The FRED® Blog

Take note: FRED has updated some series names

The FRED Team has just automated the process of how it names many of its data series. Because FRED aggregates data from 89 different sources, choosing the right name for any of the 627,000 data series is no small matter. Yes, the Bard wrote “A rose by any other name would smell as sweet.” But in the world of data, a confounding name can be a thorny problem.

Let’s choose a common example. The data series for the unemployment rate in the U.S. is collected by the Bureau of Labor Statistics (BLS). But the media can choose to report the data with a variety of names: national unemployment rate, civilian unemployment rate, official unemployment rate, harmonized unemployment rate, or U3.

The FRED graph below shows two series: the unemployment rate (from the BLS) and the harmonized unemployment rate (from the OECD). Why do we see only one line? Because the series are one and the same. So, what is the correct name for the unemployment rate data series? The answer depends on the source of the data. So, FRED will now display the series name as reported by the source of the data from the most comprehensive machine-readable location.

In the case of the BLS, that location is series LNS14000000. The series is accessible through the LABSTAT public database, which contains current and historical surveys and press releases. For the BLS series LNS14000000, the name of the data series is “unemployment rate,” so FRED will call it simply that: unemployment rate.

Although the FRED data series identifiers have not changed, there are 2,782 data series names that have changed. For a complete list, see this CSV file. You’ll notice that many data series in FRED related to the consumer price index now have updated names.

Suggested by Diego Mendez-Carbajo and Maria Arias.

View on FRED, series used in this post: LRHUTTTTUSM156S, UNRATE

Where is the U.S. growing?

Population growth in metropolitan statistical areas

If you’ve looked at FRED data, you’ve probably seen the term MSA, which is “metropolitan statistical area,” which the Census defines as “a core area containing a substantial population nucleus, together with adjacent communities having a high degree of economic and social integration with that core.” It’s that high degree of economic integration that can make MSAs more comprehensive and relevant than just the specific governmental boundaries of cities and counties. In fact, MSAs often span several counties and sometimes straddle state borders. Think of it as a commuting basin… Or create your own metaphor!

The GeoFRED map here shows population growth for MSAs: Red is at the strong end of the growth spectrum and dark blue is at the weak end. What’s behind these changes in population? The main drivers are moves between MSAs, moves from rural areas into MSAs, and immigration from abroad. In some years, the boundaries of some MSAs are adjusted and can lead to substantial increases. If you follow the “View on GeoFRED” link below the map, you can select different years and see migration patterns over time, which are affected by local economic conditions. Some MSAs, like New York–Northern New Jersey–Long Island, change pretty drastically from year to year. Other MSAs are steadier: For example, growth in St. Louis is consistently slow and growth in Las Vegas–Paradise is consistently fast.

How this map was created: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Christian Zimmermann.

Living in an uncertain world

More uncertainty data in FRED

We’ve recently looked at different ways to measure uncertainty in the U.S. economy. Today, we look at international data on economic and policy uncertainty. While U.S.-level data were measured by looking at what newspapers report, the international data are based on quarterly reports from the Economist Intelligence Unit in each country. Having a single source for each country means one must be careful in interpreting the data: It contains quite a bit of noise, and there may be some idiosyncrasies for each country that make cross-country comparisons difficult: A report may focus on one particular aspect of a country, or it may be related to uncertainties in other locations that may affect that country.

The GeoFRED map above covers the third quarter of 2019. The countries with the highest uncertainty are Ireland and the United Kingdom, no doubt due to the Brexit situation. But Switzerland also has a very high score, while Iraq and Pakistan enjoy perfect scores. And observations from other quarters change dramatically for some countries. This is where it’s important not to focus on a single data point, but to have a more holistic approach to the data.

The graph below shows a few things: The economic and policy uncertainty in the United Kingdom was not a fluke for that one quarter. The situation in Iraq is clearly not always that rosy, but it still regularly scores low, maybe because no change is expected. In Switzerland, where certainty is the norm, uncertainties are worth playing up.

As we implied earlier, there are some lessons to draw from the data taken as a whole. The authors of the data highlight in their report that this uncertainty index does usually foreshadow growth troubles. Democracies, likely due to their political process, have more uncertainties than authoritarian regimes. (Again: See Switzerland versus Iraq.) More developed economies also have fewer uncertainties to worry about.

How the map and the graph were created: The graph: From the World Uncertainty Index release table, click on the link to the individual country indices, select the relevant country, and click “Add to Graph.” The map: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: WUICHE, WUIGBR, WUIIRQ


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