Federal Reserve Economic Data

The Bureau of Economic Analysis (BEA) produces economic accounts statistics that enable decisionmakers and researchers of all kinds to track and understand the performance of the nation’s economy.

One of BEA’s headline indicators is domestic economic activity. BEA uses three different—and, in principle, equivalent—statistics to estimate the dollar value of this activity. Each of these statistics offers a different perspective on the economy, and the FRED graph above shows them side by side.

• Red bars show gross domestic product (GDP), also known as the expenditure measure of domestic economic activity. GDP reflects the value of (and demand for) US-produced final goods and services and estimates present economic activity from the vantage point of consumers, investors, governments, and foreigners.
• Green bars show the value of gross domestic income (GDI), also known as the income measure of domestic economic activity. GDI reflects the income generated from producing goods and services and estimates present economic activity from the vantage point of workers, business owners, and others (such as governments and nonprofits) that participate in production.
• Blue bars show gross value added (GVA), also known as the production measure of domestic economic activity. GVA reflects the supply of production from US industries and estimates present economic activity from the vantage point of businesses, households and institutions, and the general government.

BEA data on GDP, GDI, and GVA are available at the same time with the third estimate of GDP for each quarter, as well as in annual updates and, as of September 2023, comprehensive updates. This is a historic achievement for economic measurement in the US.

This FRED Blog post is an adaptation of The BEA Wire’s “Musings from Mackinac Bridge: Three Ways to Measure Economy Offer Different Perspectives.”

How this graph was created: Search FRED for “Gross value added: GDP: Business.” Next, click on the “Edit Graph” button and select the “Line 1” tab to customize the data. Start by searching for “Gross value added: GDP: Households and institutions.” Click on “Add.” Further customize the data by searching for “Gross value added: GDP: General government.” Don’t forget to click on “Add.” Next, type the formula a+b+c. Next, use the “Add Line” tab to search for and add two more series to the graph: “Gross Domestic Product, Billions of Dollars, Not Seasonally Adjusted, Annual” and “Gross Domestic Income, Billions of Dollars, Not Seasonally Adjusted, Annual.” Last, use the “Format” tab to select “Graph type: Bar.”

Suggested by Diego Mendez-Carbajo.

The FRED Blog has used data from the US Census to discuss the flows of net migration at the county and state levels. Those data have no information about the age of the people who switch places of residence, but other datasets offer insights into who moves and where they move.

The FRED map above shows 2022 data from the US Bureau of Labor Statistics about the average age of the person tagged as the “individual of reference” in its Consumer Expenditure Survey (CES). This is the first person listed in the survey response of a “consumer unit,” which is a group of people living together. There are four Census regions and four colored data ranges, each representing a slightly different age group. Thanks to improvements in living standards, the US population is living longer and its average age is rising.

Recent research from Victoria Gregory and Kevin Bloodworth at the St Louis Fed studies where people choose to live as they age. Here’s what they find: In their 20s, members of the Silent Generation, Baby Boomers, Generation X, and Millennials were more likely to live in large central metropolitan areas than members of Generation Z. Urban flight to the suburbs seems to generally characterize location decisions for people in their 30s, but it is too early to tell whether and where members of Generation Z may choose to move.

For more about this and other research, visit the website of the Research Division of the Federal Reserve Bank of St Louis, which offers an array of economic analysis and expertise provided by our staff.

How this map was created: Search FRED for and select “Consumer Unit Characteristics: Age of Reference Person by Region: Residence in the South Census Region.” Click on the green button “View Map.”

Suggested by Diego Mendez-Carbajo.

The price of housing has been a major topic in the United States over the past decade, especially given the expansion of the housing market over the past 4 years.

In this FRED blog post, we want to measure how affordable homes have been for the typical earner, focusing on the house price itself but not factoring-in the cost of a mortgage. So, we compare the median weekly earnings for those 25 years and older with the S&P US national home price index, using the first quarter of 2020 as a point of reference.

Our graph shows that, since the first quarter of 2012, there’s been a gradual increase in the house price index relative to wages. This is followed by a dip at the beginning of the pandemic and a rapid increase in the house price index relative to wages in the subsequent quarters. This is consistent with rising home prices throughout the pandemic.

After this peak in the price index relative to wages, in the second quarter of 2022, our index stagnates around the same values as the peak during the 2005-06 housing bubble. Will the index follow a path similar to the one from 2007 to 2012? Only the future will tell.

How this graph was created: In FRED, search for and select the series “S&P CoreLogic Case-Shiller U.S. National Home Price Index.” From the “Edit Graph” panel in the top right corner, use the Edit Line 1  option to customize the data and add the series “Employed Full Time: Median Usual Weekly Nominal Earnings (Second Quartile): Wage and Salary Workers: 25 years and over.” In the formula section, divide series a (price) with series b (earnings). Select the units to be an index and choose the reference date for the index to be 2020-01-01. Finally, change the start date to 2001-01-01.

Suggested by Alex Bick and Kevin Bloodworth.