Federal Reserve Economic Data

The FRED® Blog

Net worth losses in early 2020 were larger at the top

Your net worth is the difference between the value of your assets and the value of your liabilities.

On average, changes in household net worth are driven by changes in the value of financial assets. And these types of assets differ across classes of household wealth: The least wealthy hold assets mostly in the form of housing and consumer durables, while the wealthiest hold assets through financial vehicles or stakes in businesses.

The FRED graph above shows how the onset of the current economic recession has affected each group differently. Each bar represents the quarter-to-quarter percent change in net worth by wealth quantile. Throughout 2019, net worth increased for all four wealth classes of households. During the first quarter of 2020, net worth decreased for all classes of households but was most marked for the wealthiest 1%. The high volatility of financial markets, which peaked in late March, likely explains this phenomenon.

How this graph was created: From FRED’s main page, browse data by “Release.” Search for “Distributional Financial Accounts” and click on “Levels of Wealth by Wealth Percentile Groups.” From the table, select the “Total Net Worth” series held by each of the four wealth quantiles and click “Add to Graph.” Change the graph units by editing line 1, selecting “Units: Percent change” and clicking “Copy to All.” Last, edit the graph’s format by selecting “Graph type: Bars” and choosing colors to taste.

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: WFRBLB50107, WFRBLN09053, WFRBLN40080, WFRBLT01026

New to FRED: Manufactured home prices

Single and double wide data!

FRED has just added data from the U.S. Census Bureau for an additional type of real estate: manufactured homes. This market is separate from and smaller than the more popular and widely watched single-family homes market, but the price data for manufactured homes have several interesting characteristics.

First, manufactured homes are more uniform than other homes. For example, single-family homes come in a variety of sizes, they have tended to become larger over time, and the size composition of single-family home sales may vary from one period to another. Manufactured homes come in two standard sizes, single and double, and separate statistics are collected for each.

Second, the price of manufactured homes includes only the house—that is, the land is not part of it. This should make the price more informative. However, the market for manufactured homes is thinner, which makes measurements less precise and thus more volatile.

The graph above compares the prices of manufactured homes (single and double) with two popular single-family home price indexes. It’s striking that their trends are quite similar, despite the differences noted above. It’s a coincidence, though, that the levels of the single-family home price indexes line up with the manufactured home series. (In the graph, the value 100 could be any year.) It’s also clear, as noted above, that the price of manufactured homes is more volatile, as the market is likely too thin.

How this graph was created: Start from the release page for manufactured homes, click on the link to the release table with prices, check the two national series, and click “Add to Graph.” From the “Edit Graph” panel, use the “Add Line” tab to search for “house price” and select the S&P/Case-Shiller National series and then the All-Transaction House Price Index. From the “Format” tab, make sure the scale for these series is on the right. Finally, restrict the sample to start when all data are available.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CSUSHPINSA, SPDNSAUS, SPSNSAUS, USSTHPI

The impact of social distancing on leisure and hospitality

State-level data from the BLS

The FRED Blog has discussed the impact of the COVID-19 pandemic on national retail sales and employment. And Leibovici, Santacreu, and Famiglietti index the contact-intensity of a range of occupations and estimate the economic impact of their reduced activity. Their work ranks several leisure and hospitality occupations in the high-contact category.

Today, we look at the impact that social distancing has had on employment specifically in the leisure and hospitality industry.

The GeoFRED map above shows the percent change in employment levels in the leisure and hospitality industry by U.S. state between May 2019 and May 2020. Note that the data are seasonally adjusted. That means they discount regularly occurring increases and decreases in activity due to seasonal demand, such as winter skiing in Colorado or summer vacationing in Florida.

The number of employees in the leisure and hospitality industry decreased in all 50 states during May compared with a year ago. That decrease ranged from 18% in Oklahoma to 62% in New York. The median value was 38%.

And to learn about how closing restaurants and hotels spills over to total employment, read the work of Garriga and Sanchez.

How these maps were 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 Diego Mendez-Carbajo.



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