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.

Annual gross domestic product (GDP) is a common way to compare economic standards of living between countries. A more specific measure is the inflation-adjusted value of aggregate economic activity divided by the number of persons in the population. Or real GDP per capita.

Real GDP per capita allows us to compare, for example, rich countries with very large populations with poorer countries with smaller populations.

Our first FRED graph, above, shows real GDP per capita between 1960 and 2019 in three countries: the United States (blue line), Japan (green line), and India (red line). These countries’ economic standards of living, measured in dollars valued at 2017 prices, are markedly different throughout the 59 years of available data. But a closer inspection of the data can reveal a more nuanced picture, plotted in the FRED graph below in year-over-year growth rates.

• Between 1961 and 1974, Japan’s GDP was catching up to US GDP. Economists call this process of poorer countries catching up to richer countries convergence.
• For many years between 1961 and 2000, India’s GDP wasn’t catching up to (or even keeping up with) US GDP. Economists call this process of widening gaps between poorer and richer countries divergence.

Both of these observations are revealed in a version of the top graph with a logarithmic scale, which is best suited for analyzing long time series with different growth rates.

Recent research has looked into the relationship between growth rates and levels of GDP per capita in more than 100 countries: B. Ravikumar, Dawn Chinagorom-Abiakalam, and Amy Smaldone at the St. Louis Fed show that the year 2000 marked a change in the broad trends of economic divergence and convergence. With Penn World Table 10.01 data, they show that, between 1960 and 2000, divergence was prevalent. Between 2000 and the time of this writing, living standards in low-income countries have been catching up to those in high-income countries, signaling a period of convergence.

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 these graphs were created: First graph: Search FRED for and select “Real GDP at Constant National Prices for United States.” From the “Edit Graph” panel, use the “Edit Line” tab to customize the data by searching for “Population United States Groningen” (Groningen is to make sure to find the same source). Don’t forget to click “Add.” Next, type the formula a/b and click “Apply.” Next, use the “Add Line” tab to repeat the process for India, and then Japan. Second graph: Take the first and, for each line, change the units to “Percent Change From Previous Year” at the bottom of the menu.

Suggested by Diego Mendez-Carbajo.