Comparable Market Rent and Setting Appropriate Rent for Multifamily Development
Part 1 - Determining an Appropriate
Part 2 of 4
The 100% Database
The next step is a field survey of all conventional apartment communities within the
Effective Market Area (EMA), not just selected comparables. Our research shows that the largest single component
of support for an apartment project is tenants already residing in other conventional
apartments within the EMA. Typically, an apartment project can expect 45% to 50% of its
tenants from other conventional apartments within the EMA. Add support from within the EMA
from new household formation, home ownership, or other rental properties, and the total
EMA support increases to 60% to 70%, depending on the demographics of the EMA.
The EMA is supportive, rather than competitive. A competitive EMA, including only
projects with a similar price or amenity level to the proposed project, only examines a
portion of the market at one pricing level.
The 100% Database allows us to measure support and the depth of the market
levels. Our field surveys identify all conventional apartment developments within the EMA. Each project is surveyed to determine not only rents and vacancies, but also amenity
level and curbside appeal. The 100% Database allows analysis of the existing market
conditions experienced by those tenants most likely to move into the proposed project,
instead of only comparable properties.
The Regression Analysis
Once the 100% field survey is complete, it is not enough simply to determine medians
for each unit type and call this median comparable market rent. Median rent
may not reflect rent movement at existing properties. For an article for Apartment
Resources several years ago, we took an existing metropolitan market area field survey of
two-bedroom rents and added 500 upper-end units to the base without changing the rents of
other existing units. The median rent increased $23 despite the fact that no existing
units increased their rents. Adding only 300 units increased the median rent by $18.
Median rent can be disproportionately influenced by additions to the high or low end of
the market, and therefore does not reflect what tenants are actually paying for units of a
moderate amenity level. Therefore, we use regression analysis instead of medians, because
of its ability to determine market rent at any amenity level.
Each 100% Database field survey applies a point value for each projects unit
amenities, project amenities, and curbside appeal. These three factors are totaled to
determine each projects Comparability Rating. Next, all rents are converted to net
rents Net rent assumes that water, sewer and trash removal services are paid by the owner
and that additional utilities (heat, cable television, etc.) are paid by the renter.
Making these adjustments allow us to compare all rents on the same scale.
We then create a scatter graph by plotting net rent by Comparability Rating for each
project. Next, a regression line (weighted by the total number of units in each project)
is established showing average comparable market rent (net) for a project at any
Comparability Rating level. We then establish a comparable market rent from this regression
line. Projects below the regression line represent a value in the market at their
Regression analysis allows us to determine market rent at any amenity level. This is
particularly critical because each market sets its own standards based on what renters
will pay or what landlords have historically charged. Not every market will reward the
same apartment development with the same rents. Regression analysis allows us to identify
these differences in standards before development takes place.
Part 3 - The Regression Analysis in Action