Federal Reserve Economic Data

The FRED Blog has previously looked at the negative impact of social distancing on employment levels in the leisure and hospitality industry. Today, one year later, we take a look at how the overall economic recovery is reflected in this industry.

The GeoFRED map above shows the percent change between May 2020 and May 2021 of employment levels in the leisure and hospitality industry for each state. The data are seasonally adjusted, meaning they correct for the recurring ups and downs in activity during any given year. For example, winter ice fishing in North Dakota or summer vacationing in Florida.

Overall, the number of employees in the leisure and hospitality industry increased from May 2020 to May 2021 by a stunning average of 42%. The smallest increase was 20% in Oklahoma, and the largest increase was 73% in Delaware.

The high-growth states, with increases in employment of over 60%, are in dark green. Eight of these ten states are concentrated in the Northeast, including, in ascending order, Massachusetts, New York, Connecticut, New Hampshire, Pennsylvania, Rhode Island, New Jersey, and Delaware.

Low-growth states (in purple) were mainly concentrated in the southern region of the U.S.

Ok. So employment has rebounded. But has it returned to pre-pandemic levels?

The bar graph above shows the level of employment in leisure and hospitality in May 2021 as a fraction of May 2019 employment. From this graph, we see that only one state has reached (and even slightly exceeded) its pre-pandemic level of employment: Idaho.

The rest of the states still lag behind in their recovery, and this graph suggests there may be opportunities for employment growth in this sector. Where are these opportunities more abundant? Relative to 2019, the Northeast states, where employment contracted the most last year, still have plenty of jobs to fill. Overall, the pandemic and ensuing recession had a large impact in the leisure and hospitality industry but employment opportunities in the sector are recovering rapidly.

How this map was 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 and Victoria Yin.

Residential property can reveal insights about the financial stability of a country’s economy. The FRED graph above shows the annual changes in the residential property prices for both the United States and Australia for the past 20 years. While the size and location of properties obviously affect residential property tax values, so do the financing of these properties and financial market conditions.

For example, the Financial Crisis of 2008 dramatically dampened U.S. property prices. The U.S. house price index reflects the economic turmoil during that time, when annual house prices declined as much as 19.6% in the third quarter of 2008 from their levels during the same quarter of the previous year. The crisis also trickled down to Australia, causing local property prices to decline, although not as deeply as in the U.S.

In 2019, price declines in Australia’s housing market repeated those from 2008. While Australia’s economy was doing relatively well before this occurred (interest rates and unemployment were relatively low), policies were put in place to enforce tighter lending standards for housing. This caused property prices to decrease, which led to fewer jobs in careers such as construction, insurance, contracting, and so on. This, in return, caused a decrease in spending, which hurt Australia’s economy.

How this graph was created: Search FRED for “real residential property prices” and click on the U.S. series. From the “Edit Graph” panel, use the “Add Line” tab to search for and select the Australian series. Change the units to “Percent Change from Year Ago” then click “Copy to all.” Finally, start the graph on 2000-01-22.

Suggested by Natalie Robinson and Maria A. Arias.

Many households have been financially distressed during the COVID-19 pandemic, struggling to pay for necessities such as rent and groceries. It may seem surprising, then, that the aggregate personal saving rate has actually increased since the start of the pandemic.

The FRED graph above displays the U.S. personal saving rate from June 2009 to the present. As defined by the Bureau of Economic Analysis, personal savings are income left over after people spend money and pay taxes. The personal saving rate is personal savings expressed as a percentage of disposable personal income. From the end of the Great Recession to February 2020, the personal saving rate has averaged 7.25%; since the start of the pandemic, however, it has averaged 17.9%.

There are several reasons for this increased average saving rate:

• Households practicing precautionary saving during an economic downturn
• Inability to spend money due to business closures and social distancing guidelines
• Stimulus checks (or relief payments) distributed to a large majority of U.S. households

The FRED graph shows the spikes in the personal saving rate (dotted vertical lines) that correspond to the timing of the stimulus checks distributed in April 2020, January 2021, and March 2021. (Note that the months of distribution aren’t necessarily the same months in which the stimulus/relief bills were passed.) Many households spent their stimulus checks on necessities or other goods and services. But due to the broad nature of relief check/stimulus payment eligibility, some households that received payments didn’t need or want to spend the extra disposable income immediately; rather, they saved it. According to the Household Pulse Survey conducted by the U.S. Census Bureau, 14% of households mostly saved their stimulus check in the first round of payments, 26% did so in the second round, and 32% in the third round.

Though the overall saving rate spiked following these payments and has remained higher than usual throughout the pandemic, this aggregate measure of the personal saving rate does not reflect the variability of household financial stability within the income distribution. Low-income households have been disproportionately affected by financial hardship during the pandemic, and many of those households have had to either draw on savings or go into debt, which is not reflected in the aggregate personal saving rate. Moreover, these households were already less likely to be able to save. According to Survey of Consumer Finances data from 2019, about 37% of families in the lowest quintile of the income distribution reported saving some portion of their income over the previous 12 months. About 86% of families in the highest decile of the income distribution reported doing so.

How this graph was created: Search FRED for “personal saving rate” and select the series “PSAVERT.” The default graph will be the monthly personal saving rate as a percent. Use the date range boxes to set the beginning date to “2009-06-01.” From the “Edit Graph” panel, use the “Add Line”/“Create user-defined line” tool to add the lines indicating the passage of each stimulus check, with the following dates: 2020-04-01, 2021-01-01, and 2021-03-01. Set the lines’ starting and ending values to 0 and 35 to produce vertical lines at each of the dates. To change the colors and line style, use the “Format” tab.

Suggested by YiLi Chien, Cassandra Marks, and Julie Bennett.