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Add FRED to your blog or web page

FRED now provides a widget for your web page or blog—like the one shown here. You can fully customize it and choose up to 10 series. In this case, we chose some popular series for Ireland. But the entire FRED database is available for this widget.

Note that FRED account holders can also create dashboards with the series they like to follow closely. Dashboards are much more customizable and can be made public; for example, you can share them with your readers, coworkers, or students.

How this widget was created: Go to the Data Tools tab, then to the Embedded FRED Data section. Click on the Configure Your FRED Widget link: This form is preset with popular U.S. series, but you may add or delete series at will. Once done, click on “Get the Code!” and copy and paste the code where you want it.

Suggested by Christian Zimmermann

View on FRED, series used in this post: Settings must be an array

How much do Americans drive?

How many miles do Americans drive each month, each year, over the past 10 years…? FRED has the answers. The red line on the graph is a monthly series of miles driven. As you can see, it varies greatly according to the seasons of the year, which should surprise no one. One can clearly see the upward trend, but all the jaggedness makes it more difficult to see what’s been happening for the past 10 years or so. Has there been a recent decline?

To investigate, we can use a 12-month moving average of sorts that can be created in FRED. (This graph appears below the first one.) While some moving averages include about 6 months before and 6 months after a point in time, this moving average takes the average of the 12 preceding months, which smooths the series to make it more readable. In addition, this average is divided by the civilian noninstitutional population—that is, likely drivers. (The same result would be achieved if those below age 16 were removed from the overall data.) This second depiction makes it much clearer that, per capita, Americans are driving less these days.

How this graph was created: Search for “Vehicle Miles Traveled,” then add the data series “Moving 12-Month Total Vehicle Miles Traveled.” Add yet another series, “Civilian Noninstitutional Population,” but this time select the option to modify existing data series 2. For series 2, select right y-axis position and create the data transformation “a/b.”

Suggested by Christian Zimmermann

View on FRED, series used in this post: CNP16OV, M12MTVUSM227NFWA, TRFVOLUSM227NFWA

10-year inflation expectations

How high is inflation going to be over the next 10 years? It’s difficult to say, but we can measure what the markets expect. FRED has recently added 15 interest rate spreads, and one of them is perfect for measuring inflation expectations. There are 10-Year Treasury Inflation-Indexed Constant Maturity Securities whose price should include these expectations. You can tease them out by comparing the price of these securities with the price of securities that are identical except for the inflation indexing: 10-Year Treasury Constant Maturity Securities. From the look of the graph, it doesn’t appear that markets believe any significant inflation will occur over the next 10 years. In fact, the graph suggests that no significant inflation has been expected since these inflation-indexed securities were introduced.

How this graph was created: Search for “Breakeven inflation” and select the series of your choice. There is also a 5-year series. Both 5- and 10-year series are available in daily or monthly frequencies.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: T10YIEM

The peculiar Swiss unemployment rate

Switzerland is in many ways an atypical European country, and that includes its economy. This graph shows the Swiss unemployment rate. Pay particular attention to the scale. Compared with Europe or even most of the rest of the world, Switzerland has a very low unemployment rate. In fact, it is exceptionally low in the first years—so low, in fact, that in some places the line is scarcely visible. If you hover over the line to see the values, you’ll notice that some are even negative. This is due to the seasonal adjustment. And while this graph counts only the registered unemployed, another series counts all unemployed. Although this other series spans a shorter time period, it is not fundamentally different.

Why is Switzerland’s unemployment rate so low? One argument is that its labor market is very flexible. Another is that temporary immigrant worker permits have helped smooth fluctuations. This smoothing seems to have become less effective, though. At any rate, the Swiss secret hasn’t been conclusively explained and needs further study.

How this graph was created: Search for “Switzerland unemployment” and select the first choice. (A slightly different search will get you the employment rate for Switzerland County, Indiana.)

Suggested by Christian Zimmermann

View on FRED, series used in this post: LMUNRRTTCHQ156S


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