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Posts tagged with: "GDP"

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U.S. net exports of technology have fallen since 2011

How have tech imports and exports changed?

The FRED graph above shows the quarterly evolution of U.S. net exports of technology, from Q1 1967 to Q1 2021. Net exports of technology are measured as royalties and license fees received minus royalties and license fees paid during this period (as a percentage of GDP).

The U.S. has always been a net exporter of technology and, hence, a net receiver of royalty payments. And net exports as a share of GDP have steadily increased from 0.12% in Q1 1985 to 0.48% in Q3 2011—an increase of 300%! But after 2011, there’s been a slow decline, reaching 0.28% in Q1 2021 (its lowest level since Q1 2002). What’s caused this decline?

The FRED graph below shows, separately, exports of technology in terms of royalties received and imports of technology in terms of royalties paid (again, as a percentage of GDP). While U.S. technology exports have steadily fallen from 0.70% in Q3 2011 to 0.51% in Q1 2021, imports have remained fairly stable. Hence, the decline in net exports has been driven exclusively by a decline in exports.

The decline in royalties received by the U.S. throughout the 2010s could be attributed to two factors. First, the rise of Silicon Valley tech giants and their use of royalty payments to shift profits and avoid taxes by moving their intellectual property to tax havens. Second, the U.S.’s standing as the sole global technological power has been rapidly challenged by China over the past few decades. In fact, look for a blog post on that topic in the next week.

How these graphs were created: First graph: Search FRED for “Royalties” and select “Exports of services: Royalties and license fees.” From the “Edit Graph” panel’s “Edit Line 1” tab, use the customize data search box to search for and add “Imports of services: Royalties and license fees” and “Gross domestic product.” Then use the formula box below to type in ((a-b)/c)*100. Second graph: Search FRED for “Royalties” and select “Exports of services: Royalties and license fees.” From the “Edit Graph” panel’s “Add Line” tab, search for and add “Imports of services: Royalties and license fees.” Go to the “Edit Line” tab for each of these series and use the customize data search box to search for and add “Gross domestic product.” Then use the formula box below to type in (a/b)*100.

Suggested by Ana Maria Santacreu and Jesse LaBelle.

View on FRED, series used in this post: B684RC1Q027SBEA, B908RC1Q027SBEA, GDP

Household debt meets corporate debt

Households take on debt for a variety of reasons, such as financing education and purchasing a house. Household debt in the U.S. increased from 59% of GDP in 1990 to 98% of GDP in 2009, and many economists argue that the Great Recession was “Great” because household leverage was so high at the time. It has since declined steadily. In fact, in 2019, household debt and corporate debt were the closest they have been in nearly 30 years.

The FRED graph above shows both series as a percentage of GDP: household debt and corporate debt. Household debt has exceeded corporate debt since the early 1990s, and this difference was particularly large in the years leading up to the Financial Crisis of 2008. For instance, in the third quarter of 2006, household debt was greater than corporate debt by as much as 31% of GDP. In the years since the Great Recession, however, U.S. household debt has steadily decreased. This decline, accompanied by an increase in corporate debt since 2012, has reduced the gap between household and business debt. In fact, in the last quarter of 2019, household debt and corporate debt were both around 74% of GDP.

What has driven this decrease in household debt? There are many types of household debt: mortgages, student loans, auto loans, credit card loans, etc. The second FRED graph decomposes household debt into some of these categories and shows that the decrease in household debt is driven primarily by the decline in mortgages over the recent decade. Auto loans have remained stable as a percentage of GDP; student debt has increased slightly, but not nearly enough to offset the large decrease in mortgage debt.

How these graphs were created: First graph: Search for and select “Nonfinancial Business; Debt Securities and Loans; Liability; Level.” From the “Edit Graph” menu, add the series “Households and Nonprofit Organizations, Debt Securities; Liability, Level.” For both lines, add the second series “Gross Domestic Product, Billions of Dollars, Seasonally Adjusted Annual Rate.” To rescale the series as a percentage of GDP, change the formula to (a*100/b) in the formula bar. Second graph: Search for and select “Households and Nonprofit Organizations, Debt Securities; Liability, Level.” From the “Edit Graph” tab, search for and add each of the following FRED series IDs: HHMSDODNS, MVLOAS, SLOAS. For each line, also add the series for GDP and then change the formula to (a*100/b).

Suggested by Asha Bharadwaj and Miguel Faria-e-Castro.

View on FRED, series used in this post: CMDEBT, GDP, HHMSDODNS, MVLOAS, SLOAS, TBSDODNS

Central banking since 1701

Three centuries of Bank of England asset data

The British have a history of recording excellent historical data, and we’ve already written a few related posts. Today we look at central bank assets for the Bank of England, founded in 1694. The graph above shows the assets as a share of GDP since 1701, which is a remarkable timeline, especially because it requires estimates of GDP from before the American Revolutionary War not to mention the Battle of Culloden!

This FRED graph shows us that assets in the 18th century reached a fifth of GDP before slowly receding. There were run-ups during the turmoil of the Great Depression, World War II, and the Great Recession and its financial crisis. For comparison, we added the (much shorter) corresponding series for the United States in red. It’s pretty amazing how well they match up.

How this graph was created” Search for “Bank of England assets,” select the appropriate series, and click “Add to Graph.” From the “Edit Graph” panel, open the “Add line” tab, and search for “federal reserve assets.” Once you have the series, change its frequency to quarterly, add a series looking for “nominal GDP,” and apply formula a/b/10. (We multiply by 100 to get percent but divide by 1000 to have the same units for a and b: thus, /10.)

Suggested by Christian Zimmermann.

View on FRED, series used in this post: BOEBSTAUKA, GDP, WALCL


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