Tag Archives: BLS products and services

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!

Local Unemployment: How’s My State Doing?

The Local Area Unemployment Statistics program publishes monthly and yearly estimates of unemployment and the labor force for about 7,000 areas:

  • States
  • Counties and county equivalents
  • Metropolitan areas
  • Cities with 25,000+ population

If you’re looking for local unemployment data, we’ve got you covered!

State Unemployment Rates

This map shows the 2017 unemployment rates for all states (The lighter the color, the better!)

State unemployment rates in 2017

How do states compare with the 2017 national unemployment rate of 4.4 percent?

  • Hawaii and North Dakota had the lowest unemployment rates, 2.4 percent and 2.6 percent, respectively.
  • Alaska had the highest unemployment rate, 7.2 percent.
  • Seven states recorded the lowest annual unemployment rates since the series began in 1976: Arkansas (3.7 percent), California (4.8 percent), Hawaii (2.4 percent), Maine (3.3 percent), North Dakota (2.6 percent), Oregon (4.1 percent), and Tennessee (3.7 percent).

To learn more, table 1 in the Regional and State Unemployment — 2017 Annual Averages news release provides the unemployment rate for each state.

State Employment–Population Ratios

Another interesting piece of information is the employment–population ratio, which answers the question: “What percent of the population age 16 and older is employed?”

State employment–population ratios in 2017

The national employment–population ratio in 2017 was 60.1 percent. The employment–population ratio continues to climb from its recessionary low of 58.4 percent in 2011. Here are some 2017 state highlights:

  • North Dakota had the highest proportion of employed people, 69.6 percent. The next highest ratios were in Minnesota, 67.8 percent, and Utah, 67.2 percent.
  • West Virginia had the lowest employment–population ratio among the states, 50.5 percent.

To learn more, table 2 in the Regional and State Unemployment — 2017 Annual Averages news release provides the employment–population ratios by state.

County Unemployment Rates

What if you want to do a deep dive to find out about unemployment in the counties in your state? That’s easy to do, too. You can create your state map showing the current unemployment rates for all your counties in less than a minute by following these instructions:

Mapping Unemployment Rates (States and Counties) -> Counties tab -> Select a state from the dropdown -> Select unemployment data and time period -> Hit draw map.

That’s it! Below the map is a chart with the county data listed in alphabetical order. For comparison purposes, you may want to pick up the state unemployment rate from the state tab. Be sure to choose the not seasonally adjusted data, since the county data are not seasonally adjusted.

We have a webpage where you can get annual data for all counties for 2017 and earlier years.

How does BLS get all of this great data?

Unlike many of our other statistical programs, the Local Area Unemployment Statistics program is not a survey. Instead, the program uses survey and administrative data from multiple sources to produce its estimates, including:

We have a short summary of the estimation methods. We also have a longer description (including formulas!) in our Handbook of Methods.

What is the relationship between local information and the national unemployment rate?

We use the same definitions for our local estimates as we do for the national unemployment rate, which we get from the Current Population Survey. Through a feature known as real-time benchmarking, the local data are controlled to the national totals each month to make the data comparable.

Video: Understanding BLS Unemployment Statistics

Why should I care about local data anyway?

We’re glad you asked! As you can see, individual states and areas can have very different economic conditions than the country as a whole. Local labor force measures provide critical information for states and areas that can help local leaders, communities, and businesses make better economic decisions. The local unemployment estimates also are used by 25 federal programs across 9 departments and independent agencies.

  • Most programs use the data to help determine how to spread funds to communities across the country.
  • Some programs use the data to determine funding eligibility.
  • See the Administrative Uses of Local Area Unemployment Statistics for the full list of federal uses of local unemployment data.

Finally, check out the most recent monthly state and metropolitan area news releases to get all the latest numbers. Like maps and graphics? See our series of graphics for the most recent unemployment data for states and metropolitan areas. Head to our Frequently Asked Questions to learn more.

Have more questions? Contact the information folks at (202) 691-6392 or by email. You also can contact the offices on our State Labor Market Information Contact List.

Reaching out to Stakeholders—and Steakholders—in Philadelphia

The U.S. Bureau of Labor Statistics has staff around the country who serve several critical roles:

  • Contacting employers and households to collect the vital economic information published by BLS
  • Working with partners in the states who also collect and review economic data
  • Analyzing and publishing regional, state, and local data and providing information to a wide variety of stakeholders

To expand the network of local stakeholders who are familiar with and use BLS data to help make good decisions, the BLS regional offices sponsor periodic Data User Conferences. The BLS office in Philadelphia recently held such an event, hosted by the Federal Reserve Bank of Philadelphia.

These Data User Conferences typically bring together experts from several broad topic areas. In Philadelphia, participants heard about trends in productivity measures; a mash-up of information on a single occupation—truck drivers—that shows the range of data available (pay and benefits, occupational requirements, and workplace safety); and an analysis of declines in labor force participation.

Typically, these events provide a mix of national and local data and try to include some timely local information. The Philadelphia conference included references to the recent Super Bowl victory by the Philadelphia Eagles and showed how to use the Consumer Price Index inflation calculator to compare buying power between 1960 (the last time the Eagles won the NFL Championship) and today.

We also tried to develop a cheesesteak index, a Philadelphia staple. Using data from the February 2018 Consumer Price Index, we can find the change in the price of cheesesteak ingredients over the past year.

Ingredient Change in Consumer Price Index, February 2017 to February 2018
White bread 2.5 percent decrease
Beef and veal 2.1 percent increase
Fresh vegetables 2.1 percent increase
Cheese and related products 0.8 percent decrease

Image of a Philadelphia cheesesteak

These data are for the nation as a whole and are available monthly. Consumer price data are also available for many metropolitan areas, including Philadelphia. These local data are typically available every other month and do not provide as much detail as the national data.

While the Data User Conferences focus on providing information, we also remind attendees the information is only available thanks to the voluntary cooperation of employers and households. The people who attend the conferences can help us produce gold standard data by cooperating with our data-collection efforts. In return we remind them we always have “live” economists available in their local BLS information office to answer questions by phone or email or help them find data quickly.

Although yet another Nor’easter storm was approaching, the recent Philadelphia Data User Conference included an enthusiastic audience who asked good questions and left with a greater understanding of BLS statistics. The next stop on the Data User Conference tour is Atlanta, later this year. Keep an eye on the BLS Southeast Regional Office webpage for more information.

Up and Down the Turnpike: The Power of State Estimates of Consumer Spending

You may know New Jersey for its Turnpike, its Parkway, and ribbons of highways crisscrossing the state, but new information shows that New Jersey households have fewer vehicles than the U.S. average. New Jersey households have an average of 1.4 vehicles, compared with an average of 1.8 vehicles nationwide.

This is just one of the tidbits we can glean from experimental state weights in the Consumer Expenditure Survey just released for New Jersey. Producing state estimates is part of our continuing plan to expand the use of data on consumer spending. The first available state weights are for New Jersey. We hope to release weights for more states in the coming months.

The survey is a nationwide household survey designed to find out how U.S. consumers spend their money. It is the only federal government survey that provides information on the full range of consumer spending, incomes, and demographic characteristics. One way BLS uses the consumer spending data is to create the market basket of goods and services tracked in the Consumer Price Index. Besides the spending information, the survey also collects the demographic characteristics of survey respondents. The new state weights allow us to examine what the typical New Jersey household looks like.

New Jersey looks similar to the United States as a whole, and even more similar to the New York metro area, which encompasses much of the northern part of New Jersey. One notable difference between New Jersey and other areas is the number of vehicles. Transportation in the Consumer Expenditure Survey includes vehicle purchases and gasoline and other car-related expenses. We would expect to see lower transportation spending in New Jersey compared with the nation because of fewer vehicles present in the state and other reasons.

A chart showing income and consumer spending levels in 2016 in New Jersey, the New York metro area, and the United States.

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

Now that we can produce statistically valid state estimates from the survey, we can answer all kinds of interesting questions. Many researchers look at different spending categories to examine public policies and to evaluate how certain decisions affect consumer behavior. Because we can now use the survey data to make estimates for certain states, researchers can explore these kinds of questions with more geographic detail. The chart below shows how New Jersey compares with the New York metro area and the nation in five of the broadest spending categories.

Average annual consumer spending in 2016 for selected categories in New Jersey, the New York metro area, and the United States.

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

Policymakers, researchers, and other data users have often asked for data about spending habits and income for states. Many times, household surveys just do not have enough sample to provide reliable estimates for all possible user needs. With our continuing improvements to the Consumer Expenditure Survey, we are learning which states provide enough responses for us to produce statistically valid state estimates. Once we create these weights for the states that can support them, data users will be able to explore a wider range of questions about consumer spending.

You can learn more from BLS economist Taylor Wilson’s article, “Consumer spending by state: BLS puts New Jersey to the test.”

Average annual income and selected expenditures, 2016
Measure New Jersey New York
Metropolitan
Statistical Area
United States
Income $89,927 $87,212 $74,069
Total expenditures 63,100 65,764 54,157
Transportation expenditures 7,295 6,828 8,755
Average consumer spending in selected categories, 2016
Geography Housing Food Transportation Healthcare Entertainment
New Jersey $23,617 $8,641 $7,295 $5,239 $2,097
New York Metropolitan Statistical Area 24,308 9,190 6,828 4,260 2,277
United States 17,774 7,203 8,755 4,373 2,497

Why This Counts: Maximizing Our Data Using the Consumer Expenditure Survey

Almost all BLS statistical programs are based on information respondents voluntarily give us. We want to squeeze as much information as we can out of the data respondents generously provide. Limiting respondent burden while producing gold-standard data is central to our mission.

Let’s take a look at how one program, the Consumer Expenditure (CE) Survey, squeezes every last drop of information from the data to provide you, our customers, with more relevant information.

What is the Consumer Expenditure Survey?

The CE survey is a nationwide household survey that shows how U.S. consumers spend their money. It collects information from America’s families on their buying habits (expenditures), income, and household characteristics (age, sex, race, education, and so forth). For example, we publish what percentage of consumers bought bacon or ice cream and how much they spent on average.

A little back story: The first nationwide expenditure survey began in 1888. BLS was founded in 1884, so the CE Survey is one of our first surveys! It wasn’t until 1980 that we began publishing CE data each year, however. A 2010 article, The Consumer Expenditure Survey—30 Years as a Continuous Survey, provides more historical information.

How is the CE program doing more with what we have?

We’ll briefly look at four different areas, starting with the most recent improvements:

  • Limited state data
  • Higher-income data
  • Generational data
  • Estimating taxes

Limited State Data – Starting with New Jersey

  • Regarding geographical information, the CE survey is designed to produce national statistics. Enough sample data are available to produce estimates for census regions and for a few metropolitan areas.
  • Up to now, however, we did not produce state data. The CE program recently published state weights for New Jersey, which will allow for valid survey estimates at the state level for the first time.
  • State-level weights are available for states with a sample size that is large enough and meet other sampling conditions.
  • Right now, the state-level weighting is experimental. We provide state-level weights to data users to gauge interest and usefulness.

 Higher-Income Table

  • We evaluated the income ranges of the published tables and found that over time more and more households were earning more, and the top income range had not increased to keep pace. To provide greater detail, we divided the existing top income range of “$150,000 and over” into two new ranges: “$150,000 to $199,999” and “$200,000 and over.” We integrated these changes into the 2014 annual “Income before taxes” research table, allowing more robust analysis for our data users.
  • In addition, we added four new experimental cross-tabulated tables on income without the need for additional information from our respondents.

Generational Table

Grouping respondent information by age cohort can be helpful, since a person’s age can help to predict differences in buying attitudes and behaviors. The CE program has collected age data for years, but never grouped the data into generational cohorts before. A Pew Research Center report defines five generations for people born between these dates:

  • Millennial Generation: 1981 or later
  • Generation X: 1965 to 1980
  • Baby Boomers: 1946 to 1964
  • Silent Generation: 1928 to 1945
  • Greatest Generation: 1927 or earlier

The 2016 annual generational table shows our most recent age information for the “reference person” or the person identified as owning or renting the home included in the CE Survey. In 2016 we wrote a short article on Spending Habits by Generation, including a video, which used 2015 data. We’ve updated the chart using 2016 data:

A chart showing consumer spending patterns by generation in 2016.

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

Estimating Taxes

CE respondents used to provide federal and state income tax information as part of the survey. These questions were difficult for respondents to answer.

Starting in 2013, the CE program estimated federal and state tax information using the TaxSim model from the National Bureau of Economic Research and removed the tax questions from the survey. As a result, the quality and consistency of the data increased, and we have reduced respondent burden!

If you have any questions or want more information, our staff of experts is always around to help! Please feel free to contact us.

This is just one example of how we at BLS are always looking for ways to maximize our value while being ever mindful of the costs—and one of those important costs is the burden our data collection efforts place on our respondents. Maximizing our data means providing gold-standard data to the public while reducing the burden on our respondents—a true win-win!

Annual consumer spending by generation of reference person, 2016
Item Millennials, 1981 to now Generation X, 1965 to 1980 Baby Boomers, 1946 to 1964 Silent Generation, 1928 to 1945 Greatest Generation, 1927 or earlier
Food at home $3,370 $4,830 $4,224 $3,450 $2,023
Food away from home 2,946 4,040 3,100 2,042 1,095
Housing 16,959 22,669 18,917 14,417 17,858
Apparel and services 1,753 2,577 1,602 920 615
Transportation 8,426 10,545 9,762 5,952 3,142
Healthcare 2,473 4,492 5,492 6,197 5,263
Entertainment 2,311 3,613 3,144 2,114 1,223
All other spending 10,338 15,766 14,963 6,671 4,125