Federal Reserve Economic Data

The FRED Blog has discussed recent developments in commercial real estate and consumer credit card lending. Today, we dive deeper into the topic of consumer lending by focusing on the latest data on consumer auto loans.

The FRED graph above shows data from the Federal Deposit Insurance Corporation (FDIC) on the dollar value of three different types of loans made to individuals: credit card loans (blue area), auto loans (red area), and other loans (green area).^* We adjust the data, available since 2011, for consumer price inflation to facilitate their analysis over time.

The dollar value of auto loans made to individuals steadily decreased between the second half of 2022 and the time of this writing. That decrease is easier to see in this FRED graph of the same data plotted in year-over-year growth rates. What could explain this trend?

Juan M. Sánchez and Masataka Mori at the St Louis Fed studied the evolution of auto loans according to the income level of the borrower. Their analysis finds that the percentage of rich borrowers with auto loans markedly declined after 2019. In other words, fewer high-income households are borrowing to purchase vehicles. Higher interest rates on auto loans could be driving those borrowers to make these vehicle purchases by drawing on their savings or using other types of loans.

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

^*This is shown as the difference between “Other Loans to Individuals” and its subcategory “Auto Loans.”

How this graph was created: In FRED, search for and select “Balance Sheet: Total Assets: Loans to Individuals: Credit Cards.” Next, click the “Edit Graph” button and use the “Line 1” tab to customize the data by searching for “Consumer Price Index for All Urban Consumers: All Items in U.S. City Average.” Don’t forget to click on “Add.” Next, type the formula (a/b)*100 and click on “Apply.” Next, use the “Add Line” tab to add the other two series: “Balance Sheet: Total Assets: Loans to Individuals: Other Loans to Individuals: Auto Loans” and “Balance Sheet: Total Assets: Loans to Individuals: Other Loans to Individuals” to the graph. Follow the steps described above to customize the data. Use the “Format” tab to change the graph type to “Area” and select stacking “Normal.”

Suggested by Melanie LeTourneau and Diego Mendez-Carbajo.

The FRED Blog has used World Bank data to discuss infant mortality and life expectancy and refugee populations across groups of countries, economies, or territories classified by their level of income. Today, we discuss how these income categories are assigned.

The FRED graph above shows annual population growth data between 1961 and 2023 for the four income categories defined by the World Bank: high (blue line), upper middle (red line), lower middle (green line), and low (purple line).

Each country’s income is measured through its gross national income (GNI), the economic value added by all national producers (plus and minus some adjustments). The income figure is converted from various local currencies to US dollars, then divided by the number of persons in the total population and compared against a series of numerical thresholds for each group. For example, at the time of this writing, a low-income economy is defined as one with a GNI per person of $1,145 or less.

The threshold values separating each income category are updated every year to account for price inflation. Also, because income levels do change over time, some countries move into different categories. For example, all South Asian countries were classified as low-income countries in 1987, whereas in 2023 only one in eight were in that category.

This FRED Blog post is adapted from the World Bank’s Data Blog post “World Bank country classifications by income level for 2024-2025.”

How this graph was created: Search FRED for and select “Population Growth for High Income Countries.” Next, click the “Edit Graph” button and then the “Add Line” tab to search for and add “Population Growth for Upper Middle Income Countries.” Repeat that last step two more times to add the “Population Growth for Lower Middle Income Countries” and the “Population Growth for Low Income Countries” to the graph.

Suggested by Diego Mendez-Carbajo.

Before the Civil War, the principal way the US federal government raised income was through customs duties, a.k.a. import tariffs. These duties were easy to implement, by simply imposing them on all incoming ships at US ports.

During the Civil War, sales and excise taxes were introduced to help defray wartime costs.

During World War I, income taxes were introduced to help defray those wartime costs. By then, technology had made it possible to raise taxes in a much more decentralized way.

After the Great Depression, the US government put considerable effort into reducing customs duties through bilateral or regional agreements and the United Nations–sponsored General Agreement on Tariffs and Trade (GATT), to avoid hurting economies with tariff rates that might be set too high (or set at all). Thus, the importance of customs duties as a source of revenue has decreased.

The FRED graph above shows quarterly federal government income from customs duties since 1959. Contrary to the comments above, the data seem to show strongly increasing revenue from customs duties. Why?

The graph above ignores two important pitfalls that can cause a long series of macroeconomic data to appear misleading: The US economy grew considerably over this time period, as did the general level of prices. To correct for both these factors, we can divide this series by another series that also increased with the economy and inflation. Total tax receipts of the federal government is a good choice, as it allows us to see the share of customs duties in those receipts.

The FRED graph below shows that, while customs duties are on the high side nowadays, they have never exceeded 4% of total tax revenue for the 1959-2024 period and typically make up only about 2%. Quite far from the nearly 100% share two centuries ago.

How these graphs were created: Search FRED for “customs duties” and you have the first graph. For the second, take the first, click on “Edit Graph,” search for “Federal government tax receipts,” and apply the formula a/b*100.

Suggested by Christian Zimmermann.