Federal Reserve Economic Data

Visit any data series page in FRED and you’ll see a “Notes” section below the graph. The metadata there provide details that help tell the story behind the numbers. Arguably, the single most important metadata are the data units.

Our FRED graph above shows potato farming acreage in four different countries—the US, France, Germany, and Great Britain—between 1829 and 1951.

Just as languages can differ across countries, so can the units of measure. So when using data to measure the land area used to plant potatoes, potatos, Kartoffeln, or pommes de terre, it’s important to confirm all data series are using the same units.

In this case, data from continental Europe were reported using the decimal system (in hectares) and data from Great Britain and the US were reported using the imperial system (in acres). Fortunately, FRED makes data customization very easy: Use the “Edit Line” tab to select the relevant series that use hectares and input the formula a*2.47105 to effectively convert those units to acres.

After customizing the potato acreage data, we can properly compare the disparate size of potato farming across these four countries. Note the very large land area that Germany devoted to potatoes. If we hadn’t accounted for the difference in units, we could have easily drawn a completely different conclusion. What a dis-tater that could have been.

A note about the metadata in FRED’s notes section:

• Source. Name of the organization reporting the data.
• Release. Name of the publication in which the data are reported.
• Units. Standardized quantities used to measure a concept.
• Notes. Additional information about the methods used to report the data or guidelines for sharing those data.
• Suggested citation. Bibliographical citation of the data series shown in the graph, ready to copy and paste .

How this graph was created: Search FRED for and select “Potato Crop Acreage for United States.” From the “Edit Graph” panel, use the “Add Line” tab to search for and select “Potato Crop Acreage for France.” Click on “Add data series.” Next, use the “Edit Lines” tab to select “Line 2” and customize the data by typing the formula “a*2.47105” and clicking “Apply.” Repeat the “Add data series” steps to search for and add “Potato Crop Acreage for England, Wales, Scotland, Great Britain” and “Potato Crop Acreage for Germany.” Lastly, customize the data for Germany applying the formula spelled out above.

Suggested by Diego Mendez-Carbajo.

The labor force participation rate (LFPR)—the percentage of civilians employed or actively seeking work—has declined since the turn of the century as shown in our first FRED graph above. Previously, total LFPR had risen after an increase in women entering the workforce and a corresponding but smaller drop in men’s LFPR. Since 1990, women’s LFPR has stabilized but men’s LFPR has continued to decline at an average rate of 2.7 percentage points per decade.

Our second FRED graph above splits male workers into three age groups—15 to 24 (high school and college age); 25 to 54 (prime working age); and 55 to 64 (near-retirement). The rate for older men (orange line) has been relatively constant, but the rate for prime-age men (green line) has steadily decreased. The decline for younger men (blue line) is even more pronounced, which may be explained by more young men opting for more education.

The drop in the LFPR for prime-age men was studied by Leila Bengali, Evgeniya Duzhak, and Cindy Zhao at the San Francisco Fed. They state that the gap in  participation between prime-age male Millennials today and male Baby Boomers (when they were of prime working age) can be explained by higher incidence of postsecondary education attainment, self-reported disabilities or illnesses, and caretaking responsibilities. They also summarize other economic research that attributes this decline to changing industry structure, falling demand for jobs that prime-age men have traditionally held, and the opioid crisis.

How these graphs were created: Search FRED for and select “Labor Force Participation Rate.” Below the graph, click on the release table link, select the series, and click “Add to Graph.” Use the “Format” tab to customize line style and color. Take a similar approach for the second graph after searching for “Infra-Annual Labor Statistics: Labor Force Participation Rate Male: From 15 to 24 Years for United States.”

Note: Labor force participation rates by age group in FRED are sourced from the Organisation for Economic Co-operation and Development. The labor force participation rate data in the first graph is from the Bureau of Labor Statistics. There may be slight differences in LFPR values between the two agencies.

Suggested by Brooke Hathhorn and Michael Owyang.

The value of the US dollar can influence trade flows by changing the relative prices of exports and imports. A stronger dollar tends to make imports cheaper for Americans and US goods more expensive abroad, which can put upward pressure on the trade deficit.

In practice, though, the relationship between the dollar and the US trade balance is far from consistent.

Our FRED graph above shows two measures:

• A trade balance ratio, defined as (exports − imports) ÷ (exports + imports), which expresses the US trade position relative to the total value of trade flows.
• An exchange rate measure, which in this case is the trade-weighted US dollar index, which reflects the nominal value of the US dollar against a broad basket of currencies for goods trade.

When we plot these two series together, we see that the relationship varies over time.

• In 2014-16, the dollar strengthened considerably and the trade balance ratio (exports minus imports, divided by total trade) weakened, consistent with the idea that a stronger dollar can reduce net exports by making US goods more expensive abroad and imports cheaper at home.
• In both the 2008-09 recession and 2022-23, the trade balance ratio improved alongside a stronger dollar, suggesting that other forces, such as collapsing import demand during a downturn or shifts in commodity prices, were the dominant drivers.

Trade policy can also affect both the dollar and the trade balance in ways that break the usual pattern.

• The 2018-19 tariff increases on a broad set of imports, especially from China, affected relative prices and sourcing decisions directly. They may have contributed to a stronger dollar through capital inflows, while at the same time reducing certain import volumes.
• In 2025, across-the-board tariffs and targeted increases on specific goods could again influence the trade balance through price and sourcing effects that do not operate primarily through exchange rate changes. They have the potential to shift both import volumes and export competitiveness, sometimes reinforcing and other times counteracting the influence of the dollar.

These episodes underscore that the link between the dollar and the trade balance is not systematic. Exchange rates are just one factor in shaping trade outcomes. Domestic demand, global growth, commodity price swings, and trade policy all play a role. And in recent years, tariffs and other trade measures have been especially relevant.

How this graph was created: Search FRED for and add “Trade Weighted U.S. Dollar Index: Broad, Goods” (DTWEXBGS) to the graph on the left axis. From the “Edit Graph” tab, add “Exports of Goods and Services” (EXPGS) and “Imports of Goods and Services” (IMPGS) as Line 2. To do this, enter the formula (a-b)/(a+b) in the Line 2 tab. Finally, change the starting date to “2006-01-01.”

Suggested by Ana Maria Santacreu.