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The decline of U.S. pharmaceutical production

Likely sources and possible solutions for domestic drug shortages

The COVID-19 pandemic has led to a shortage in the supply of prescription drugs and their main active ingredients. These shortages pose a challenge for countries such as the United States, which depend heavily on imports of these types of products.

The FRED graph above shows monthly, seasonally adjusted data for the industrial production of pharmaceutical products and medicines in the United States from January 1972 to April 2020. Since the peak in December 2006, U.S. production has consistently declined—by about 35%.

What’s behind this decline? According to data from the U.S. Food and Drug Administration, most of the manufacturing of active ingredients for medicines that are sold in the United States are located in other countries, mainly in China and India because of their lower costs of production and in Ireland because of tax incentives. So, imports of these types of products have been increasing in the United States, causing a substantial decline in their domestic production.

The COVID-19 pandemic has exposed this U.S. dependence on imports of drugs and their active ingredients. The pandemic is global, so supply chain disruptions and other complications can have negative consequences for any country that’s heavily dependent on these products. One option to mitigate the shortages in the short run could be to scale-up domestic manufacturing of active pharmaceutical ingredients; in the medium run, international agreements could be created with the main foreign suppliers of these products.

How this graph was created: Search FRED for “pharmaceuticals” and select the series “Industrial Production: Nondurable Goods: Pharmaceutical and medicine (IPG3254S).”

Suggested by Ana Maria Santacreu.

View on FRED, series used in this post: IPG3254S

How fast can the U.S. economy recover? V-shape vs. “swoosh”

How fast can the economy recover from a recession? A faster recovery would look like a V-shaped bounce. A slower recovery would look like a “swoosh.” The path depends on the economic sectors and time series data you look at. Here are some FRED Blog examples that study past episodes.

Slow recoveries:

Fast recoveries:

What about the headline economic indicator, gross domestic product? The speed of the recovery of GDP depends on factors such as the immediate cause of the recession, the depth and length of the economic contraction, and global events occurring during the recovery.

In the hope that, even in these extraordinary times, history can teach us a lesson, we look at the FRED graph above. It shows recoveries since GDP data have been available:

  • the slowest, from the Great Recession of 2007-2009
  • the fastest, from the 1937-1938 recession
  • and three “goldilocks” recoveries: after the 1981-1982, 1990-1991, and 2001 recessions.

The zero “date” represents the year each recession started. For all recessions except the one in 2001 (purple line), the path dips below 100 a year later, which represents a contraction in overall economic activity. For all recessions except the Great Recession (teal line), two years later real GDP is already higher than pre-recession levels. You can read more about tracking recoveries here.

How this graph was created: From a previous blog post: Search FRED for “annual real gross domestic product” and select the series with the ID “GDPCA.” Add the same series to the graph four more times. Next, change the units to “Index (Scale value to 100 for chosen date)” and use the expanded menu to select the date to which you’d like to index each series. From the U.S. recession menu, select these dates for the five series: 1937-05-01; 1981-07-01; 1990-07-01; 2001-03-01; and 2007-12-01, the start dates of the Great Depression’s second recession, early 80s recession, early 90s recession, early 2000s recession, and Great Recession (according to the NBER), respectively.
For each series, check the “Display integer periods” box. The x-axis will show integers as time periods instead of dates. The base period is shown as 0: Negative numbers represent periods (years, in this case) before the base period, and positive numbers represent periods after the base period. Change the start integer to 0, so the graph begins at the start of each recession. Change the end integer to 7, so the graph ends 7 years after each recession started. Finally, to use the same graph style shown here, select the circle option under “Mark Type.”

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: GDPCA

Changes in retail sales: Not by bread alone

The FRED Blog has previously discussed the impact of social distancing on retail sales for food and beverages. In today’s post, the pie graphs break down retail sales for items other than food and beverages.

The first graph shows consumer shopping habits in February 2020, before social distancing was mandated or encouraged across the U.S. At that time, the largest non-food category was motor vehicle and parts dealers.

The second pie graph shows the same categories of retail sales in April 2020, a full month after social distancing. Note how sales from non-store retailers, which include home delivery sales and electronic shopping, is now the largest category. You may also notice the category that has contracted the most is clothing and clothing accessory stores. Social distancing may have reduced consumer need for fashion, except for maybe “I *heart* social distancing” sweatpants.

How these graphs were created: From FRED’s main page, browse data by “Release.” Search for “Advance Monthly Sales for Retail and Food Services” and select “Advance Monthly Sales for Retail and Food Services by Kind of Business, Millions of Dollars, Seasonally Adjusted.” From the table, select each of the 11 non-food-related categories and click on “Add to Graph.” From the “Edit Graph” panel, use the “Edit Line” tab to change graph type to “Pie.” To show data from different months, edit the date above the graph canvas.

Suggested by Diego Mendez-Carbajo.


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