Federal Reserve Economic Data

No doubt about it, mortgage rates are up. The FRED graph above shows the rates for the most popular fixed-rate mortgages: the 15-year and 30-year. Every data point is the average rate offered at that point in time for new mortgages. Although the graph shows the recent data, at this point very few people are actually paying these increased rates.

One could say that current mortgage holders are enjoying a good deal: They’re paying a lower rate, and inflation is higher. Inflation matters because mortgage debt is nominal. So, if inflation increases all prices (and in particular wages), paying a nominal debt such as a mortgage becomes much easier. One might then consider that even new mortgages are also a good deal when there’s inflation.

The previous low-rate mortgages were not set during a time of higher inflation, and those who set the rates must not have anticipated the higher inflation to come. But the new mortgage rates now include the anticipation of higher inflation, and thus this inflation advantage is factored into the mortgage rate.

To look at the data behind this argument, we use the FRED graph below. Here, we deflate each mortgage rate by the corresponding “breakeven” rate, which takes into account the anticipated average inflation from the point of measure over the relevant number of years. (Unfortunately, there’s no 15-year breakeven rate, so we average the 10- and 20-year rates using FRED’s fancy tools.)

The result is actually not that different. The real mortgage rates are still significantly up. The reason is that inflation expectations over such long horizons (15 to 30 years) have not moved that much, likely reflecting a general expectation that inflation won’t last. Our last FRED graph documents those expectations.

How these graphs were created: First graph: Search FRED and select the 15-year mortgage rate. Once you have the graph, use the “Edit Graph” panel’s “Add Line” tab to search for and add the 30-year mortgage rate. Second graph: Start with the first, use the “Edit Line” tab for the 30-year mortgage series: Search for and add the “Breakeven 30-year” series and apply formula a-b. In a similar way, add two series to the 15-year mortgage line: “Breakeven 10-year” and “Breakeven 20-year,” and apply formula a-(b+c)/2. Third graph: Use the interest rate spreads release to select the relevant breakeven rates and click “Add to graph.”

Suggested by Christian Zimmermann.

U.S. Census data in FRED has helped us examine income inequality before, including mean and median income and the Gini ratio. Here, we examine income inequality through a different lens.

The GeoFRED map above shows the level of income inequality across U.S. counties. This particular measure is the ratio of average (mean) income for the highest earners (top 20%) divided by the average income of the lowest earners (bottom 20%) for each county. The Census data track the average income over a five-year period, in this case 2014 to 2019, to account for the fact that people’s income changes from year to year.

Measured this way, income inequality can be as high as 90 or as low as 5. That means that the most-affluent households in a particular county can earn as much as 90 times or as little as 5 times what the least-affluent households do. But those are the two extremes of income inequality. The typical (median) value is 13 times.

Because income levels vary widely across counties, two counties with similar degrees of income inequality can have very different economic profiles. For example, both Bath County, KY, and Ocean County, NJ, have a typical income inequality ratio, but the percentage of persons below the poverty line is 2.4 times higher in the Kentuckian county than in the New Jerseyan county.

How this map was created: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Diego Mendez-Carbajo.

During the Great Recession, between 2008 and 2010, the unemployment rate climbed gradually and then slowly declined over nearly a decade. During the COVID-19 pandemic, between February and April 2020, the unemployment rate spiked to historically high levels but quickly dropped and had largely returned to pre-pandemic levels by April 2022, just two years later.

These are overall patterns, but do they hold across different racial and ethnic groups? To see how the unemployment rate differs by race and ethnicity within each recession, we can look to FRED. Our FRED graph above plots the unemployment rate for Black, White, Latino, and Asian workers—in blue, red, green, and purple, respectively—from October 2006 to the latest available data. Historically, Black workers have usually faced the highest unemployment rate, followed by Latino workers. The unemployment rates of White and Asian workers closely track one another, with Asian workers generally facing the lowest unemployment rate.

COVID-19 recession

During the COVID-19 recession, Latino workers suffered the largest shock: Their unemployment rate skyrocketed from 4.3% in January 2020 to 18.8% by April 2020—a 14.5-percentage-point increase. Asian workers suffered the second highest increase (11.4 percentage points), followed by White workers (11 percentage points) and Black workers (10.3 percentage points). Unemployment rates have since been on a rapid and steady decline. By April 2022, rates had dipped below January 2020 levels for Black and Latino workers, while remaining only 0.1 percentage point above for both White and Asian workers.

Great Recession

On the other hand, unemployment rates gradually climbed over the Great Recession period. Consistent with historical patterns, Black workers faced the highest unemployment rate throughout the episode, followed by Latino workers. By June 2009, the two groups had seen comparable increases in unemployment rates (from pre-recession levels in November 2007) of 6.3 and 6.2 percentage points, respectively. Even though unemployment rates increased by over 4 percentage points for both White and Asian workers over the same period, they faced low unemployment relative to Black and Latino workers. The gradual recovery pattern holds, with unemployment rates stabilizing around pre-recession levels in mid to late 2016 for all four groups.

How this graph was created: In FRED, search for the seasonally adjusted unemployment rate for one group, e.g. “Unemployment Rate – Black or African American.” From this graph, click “Edit Graph” at the top right corner and navigate to the “Add Line” tab. Search for the unemployment rate of next group, e.g. “Unemployment Rate – White,” and click “Add data series.” Repeat for the remaining groups.

Suggested by Serdar Birinci and Ngân Trần.