Comparable Market Rent and Setting Appropriate Rent for Multifamily Development
Part 1 - Determining an Appropriate
Market Area
Part 2 - Regression Analysis and the 100% Database Field
Survey
Part 3 - The Regression Analysis in Action
Part 4 of 4
Making Proper Adjustments
Often, the regression analysis cannot tell the full story. Therefore, to go from a
regression-driven comparable market rent to a recommended rent for the subject property,
we refine the process of determining appropriate rent by using additional analysis tools.
That is why we use step-up/step-down support analysis in conjunction with regression
analysis to set appropriate rents for a proposed development. Our research indicates that
there is a limit to rent increases that renters are typically willing to endure. If the
new unit represents a value, Tax Credit renters are typically willing to increase their
rents up to $60 and renters at market-rate properties are willing to step up their rents
up to $150 (depending on the Comparability Index and the market). Renters who are paying
rents below the proposed rent, yet within step-up range are considered the step-up support
base.
Since most support for a rental property typically consists of renters already within
the EMA, setting rents at levels with little or no step-up support will slow absorption
(initial and replacement) considerably. We often recommend setting rents below the
comparable market rent in order to maximize the step-up support and increase absorption.
Large properties (200 units or more) also require special adjustment of the
regression-driven comparable market rent. Because of the high traffic volume required to
replace turnover, these projects must be perceived as offering a greater value within the
market than smaller projects. As a result, large projects must offer greater discounts
from the regression-driven comparable market rent.
A recent analysis we conducted of the Columbus metro area illustrates this
dramatically. Two-bedroom units in projects with 200 to 299 units achieved an average of
$21.64 less than projects with 100 to 199 units at the same Comparability Index. Projects
with 300 or more units achieved $52.13 less than those with 100 to 199 units.
Selected Comparables vs. The Danter Company Methodology
The following table illustrates some of the differences between The Danter Company Methodology and Selected Comparables Methodology.
| Danter Company Methodology |
Selected Comparables |
| Developed by The Danter Company Specifically for market feasibility study. |
Really an appraisal methodology. Well-suited for determining value, but not for
determining comparable market rent or support potential |
| Identifies market status at all pricing levels, allowing analysis of potential support
and competition. |
Identifies market conditions at only one market level, so it only analyzes potential
competition. |
| Analyses limited to market area directly affecting subject site. |
Often uses comparables outside of market area which may draw from a different tenant
base. This can skew analysis. |
| Not subject to sampling errors given 100% database. |
Poor selection of comparables can lead to sampling errors. Properties performing
better or worse than the market can skew the results. |
| Examines project in context of the entire market. |
Often compares new product with modern design to older product that is functionally
obsolete. |
Special Tax Credit Issues
Accurate comparable market rent is particularly critical for Low Income Housing Tax
Credit (LIHTC or Tax Credit) developments because Tax Credit rents are not determined
based on prevailing market conditions. Rather, the Tax Credit program establishes maximum
rents based on the area’s median household income as determined by HUD. In addition,
Tax Credit rents can be adjusted annually based on changes in the area’s median
household income.
Therefore, once a project is operational there may be little or no connection between
allowable rents and comparable market rent. A project can raise rents every year if the
area median household income increases, regardless of whether an increase is
market-justified. In most markets, median income increases faster than rents. If income
increases 4% per year and rent increases only 2%, then each year the project loses 2%
against competitive value by taking the maximum rent increase. It only takes a couple of
years of rent increases that outpace the market before a project is in trouble, becoming
less of a value in the market and suffering from increased turnover and vacancies.
Remaining a value is critical for Tax Credit projects because tenant income limitations
narrow the prospective tenant base. In addition, our research indicates that “cheaper
prices/rents” is the most important reason for moving given by survey respondents who
are income-qualified for Tax Credit units. Because Tax Credit tenants are extremely
price-driven , they are more likely to move to cheaper lodgings, even to a project of
lesser quality when their rents cease to be a value. The combination of a limited tenant
base and the ability of potential tenants to find quality lodgings in the market at a
cheaper rent could be devastating to a poorly managed Tax Credit project. Therefore,
initial pricing and future rent increases for Tax Credit units should only be entered into
after thorough research into the state of the market.
Some Conclusions
Maximizing a property’s performance begins with solid market-based information. A
regression analysis based on a full 100% database field survey, especially in conjunction
with step-up support analysis, provides the best opportunity to set rents that will
maximize performance and provide the best return on investment.
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