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Gimme shelter: The lag in inflation for living spaces

In January 2024, overall CPI rose 0.3% on a seasonally adjusted basis—a slight uptick from its 0.2% rate in December. It’s still a slowdown year-over-year, but this increase came as an unwanted surprise to observers expecting to see inflation continue to moderate. What’s stopping the headline inflation rate from continuing its decline?

The answer, at least in January, was shelter inflation. For January 2024, the shelter index rose by 0.6% and contributed more than two-thirds of the total CPI increase. The above graph shows the year-over-year change in shelter prices over the past decade. It’s evident that the trajectory of shelter inflation has been different from the non-shelter components of CPI: “All items less shelter” inflation peaked in mid-2022 and has been declining since, but shelter inflation peaked about one year later in March 2023 and has been declining at a slower rate.

Why is this? Shelter costs have unique characteristics that distinguish them from other goods and services. The shelter component of CPI comprises rent, lodging away from home, and owners’ equivalent rent (OER).

Rents are sticky. They change only when leases renew or a tenant moves, so it may take some time for those prices to reflect market conditions. OER comes from the same housing survey and is an attempt to estimate what owner-occupied houses would rent for, based on surveying local renters. In addition, these measures are sampled less frequently than for other goods, precisely because they change so sluggishly. This results in CPI shelter data lagging current housing market conditions.

Researchers at the San Francisco Fed, among other places, have tried to incorporate real-time data to predict what will happen to CPI shelter measures. They find that pressure from shelter inflation could ease over the coming year.

How this graph was created: Search FRED for and select “Consumer Price Index for All Urban Consumers: All Items Less Shelter in U.S. City Average.” From the “Edit Graph” section, click “Add Line” and select “Consumer Price Index for All Urban Consumers: Shelter in U.S. City Average.” In the “Edit Line” section, set units to “Percent Change from Year Ago” for both graphs.

Suggested by Nathan Jefferson.

Discounting the future

Long-horizon bond yield data from the US Treasury

The FRED Blog has discussed data from the High-Quality Market (HQM) corporate bond yields release reported by the US Department of the Treasury. In short, that executive agency of the federal government uses the spot rate yields of actual high-quality (that is, low-risk-of-default) corporate bonds to calculate the interest rates of 200 individual bonds with maturity dates extending far into the future. Up to 100 years in the future, in fact.

The FRED graph above shows the calculated interest rate of a hypothetical 100-year bond. The latest data available at the time of this writing is from December 2023: As of that date, the yield of a bond maturing in December 2123, had it been possible then to buy one, was projected to be 5.1%.

This information is used by the Internal Revenue Service (IRS) to calculate the present value of payment from defined benefit plans. The standard formula to compute the present value (PV) of a future value (FV) payment is PV=FV*(1/(1+i)^n), where i is the interest rate and n is the number of periods between now and the future date. The Treasury data provide the value of the interest rates in the IRS’s present value calculations.

So, how are the present values of very distant future payments looking lately? The FRED graph shows that the 100-year interest rate followed a decreasing trend between January 1984 and August 2020. Basic algebra shows that lower values of interest rates, holding constant future values and the number of periods, boost the present value of future payments. The inverse is true when interest rates rise and that has generally been the case during the past three years. Thus, as the present values of very distant future payments decrease, perhaps we should conclude this post by saying carpe diem.

How this graph was created: Search the alphabetical list of FRED releases for “Corporate Bond Yield Curve” and select “Corporate Bond Spot Rates by Maturity, Monthly, Not Seasonally Adjusted.” Scroll all the way down the page to select the series “100-year.”

Suggested by Diego Mendez-Carbajo.

The economic impact of February 29

Measuring variation in workdays, holidays, and leap years

Months of the year differ in terms of economic activity, so it’s often difficult to compare them. Seasonal factors are often at play, such as end-of-year holidays that raise postal employment and retail sales.

Months also have different numbers of workdays, depending on when holidays fall in the week. So it may also be difficult to compare the same month across years. The FRED graph above shows the number of workdays within a month, taken from a Board of Governors release related to the automobile industry: The range spans from 20 to 23 days, a 15% difference. When you compare year-to-year variations on a monthly or even quarterly basis, you may want to consider the number of workdays. And this graph doesn’t even take into account all federal or regional holidays.

One constant source of variation, though, is the month of February. It always has 20 workdays, except for leap years, when an additional day is thrown in. Today, in fact. Thus, this February will be 5% more productive than usual because this additional day is a workday. For the quarter, it will be roughly one-third of that; for the year, it will be one-twelfth. And these are not negligible differences when you think about yearly growth numbers.

How this graph was created: Search FRED for and select “weekdays.”

Suggested by Christian Zimmermann.



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