Does a tighter spread between occupancy and stabilized occupancy indicate higher demand? I'm trying to understand how to think about real estate markets and how to identify markets where there might be strong demand for additional housing (I'm looking at senior housing in particular) and am new to real estate, so I had a few questions about metrics.

In particular, two that seem important are occupancy rates (measured as beds filled/available beds in all facilities) and stabilized occupancy rates (measured as beds filled/available beds for facilities that are at least 2 years old.

Obviously, if there's lots of new construction, we'd expect occupancy to fall as a lot of new beds are coming online and it takes time to fill them.

What I'm wondering, however, is if there is significance in comparing the spread between occupancy and stabilized occupancy. For example, if we had a fake and overly simplistic example of two markets that looked like this:

Market 1, Occupancy Rate of 88%, Stabilized Occupancy Rate of 90%, Construction vs. Inventory of 5% 
Market 2, Occupancy Rate of 50%, Stabilized Occupancy Rate of 90%, Construction vs. Inventory of 7%


then the conclusion I would draw is there is likely much more latent demand in Market 1 than Market 2 because at at the same new construction levels, the spread is so much lower in Market 1 (2%) than Market 2 (40%), indicating that properties are filling up much faster in Market 1.

Is that the right way to think about this metric? If so, how should I think about adjusting or scaling this kind of metric for the amount of new construction?
Does a tighter spread between occupancy and stabilized occupancy
  indicate higher demand?


Not necessarily. Demand is not the only factor that determines occupancy rates. A tight spread by itself only indicates market steadiness (that is, uniformity over time).

Using your example, Market 2 could have experienced a significant increase of demand in the past two years and yet present a lower occupancy rate if cost at new facilities outweighs the demand increase. The new bedrooms are available but only few consumers can afford them.

Government intervention and/or expectations about the future might also discourage suppliers from effectively releasing to the market much of the new facilities. This certainly amounts to a reduction of supply (and a higher Occupancy Rate, accordingly), but metrics might fail to capture that reduction in a market that would otherwise reflect the same demand and Occupancy Rate as Market 1.