Federal Reserve Economic Data

Military conflict and geopolitical tensions in the Middle East tend to be associated with disruptions in the global supply of oil. These disruptions can raise both the level and the volatility of the price of oil. And rising oil prices have many direct and indirect macroeconomic effects.

• Oil is an important intermediate input in the production of goods—plastics, for example. So, increases in the price of oil can lead to increases in the prices of other final goods.
• Many households rely directly on gasoline for daily activities, such as commuting to work and visiting family.
• Households and businesses also rely on oil indirectly for electricity consumption.

Another channel through which oil prices may have macroeconomic effects is related to a country’s status as a net importer or exporter of this commodity: A rise in oil prices tends to harm net importers while benefiting net exporters. Is the US a net importer or a net exporter of oil?

Our FRED graph above helps us answer that question by displaying the time series of net exports of petroleum-related products for the US as a share of GDP. From 1985 (when data are first available) through 2020, the US was a net importer of oil. The series was negative during that period. The series became positive around 2020, indicating that the US became a net exporter. This change is primarily explained by rising exports of refined petroleum products, such as gasoline and jet fuel.

Our second FRED graph, below, displays imports and exports of petroleum and its related products separately, both divided by nominal GDP. This graph helps rationalize some of the trends that underlie the first graph: Imports of petroleum products as a share of GDP rose throughout the 1990s and 2000s. But this ratio has fallen, suggesting the US economy has become less dependent on oil. At the same time, technological improvements, such as the development of the shale oil industry, have led to an increase in the importance of petroleum exports as a share of GDP. It’s also worth noting that not all types of oil are identical: Different grades of oil have different uses, and the US economy tends to import crude oil while exporting refined petroleum products.

While an increase in the price of oil could benefit at least some sectors of the US economy, the fact that oil is a commodity with globally determined prices means that domestic consumers still pay more when supply disruptions occur and prices rise.

How these graphs were created: First graph: Search FRED for “exports of petroleum” (FRED series ID LA0000061Q027SBEA) and click on “Edit Graph.” Search for “imports of petroleum” (FRED series ID B648RC1Q027SBEA) and then “nominal GDP” (GDP). Apply formula (a-b)/c. Second graph: Repeat the above process for exports and GDP with formula a/b, then open the “Add Line” tab and repeat with imports and GDP.

Suggested by Miguel Faria-e-Castro.

In early April 2026, the Bureau of Labor Statistics (BLS) released the annual benchmark revision to state employment data for 2025. Before this benchmark revision, the data showed positive job growth in 2025 in just over two-thirds of US states: 34 of 50. The median job growth rate was 0.45%. After this revision, the data show job growth was positive in fewer than half the states: 22 of 50. And the median job growth rate was -0.09%, a slight job loss. This FRED blog post explains why these data revisions occur and provides examples of how ALFRED can be used to examine these data revisions over time.

Why do data revisions occur?

Data revisions occur because counting new jobs is a difficult process that relies on samples and advanced statistical techniques. As more information becomes available, data are revised. The BLS uses the monthly Current Employment Statistics (CES) survey to estimate local employment for nonagricultural industries. But the best source of local employment statistics comes from their Quarterly Census of Employment and Wages (QCEW). The QCEW includes data derived from establishments’ reports to the various unemployment insurance programs that are released with about a 6-month lag. Every spring, the BLS reconciles the CES estimates with the data from the QCEW, which can result in significant revisions.

What do the data show us?

The BLS often revises employment data significantly, and 2025 was no exception.

• The average absolute revision to 2025 state employment growth was 0.70%.
• Job growth was revised lower in 40 states and higher in 10 states.
• Nevada (+2.33%) and Alaska (+0.47%) had the largest positive revisions to job growth, while Maryland (-1.82%) and Missouri (-1.99%) had the largest negative revisions.

Our two FRED graphs above show the 12-month change in nonfarm payrolls for Missouri and Nevada, the two states with the largest revisions. The dashed blue line in each graph is the most recent vintage of data in ALFRED (April 13, 2026), and the solid line green lines is the the vintage of data prior to this benchmark revision (January 27, 2026).

Although it can be tempting to take unrevised data at face value, this year’s revisions underscore the importance of always taking a cautious approach.

How these graphs were created: Search ALFRED for and select the “Missouri nonfarm employment” series. Adjust the date range to “2021-01-01” to “2025-12-01.” Click “Edit Graph” and change the “Units” to “Change from Year Ago, Thousands of Persons” and click “Copy to all.” Open the “Format” tab to change the “Graph type” to “Line” and click “Customize” on “Line 1” to change the “Line Style” to “Dash.” For the second graph, repeat for Nevada.

Suggested by Charles Gascon.

More data from the Chicago Fed’s Advance Retail Trade Summary (CARTS) release are now in FRED. These estimates of retail and food service sales (excluding some motor vehicles and parts) track the U.S. Census Bureau’s Monthly Retail Trade Survey (MRTS) on a weekly basis, providing an early snapshot of national retail spending.

Our ALFRED^* graph above plots CARTS and MRTS data side by side between April 2025 and March 2026.

1. The two lines in the graph look like a single line, which indicates the monthly averages of benchmarked weekly estimates from the Chicago Fed are identical to the figures reported by the Census.
2. The graph also shows the CARTS data projection beyond the latest MRTS data. These estimates allow economic researchers and policymakers to make early assessments of trends in consumer purchases using higher-frequency data.

CARTS data in FRED go back to January 2018 and also include series about inflation-adjusted estimated retail sales figures, a price index of retail sales, and projections for both.

^*Happy Birthday, ALFRED! For 20 years, ArchivaL FRED has taken people back in time to see the data that were available on specific dates. Learn more about how it can help you understand economic history.

How this graph was created: Search ALFRED for and select “Advance Retail Sales: Retail Trade and Food Services, Excluding Motor Vehicle and Parts Dealers.” Click on the “Edit Graph” button and select the “Add Line” tab to search for “Chicago Fed Advance Retail Trade Summary: Retail and Food Services Sales Excluding Autos.” Don’t forget to click on “Add data series.” Select the “Edit Lines” tab to change Line 2’s data frequency to “Monthly.”

Suggested by Diego Mendez-Carbajo.