Federal Reserve Economic Data

Our FRED graph above displays the average annual interest rates (also called yields) for three common types of retail bank and credit union deposits, as reported by Bankrate Monitor.*

• CDs/certificates of deposit. The funds are left on deposit for several months or years to collect a set interest rate. Withdrawing the funds early requires paying a penalty fee. (The dashed green line shows 1-year CDs, and the solid blue line shows 5-year CDs.)
• Savings accounts. Funds not needed for daily expenses earn a variable interest rate. There may be limits to how often or easily money can be withdrawn. (Shown by the dotted red line.)
• Checking accounts. Money used for daily expenses can be accessed by writing checks or by using automated teller machine (ATM) cards or debit cards. Some checking accounts offer a variable interest rate. (Shown by the dashed-dotted purple line.)

Bank accounts where funds can be withdrawn more easily or at low cost generally offer relatively lower interest rates. Put differently, accounts where funds are relatively harder to turn into cash will generally offer relatively higher interest rates to attract depositors.

So, we’d expect to see a 5-year commitment to storing funds to earn you a higher interest rate than a 1-year commitment. But what do the data show us?

Between October 2022 and the time of this writing, the average interest rate on a 1-year CD was reported to be higher than the average interest rate on a 5-year CD, due to uncertainty about future financial market conditions. This type of inversion in the expected structure of interest rates is discussed in a FRED Blog post from 2018 and further described here.

*FRED recently added 15 new series from the Bankrate Monitor National Index. These weekly data report average interest rates on checking and saving accounts, certificates of deposit, credit cards, auto loans, mortgages, and other lines of personal credit. The Bankrate data are collected weekly from a survey of the “10 largest banks and thrifts in 10 large U.S. markets.” Data on CDs are available since 1984, and data on other types of deposits were added in more recent decades.

How this graph was created: Search FRED for and select “Bankrate Monitor (BRM): Certificate of Deposit APY – 5 Year CD – APY.” Click on the “Edit Graph” button and select the “Add Line” tab to search for “Bankrate Monitor (BRM): Certificate of Deposit APY – 1 Year CD – APY.” Don’t forget to click on “Add data series.” Repeat the last two steps to add data on “Saving accounts” and “Interest checking accounts.”

Suggested by Diego Mendez-Carbajo.

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.