Why Shelter Inflation Will Persist in a Higher for Longer Interest Rate Environment

Looking at recent CPI prints, at first glance it appears the Fed was able to successfully taper the heightened inflation we saw in the wake of COVID, which I’ve argued was largely a monetary phenomenon. Inflation peaked at ~ 9.1% in June 2022 (~7% PCE headline), the third highest read since November 1981. By measure of most CPI components, we are largely out of the woods – excluding shelter, inflation was reported at ~ 1.0% YoY (3.3% incl. shelter) in July 2023, the lowest average since November 2020 & and less than half the 20-year average.

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Shelter, the largest component of CPI (~ 42% of CPI, according to the Federal Reserve of Boston) has also been cooling, with rent inflation declining four consecutive months since April 2023, at .41% MoM (now ~ 8.0% YoY), the lowest since December 2021 after a 20-month climb. Additionally, asking rent, the proxy for future forecasts of rent inflation, is cooling at an even faster pace, expected to normalize by late winter or early spring 2024 (Jay Parsons, Real Cap Analytics) [1].

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At the Jackson Hole Symposium on Friday, August 25, Fed Chair Jerome Powell echoed this optimism: “Mortgage rates doubled over the course of 2022, causing housing starts and sales to fall and house price growth to plummet. Growth in market rents soon peaked and then steadily declined.”

Additionally, he correctly pointed out that “measured housing services inflation lagged these changes, as is typical, but has recently begun to fall. This inflation metric reflects rents paid by all tenants, as well as estimates of the equivalent rents that could be earned from homes that are owner-occupied. Because leases turn over slowly, it takes time for a decline in market rent growth to work its way into the overall inflation measure. The market rent slowdown has only recently begun to show through to that measure. The slowing growth in rents for new leases over roughly the past year can be thought of as "in the pipeline" and will affect measured housing services inflation over the coming year. Going forward, if market rent growth settles near pre-pandemic levels, housing services inflation should decline toward its pre-pandemic level as well. We will continue to watch the market rent data closely for a signal of the upside and downside risks to housing services inflation.”

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These facts, however, don’t tell the full story. True, the lag driven by leases expiring does take time to make its way into the overall shelter index, given the refreshing of survey sample sets and typical annual term of lease agreements. Also true, as I’ll detail later, asking (or “market”) rent is the leading proxy for future housing inflation (especially within ~ a year of certainty). But what Powell, and I’ll argue the Bureau of Labor Statistics and Federal Reserve Banks alike are overlooking, is Owner’s Equivalent Rent (also “OER”), the second and larger component of the housing services cost index[2]. And, by everything I can gather, the nature of how this index is calculated underestimates the level of OER inflation (and, further, shelter inflation) we should expect in a new higher-for-longer interest rate regime.

How is shelter inflation data collected?

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The CPI Housing Survey / Consumer Expenditure Survey provides the price change for these two components at the time of observation, by definition a trailing factor: (1) rent of primary residence (rent) and (2) owner’s equivalent rent of primary residence (OER).

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For both, data sampled is the latest available from the US Census Bureau; the sample of rented housing units is updated on an annual basis by replacing one-sixth of the prior sample size. The census survey collects information by sampling neighborhoods split into six panels, sampled once a month such that each panel is sampled twice a year, once every six months. The US samples core-based statistical areas[3], the grand majority of which are located in or contain cities, representing the CPI for All Urban Consumers (CPI-U population). About 93% of the US population lives in what are deemed by the bureau “urban households”; what’s not covered are people living in rural nonmetropolitan areas (farm households, military installations, religious communities, prisons, hospitals, etc.).

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The Bureau of Labor Statistics defines and draws from a bag of primary sampling units (PSUs), 75 in total since 2018, that fall into one of three categories:

1. Self-Representing PSU’s (known as “S” PSUs) are selected with certainty. There are 21 PSU’s, which are metropolitan CBSAs with a population over 2.5 million people. This represents ~ 39% of the CPI-U (~36% of population).
2. Non-Self-Representing PSUs (known as “N” PSUs) are those selected randomly. There are 52 “N” PSUs, which are metropolitan and micropolitan CBSAs[4] with a population under 2.5 million people. This represents ~ 42% of the CPI-U (~39% of total population).
3. Rural PSUs (known as “R” PSUs). There are 16 “R” PSUs, which are non-CBSA areas.

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What’s glaring is how the CE Survey collects information. For reference, the survey collects the following owner-reported information on OER related to owner’s primary residence to calculate the index – included are questions relevant to determining pricing (non-exhaustively, but covering the driving factors):

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Current Cost of Living (03A1):

• What % of expenses were deducted for business, farming, or in rent to someone outside of the HH?
• If there was a change, what was the reason for the change in your property expenses (tax reassessment, change in interest rate, refi, sale, etc.)?
• What type of mortgage is outstanding (30-year, 15-year, etc.)?
• Is the mortgage fixed rate, ARM, variable, IO, etc.? What is the current rate?
• What was the initial debt proceeds amount at the time the property was purchased?
• What components are included in your regular housing payments (principal, interest, escrow, PMI, etc.)?
• What is your mortgage payment per month, what is the interest / principal split?
• What is your monthly payment on your HELOC? Second Mortgage?
• Have you paid additional costs above and beyond your existing liability payments, if so what and how much (utilities, management fees, condo fees, maintenance, coop fees, etc.)? (03I)

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Herein lies the fundamental tension that I argue is likely causing shelter inflation projections to be under-forecasted.

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All of this is to be reported as of the month prior to the survey’s collection. Given ~ 77% of homes owned in the US were encumbered with some form of debt as of 2022, OER’s driving component, not surprisingly, is related to the proceeds and interest rate attached to service said debt. Home mortgage lending has fallen to more than a 20-year low for both refinancing and new acquisitions, off 70% from the recent high during Covid rates in early 2021, largely due to the fact that 85% of current mortgage holders have locked in fixed-rate debt under a 5% effective interest rate.

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As of August 31, 2023, according to Freddie Mac, the current 30-Yr FRM stands at 7.18%, the 15-Yr FRM at 6.55%. Further, according to a Morgan Stanley study published in August 2023, US homes would need to either decrease 41% or see rates fall by 430 BPs in order to return to pre-pandemic affordability. But unlike the GFC, the majority of US homeowners now sit in below-market debt and do not feel the same pressure to sell given the limited exposure to variable / adjustable-rate mortgages. And, looking at pricing during the GFC, the market correction from the local peak in Q1-2007 to the trough in Q1-2009 implied only a ~ 25% reduction in the average sales prices of homes throughout the US. Additionally, it does not appear that timing will induce a market-wide selling event due to a credit crunch. Though an imperfect benchmark, an NAIC capital markets report detailing the US insurers' investments in RMBS (both agency and private label) demonstrates that, as of 2022, 93% of RMBS held by US insurers will mature in more than 10 years [5].

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In addition to interest rates, insurance premiums and real estate taxes are also putting pressure on home ownership. After a year of climate disaster-related losses, home insurance premiums are up 20% in 2023, after rising ~ 7% in 2022; additionally, increases in home prices experienced over the last several years are slowly being incorporated into re-assessments across the country.

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As Powell mentioned, housing starts and sales volume, along with mortgage origination volume, have fallen – starts are 13.0% below July 2022 numbers (but up month on month), and sales volume of existing homes is down 16.6% YoY (and far below the 10-year average). Sales volume of new homes rose to the highest mark since February 2022, though representing 714K annualized sales vs. annualized 4.070M sales for existing homes (net, sales volume has decreased YoY). What we have not seen by any measure is any substantial downward pricing in the housing market, at least not anywhere close to a level needed to reset affordability; for example, the National Association of Realtors pegs Median housing prices at $406.7K, up 1.6% YoY; Zillow is forecasting a 6.5% rise across the county between now and July 2024.

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Given that fewer Americans are moving into new homes and signing new mortgages, the read on the current OER, applying the logic of the CE survey, has (a) not moved substantially and (b) is necessarily lagging in incorporating the new cost of living, given only one-sixth of housing units are refreshed from census surveys each year. Unlike the rental market, where pricing is more elastic and rent costs re-price ~ completely about every year, the homeownership market has only turned over about ~ 5 million homes a year on average over the last decade, representing less than 5% of the total US housing stock.

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Pricing Elasticity & Future Inflation Forecasts

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Now, how exactly is future shelter inflation forecasted? For the rental component, as aforementioned, asking rents are the primary bellwether, as persistent shifts in asking rent are gradually incorporated into the total stock of rents as households move and leases are renewed. The contractual pricing elasticity of the rental market makes this index easier to predict in real-time.

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The mark-to-market for ownership, however, is a trickier item to forecast, largely because of (a) its inelastic pricing, (b) that volume, as a percent of total stock, has fallen significantly, and (c) that sales occur less frequently, as a percent of all homes (<5%), than leases signed, as a percentage of all leases outstanding (likely near the majority of all leases outstanding expiring every year). If there is no pricing correction – which we have yet to see and is unclear we will see anytime in the next several years given data collected above – and housing prices remain elevated, near an all-time high, then the implied mark-to-market of ownership is likely the largest we’ve seen in recent history, if we were to apply the logic of reversion to pre-pandemic affordability. Pair this with a structural undersupply of housing, historical asset appreciation as a proxy for general growth, and the inability to finance construction given heightened labor and financing costs, the prospects for controlling home prices, and, further, long-term inflation, seem unlikely in a high interest rate environment.

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It seems if we want to get shelter back down to target in the long term, there needs to be a breaking point. Either value declines per housing unit (secular repricing), interest rates come in (return to a dovish policy), both measures occur by varying rates, or the government finds a way to subsidize the building of new and the renovation of obsolete housing stock. To further obfuscate the issue, if the cost of ownership persists to remain out of reach, rental costs should also inflate, given multifamily developers will remain unable to build to attractive yields relative to their cost of capital and the lack of liquidity in the banking system, and, as a result, supply will remain suffocated, putting further pressure on pricing.

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The lack of transaction volume has obscured true price discovery for the housing market, which is today in better shape than it was during the GFC rate hike cycle and isn’t showing signs of cratering. In this environment, existing and new households will continue to rent as they are sidelined from home ownership due to affordability. There is no easy way out of the current pricing predicament that the Fed can orchestrate, besides its best efforts over the last cycle of rate hikes. That is, unless the recent interest rate cycle forces a major spike in unemployment, which has historically been highly correlated with mortgage defaults; structural undersupply of qualified labor, I’d argue, may keep us near all-time lows for the near future (with 50% office utilization and near job-seeking vs. job-opening parity, I don’t see the labor dynamic reverting drastically any time soon).

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What needs to be addressed, on a federal, state, and municipal level, is the fundamental housing shortage we face. And, with budgets across each of those levels at significant fiscal deficits, it doesn’t appear that public dollars can efficiently solve this problem. Facing the headwinds identified, the fastest means of easing the issue will come in incentivizing private development of housing, something, in a supply-constrained and high-rate environment, can only be achieved by pulling the final lever in easing taxation, which remains an unaddressed issue in the most populous and non-developer friendly US states. We are currently an estimated 1.5 million housing units below demand – if we can’t create incentives for additional development and rates remain higher for longer, supply dynamics will likely prop up shelter inflation, either in a slow transition to high OER indices or in a graduated return to rent growth on a seasonally adjusted basis.

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Appendix

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To be thorough, there are two survey questions that do canvas for forward rental projections. Though most of the questions refer to homeowners using a property for non-primary purposes, whether holding it as a rental or timeshare ownership, there are two questions that incorporate owner’s perception of mark-to-market cost of ownership.

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Hypothetical Costs (03I):

-??????? If someone were to rent this home today, how much do you think it would rent for (excl. of furnishing and utilities)?

-??????? How much do you think this property would sell for on today’s market?

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Though un-substantiated, I would assume that the former question would be difficult to gauge, given limited forethought into what the equivalent rent would look like for homeowners in locations in which there aren’t many rental options. Additionally, it is unclear how exactly the latter question is integrated into OER figures. Per the Bureau of Labor Statistics’ definition of the OER approach, it does not appear that the answer to the former question is weighted as much as the actual, nominal costs that the survey reports:

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“The OER approach to price change for owner-occupied housing is designed to measure the change in the rental value of the owner-occupied housing unit; the investment portion is excluded. In essence, OER measures the change in the amount a homeowner would pay in rent or earn from renting his or her home in a competitive market. It is a measure of the change in the price of the shelter service provided to the homeowner by the owner-occupied housing unit.”

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[1] Most of this was paraphrased/sourced from a post last week published by Jay Parsons’ posting

[2] 65.9% of Americans live in owner-occupied homes as of June 2023

[3] CBSA’s consist of the county or counties or equivalent entities associated at least one “core” (urbanized area or urban cluster) of at least 10,000 population, plus adjacent counties having a high degree of social and economic integration. There are 939 as of 2022.

[4] Metropolitan CBSAs are areas that have an urban “core” of 50,000 or more people, plus the adjacent counties that have a high degree of social and economic integration with the core as measured by commuting ties. Micropolitan CBSAs are similar to metropolitan CBSAs but they have an urban core of 10,000 to 50,000 people.

[5] If anyone has a better proxy here for weighted average duration, please let me know.