Tag Archives: Data visualization

Modernizing BLS News Releases for the Next Generation

At BLS we are always trying to refine our products to serve our customers better. Over the years, we have updated several of our publications to be more web-friendly and include more interactive features. One major exception has been news releases. In the past few years we have conducted a great deal of outreach and investigation with our news release readers to understand what would make our releases easier to digest and provide greater context to the data. The outcome of this research is the two news release prototypes we’re presenting.

On our beta site, you can find prototypes for the Consumer Price Index and The Employment Situation news releases. We incorporated interactive charts, downloadable excel tables, and a redesigned technical note (now called “About this release”).

We’d love to hear what you think! Please either drop a comment here, or on our beta site, so we can better refine these prototypes for future news releases.

Building a Business? Start Here

You have an idea.

It’s time to get serious about it.

Entrepreneurial drive got you to this point, but now it’s time to chart a plan. For that you need a reliable overview of the factors that can lead to a flourishing business — or work against it.

The U.S. Census Bureau’s Business Builder application is designed to provide small business owners with key data to give them a clear-eyed view of their potential market. This data-mapping tool combines data from the Census Bureau’s American Community Survey, Economic Census, and County Business Patterns, and the U.S. Department of Agriculture’s National Agricultural Statistics Service.

For version 2.6 of the tool, released this month, the Bureau of Labor Statistics has collaborated with the Census Bureau to include data from our Quarterly Census of Employment and Wages (QCEW). QCEW is based on quarterly mandatory reports to the Unemployment Insurance systems in each state, covering more than 95 percent of the jobs in the U.S. economy. It is the most complete and current source of data on employment and wages at a detailed geographic and industry level.

To help illustrate why this tool is so useful, and why the data from the QCEW broadens that usefulness, I’ll make up an example.

Ever since you can remember, your grandmother, who was born and raised just outside of Naples, has fed you a type of pizza full of unusual flavors that has never been equaled in all your travels. As you grew and came into your own as a cook, she entrusted you with her secret knowledge, like a magician passing along her repertoire to a favored protégé.

Ever since, you’ve dreamed of sharing the pleasures of that delicacy with the world, and you’re going to start with a pizzeria somewhere near your home in Olympia, Washington. You may ask yourself: What exactly does the restaurant market look like in Olympia? Who are my potential customers? What kind of wages do they earn?

The Census Business Builder is a good place to start.

Census Business Builder home screen

Here, you can enter the type of establishment you’d like to research, as well as the area where you intend to do business. You find that data are not available for Olympia, but knowing that Olympia is the county seat, you are able to search in Thurston County.

The resulting map provides data on income, education, wages, and perhaps most importantly for you, the number of similar establishments in the area – also known as your competition.

Map of Thurston County, Washington, showing Census Business Builder search results

With the new QCEW data, another crucial batch of information is at your fingertips: more up-to-date establishment counts, employment numbers, and wages. It also provides an important metric known as the location quotient. This measure lets you compare an industry’s employment concentration or wages in your search area with the country as a whole. Will you be able to hire enough staff? What might you need to pay them if you want the best in the business?

Map of Thurston County, Washington, showing Census Business Builder search results with QCEW location quotient

The possibilities advance from this example as far as your entrepreneurial mind wants to take them. It is you, after all, who will transform these numbers into the real-world business that fulfills your vision. Our job as public servants is to give you the most relevant tools to realize that transformation. We’re grateful for the opportunity to collaborate with the Census Bureau to bring you this vital information in this user-friendly format.

The Census Business Builder is updated twice per year using feedback that comes from customers and stakeholders, including small business owners, trade associations and other government agencies. The update also adds QCEW data into the Regional Analyst version of the tool, which is designed for chambers of commerce and regional planning staff who need a broad portrait of the people and businesses in their area. The December release, for example, will add more QCEW features to the Regional Analyst version.

BLS publishes data from the QCEW program every quarter in the County Employment and Wages news release. QCEW data are available through our Open Data Access and the QCEW Databases.

Improved Mapping Tool for Local Area Unemployment Statistics

We publish thousands of unemployment rates each month for states, metro areas, and counties. That can make them hard to follow, but we just upgraded our mapping tool to make it easy. Instead of wading through all those numbers, just check out the latest maps for what you need. We have rebuilt the tool using a more modern and versatile mapping technology. That will make it easier to update with future geographic changes. We have improved several features of the tool:

  • We have added tooltips to help you identify each area and its data. Just hover over an area on the map to see its information.
  • In the tab for state data that are not seasonally adjusted, you can choose a state and pull up a map of that state’s county data for the same period.
  • The metro area tab has returned and reflects the areas currently used by the Local Area Unemployment Statistics program.
  • You can choose the dates, states, areas, and measures you want to see.
  • You can select the key data ranges to highlight all areas in the same group. (Click or press the range a second time to deselect.)
  • The map space is larger and framed.
  • Use the arrow in the lower right corner of the map space to print the map image or export it to .PNG, .JPEG, and .SVG formats.

Missouri map showing counties and their unemployment rates

We hope these improved maps make finding data for your state and local area easier. Let us know what you think.

BLS Local Data App Now Available for Android Devices

The wait is over! The BLS Local Data app — a mobile application that connects users with the data they need to know about local labor markets — is now available for Android devices. Search “BLS Local Data” in Google Play.

The BLS Local Data app, first released for iPhones last fall, uses the BLS API to present local data and national comparisons for unemployment rates, employment, and wages. You can search using your current location, a zip code, or a location name to find relevant data quickly without having to navigate through the huge BLS database. With one click, you can find data for states, metro areas, or counties.

BLS continues to partner with the U.S. Department of Labor’s Office of the Chief Information Officer to expand the features and data in the app. A second version is in development and will be available soon for both iPhone and Android devices. Version 2.0 will include employment and wage data for detailed industries and occupations. It also will have new charting functionality that will allow users to plot the historical unemployment rate time series for their local area of interest.

Check out the app and bring the wealth of local labor market data produced by BLS directly to your mobile devices!

The BLS Local Data App showing employment and wage data for Allegheny County, Pennsylvania.

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