Federal Reserve Economic Data

The FRED® Blog

What’s common among cryptocurrencies?

Comparing crypto prices with data from Coinbase

FRED has listed the prices of certain cryptocurrencies for some time now. The FRED graph above shows four of them. Note that their prices are measured through an index number, normalized to 100 on 01-01-2018, so we can compare their growth, not their levels in actual dollars and cents.

Just eyeballing the graph reveals that they seem to largely move in unison, which is remarkable given that these prices are highly volatile. So, a significant component of their price variations must be common across all these cryptocurrencies. This commonality may come from news that pertains to all of them, such as regulation, adoption by some large player, or fiscal rulings, for example. Changes to the relative value of their counterpart, the U.S. dollar, can also play a role.

Obviously, there’s also a significant part of these price changes that is idiosyncratic to each cryptocurrency. After all, FRED’s source for these data, Coinbase, lists 5,329 different cryptocurrencies at the time of this writing; something must be differentiating them. They may have different protocols, different underlying assets (if any), different constraints on supply, and different purposes.

How this graph was created: Search for the Coinbase source in FRED, select all series, and click “Add to graph.” From the “Edit Graph” panel, change units to 100 for 2018-01-01.

Suggested by Christian Zimmermann.

Jolts in the labor market: It’s harder to hire

Average time to fill an open job rose from 20 to 50 days

It should be no surprise that the job market has had some ups and downs during this pandemic, and one related measure is how long it has taken to fill an open position. FRED, with the help of the Job Openings and Labor Turnover Survey (JOLTS), gives us the tools to look into this.

JOLTS, among other things, provides monthly data on the number of job openings and how many openings have been filled during that month. A simple ratio of these two numbers tells us how many months it takes to fill an open position, on average.* And that’s exactly what we show in the FRED graph above. For example, in early 2011 (the start of this data series), it was taking less than a month to fill an open position.

The pandemic created special circumstances: First, job openings dropped like a stone, so these few remaining open positions could be filled quickly. Soon, conditions reverted. And now we’re in a situation where there are many openings and relatively few of them are being filled. In a matter of months, the time to fill an open position went from 20 days to 50 days, which may go higher still.

*A ratio of 1 means open jobs are filled within a month, on average. A higher ratio means it takes longer.

How this graph was created: Search FRED for “job openings” and use the non-farm series. From the “Edit Graph” panel, add a series by searching for “hires.” Finally, apply formula a/b.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: JTSHIL, JTSJOL

Jumps in county population

Fresh data from the Census Bureau

The first results of the 2020 population census are trickling in, and FRED is adding them to the database as the Census Bureau makes them available.

The FRED graph above shows the resident population for Jefferson County, Wisconsin; Prince George’s County, Maryland; and St. Louis City, Missouri (which is its own county).

The Census Bureau measures and adjusts the population data yearly from estimates about births, deaths, and migration. Again, these are just estimates. While births and deaths are well measured, migration is more difficult because there’s no U.S. requirement to register when you move, as there is for some countries.

The more precise population measurements come in the form of the decadal census, and this is the type of data FRED is receiving now. In the graph, do you see how population sometimes jumps up or down somewhat sharply? These are points in time when the new census data are added and the estimates for the previous years were a bit off. This doesn’t happen frequently, though. If you look at the full dataset, it’ll take some patience to find a handful of similar cases.

How this graph was created: Search for “resident population county” for your county of choice. From the “Edit Graph” panel, use the “Add Line” tab to search for other counties. Change units to 100 for 1970 and click on “Apply to all.”

Suggested by Christian Zimmermann.



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