The FRED graph above depicts the St. Louis Fed’s Financial Stress Index (STLFSI). This data series in FRED was created in 2010 to measure changes in U.S. financial market conditions in response to a broad array of macroeconomic and financial developments. In particular, the STLFSI is designed to quantify financial market stress. There’s no specific definition for financial market stress, but periods of stress have historically been characterized by increased volatility of asset prices, reduced market liquidity conditions, or the narrowing or widening of key interest rate spreads. The STLFSI is constructed using 18 key indicators of financial market conditions—7 interest rates, 6 yield spreads, and 5 other indicators.

In late 2021, some Federal Reserve officials encouraged financial market participants and others to consider using an alternative short-term interest rate benchmark because of concerns about the eventual retirement of the London interbank offered rate (LIBOR). Since the STLFSI had two yield spreads based on the LIBOR, we replaced the LIBOR rate with the secured overnight financing rate (SOFR). Specifically, we shifted to the 90-day average SOFR. This rate measures the compounded average of the SOFR over a rolling 90-day period. In other words, it’s a backward-looking measure. We showed that the correlation between the previous version (STLFSI2) and the new version (STLFSI3) was 0.99 over the sample period dating back to December 1993. Click here for details and more information about this switch.

In 2022, we received numerous inquiries about the behavior of the STLFSI during the year. Most asked why the STLFSI was continuing to indicate lower-than-average levels of financial market stress, while other measures showed a “tightening” in financial market conditions. The divergence between the STLFSI and other indexes occurred more or less at the time when the Federal Open Market Committee (FOMC) began to signal its intent to raise its federal funds rate target in March 2022 and, importantly, subsequently signaled that further increases in the policy rate were likely in 2022—and perhaps in 2023.

Our analysis showed that instead of using the 90-day backward-looking SOFR rate, we should have used the 90-day forward-looking SOFR rate. In our view, using the forward-looking SOFR better captures financial market expectations in response to expected changes in the federal funds rate and its attendant effects on other asset prices and yields.

The second FRED graph plots the STLFSI4 and the STLFSI3 since early January 2020—just prior to the financial market turmoil and deep recession spawned by business and government actions designed to counteract the COVID-19 virus. In the graph, the two versions track each other closely over most of this period. But the close comovement began to erode in early February 2022, as it became clear that the FOMC was poised to begin raising its policy rate to combat an inflation rate that was the highest in 40 years. For example, the correlation between STLFSI3 and STLFSI4 was 0.993 from the week ending December 31, 1993, to the week ending January 28, 2022. Since the week ending February 4, 2022, the correlation has declined to 0.526.

A final takeaway from this second graph is that the new measure of the STLFSI shows that financial market stresses during the current Fed tightening episode are moderately higher compared with the previous version. Still, levels of financial market stress are currently near their historical levels. (In the index, zero is designed to be an “average” level of stress.) Moreover, the current Fed tightening episode has not triggered the kind of financial market stress seen during the heights of the pandemic-spawned shutdowns in the economy.

How these graphs were created: Search FRED for “Financial Stress Index” and make sure to take version 4. For the second graph, take the first, click on “edit graph,” open the “add line” tab, and search for “Financial Stress Index,” making sure to take version 3.

Suggested by Cassandra Marks, Kevin Kliesen, and Michael McCracken.

The FRED graph above shows that real gross domestic product (GDP) has declined over the first two quarters of 2022, after increasing by an average of 5.3% over the previous five quarters. In the eyes of some economists and financial market participants, two consecutive quarters of negative real GDP growth is sufficient evidence to declare a recession.

In the 75-year history of quarterly estimates of real GDP growth, there has been only one episode when two consecutive quarters of negative real GDP growth was not associated with a recession episode: the second and third quarters of 1947. So, from a historical standpoint, two consecutive quarters of negative real GDP growth is a pretty consistent signal for dating recessions. But what do the arbiters of dating business cycles have to say?

The dating committee

The National Bureau of Economic Research Business Cycle Dating Committee (hereafter NBER) maintains a chronology of monthly and quarterly dates of the peaks and troughs (i.e., turning points) of the business cycle. Rather than the popular two-quarter definition, the NBER employs a more comprehensive approach to dating the beginnings and ends of recessions. Specifically, they determine both the months and the quarters when economic activity peaked and troughed. Typically, the peak month occurs in the same quarter—but not always. For example, the NBER’s monthly peak of the pandemic-spawned recession occurred in February 2020, but their quarterly peak occurred in the fourth quarter of 2019.

The indicators

To determine the months of peaks and troughs, the NBER looks at several data series, such as industrial production, nonfarm payroll employment, civilian employment, and real personal income less transfer payments. The NBER also considers two other monthly series: real personal consumption expenditures and civilian employment. Civilian employment is measured using the household survey (Current Population Survey), while nonfarm payroll employment counts the number of jobs and is measured using the establishment survey (Current Employment Statistics).

The NBER also looks at estimates of the expenditure- and income-side measures of aggregate economic activity—otherwise known, respectively, as real GDP and real gross domestic income (GDI). Theoretically, GDP and GDI should equal each other in dollar terms, but they rarely do. (This difference between the two series is known as the statistical discrepancy.) The NBER also examines average GDP and GDI.

A new resource in FRED

This is a lot of information to gather, so FRED now offers some help navigating the ebbs and flows of these key data series with a new dashboard that compiles all these series on one page.

As with any user-created FRED dashboard, it updates automatically. Now, there won’t be any commentary on the current or prospective trends in the dashboard. But FRED users can make their own determination as to the likelihood of a turning point in the business cycle. Users can also use the dashboard as a starting point for creating their own variations.

Suggested by Kevin Kliesen.

Inflation is at a 40-year high—as measured by either the consumer price index or the personal consumption expenditures price index.

Federal Reserve officials have long believed that controlling inflation is a necessary condition for achieving the Congressional mandates of price stability and maximum employment. Implicit in this belief is the view that high inflation—particularly if it’s unexpected—imposes a broad array of economic costs on the economy.

For example, parts of the U.S. tax code are not annually adjusted for inflation. Inflation is a tax on cash balances. And high inflation can worsen uncertainty about future interest rates, which tends to raise financial market volatility and lower prices for financial assets such as stocks and bonds. In short, high inflation reduces the efficient allocation of resources in a market economy.

The Great Inflation, from the late 1960s to the early 1980s, was a prime example of the corrosive effects of high inflation. U.S. inflation rose sharply, as did the unemployment rate; but it also became much more volatile. High and volatile inflation meant the FOMC was never sure in real time if a decline in inflation was temporary or longer lasting. These distorted inflation signals contributed to the “stop-go” policy of the 1970s, including the tendency to ease policy when inflation fell. But inflation did not return to its previous rate. It rebounded rapidly and eventually rose to more than 14% in 1980. This turbulence increased the volatility of real GDP growth as well.

The FRED graph above shows four recessions in about a dozen years—roughly every three years beginning with the 1970-71 recession and ending with the 1981-82 recession. Until the 2007-09 recession, the 1973-75 and 1981-82 recessions had been the deepest in the post-WWII period. Also, there was a sharp slowing in labor productivity growth around 1973 that lasted for 20 years, until the microchip-led productivity boom commenced around 1994.

There were many factors that led to the Great Inflation—both bad luck and bad policies:

• oil and commodity price shocks that reduced aggregate supply
• rising transfer payments that helped boost aggregate demand
• the imposition (and subsequent loosening) of price controls imposed after the Camp David meeting in 1971

However, as former Federal Reserve Chairman Paul Volcker demonstrated early in his tenure, one key ingredient that was lacking during the Great Inflation was a commitment to restore price stability.

How this graph was created: Search for and select the CPI series in FRED. Restrict the sample period to 1966-01-01 to 1982-12-10 with the date picker above the graph, the slider below the graph, or your mouse (by highlighting the period you want in the graph itself. From the “Edit Graph” panel, change the units to “Percentage change from year ago.”

Suggested by Kevin Kliesen.