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The spirit of the Olympics in FRED’s housing data

When it comes to data delivery, FRED wholeheartedly embraces the motto of the Olympics: “Faster, Higher, Stronger – Together!”

Although the FRED Blog team won’t be able to travel to Paris, France, to attend the 33rd Summer Olympic Games, we can talk about the Olympians and Parisiens right here at home.

And, of course, we’re talking about the residents of Olympia, Washington, and Paris (in both Texas and Tennessee).

The FRED map above shows the median number of days a real estate listing spent on the market from the time it was listed for sale until the sale was reported as pending or closed or the property was no longer for sale.*

First, hover over Olympia-Tumwater, Washington, in the map. You can see that, as of June 2024, the median time it took for a real estate property there to exchange hands was 30 days: That is, half did so in 30 or fewer days and the other half did so in 30 or more days. By contrast, the median time a real estate property stayed on the market in Paris, Texas, was 58 days. In Paris, Tennessee, it was 60 days. So, in the parlance of the Games, we have our gold, silver, and bronze medals—at least for this race.

How this map was created: Search FRED for “Housing Inventory: Median Days on Market Year-Over-Year in Olympia-Tumwater, WA (CBSA)” and click the “View Map” option.

*The data are reported by Realtor.com. You can learn more about data geographies in FRED here.

Suggested by Diego Mendez-Carbajo.

The comprehensive costs of housing

Detailed CPI data on shelter, utilities, and furnishings

Paying for the place where you live—categorized as “shelter” in the consumer price index—amounts to 36% of the overall cost of goods and services purchased by an average urban household during a month. However, putting a roof over your head also involves paying for creature comforts such as heating and cooling, utilities, furniture, appliances, and operations. Together, those expenses amount to an additional 9% of the overall consumer price index. Today we look at recent housing inflation for both shelter and making that shelter habitable.

The FRED graph above shows consumer price index (CPI) data on housing expenses organized in four categories:

  • Shelter (dashed blue line) includes rent, owner’s equivalent rent of residences, lodging away from home, and home insurance.
  • Services (red line) includes water, sewer, and trash collection.
  • Furnishings and operations (green line) includes furniture, appliances, housekeeping supplies, and a variety of items and services.
  • Energy (purple line) includes fuel oil, gas, and electricity.

We customized all the data to have a value of 100 in April 2020, the end of the COVID-19-induced recession, to facilitate the analysis of housing costs over time. The data plot shows that, over the past four years, shelter became 23% more expensive and the cost of furnishing and operations and paying for non-energy utilities kept roughly that same pace.

Energy inflation has been a different story: As of the latest available observation, heating, cooling, cooking, and running electric appliances is, on average, 33% more expensive than four years ago, although those costs have come down from their peak in January 2023.

How this graph was created: Search FRED for “Consumer Price Index for All Urban Consumers: Shelter in U.S. City Average.” Next, click the “Edit Graph” button and use the “Add Line” tab to add the other three CPI series: “Water and Sewer and Trash Collection Services,” “Household Furnishings and Operations,” and “Energy.” Next, use the “Edit Lines” tab to change the units to “Index (Scale value to 100 for chosen date)” and under “Select a date that will equal 100 for your custom index:” enter “2020-04-01.” Last, click on “Copy to all” to apply that unit customization to all series in the graph.

Suggested by Diego Mendez-Carbajo.

How housing prices have impacted PCE inflation

Two new measures of PCE inflation from the BEA

FRED recently added two new personal consumption expenditures (PCE) price index data series from the US Bureau of Economic Analysis: one excluding the energy and housing categories from the all-items PCE price index and a second one excluding the food, energy, and housing categories. These series are timely additions to FRED’s substantial repository of measures of trend inflation.

The FRED graph above shows these two new PCE price index series from the BEA (blue and red lines), along with the all-items price index (green line). The data are plotted as inflation rates, or percent changes from a year ago.

Between April 2020 (the end of the COVID-19-induced recession) and roughly the last quarter of 2021, the three measures of PCE inflation moved broadly in sync. However, during the better part of 2022, food, energy, and housing prices changed at a different pace from the remaining PCE price categories. Russia’s invasion of Ukraine was a large shock to international energy and food markets, but housing markets are local. So, what happened to those prices?

In short, and paraphrasing Jerome Powell, because rental leases are renewed annually or even less frequently, housing price inflation tends to lag other prices after speedups or slowdowns in overall inflation. This apparent lack of co-movement between the all-items PCE inflation and the other two measures of personal consumption expenditure prices was due to the timing of new housing data, particularly rental prices. This phenomenon has also been visible during other time periods when inflation changed its direction of growth, particularly during the 2007-2009 recession: See this FRED graph with the three PCE series plotted since 1960.

How this graph was created: In FRED, search for and select “Personal Consumption Expenditures: Services Excluding Energy and Housing (Chain-Type Price Index).” From the “Edit Graph” panel, use the “Add Line” tab to search and select “Personal Consumption Expenditures Excluding Food, Energy, and Housing (Chain-Type Price Index).” Repeat the last step to add “Personal Consumption Expenditures: Chain-type Price Index.” Lastly, use the “Edit Lines” tab to change the units into “Percent Change from Year Ago” and click on the “Copy to all” button to apply the change to the other two series in the graph.

Suggested by Diego Mendez-Carbajo.



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