Federal Reserve Economic Data

What do steam locomotives, gas-powered automobiles, and generative artificial intelligence all have in common? They’re impactful and disruptive technologies that became widely adopted.

In this post, we discuss how quickly these technologies were adopted, with the help of a graph of macrohistory data from the National Bureau of Economic Research and recent research from St. Louis Fed economist Alex Bick and co-authors Adam Blandin and David Deming.

The FRED graph above shows the number of available steam locomotives (solid line) and automobile registrations (dashed line) in the United States between 1889 and 1916. Each data series is plotted on a separate axis and displayed in a logarithmic scale to make their comparison easier.

Both transportation technologies show fast adoption rates. The number of available steam locomotives doubled between 1889 and 1911, a time span of 22 years. During roughly the same time, 1895 to 1917, the number of car registrations grew by a factor of 1 million.

On a completely different scale, the first nationally representative US survey of GenAI adoption at work and at home shows that at least 1 million subscriptions of the first GenAI model were sold in roughly two years.
Comparing the adoption rates of capital-intensive transportation goods such as steam locomotives and automobiles to a service such as computer-assisted text, image, and audio generation has obvious limitations. But, the speed of adoption of all these technologies speaks to their impact on people’s lives and the economy at large.

For more about this and other research, visit the publications page of the St. Louis Fed’s website, which offers an array of economic analysis and expertise provided by our staff.

How this graph was created: Search FRED for and select “Steam Locomotives Available for United States.” Click on the “Edit Graph” button, select the “Add Line” tab, and search for “Automobile Registrations, Passenger Cars, Total for United States.” Don’t forget to click “Add data series.” Next, use the “Format” tab to customize Line 2 by selecting “Y-Axis position: Right.” Last, customize the “Display” by selecting both “Log scale left” and “Log scale right” checkboxes.

Suggested by Diego Mendez-Carbajo.

The FRED Blog has described how the value of technology exports from the United States to the rest of the world has steadily declined. This post adds geopolitical characteristics to the discussion.

The FRED graph above uses Bureau of Economic Analysis data to track the inflation-adjusted value of US technology services exported to other countries, measured in royalties and licensing fees. The data are presented as a fraction of the total value of exported services to more easily observe their change over time.

Between 2007 and 2019, the relative value of US technology exports shrank. After a short-lived reversal in 2020-2022, likely related to economic disruptions from the COVID-19 pandemic, that value continued to decline.

Recent research from the Federal Reserve Bank of St. Louis could help explain at least part of this trend.  Ana Maria Santacreu and Samuel Moore use country-specific trade data and a measure of foreign policy preferences to discuss how countries’ geopolitical characteristics affect their purchase of US technology services:

Countries that don’t share the same foreign policy priorities and values espoused by the US are less likely to have robust international trade relations with the US than countries that do share these priorities and values. So, contentious political relations and shifting strategic alliances do erode the economic ties that bind countries. Although geopolitical tensions don’t drive the overall relative decline of US technology exports, they do offer a relevant context for telling the stories behind the numbers.

For more about this and other research, visit the publications page of the St. Louis Fed’s website, which offers an array of economic analysis and expertise provided by our staff.

How this graph was created: Search FRED for and select “Real exports of services: Royalties and license fees.” Click on the “Edit Graph” button and select the “Edit Line” tab to customize the data by searching for “Real exports of services.” Don’t forget to click “Add.” Next, type the formula (a/b)*100 and click “Apply.”

Suggested by Diego Mendez-Carbajo.

The red line in the FRED graph above shows that the average fixed rate for a 30-year mortgage began to climb significantly in the third quarter of 2021 and, by 2022, had returned to levels not seen since 2001. Although these rate increases have affected interest payments for new mortgages, the blue line shows that the share of household income devoted to mortgage payments overall is still in line with its 2015-2019 trend.

Though this divergence between average rates and debt service might seem counterintuitive, consider the effects of higher mortgage rates on the housing markets. As mortgage rates rise, homeownership becomes more expensive for prospective buyers. Those eager to build or purchase their first home may wait for rates to fall. Existing homeowners may also be dissuaded from re-entering the market, especially if they’d have to give up their current low-rate mortgage that they originated years earlier. In other words, higher mortgage rates have a broad chilling effect on housing markets.

This aversion to high rates is borne out in the data on mortgage originations. The FRED graph below shows that, as the average mortgage rate began to ascend, new mortgage lending began to decline. And despite the rise in interest rates for new mortgages, existing home owners have overwhelmingly retained low interest rate loans that originated prior to 2021.

Thus, changes in rates and lending essentially offset each other and, coupled with the high number of existing low-rate mortgages, mortgage debt service as a percentage of income did not grow proportionally with interest rates. It’s possible that a decrease in mortgage rates, even if they remain high by recent standards, will entice buyers to reenter the market; if so, home sales and mortgage lending would grow again, and mortgage debt service payments would rise.

How these graphs were created: First graph: In FRED, search for and select “Mortgage Debt Service Payments as a Percent of Disposable Personal Income.” From the “Edit Graph” panel, use the “Add Line” tab to search for and select “30-Year Fixed Rate Mortgage Average in the United States.” Use the “Edit Line” tab to edit line 2 and change the frequency to “Quarterly.” You can also change the date range above the chart to begin on March 31st, 1985. Second graph: In FRED, search for and select “Large Bank Consumer Mortgage Originations: New Originations.”

Suggested by Charles Gascon and Joseph Martorana.