The nearest recent sale is a neat three-bedroom house. The property being studied used to be a school. It has a generous plot, a room that still looks like a classroom, and a heating system that needs its own explanation. This is an invented address, but the analyst's problem is ordinary: a database can return a dozen nearby sales without returning one close comparison.
There is a buyer for this property somewhere. Perhaps several. Their willingness to pay and their ability to close by a particular date are not printed in a completed-sales record. The owner wants to know what usable cash a sale might produce before winter. The analyst opens a worksheet of comparable sales and pauses at the first empty row. An automated valuation offers a number to the nearest dollar. The precision belongs to the display, not necessarily to the evidence.
How far away is a comparable?
The analyst has choices, none harmless. Use the house across the road because it is close. Use a converted building across the county because its layout and buyer appeal are closer. Use a sale from three years ago and adjust for a market that has changed. Or admit that each observation illuminates only part of the question. Distance on a map is one kind of similarity. Condition, legal use, financing, maintenance and the likely buyer pool can matter more.
Fannie Mae's comparable-sales guidance recognizes this difficulty in appraisal work. When genuinely similar sales are scarce, appraisers may need to use older, farther or less similar transactions, provided they explain their choices and differences. This is guidance for US mortgage appraisals, not a recipe for a property-liquidity model. It makes one principle plain: selecting imperfect evidence is a judgment that should be visible, not an invisible search-radius setting.
Suppose the nearby three-bedroom home sold within a month. It gives a signal about local demand and perhaps about the seller's timing. It does not show how many buyers can use the old school building or finance its repairs. The converted property farther away tells a different story about buyer appetite for unusual space, but it lives in another local market. A past sale from the same street may be closer in both respects, yet its contract was made under old borrowing costs. If a model silently blends the three into one smooth answer, the result can look more certain than any of its ingredients.
The local price index is useful, too, within its limits. FHFA research found that more localized house-price indexes can improve fit where appreciation varies among submarkets and there are enough transactions to construct them. That last condition matters here. The thinner the local evidence, the more tempting it is to use a very broad index. A broad index can provide context while missing what makes this address difficult to compare.
There is another pile of evidence on the desk: listings that did not sell. An asking price is not a transaction price. Still, a similar unusual property that sat on the market for months may say something important about how long a seller could wait. Its failure might reflect an ambitious price, a defect or a private decision to withdraw. Without the full listing history, it should neither be ignored nor treated as a direct estimate of this home's fate.