Federal Reserve Economic Data

Some commodities have seen some wild price fluctuations during the COVID-19 pandemic. One that was much discussed in the news is softwood lumber. While FRED does not have data on its retail price, it does have the price that the producer gets: the Producer Price Index, formerly called the Wholesale Price Index.

Our first FRED graph shows how unusual these price fluctuations have been. While the price stayed within a narrow band for years, it has suddenly spiked and plummeted in unprecedented ways since the middle of 2020. When data points rise or fall by multiples of their preceding values, it’s useful to transform the data to ensure an accurate understanding. In this case, taking logs of lumber prices provides us with that clarity—and a nice pun!

Our second FRED graphs shows exactly the same data, except that we took logs (i.e., the natural logarithm). The advantage of such a graph is that a 10% price increase looks the same whether the price is high or low. And the graph confirms that even when the price was high, the fluctuations were proportionally (or in percentages) very large.

How these graphs were created: Search for “PPI softwood lumber,” open the graph, and restrict the sample period to start in 2014 (due to preceding data interruptions). For the second graph, click on “Edit Graph” and set units to “Natural log” (last field).

Suggested by Christian Zimmermann.

After COVID-19 induced a recession, the FRED Blog discussed the consequent drop in spending on services caused by mandated social distancing. This decreased demand for services (i.e., work done on one’s behalf) was partially offset by an increased demand for goods. Today, we revisit the topic to gauge the recovery in consumption spending on services.

The FRED graph above shows data from the Personal Income and Outlay Survey from the U.S. Bureau of Economic Analysis in inflation-adjusted U.S. dollars. The values are presented as a custom index equal to 100 in February 2020, the start of the COVID-19-induced recession. This data transformation allows us to easily observe the evolution of the three main components of personal consumption: services (in red), durable goods (in purple), and nondurable goods (in green).

The initial value of all three categories of consumption spending is noted by the dashed black line, and they all decreased between February and April 2020. Remarkably, spending on both durable and nondurable goods grew past their pre-recession levels soon afterward. However, the recovery in services spending has been much slower. At the time of this writing, spending on services stands at 99.3% of pre-recession levels. Because household purchases of services represent the majority of personal consumption expenditures, that is good news for overall economic activity.

Nevertheless, the combination of sustained high spending on durable goods and the type of supply chain bottlenecks documented by Fernando Leibovici and Jason Dunn might be helping to fuel the ongoing surge in consumer price inflation.

How this graph was created: From FRED’s main page, browse data by “Release.” Search for “Personal Income and Outlays” and click on “Table 2.8.6. Real Personal Consumption Expenditures by Major Type of Product, Chained Dollars.” From the table, select the “Durable goods,” “Nondurable goods”, and “Services” series and click on “Add to Graph.” To change the units of the series, select “Units: Index (Scale value to 100 for chosen date)” and click on “Copy to all.” To add the custom horizontal line, use the “Add Line” tab and click on “Create user-defined line.” Enter “100” as both the start and end value. Use the “Format” tab to change the line colors, styles, and marks.

Suggested by Diego Mendez-Carbajo.

The pandemic brought about serious upheaval in the health care sector. Services directly connected to the COVID-19 virus were overwhelmed at times, while non-essential services came close to a standstill. Our question for today is, in sum, how has the health care sector fared?

The FRED graph above shows personal consumption expenditures on health care. This measure probably isn’t a good indicator to answer our question, as it doesn’t include any of the expenses paid by other entities, such as businesses and various levels of government. So we need a measure that encompasses all of the health care sector.

The second FRED graph gets closer to what we want, although with data that are not as current as the data in the first graph.

We see that total revenue of health care establishments (in blue) dipped severely at the start of the pandemic, but then got back on track with its previous trend. This pattern is actually not that much different from the rest of the economy. Health care employment (in red) shows a different picture: Employment is still far below the peak before the pandemic and, hence, even further below the long-term trend.

But one has to be careful here: The revenue numbers aren’t adjusted for inflation. So, one more graph…

Our last FRED graph (below) shows that this storyline still holds: The health care sector has had to deliver more than what had been expected before, but with far fewer employees.

How these graphs were created: First graph: Search for and select “health care expenditures.” Second graph: Search for and select “health care revenue.” From the “Edit Graph” panel, use the “Add Line” tab to search for and select “health care employment.” Use the “Format” tab to put the y-axis on right for the second series. Reduce the sample period to focus on the last years. Third graph: Starting with the second graph, use the “Edit Graph” panel to add a series to the first line by searching for “GDP deflator” and applying formula a/b*100.

Suggested by Christian Zimmermann.