Federal Reserve Economic Data

The FRED Blog has discussed how household wealth increases and decreases when the values of financial assets and housing assets go up and down. It’s useful to also consider the concept of net worth, which is the difference between the value of your assets and the value of your liabilities. Our question today is, What impact does age have on the net worth of households?

The FRED graph above uses data from the US Bureau of Labor Statistics’ Consumer Expenditure Survey to track the net change in total assets and liabilities (i.e., net worth!) of six different age groups, from under age 25 to age 65 and over.

The data are plotted in stacked bars to show how changes in net worth differ across these age groups and how business cycles affect every group’s wealth. For example, those aged 25 to 34 (red bars) most frequently report decreases in net worth: At this age, the value of student, consumer, and mortgage loans tends to grow faster than the value of the underlying assets.

The observations in this data set don’t allow us to examine how different generations of these age groups have grappled with wealth accumulation, but recent research does. Victoria Gregory and Kevin Bloodworth at the St. Louis Fed explore how Baby Boomers, Generation Xers, and Millennials have balanced student loan debt and homeownership debt to accumulate wealth. Here’s what they found for the college-educated: Millennials and Generation Xers earn as much as Boomers did, but the larger amount of student loan debt the two younger generations carry can reduce their ability to own a home and, thus, accumulate wealth.

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 graph wase created: Search FRED for and select “Net Change in Total Assets and Liabilities by Age: Under Age 25.” From the “Edit Graph” panel, use the “Add Line” tab to search for and add the other five series. To save yourself some time, simply replace the age group after the colon with: “from Age 25 to 34,” “from Age 35 to 44,” “from Age 45 to 54,” “from Age 55 to 64,” and “Age 65 or over.” Last, use the “Format” tab to change the graph type to “Bar” and the stacking option to “Normal.”

Suggested by Diego Mendez-Carbajo.

The FRED graph above shows a data series that has been featured in recent FRED Blog posts: ”Dating a recession,” “Are we in a recession (yet)?” and “Assessing recession probabilities.”

Each data point represents the probability of the US economy being in a recession during the preceding month. In other words, these are backward-looking probabilities. These probabilities can range between 0 (complete confidence the economy is expanding) and 100 (complete confidence the economy is contracting).

As of October 2023, the latest observation available at the time of this writing, the data signaled a 2.2% probability the US economy was in recession during September 2023.

But what about forward-looking probabilities? Organizations of professional forecasters such as Consensus Economics synthesize available economic data to estimate the likelihood of an economic downturn occurring in the near future. Recent research from Christopher Neely at the St. Louis Fed investigates what variables that organization appears to use to predict the probability of recession occurring in the next 12 months.

Neely finds that although 10 economic variables are useful when forecasting recessions, they do not explain the Consensus Economics estimated probability of recession very well. Moreover, Treasury yield spreads are not among those best predictors, though they have a well-established record in predicting recessions. You can learn more about forecasting from yield spreads.

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 graph wase created: Search FRED for and select “Smoothed U.S. Recession Probabilities.”

Suggested by Diego Mendez-Carbajo.

The FRED Blog has discussed the stress in the rental industry during the COVID 19-induced recession and the recent tightening in lending standards. Today, we focus on a broad change in the commercial real estate market brought about by the pandemic and its downside risks for the financial sector.

The FRED graph above shows data from the Board of Governors of the Federal Reserve System about the percent change from a year ago in the value of commercial real estate loans made by all commercial banks. The monthly data are available since June 2005.

Cycles of expansion and contraction in lending are clearly visible, but the underlying fundamentals in the real estate market are not. For example, the pandemic boosted the ability to work away from the office and reduced the demand for office space. Weaker demand depresses prices and lowers the collateral value of commercial real estate loans. That, in turn, increases financial risks for lenders.

Recent research from Miguel Faria e Castro and Samuel Jordan-Wood at the St. Louis Fed explore the financial risks associated with recent trends in the commercial real estate market. They find the risks from a potential downturn in that market are concentrated in smaller banks and not in the large bank holding companies that are commonly perceived as “too big to fail.”

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 graph wase created: Search FRED for and select “Real Estate Loans: Commercial Real Estate Loans, All Commercial Banks.” From the “Edit Graph” panel, use the “Edit Line 1” tab to change the units to “Percent Change from Year Ago.” Last, use the “Format” tab to change the graph type to “Bar.”

Suggested by Diego Mendez-Carbajo.