The FRED® Blog

“Log in” to regional data

FRED has compiled regional U.S. data for many economic indicators. The vast amount of regional data can make searching through the categories a bit overwhelming. But there are simpler ways to find what you want: You can search the releases if you have a good idea what you’re looking for. You can also use tags to quickly narrow down your search results—for example, by selecting specific geographies and geography types. Here, we look at per capita income for a sample of metropolitan statistical areas (MSAs) across the U.S.

In the graph above, we took the natural logarithm for each series, for the following reason: If the economic aggregate you’re looking at is growing at a constant rate and you have a sufficiently long sample, the data series will look convex and may give the impression that growth has been explosive. But if you take the natural logarithm, then a constant growth rate will look like a straight line. The graph above uses the natural logarithm: All four metropolitan areas have a kink around 1980 with a subsequent slowdown. The graph below doesn’t use the natural logarithm: That kink is not visible. Also, below it looks like San Francisco is taking off and separating from the others. Above, the distance between the lines can be interpreted as percentage difference, and it is clear that in relative terms San Francisco stays within range.

How this graph was created: Go to the list of MSAs for which FRED has per capita income, select the series you want, and click the “Add to graph” button. That’s the bottom graph. For the top graph, go to the graph tab and, for each series, expand “Create your own transformation” and select “Natural Log.”

Suggested by Christian Zimmermann

View on FRED, series used in this post: BIRM801PCPI, LEBA142PCPI, SANF806PCPI, STLPCPI

Components of M2

What is money? Well, there are many statistical definitions and FRED’s new release tables can help us sort them out. The release table for monetary aggregates shows us the various components of M2, the broadest monetary aggregate currently measured. The major components are represented in the graph above, as shares of total M2. The strictest measure of money is currency, in red at the bottom. Add to that checkable deposit accounts in banks and elsewhere, and you have M1. Add savings accounts, small time-deposit accounts, and money funds to M1, and you get M2.

The graph shows how the composition of M2 has changed over time. Deposit accounts in banks used to be much more important. This has changed as the financial industry and its customers have become more sophisticated. Also, regulatory changes as well as amendments to accounting rules have had a direct impact on measurements or have nudged market participants to hold liquidity or savings differently. But currency has been largely unaffected by such changes.

How this graph was created: Go to the Money Stock Measures release, choose a table from the top, click the series you want graphed, and click on “add to graph.” Then, open the tab for the currency component and move it to the bottom of the pile by clicking on the “down” button. Finally, under graph settings, set graph type to “bar” with stacking set to “percent.” You will notice that the early data series have only currency; thus, start the sample in January 1959.

Suggested by Christian Zimmermann

View on FRED, series used in this post: CURRNS, DEMDEPNS, NOM1M2N, OCDNS

Quits by industry

FRED recently introduced “release views,” which make it much easier to split an economic aggregate into various components or categories. Here, we use the Job Openings and Labor Turnover release to examine quits and hires by industry. In the graph above, it is striking how the ranking of industry quit rates remains the same no matter how well the economy is doing. Also, the quit rates of some sectors respond more strongly as the economy improves. Naturally, one is more likely to quit a job when it’s easier to find another. This is confirmed by looking at the industry hiring rates in the graph below, where the ranking and trend of the lines are the same as above. See the spike for government hiring around 2010? That corresponds to temporary workers hired for the decennial census.

How these graphs were created: For each graph, go to the Job Openings and Labor Turnover release, find the right release table from the top list, check the industry series you want, and click on the “add to graph” button.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: JTS3000HIR, JTS3000QUR, JTS4000HIR, JTS4000QUR, JTS6000HIR, JTS6000QUR, JTS7000HIR, JTS7000QUR, JTS9000HIR, JTS9000QUR


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