in each industry that is in small establishments, March 2017

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

Highlights:

  • Employment in small establishments varies among industries.
  • Real estate and rental and leasing, construction, and wholesale trade have much of their employment in small establishments. It’s more than 80 percent in real estate and rental and leasing.
  • In contrast, 36 percent of manufacturing employment and 43 percent of transportation and warehousing employment are in small establishments.

“QED Consulting provides consulting and training in Leadership, Ethics, Culture, Diversity, & Inclusion to global Fortune 500 companies, governments, and international organizations. We use the Bureau’s data on demographic trends to illustrate the need for organizational policies that make diversity and inclusion work. These objective statistics assist us to help our clients be best in class in terms of diversity and inclusion.” --Alan Richter, Founder and President (New York, New York)

Want to learn more about small businesses? Check out the most recent news release to get all the latest numbers. See our Frequently Asked Questions, or contact us at (202) 691-6567 or by email.

Thank you, small businesses, for your participation and know that we are here to help you in your statistical needs. Happy Small Business Week!

 

Percent distribution of establishments and employment by size of establishment, private sector, March 2017
Establishment size Establishments Employment
Fewer than 5 employees 62% 7%
5–9 employees 15 8
10–19 employees 11 11
20–49 employees 7 18
50–99 employees 2 13
100 or more employees 2 43
Percentage of private employment in each industry that is in small establishments, March 2017
Industry Percent
Real estate and rental and leasing 82%
Construction 74
Wholesale trade 71
Retail trade 64
Services 59
Mining 51
Finance and insurance 51
Transportation and warehousing 43
Manufacturing 36

Why This Counts: What is the Producer Price Index and How Does It Impact Me?

The Producer Price Index (PPI) – sounds familiar, but what is it exactly? Didn’t it used to be called the Wholesale Price Index? It is related to the Consumer Price Index, but how? How does the PPI impact me?

Lots of questions! In this short primer we will provide brief answers and links for more information. Note, if you are an economist, this blog is NOT for you. It’s an introduction for everyone else!

Video: Introduction to the Producer Price Index

Before we go any further – what is an index? (You said this was a primer!)

An index is like a ruler. It is a way of measuring the change of just about anything. Producer price indexes measure the average change in prices for goods, services, or construction products sold as they leave the producer.

Here is an example of how an index works:

  • Suppose we created an index to track the price of a gallon of gasoline.
  • When we start tracking, gasoline costs $2.00 a gallon.
  • The starting index value is 100.0.
  • When gasoline rises to $2.50, our index goes to 125.0, which reflects a 25-percent increase in the price of gasoline.
  • If gasoline then drops to $2.25, the index goes to 112.5. The $0.25 decline in price reflects a 10-percent decrease in the price of gasoline from when the price was $2.50.

If you are a gasoline dealer, you might find a gasoline index useful. Instead of driving around every day to write down the prices of each competitor’s gasoline and averaging them together, the index can provide the data for you. (Question #5 in the PPI Frequently Asked Questions explains how to interpret an index.)

PPI is called a “family” of indexes. There are more than 10,000 indexes for individual products we release each month in over 500 industries. That is one big family!

OK, so PPI has lots of data – but what kind of data?

PPI produces three main types of price indexes: industry indexes, commodity indexes, and final demand-intermediate demand (FD-ID) indexes.

An industry refers to groups of companies that are related based on their primary business activities, such as the auto industry. The PPI measures the changes in prices received for the industry’s output sold outside the industry.

  • PPI publishes about 535 industry price indexes and another 500 indexes for groupings of industries.
  • By using the North American Industry Classification System (NAICS) index codes, data users can compare PPI industry-based information with other economic programs, including productivity, production, employment, wages, and earnings.

The commodity classification of the PPI organizes products by type of product, regardless of the industry of production. For example, the commodity index for steel wire uses pricing information from the industries for iron and steel mills and for steel wire drawing.

  • PPI publishes more than 3,700 commodity price indexes for goods and about 800 for services.
  • This classification system is unique to the PPI and does not match any other standard coding structure.

We also have more information on the differences between the industry and commodity classification systems.

The FD-ID classification of the PPI organizes groupings of commodities by the type of buyer. For example, the PPI for final demand measures price change in all goods, services, and construction products sold as personal consumption, capital investment, export, or to government. As a second example, the PPI for services for intermediate demand measures price change for services sold to business as inputs to production.

  • PPI publishes more than 300 FD-ID indexes.
  • This FD-ID classification system is unique to the PPI and does not match any other standard coding structure.

Now let’s go back to the beginning

  • 1902: Wholesale Price Index program begins, which makes it one of the oldest continuous set of federal statistics. The Wholesale Price Index captures the prices producers receive for their output. In contrast, the Consumer Price Index captures the prices consumers pay for their purchases.
  • 1978: BLS renames the program as the Producer Price Index to more accurately reflect that prices are collected from producers, rather than wholesalers.
  • PPI also shifts emphasis from a commodity index framework to a stage of processing index framework. This minimized the multiple counting that can occur when the price for a specific commodity and the inputs to produce that commodity are included in the same total index. For example, think of gasoline and crude petroleum both included in an all-commodities index.
  • 1985: PPI starts expanding its coverage of the economy to include services and nonresidential construction. As of January 2018, about 71 percent of services and 31 percent of construction are covered.
  • 2014: PPI introduces the Final Demand-Intermediate Demand system.
  • The “headline” number for PPI is called the PPI for Final Demand. It measures price changes for goods, services, and construction sold for personal consumption, capital investment, government purchases, and exports. We also produce a series of PPIs for Intermediate Demand, which measure price change for business purchases, excluding capital investment.
  • Let me give you an example: Within the PPI category for loan services, we have separate indexes for consumer loans and business loans. The commodity index for consumer loans is included in the final demand index and the commodity index for business loans is mostly in an intermediate demand index.
  • The Frequently Asked Question on the PPI for Final Demand provides even more information on this new way of measuring the PPI. The blog, Understanding What the PPI Measures, may also be helpful.
  • We also have an article that explains how the PPI for final demand compares with other government prices indexes, such as the CPI.

Why is the PPI important?

To me?

  • Inflation is the higher costs of goods and services. Low inflation may be good for the economy as it increases consumer spending while boosting corporate profits and stocks.
  • A change in producer prices may be a leading indicator of consumers paying more or less. Higher producer prices may mean consumers will pay more when they buy, whereas lower producer prices may mean consumers will pay less to retailers. For example, if the PPI gasoline index increases, you may see an increase soon at the pump!

To others (which may impact me!)?

  • Policymakers, such as the Federal Reserve, Congress, and federal agencies regularly watch the PPI when making fiscal and monetary policies, such as setting interest rates for consumers and businesses.
  • Business people use the PPI in deciding price strategies, as they measure price changes in inputs for their goods and services. For example, a company considering a price increase can use PPI data to compare the growth rate of their own prices with those in their industry.
  • Business people adjust purchase and sales contracts worth trillions of dollars by using the PPI family of indexes. These contracts typically specify dollar amounts to be paid at some point in the future. For example, a long-term contract for bread may be escalated for changes in wheat prices by applying the percent change in the PPI for wheat to the contracted price for bread.

Video: How the Producer Price Index is Used for Contract Adjustment

PPI is a voluntary survey completed by thousands of businesses nationwide every month. BLS carefully constructs survey samples to keep the number of contacts to a minimum, making every business, large and small, critical to the accuracy of the data. We thank you, our faithful respondents! Without you, BLS could not produce gold-standard PPI data.

Finally, check out the most recent monthly PPI release to get all the latest numbers. Head to the PPI Frequently Asked Questions to learn more. Or contact the PPI information folks at (202) 691-7705 or ppi-info@bls.gov.

Want to learn more about BLS price programs? See these blogs: