Erdmann Housing Tracker · Housing & Cities
TIER 4 Thu, 23 Oct 2025 16:56:48 +0000
One last post about the information in these housing market packages. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ | | ---|---|--- | | | Forwarded this email? Subscribe here for more --- --- # Metro Area Housing Analysis Packages: Part 6 | | Kevin Erdmann --- | Oct 23 --- | --- --- | | | --- | | --- | | --- | | --- | | READ IN APP --- One last post about the information in these housing market packages. Upgrade to paid First, I want to reiterate, these packages contain one simple piece of motivating data - the lot premium in each housing market related to the supply shortage. It is simple, but it is a very important piece of data. And it is data that your competitors and trading counterparties likely do not understand. This product is naive on cyclical or regional demand trends. It is naive about local underwriting details. It is a macroeconomic variable that for decades has not been relevant or significant, but it is now. Adding it to your other forms of analysis and underwriting can create a competitive advantage and steer capital allocation decisions in more optimal directions. I have been pushing deeper with each post into the ways the model can be used. But, on the surface, it can be useful as a simple signal of relative metropolitan area supply conditions. Figure 1 compares the lot premium in 5 different markets. The orange line is Los Angeles. I can track the lot premium in Los Angeles, New York City, San Francisco/San Jose, and Boston, but my model isn't very useful there. The small amount of construction in those markets is idiosyncratic in nature. Trends in rents and prices will be driven by political policy changes and perennial outmigration. I suspect that Los Angeles is tickling the upper limit of lot premium potential. The lot premium is created by resistance to regional displacement. Essentially, at such high valuations, the marginal demand for being poor as a substitute for being regionally displaced becomes highly elastic. Marginal out-migration is now high enough to keep the lot premium from rising more. Los Angeles is shrinking rather than becoming more expensive. My model can't foretell the outcomes of the political changes that might change those trends. | | ---|---|--- Figure 1 The black line in Figure 1 is the lot premium in the market I have been citing in this series of posts. I think it is actually at the bottom of a cycle on a rising trend under current conditions, and that as the cycle recovers, lot premiums might continue to rise. I have included 3 other markets in Figure 1. Directional patterns were somewhat parallel in the 2000s and 2010s because uniform credit conditions were driving the market. But, as we escape the dislocations caused by the 2008 mortgage crackdown, markets are starting to carve out idiosyncratic patterns. Some have higher demand, pushing up lot premiums more quickly. Some have lower demand. Some have reached a rate of new construction that can reverse the lot premium sooner while others are later. There is no certainty here, but if I was interested in being exposed to real estate equity in the yellow market or the blue market, I would want to take those different trends into account. I would want to know that a land position in the black market has more downside risk than a land position in the gray market. But, there are ways to use this information to dig a little deeper too. In the following figures, I have taken the analysis one step further than I did in the previous post. There, I disaggregated home values into the lot premium and the net price of the property without the lot premium. Here, using price/rent ratios, I will further separate home values into (1) structure, (2) location amenities, and (3) lot premium. These values are corrected for inflation and for compositional drift in the housing stock. Unfortunately, Zillow coverage of rental values isn't always comprehensive enough to review these measures at the ZIP code level, but it is possible in all major metro areas to view it at the metro area level. Figure 2 shows the values of those 3 components using the metro area values of prices and rents reported by Zillow, which is basically a median value. There is little locational value for the median home in most American cities. The median home in this market is a $211,000 home on a lot with marginal locational value and a $153,000 lot premium. Think of the locational value as the price families are willing to pay to have access to certain public services and benefits. Lot premiums are the price families are willing to pay to avoid trading down or moving away. | | ---|---|--- Figure 2 Home prices are skewed, and there are some areas of every city with locational value, whether it is bustling neighborhoods in the urban core or gated neighborhoods at the country club, but they tend to be above-median homes. Figure 3 shows the average of these components among the ZIP codes with Zillow price and rent data. It appears that skewed valuations are largely the result of locational value. The mean home value is higher than the median, and it is largely due to higher average locational value. | | ---|---|--- Figure 3 In Figures 2 and 3, the structure value suggests that the model is sound. The value of structures should be stable over time. The cyclical ups and downs of this market are visible in the lot locational amenity value. Lot values increased a bit in 2022 when there was a cyclical upswing in this market, and locational values have declined since then. That could also be a sign of arbitrage opportunities. In the previous post, I suggested ways that this data could highly both efficient and inefficient market dynamics. In this market, it could be the case that the elevated lot premiums create buyer stress. One way that buyers deal with elevated costs is by downgrading. That has happened in new homes with declining average square footage over the last decade. It could also be the case that households are less willing to pay for locational amenities. _If_ that is the case, it might suggest that neighborhoods with high locational value might experience some price and rent recovery on amenity value that will counter declining lot premiums. I don't have enough confidence to claim that as a certainty, but it is the sort of market shift that might be in play which this sort of analysis can help to consider. Figure 4 shows a ZIP code with low rents and little locational value. There will likely not be much construction activity in this ZIP code unless it is in an area with rising local socioeconomic trends. Property owners of the existing homes in this ZIP code will likely take capital losses (in real terms) as the lot premium normalizes. Homes selling for more than $300,000 will sell for $165,000, adjusted for inflation, once supply recovers. Of course, though, that will take years or decades. | | ---|---|--- Figure 4 Figure 5 shows a more expensive ZIP code with large homes and lots but with little locational value. Homes worth $300,000 are sitting on lots inflated by $153,000. | | ---|---|--- Figure 5 Figure 6 shows an expensive ZIP code that is located in a highly valued central location so that properties selling for $615,000 are $234,000 homes sitting on lots with $228,000 locational value and $153,000 lot premiums. | | ---|---|--- Figure 6 Properties in these different parts of the market will have different sensitivities to changing construction costs, cyclical fluctuations, and recovering supply. This way of viewing those sensitivities can inform decisions across and within markets and over time. Upgrade to paid You're currently a free subscriber to Erdmann Housing Tracker. For the full experience, upgrade your subscription. Upgrade to paid --- | | | Like --- | | Comment --- | | Restack --- (C) 2025 Kevin Erdmann 548 Market Street PMB 72296, San Francisco, CA 94104 Unsubscribe