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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 Rating 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 Rating. 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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