Why is vintage ‘unknown’ for many nonresidential buildings?

Summary: Many buildings lack known construction years in NREL’s Commercial Building Inventories data set because it relies heavily on CoStar, which underrepresents public-sector and low-turnover properties. Missing vintage data is more common in smaller jurisdictions and among public or institutional buildings. While building age is a familiar metric, it's not a strong predictor of energy use; factors like building type, size, and system efficiency are more influential. Including vintage data allows users to explore its relevance, but caution is advised in areas with high rates of unknowns.

More: Vintage appears as unknown when no construction year data is blank in the data source used by the Cost-Effectiveness Explorer team–a national commercial building inventory developed by the National Renewable Energy Laboratory (NREL). That inventory draws heavily from CoStar, a private real estate database.

Some jurisdictions have almost complete coverage, while others may have a substantial share of buildings without vintage information—this varies significantly across California cities and counties. Overall 59% of CA jurisdictions have vintage data for at least 4 out of 5 buildings, and 88% have vintage data for at least 3 out of 5. It's important to understand that missing year data is not random. It is more common in smaller jurisdictions (with less commercial building area) as illustrated below.

Missing vintage value are also more likely for certain building type, especially public or institutional building types (like schools and hospitals).

One of the main reasons for missing vintage data is that CoStar’s coverage is biased toward private-sector buildings that are bought, sold, or leased in the commercial market. As a result properties that don’t tend to change hands, like public buildings, or properties in markets with low transaction volumes, are often underrepresented. While this dataset is the most comprehensive of its kind, the gaps in vintage data are a known limitation. We encourage users to interpret vintage characteristics appropriately with this in mind. For jurisdictions with an especially high proportion of unknowns, it may be best to ignore the vintage data here.

It's also worth noting that after controlling for building size, type and other factors building age is not a strong predictor of energy consumption in commercial buildings. For may this is counter intuitive. But in fact research has shown that energy performance is more directly influenced by building type, size, operational characteristics, and the efficiency of installed systems. (1,2,3)