Tag Archives: Regions and states

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

Do You Understand Your Local Economy?

The national unemployment rate may make the headline news every month, but many folks are most interested in understanding their own local economy.

BLS has a stat for that (really MANY statistics for that)! In fact, BLS data were highlighted in a webinar focusing on local data sponsored by the Association for Public Data Users, the American Statistical Association, and the Congressional Management Foundation.

Dr. Martin (Marty) Romitti, a Senior Fellow at the Center for Regional Economic Competitiveness, presented a webinar called “Understanding Your Congressional District’s Economy and Workforce Using Federal Statistical Data.” Though geared to Congressional staff, the information is applicable to anyone interested in knowing more about their local economy.

By using an extended example of the Napa, California, metropolitan area (where we immediately think, “Wine Country!”), Dr. Romitti finds some interesting information that may shatter some of your preconceived notions of that region.

He does this by answering 10 questions — 5 about “our people,” where he uses U.S. Census Bureau data and 5 about “our economy,” where he uses BLS data.

We are going to focus on the BLS portion (run time 31:12)* of the webinar. The five questions Dr. Romitti poses about our economy are:

  1. How healthy is my economy now?
  2. How many unemployed people live in my area?
  3. What are the largest employing industries?
  4. Which industries pay most to workers?
  5. What are our economic strengths?

Below are some steps and tips if you want to access the same information as Dr. Romitti on www.bls.gov. Note that he uses Internet Explorer; use a different browser and your screen will look different.

Dr. Romitti uses two BLS tools; we have included the path and links to pages as appropriate:

  • To answer Questions 1 and 2: Economy at a Glance -> California -> Napa (Dr. Romitti suggests clicking on the maps.)
    • Tips:
    • For context, suggest you compare your area data to your state numbers. Beware: Your state unemployment rate is seasonally adjusted, while your area data are not.
    • Also, for context, you may want to look at the data over time, such as the last 10 years. Just remember the “Great Recession” occurred starting in late 2007.
  • To answer Questions 3, 4, and 5: BLS Data Tools -> Employment -> Quarterly -> State and County Employment and Wages -> Tables

By following these instructions, you can uncover the same information as Dr. Romitti. We believe Dr. Romitti does a good job of explaining how to answer questions related to local economic data in under an hour!

But wait, there’s more! Let me offer two more resources in your quest for local data:

  1. Are you familiar with our Economic Summaries? These summaries present a sampling of economic information for the area covered, such as unemployment, employment, wages, prices, spending, and benefits. For example, take a look at San Francisco. If you are looking for something quick and easy, you might find what you need in one of these summaries.
  2. The Economic Summaries are produced by the BLS regional information offices. The BLS regional office staff stand ready to assist you with questions about your local economy.

*The taped webinar starts with a musical interlude and some brief introductions. The real action starts at the following run-time intervals:

Run Time                    Presentation Topic   

6:46                             Introduction by Dr. Romitti

11:30                           About our people (Census Bureau data)

31:12                           About our economy (BLS data) begins

52:36                           Regional Economic Accounts (Bureau of Economic Analysis data)

58:53                           Conclusion

60:00                           End

Recalibrating the Jobs Thermometer

The U.S. Bureau of Labor Statistics is responsible for measuring labor market activity. Each month BLS releases some of the most up-to-date measures of economic health in The Employment Situation, often called “the jobs report.” We also release the Commissioner’s statement each month at the same time as the jobs report.

Most of the attention focuses on the headline numbers—how many jobs were added (or lost) that month and did the unemployment rate change? However, with the release of January data each February, we make some yearly updates to improve the accuracy of the numbers. In our survey of households, which is the source for the unemployment rate and other measures, we update the U.S. population totals to reflect the latest information about births, deaths, and international migration. In our survey of nonfarm establishments, which is the source of the jobs count, we make our annual benchmark revisions. Today I’m going to focus on the establishment data.

Each month, the establishment program surveys a sample of businesses and governments around the country. The survey asks how many people worked or received pay for the pay period that included the 12th of the month. While the establishment sample is large, covering about one-third of all nonfarm jobs, the employment changes reported each month are still subject to revisions. Monthly revisions result from more establishments reporting their numbers or correcting previous reports, and from updated information about seasonal employment patterns.

The establishment survey also benefits from another source of data, the Quarterly Census of Employment and Wages. That is a nearly complete count of all establishments, although it is available with a delay of about 6 months. A full count of employment helps us in several ways. We use the data to measure the error associated with the establishment survey. This way data users don’t have to guess how accurate the monthly employment data are. We have a stat for that! In case you are wondering, the data are very accurate. Annual benchmark revisions (which I will explain in a moment) have averaged only 0.3 percent in absolute terms over the past 10 years.

Besides measuring error, once a year we realign the sample-based estimates with the full count of employment. We call this “benchmarking.” This realignment makes sure the employment levels do not stray too far from the “truth” over time. (For several reasons that I won’t go into right now, the establishment survey employment totals will not exactly equal employment totals from the full counts. If you really want to know the details, you can read more about benchmarking, but remember I tried to spare you.)

During this annual benchmarking, we also introduce other changes to the survey. Sometimes we update the industry classification, like we will this year. We also use new information to update the statistical model that accounts for business births and deaths. We review the establishment sample for size, coverage, and response rates, and we may drop some series if the data quality doesn’t meet our standards. We also update the models and information used in seasonal adjustment.

As you can see, there’s a lot going on during this annual updating. All establishment data, including employment, hours, and earnings, are subject to adjustment. I hope this brief explanation and the material we have on our website help to make everything more transparent and easier to understand.

The same basic benchmarking that occurs nationally also happens for the state and local employment estimates. Want to know more? Visit their homepage. If you still have questions, call or email us. We are here to help.