Erdmann Housing Tracker · Housing & Cities
TIER 4 Wed, 22 Oct 2025 23:14:19 +0000
I have been outlining a standardized package I will be making available for dozens of metropolitan areas that is based on estimating a lot premium, which applies uniformly across all homes in each housing market as a result of systemic underbuilding in recent decades. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ | | ---|---|--- | | | Forwarded this email? Subscribe here for more --- --- # Metro Area Housing Analysis Packages: Part 5 | | Kevin Erdmann --- | Oct 22 --- | --- --- | | | --- | | --- | | --- | | --- | | READ IN APP --- I have been outlining a standardized package I will be making available for dozens of metropolitan areas that is based on estimating a lot premium, which applies uniformly across all homes in each housing market as a result of systemic underbuilding in recent decades. This novel data point unleashes some basic quantitative insights that can be used to inform investment decisions across locations in housing markets. Upgrade to paid The package provides: Part 1: * An estimate of the **lot premium** embedded in home prices in most markets today, which will correct in most markets as more homes are constructed and rents moderate. * An estimate of the **neutral rate of construction** required to counter excess rent inflation in each housing market. Part 2: * Using the estimate of the lot premium in each market, we can estimate the portion of home prices that are temporary aberrations vs. permanent. * Permanent factors: Population growth, income growth, past general inflation * Temporary factors: Cyclical fluctuations (fast), lot premiums (slow) Part 3: * The simple process of isolating the lot premium caused by underbuilding can help to highlight which homes within a market are most affected by the premium and most at risk of changing lot values. * Comparing homes within markets, exposure to construction costs, locational amenities, and the lot premium can be matched to investor or builder risk preferences. * Comparing homes across markets, and comparing the expected lot premium with market land prices, can identify markets with better risk/reward opportunities. Part 4: * Trends in the lot premium at different rates of local construction activity can be used to estimate the scale of homebuilding associated with stable home prices. * This can help to nudge forecasts of rents, prices, and new construction in each market. The lot premium associated with the large post-2008 shock to new housing supply is a novel, temporary, and significant factor in future housing trends. This has not previously been a relevant analytical input. It is a necessary component to optimizing capital allocation decisions now. #### Rent Excess rent fetches a higher price than rent in an amply supplied market. This is obvious from a cursory review of price/rent ratios across metro areas. As I have written about frequently, this is one of the key points of confusion in the conventional economic approach to housing analysis. Rising price/rent ratios are treated, axiomatically, as evidence of cyclically unsustainable price inflation. There are cyclical price fluctuations which can be associated with rising price/rent ratios. But, over the long term, those fluctuations are mean reverting. The rise in price/rent ratios across the American housing market that have endured or returned over a period of decades are not cyclical fluctuations. Permanent excess rents lead to higher price/rent ratios. In very basic terms, arithmetically, when there is excess rent inflation, the excess rent is for the lot. The home and the cost of maintaining the home hasn't changed. The extra rent comes cheaper than the original rent did, so it is worth more to the owner. This creates a quantitative margin on which to analyze a market. Where inadequate supply leads to lot premiums, prices will fluctuate much more than rents do. In the sample city I have been referencing, I estimate the lot premium to be 44% of the median home value, but that corresponds to rent that is only 20% of the rent on the median house. Figure 1 here shows the nominal rent reported for this market by Zillow. And, the figure includes my estimates of how much of that rent reflected supply conditions over time. | | ---|---|--- Figure 1 As with the lot premium, I treat the rent premium as a constant across the market. When analyzing the market value of a given home in this market, the investment is a bundle of a traditional real estate investment together with speculation on land value. In this case, the home has $1,642 rental value and the speculative land value has rental value of $420. The net rental value of $1,642 should be valued with standard analysis - required ROI, expectations of local population and income growth, cost of capital, etc. The lot rent premium of $420 is a temporary cash flow that will dissipate. If the market might continue to accumulate rising lot premiums, perhaps it will provide satisfying returns. If lot premiums are declining, it will likely provide lower net present value than investment in real estate normally requires. There are several possibilities this creates. An investor expecting lot premiums to rise for, say, an additional 5 years, might invest in this rental unit intending to earn rental income until selling at the peak of the market. An investor might decide that the rental yield is high enough to make up for potential losses in the lot premium, so that the unit could be a long-term investment. Underwriting of potential investments will always involve comparison of income expectations and current market prices. This model provides an additional margin on which to consider value vs. price. In the sample market, I have assigned a yield on the lot premium of 3.2%. The yield on land is not likely to be so fixed. This is a simplification. However, this simplification is not as important as it might seem. The yield on the lot premium is definitely significantly lower than the yield on structures is. And, most importantly, in 2015 and 2016, there was no significant premium, but now the lot premium accounts for 44% of the median home value in this market. Mathematically, the change in composition is much more important than small changes in the rent yield over time on the lot premium. In Figure 2, I have disaggregated the bundle of the investment between the lot premium and the yield on the net portion of the investment. The rent yield on every home is a combination of the yield on the structures and the yield on the land. When there isn't a lot premium, the yield on the land reflects locational value and local amenities. The net yield includes the yield on the home as well as the yield on the lot's amenities. In normal markets, more expensive homes tend to have higher price/rent ratios, in part because they tend to be on lots with more locational and amenity value. So, comparing two homes in a given market, even if they sell at similar prices, a home with more amenity value will tend to sell for a higher price/rent ratio than homes on less valuable lots. The red line in Figure 2 is the market average, but there can be a lot of variation. | | ---|---|--- Figure 2 Figure 3 compares the monthly rent to the price/rent ratio for the typical home in 35 ZIP codes in this market in January 2016, when there wasn't a significant lot premium in this market. It isn't a strong relationship, but there is positive correlation between rent and price/rent ratios. Poor families don't have the means to pay for locational amenities, so they tend to be limited to older neighborhoods where crime might be relatively elevated, schools might be worse, commuting might be longer, etc. The dots in the lower left quadrant of Figure 3 tend to be modest homes in poor locations or locations with disamenities. Disamenities mean that the location has minimal or even negative value. That is why there are neighborhoods with empty lots near some city centers. If the area has issues with crime, etc., it may not be feasible to maintain or build homes even if the lots are free. As it relates to this model and lot premiums, that means that the value of those homes has been significantly affected by the uniform lot premium. ZIP codes where gross rental yields were around 15% in 2016 (because they were bundled with disamenities) now have rental yields under 10% because the regional lot premium has inflated the value of the lots they sit on. The premium is sizeable compared to modest homes on lots with little value. The ZIP codes with moderate rents but very high price/rent ratios are very well located and populated with dense condo and apartment buildings. The ZIP codes with high rents and moderate price/rent ratios are relatively nice homes in the outer suburbs. | | ---|---|--- Figure 3 In Figure 4, you can see the relative effect of the lot premium on home values over time. The price/rent ratio in 2016 largely reflected locational amenities. At the left, there were a handful of locations with disamenities. Most of the region had price/rent ratios in the 12x-17x range because families make many tradeoffs across the landscape of a region between location and structure value. And, a handful of locations had high price/rent ratios because they were locations were households with higher incomes chose to spend those incomes on location relative to structure value. The rise of $150,000 lot premiums lowered yields for most of the region in proportion to their starting price/rent ratios. But, in locations where lot value was already half or more of the value of the home (and, thus, associated with higher price/rent ratios), and where the homes tended to be more valuable to begin with, adding $150,000 of lot value had negligible effect on gross rental yields. | | ---|---|--- Figure 4 We can construct Figure 4 without using lot premiums. It just reflects rents and prices over time. No special model or understanding of the undersupplied market is necessary to make Figure 4. But, knowing that Figure 4 will tell you something important requires understanding the undersupplied market and the model of how it has affected prices. And, understanding this factor means that you can understand where profits have come from and where profits will continue to come from. One conclusion suggested by Figure 4 is that well-located infill residences likely have the least valuation risk in this market. Projects with lower yields may be systematically less risky because of this. Of course, the problem is that one reason this city has a lot premium is that it obstructs those developments. This adds value to internal, local underwriting work. For instance, looking back at Figure 2, the typical gross yield on units in this market has declined from 8.1% in 2015 to 6.9% today. That looks like a market that is overpriced. But, the estimated yield on the home and lot amenities has increased from 7.5% to 9.6% and the lower total yield is because it is bundled with the lot premium that fetches a lower yield. It could be that homes are trading at good valuations in this market. You can't avoid exposure to the lot premium, but you can lower its relative importance by focusing on investments with high amenity or structure value. And, it is possible that the high yield on houses reflects a market with risk averse sentiment where land values may not be efficient. If land can be purchased that doesn't fully reflect the lot premium imbedded in existing home prices, then risk can be further avoided. Each market has different trends in these yields. Of course, there is model risk here. I begin with a relatively reliable measured lot premium, and each step along the way of estimating capacity for new construction, rent inflation, and yields involves estimates and assumptions. Yet, using this framework can add a margin of analysis that helps select investments among and within each market. The estimated yields in Figure 2 suggest that investors in this sample market are already demanding higher yields on purchases of existing homes which counters the lot premium risk. If that is the case, it could reflect efficiency in markets. There could also be weak for efficiency. There could be markets where the lot premium is still inflating, and land prices reflect reasonable yields on current rents but not the predictable rise in rents that will accumulate until construction recovers more. Or, on the other side of the coin, where the lot premium is now deflating and prices based on current conditions will prove to have been inflated. On the other hand, where land markets are not deep, there could be inefficiencies in land markets where lot premiums have just recently started to inflate but where a lack of development activity has created a lag in the discovery of those premiums. It is a simple central observation - lot premiums from inadequate supply can be measured. Because current housing markets are historically odd, it has potential applications on many margins. Upgrade to paid You're currently a free subscriber to Erdmann Housing Tracker. For the full experience, upgrade your subscription. 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