The U.S. labor market has been changing, and FRED can help us reveal some patterns. The graph traces four major occupational groups: nonroutine cognitive (green line), nonroutine manual (purple line), routine cognitive (blue line), and routine manual (red line). Managers and computer scientists, for example, fall into the nonroutine cognitive category since their jobs require mental skills and adapting to the project at hand. Manufacturing and transportation-related jobs fall in the routine manual category.
The trend is clear: Middle-skill occupations such as manufacturing and production are declining, and both high-skill and low-skill occupations such as managers and professionals on one end and personal care services on the other are growing. Another way to describe the trend is that routine jobs are decreasing and nonroutine jobs are increasing. Economists refer to this process as “job polarization,” which is driven by both automation and offshoring. Automation reduces routine jobs because repetitive tasks are easily performed by machines or computers. Offshoring reduces low- and mid-skilled labor-intensive jobs because these tasks may be performed more cheaply or efficiently in foreign countries.
How this graph was created: Search in the “Release” view on the FRED home page for the “Employment Situation” report, choose the first link to view the data from the Current Population Survey, and select Table A-13. In the first subsection (Monthly, Employed), select these four series and add them to the graph: Management, professional, and related occupations; Service occupations; Sales and office occupations; and Production, transportation and material moving occupations. For this last series, use the “Add Data Series” feature to add the employment levels for Construction and extraction occupations and Installation, maintenance, and repair occupations. Then edit the group of series with the “Create your own data transformation” option and type a+b+c in the formula box.
Suggested by Maximiliano Dvorkin and Hannah Shell
GeoFRED is a young addition to the FRED family, and this first map uses that newer technology to reveal something about our collective age: specifically, the percentage of the population over 65 years of age in 2014, per the World Bank. The darker regions represent higher percentages of an older population. Western countries and advanced economies in general have significantly higher percentages of those over 65 than do many countries in Africa, Asia, and South America. In Germany and Italy, more than 20% of the population is over 65—a trend typical for countries with long life expectancies, low death rates, high levels of education, and good health care.
This older segment of the population wasn’t as large 10 years ago. The 2004 map below shows that no country had more than 20% of its population over 65. Longer lives, migration, and fewer children per woman have changed both sides of this ratio: many more people over 65 and only a slight increase in population, if not a decrease in some countries.
How these maps were created: On the GeoFRED page, click on “Tools” and expand the “Choose Data” section. Under “Data” search for “Population” and select “Population ages 65 and above.” After the population map is loaded, it will default to the most recent year of data available. Expand the “Edit Legend” section, change the number of classes to 4, and manually set the interval values. To change the sample year for the second graph, expand the “Choose Data” section and adjust the date.
Suggested by Yvetta Fortova.
We’re wrapping up a week-long celebration of FRED’s first 25 years by looking ahead at the next 25 years. FRED does in fact include data about the future, at least in forecast form. The graph here shows potential output and the “non-accelerating inflation rate of unemployment” (NAIRU) for the U.S., as estimated by the Congressional Budget Office. FRED also has various forecasts from the International Monetary Fund for GDP growth and inflation rates in some countries.
So, what’s in FRED’s future? There’s no way we can fathom how FRED will look 25 years from now (interplanetary data mapping, maybe?) just as the original creators of FRED 25 years ago could not have imagined our current FRED apps, which let you use a phone to graph data as you’re walking in the park. However, without committing ourselves to all of this, here’s a sneak peak at what we’re planning for over the next few years:
- More series. We continually add data series, and we won’t stop doing that any time soon.
- Redesign of the FRED series page. We’re revamping the pages that display our famous FRED graphs so novice users can more easily tap into the graphing power of FRED.
- FREDcast. The St. Louis Fed is releasing a forecasting league for major U.S. economic aggregates. Create teams with your students or co-workers and let the games begin!
- More related content. We’re working to add more curated content for many series, pointing users to related resources.
- More help. Improved content (including tutorials) for anyone looking for a little guidance.
- Reimagining FRED user accounts. We’ll take a fresh look at modernizing these accounts and adding functions.
- Better search results. Yes!
- Better mobile apps. We’ll further enhance the iOS apps and gird up the Android apps.
As usual, we’re always open to suggestions about content and function. Use the feedback form on any FRED page (in the right margin) to send us your thoughts.
We hope you’ll still be using FRED in 25 years!
How this graph was created: On the FRED homepage, mouse over the description of FRED in the top center of the page; click on the link to all FRED series. Use the pull-down menu on the top right to sort the results by observation end (Obs End). Select the three series shown here, which appear at or near the top of the search results, and click on “Add to Graph.” Modify the units of potential GDP to “Percent Change from Year Ago.”
Suggested by Christian Zimmermann
View on FRED, series used in this post:
We’ve been celebrating FRED’s first 25 years on earth with some milestones and fun facts. Here’s one: This graph shows brick production in England and Wales, which is FRED’s oldest series, harkening back to 1785.
The time span of this series includes the British industrial revolution, when workers migrated from rural areas to urban centers to work in factories. Obviously, they needed housing. Better transportation infrastructure also allowed brickmakers to send their product over longer distances at lower cost, so bricks became common building material.
But what about all the spikes in production? It’s hard to know the precise causes, but consider this: By the early 19th century, London had become the largest city in the world; by the middle of the century, it had about 3 million residents. Other industrial cities boomed at different times, as well, including Leeds, Liverpool, and Manchester.
Suggested by George Fortier.
View on FRED, series used in this post:
FRED was born of woman. That may sound Shakespearean or even biblical, but it’s metaphorically true. Lora Holman, former St. Louis Fed research coordinator, brought FRED to life. FRED toddled around as a bulletin board service for a few years before Holman made a more ambitious appeal in the summer of 1995 to introduce FRED to the masses on the world wide web. She convinced senior management to take a chance on her baby, armed with an old computer running Linux, a dedicated ISDN line, and an upload process that involved magnetic tape.
FRED memo 1995
Holman described the reception from the public as “fantastic,” including numerous emails expressing gratitude and asking a variety of questions. And what parent isn’t proud to hear good words about their offspring? The good words poured in from many sources, including the New York Times, which called FRED “one of the snappiest of the Fed’s home pages.”
If Holman delivered FRED to the public, then George Essig raised FRED right, with plenty of attention and love and support. Essig, who’s on the St. Louis Fed Research web development team, was the first to work on FRED full time, in the year 2000. One of his many contributions was to store economic data in a database instead of text files, so the data could be queried and transformed. Others, such as Julie Knoll, also contributed a great deal of time, effort, and expertise.
We haven’t even mentioned this FRED graph yet, which adds a little flavor to FRED’s childhood story. It provides, with childlike simplicity, our decreasing birth rate and our increase in resources devoted to data technology.
Suggested by the FRED Team.
View on FRED, series used in this post: