SNEAK PREVIEW: LIHTC Property Operating Expense Analysis

8 min read

For the past 15 years, members of CohnReznick’s Tax Credit Investment Services group have worked on housing credit performance studies in various capacities, and in that period, we have witnessed the pool of properties surveyed balloon from 5,000 to more than 20,000. (The Low-Income Housing Tax Credit Program at Year 30: Recent Investment Performance 2013-2014)

Our close ties and frequent contact with the data providers have allowed us to continually add new data points for analysis. Increasingly, operating expenses are a concern among our clients. How do certain categories trend from year to year? What are the most volatile expense categories? What are reasonable repair and maintenance expenses for an acquisition rehab? In an attempt to answer these questions and others, our most recent data request included a survey of property level operating expense data, and we were pleased to have received viable operating expense data for more than 15,000 stabilized properties.

We know that our data providers actively mine their portfolios for operating expense data to better underwrite and evaluate future property investments. Upon seeing the aggregated breadth of data, we were impressed by the potential value of the data before us. The forthcoming CohnReznick report, A Low-Income Housing Tax Credit Property Operating Expense Analysis, attempts to scratch the surface of what is possible to glean from this wealth of information, and this article provides an initial overview of our findings.

Data was requested in the custom format that each individual provider tracks operating expenses in their portfolios. Because of the myriad methods of categorizing expenses, segregating charts of account into comparable categories was a painstaking exercise. Once complete, the main categories on which we focused the analysis were: administrative, insurance, property management fee, property tax, repair & maintenance, salary & benefits, and utilities.

Per unit per anum
Based on the data provided, median gross per unit per annum operating expenses for 2014 (not including replacement reserves) were $5,336.

From a national median perspective, salary, repair & maintenance, and utilities comprised the majority of gross expenses. While nationally aggregated data serve as a starting point, we found the most interesting analyses borne out through statewide analysis, and by exploring other variables.

For instance, a large part of the story behind property tax expense cannot be seen at the national level.

Property Tax
The data shows that property tax expenses are significantly impacted by a State’s stance on including the value of housing credits in a property’s valuation and the availability of property tax abatements or exemptions. For instance, Idaho is the only state where there is agreement that the credits should be considered in property valuations; not surprisingly, the Idaho housing credit portfolio ranks among the highest property burden as a percentage of overall gross expenses (15%+). At the other end of the property tax spectrum, California and Washington allow for wide-ranging statutory property tax abatements, and the data show that these states experience the least property tax burden (less than 4%) as a percentage of total gross expenses. The large concentration of California properties in the overall portfolio (11%), and the fact that a significant portion of these properties have some form of property tax abatement (58%), has a significant impact on the overall national median per unit property tax expense.

The data also shows that property tax as a percentage of gross expenses in the initial years (years 0-4) is higher than the national median and higher than the remaining years of the compliance period due to the impact of initial years’ overvaluation. Interviews with asset management professionals confirmed that inaccurate assessments are not an uncommon occurrence as assessors often erroneously overvalue housing credit properties.

With the exception of Vermont ($534), every other state in the Northeast exhibited a median administrative expense that exceeded the $574 national median in 2014. This is not surprising as the Northeast has been known to have a higher cost of living relative to other parts of the country.

When analyzed by property age, administrative expenses were found to be the highest among newer projects. Median administrative expense appears to decline gradually as properties age within the first two decades (from $741 in the first four years to $546 by years 15-19 at an average reduction of $65 per unit every five years). In years 20 through 24, median administrative expense decreased by roughly $150 per unit per annum; and after year 25 (in a limited sample size), an additional $170 per unit decrease. Compliance expense savings is an easily identifiable reason for the steady reduction in administrative expense as projects age. As we know, during the compliance period, projects must comply with all compliance monitoring requirements established by state housing finance agencies, as well as those stipulated by the IRS. While properties are subject to compliance requirements in the extended use period, projects are no longer required to meet IRS compliance monitoring standards and any project non-compliance during the extended use period do not need to be reported to the IRS. While the compliance requirements post-year 15 vary from state to state, the guidelines are generally more lenient in the extended use period.

The primary determinant of property insurance expense is geography – specifically, those areas with higher risk of natural disaster had a correspondingly higher property insurance expense.

Additionally, since insurance expense is based on replacement cost – the labor and materials required to rebuild a property – a property’s location, and the corresponding labor, regulations and the cost of business can skew insurance expense. Additional costly design features being added to qualified allocation plans (“QAP”) also increase development costs, which can increase corresponding insurance expense.

Finally, the insurance expense of older properties accounted for a larger portion of total gross expenses than younger properties. Insurance expense at properties aged 20-25 years was 6.7% of expenses and was 7.9% of expenses at properties aged 26-29 years – which is significantly higher than the 5.9% average for all properties aged 19 years or younger.

Repair & Maintenance
The primary determinant of repair and maintenance expense in the data set was property age. Recently constructed or rehabilitated properties had a median percentage of gross expense of 19.0%, an amount that gradually increased to a median of 26.5% for properties aged 25 to 29 years. On a nominal basis repairs and maintenance costs appear to rise significantly at or around Year 15.

Nominally, and as a percentage of gross expenses, repairs and maintenance costs are inversely related to unit counts. As unit counts increase, repairs and maintenance generally decreases, reflecting economies of scale at larger properties.

While age and location were the prime drivers of expense variability, as noted, additional factors contributed to certain operating expense category’s results.

Property Management Fee
Given that we did not have access to each property’s unit mix, rent restrictions, and rent levels the primary determinant of property management fee expense is unit count. As a property’s unit count increases, its effective gross income increases. Because property management fees are largely a function of effective gross income, it follows that nominal property management fees were positively correlated with the unit count of a property. As a percentage of gross expenses, however, property management fees increase as unit count decreases.

This appears to be a result of diseconomies of scale in managing small properties. At the property management company level, management costs do not vary with unit counts. As such, it stands to reason that higher fees are being negotiated on properties with smaller unit counts.

While the actual staffing needs may vary from project to project depending on a multitude of factors, generally, the larger a property, the more staff that is required. This indicates that larger projects may not always be able to benefit from “economies of scale” when it comes to salary expense.

On a national median basis, projects with 25 units or less incurred the least amount of salary expense (at $866 per unit) in 2014 while projects with more than 300 units reported the highest amount of salary expense (at $1,304 per unit) in the same year. The general trend came as somewhat of a surprise to us, which suggests that per unit salary expense tends to increase as unit count increases. We suspect that projects with less than 25 units may be able to share management and maintenance personnel with nearby projects to an extent that the overall staffing level is equivalent to less than a full-time employee. Additionally, it may not be cost effective for a small project to employ a full-time manager and/or maintenance staff. Since part-time employees are not required to be offered a standard benefits package, small properties may be able to save on expenses associated with employee benefits.

The forthcoming report explores aforementioned analyses and many other factors in greater detail, including comprehensive appendices for each state to be used as benchmarking data points. We encourage all those who are interested to read the report, comment and suggest additional avenues for analysis in future studies. Please direct all inquiries to

Matt Barcello, 617-603-4514, For more information on the study, visit

Matt Barcello is a Senior Manager with the National Real Estate Consulting practice of CohnReznick where he provides real estate due diligence and transaction services. Mr. Barcello advises clients on low-income housing tax credit underwriting, allocation and due diligence services. Matt’s experience in connection with the low income housing tax credits primarily includes conducting due diligence and providing other advisory services on behalf of institutional investors and syndicators. While at CohnReznick Matt has authored numerous reports that analyze the performance of Low Income Housing Tax Credit properties, and recently launched an online tool allowing users to navigate the data geographically.