Federal Reserve Economic Data

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.

The lemonade stand. A longstanding symbol of childhood summer entrepreneurship.

In this FRED Blog post, we answer the cornerstone question of every sound lemonade stand business plan: “How much does it cost to produce a glass of lemonade?”

The FRED graph above uses data from the U.S. Bureau of Labor Statistics to calculate the cost of a single glass of lemonade. The white bars represent the cost of the sugar and the yellow bars represent the cost of the lemon juice. The white and yellow bars are stacked to more easily show the total cost. We use tap water, which is so cheap in this recipe that we can ignore it without substantially impacting our calculation.^*

The latest data available at the time of this writing showed that the cost of a glass of lemonade was $0.36 in 2023. Since 1980, when the data were first available, that cost has increased almost threefold. However, the year-over-year inflation rate of this sweet and tart drink has been volatile, given that food item prices themselves are volatile.

Clearly, the cost of the ingredients is only one of the factors that drives how much money one spends at a summer lemonade stand. The cost of labor, overhead, marketing ingenuity, and overall entrepreneurial tactics of the stand owners will account for the rest.

^*The recipe is from MyPlate.gov, the website of the U.S. Department of Agriculture that provides recipes based on the Dietary Guidelines for Americans, 2020-2025.

How the graph was created: Search FRED for and select “Average Price: Lemons (Cost per Pound/453.6 Grams) in U.S. City Average.” Next, use the “Edit Line” tab to customize the data by typing the formula (a/15)*2. Next, use the “Add Line” tab to search for and add “Average Price: Sugar, White, All Sizes (Cost per Pound/453.6 Grams) in U.S. City Average.” Use the “Edit Line” tab to customize the data by typing the formula (a/12.5). Next, use the “Format” tab to change the graph type to “Bar” and the stacking to “Normal.” Last, customize the plot area and bar colors to your liking, stir well, and serve cold.

Suggested by Elizabeth Marmer and Diego Mendez-Carbajo.

Women have increased their representation in the labor force over time. In this post, we discuss how this process has differed by age group.

The FRED graph above tracks women’s share among the employed for two age groups: 20-24 years old and 35-44 years old. Women in both age groups have increased their share of employment since 1950, although growth slowed considerably after 1990.

In the younger group, women account for about 50% of total employment today, implying that young women are just as likely to work as young men. In the older group, which includes a greater representation of the married population, women account for about 46% of total employment. This smaller share reflects the fact that, within marriages, mothers are still more likely than fathers to specialize in childcare. Still, this share has increased dramatically from its 1950 level of 30%, when it was much more common for women to completely exit the labor force while raising children.

A couple of observations about women in the younger group:

First, their overall increase in employment share was smaller compared with the older group’s, given that younger women are less likely to have children and therefore more likely to be working, even back in the 1950s.

Second, their share declined in the 1950s, which may seem puzzling given the overall upward trend in women’s employment share. This decline was driven by falling labor force participation among younger women. Doepke, Hazan, and Maoz (2015) argue that these young women faced increased labor market competition, prompting them to forgo entry into the workforce in favor of marriage and childrearing, fueling the US baby boom. They explain that this increased competition came from higher labor force participation rates of women that had entered the workforce during World War II.

How this graph was created: Search FRED for and select “Employment Level – 35-44 Yrs., Women.” From the “Edit Graph” panel, use the “Edit Line 1” tab’s “Customize Data” option: Use the “Select…” bar to search for and select “Employment Level – 35-44 Yrs., Men” and add the series. In the “Formula” field, type (a/(a+b)) and select “Apply” to create the share of the employed that are females. Under the “Modify Frequency” tab, select “Semiannual” to smooth the timeseries. Now, from the “Add Line” tab, search for and select “Employment Level – 20-24 Yrs., Women” and repeat the previous steps to add “Employment Level – 20-24 Yrs., Women/(Employment Level – 20-24 Yrs., Women + Employment Level – 20-24 Yrs., Men)” to the graph. Last, use the “Format” tab to customize the line colors.

Suggested by Oksana Leukhina and Mickenzie Bass.