Federal Reserve Economic Data

Next Monday is a holiday for the St. Louis Fed: since 1937, Columbus Day, and since last year’s presidential proclamation, Indigenous Peoples’ Day. This post, like so many others, offers timely examples of the data you can find in FRED—today, it’s specific to places in the U.S. bearing the name Columbus.

For these 3 metropolitan statistical areas and 1 county, we focus on the unemployment rate because it’s a good gauge of the health of a region and has units that don’t depend on the region’s size. And, as it turns out, these four regions are quite different from each other:

• Columbus, Ohio, is a major city with substantial public employment, led by Ohio’s state government and The Ohio State University.
• Columbus, Indiana, concentrates more on manufacturing.
• Columbus, Georgia (plus a county in Alabama), is remarkable for its military focus.
• Columbus County, North Carolina, is rural with a declining population.

The FRED graph above shows that the unemployment rate in these four regions varies quite a bit over time but, remarkably, consistently maintains the ranking of these four regions. (The brief exception is when the rate in Columbus, Indiana, shot up at the height of the pandemic: The many factories there didn’t have a work-from-home option and closed temporarily.)

How this graph was created: Search FRED for “Columbus unemployment” and select one of the four, making sure not to take the smoothed series. From the “Edit Graph” panel, open the “Add Line” tab and repeat the search until the graph is complete.

Suggested by Christian Zimmermann.

Since 2019, the Board of Governors of the Federal Reserve System has combined data from two different surveys to provide quarterly estimates of how wealth is distributed among U.S. households. The Distributional Financial Accounts (DFA) provide these data as far back as 1989 and help describe patterns in wealth concentration in the United States.

FRED recently added several series from this dataset, which allows us to identify wealth holdings of segments of the population, from the top 0.1% through the bottom 50%.

The areas in the FRED graph above show the total wealth held by five different groups of households:

• the wealthiest 0.1% (in blue)
• the next 0.9% (in red)
• the next 9% (in purple)
• the next 40% (in cyan)
• the bottom 50% (in orange)

Keep in mind there are large differences in the number of households in each of these five groups.

What does it take to be counted among the wealthiest households? Well, FRED also has data on the minimum thresholds for each segment. At the time of this writing, each of the wealthiest 0.1% of households had at least $38 million worth of assets. In total, those 130,757 households in the top segment held almost twice as much wealth as the 65 million households in the bottom 50%.

Check back soon. The FRED Blog will continue to use DFA data to describe the current distribution of wealth in the U.S. and its changes over time.

How this graph was created: In FRED, navigate the list of releases to “Distributional Financial Accounts.” Click the boxes next to the five categories of total assets held by wealth percentile groups and click “Add to Graph.” Use the “Format” tab in the “Edit Graph” panel to change the graph type to “Pie chart.”

Suggested by Diego Mendez-Carbajo.

How and why do financial markets react to war? One aspect of war is to endure losses, and financial markets typically don’t respond enthusiastically to even the risk of loss, let alone widespread destruction on their own soil. Markets may also rise and fall over the course of the war as the fortunes of the warring parties change.

FRED has a peculiarly helpful dataset that provides examples of this dynamic: Weekly U.S. and State Bond Prices, 1855-1865. The authors, Gerald P. Dwyer Jr., R. W. Hafer, and Warren E. Weber, compiled a time series of bond prices for some U.S. states leading up to and through the U.S. Civil War.

The FRED graph above shows bond price data for two states in the South (Virginia and Louisiana) and two states in the North (Pennsylvania and Ohio).

The bonds in question were used for infrastructure, such as roads, canals, and railroads. The war’s potential to destroy that infrastructure could affect the ability of states to pay back the bonds. More generally, war disrupts productive capacity, impedes the raising of tax revenue, and ramps up state expenses—all of which increases the likelihood of state default.

Not surprisingly, the graph shows increasing risk, with prices dropping in late 1860 and then plunging as hostilities began in 1861. These effects were more pronounced in the South than in the North. And the graph also shows that Southern bonds stayed low as the war unraveled, while Northern bonds roughly returned to parity.

How this graph was created: Search FRED for “disunion bonds” and click on, say, Virginia. From the “Edit Graph” panel, use the “Add Line” tab to search for and select the other states.

Suggested by Christian Zimmermann.