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Graphics Improve the Analysis of Income Data.

abstract

Computer graphing is a powerful and accessible tool for forecasting income. This article discusses how providing clients with a visual display of income data can enhance the readability, credibility, and persuasiveness of an appraisal report. This article demonstrates useful techniques for analyzing rent rolls, market rents, percentage rents, and absorption. It emphasizes the importance of visual display as a means of gaining insight from income data.

Portfolio managers, investment bankers, and rating agencies crave insight on the expected performance of a property's income stream over the life of their investment or loan. These appraisal users appreciate visual displays that concisely and forcefully identify the timing and magnitude of future income events or risks. With cogent income charts, they can easily evaluate the sustainability of income and future downside risks. In litigation support and tax work, the expert appraisal witness who accurately explains and captures complex income issues using a simple and compelling picture can build a solid consensus for the conclusions of an appraisal.

Various income approach examples are presented and discussed. Although they are not complete case studies, these examples show isolated techniques for extracting insight from income data. This treatment is intended to be representative, not exhaustive.

Rent Roll

Visual presentations can be significantly more understandable and persuasive than tabular or narrative presentations, especially for lengthy and detailed rent rolls, which can be difficult to grasp even by experienced real estate analysts. An appraiser should, therefore, carefully mine the rent roll for all relevant information that can support reasonable estimates and arguments.

Figure 1 is a good example of how a visual display can reveal important information that would not be apparent in a tabular format. This plot of lease rates at a new shopping center demonstrates a clear rent pattern based on tenant size, except for two outliers which are separately identified and labeled as tenant A and tenant B.

The wide range in contract rents ($18-$28 per square foot) is logical based on size differences (1,664-26,000 square feet). The indicated pattern and trendline equation (y = [86.83x.sup.-0.1552]) could be used as a starting point to estimate market rent for spaces that have not yet been leased.

More subtle insight can be gained from the outliers because they may be uniquely influenced by particular elements of comparison. For example, tenant A demonstrates that upgraded air conditioning costs were amortized as additional rent, not granted as a concession. This observation can be cited as support for baseline tenant improvement estimates in a discounted cash flow analysis.

In addition, the trendline constitutes a base rent from which the air conditioning upgrade premium can be computed and compared with the landlord's actual cost. This rent-to-cost amortization relationship could be used later to support a specific adjustment to a lease comparable. It could also be used in a highest and best use analysis to support the building capitalization rate of the property or its components. These subtle observations might have been missed if the data had not been plotted because tenant A's above-average rent would not be evident from the tabular rent roll. Plotting rents often prompts further inquiry which can lead to additional insight.

For existing buildings, plotting the initial rent can be used to support the direction and magnitude of adjustments attributed to changes in market conditions over time, as shown by Figure 2 for office building rents.

In extreme cases, plotting contract rent can explain why the direct capitalization method must be eliminated altogether. Figure 3 represents an old, single-tenant property with irregular cash flows and with the federal government as the only tenant. Because the first year's income is not indicative of later income, direct capitalization does not apply unless a comparable sale with a similar declining income pattern can be identified. The benefit of this chart is that it highlights the irregularity of rent beyond a typical investor study period. This chart suggests that a longer 19-year discounted cash flow period may be warranted, with land value used for reversion.

In some cases, contract rent data is clustered in logical groups, as shown in the current rent charts for an office building and a mixed-use property (Figures 4 and 5).

These graphs show that two-dimensional charts can readily accommodate multiple elements of comparison when obvious clusters are properly labeled.

A rent roll also contains information about a project's tenant mix and lease expirations, which can be used to evaluate a property's future vacancy and turnover risks. In Figure 6, the juxtaposition of a pie chart and column chart highlights the importance of one particular tenant, the state government. These charts suggest that the renewal probability and turnover costs for this particular tenant deserve special attention for leased-fee valuation.

The charts in Figure 6 forcefully demonstrate the amount and duration of contract rents, two key considerations that drive leased fee value. The reader's attention is drawn to a specific tenant or class of tenants and to those considerations that most heavily affect leased fee value. Without this data display, key valuation insights could be overlooked or treated cursorily, especially if the rent roll is lengthy and presents the tenant mix in random order.

A tabular rent roll contains all the raw data used to develop each of the charts in Figures 1 through 6. However, these well-focused charts are not superfluous or redundant if they help the reader to quickly understand important economic issues. The objective of rent roll analysis is to create a picture that makes the data manageable and memorable. [1]

Market Base Rent

Establishing whether a property's contract rents are above, below, or equal to market rent is an important consideration for income risk assessment and leased-fee valuation. A market rent analysis is a comparative exercise analogous to sales comparison analysis, which also benefits from visual techniques. [2]

In many cases, comparable rent analysis mirrors the rent roll analysis described previously. For example, Figure 7 uses comparable single-tenant office/warehouse leases to estimate market rent for a speculative building with 65% office finish. The comparable properties are very similar to one another and to the proposed property, except for the amount of office finish.

Based on Figure 7, a market rent indication for the appraised property is readily supported at 64 cents per square foot per month ($0.64 = [0.4065 x 65%] + 0.3787). The same conclusion could be supported by using linear interpolation or linear estimation from the rent comparable summary. However, because there is no mathematical test for linearity, it would be inappropriate to use linear models without first plotting the data to identify the shape of the trend. Analysts should not apply a linear model to nonlinear data because significant errors can result. [3]

In Figure 8, a plotting of single-tenant office/ warehouse rents is used to support the magnitude of a size adjustment between big-box projects (more than 400,000 square feet) and smaller projects (less than 100,000 square feet).

Based on this graphic analysis, a -6% size adjustment is well supported for the smaller comparables. The magnitude of this adjustment would be difficult to visualize and support with only a table listing the comparable data.

For multitenant projects, two rent rolls can be plotted as separate series on the same scatter diagram for comparison. A rent plotting of two very similar new shopping centers shows the location of project A to be superior to that of project B (Figure 9).

In this case, the noise caused by the elements of comparison has not been filtered out by the adjustment process. However, overall clustering provides a clear basis for applying a location adjustment.

Percentage Rent

Base rent and percentage rent, which are components of total rent, can be broken out graphically (Figure 10).

This chart shows that sales volume and percentage rents are declining. In addition, base rent recently increased. As a result, 1999 and 2000 percentage rent will likely be considerably lower than prior years. Using this graphic analysis, annual and seasonal sales can be projected, base rent adjustments applied, and a reasonable forecast supported. A competitive supply-and-demand analysis may help predict the depth and duration of the tenant's sales decline. A remodel or upgrade of the improvements may also help reverse the tenant's sagging sales by improving the capture rate vis-a-is the competition.

The frequency of percentage rent calculation periods can affect collections because of the seasonality of sales volume. A visual presentation shows the actual treatment of percentage rents in an intuitive way.

Absorption

For speculative projects or properties with significant vacancy problems, the timing of absorption is an important consideration that must be supported by market evidence. There are many graphic techniques for presenting absorption patterns.

Detailed absorption comparables demonstrate evolving submarket trends. By contrast, "average" absorption time may fail to capture the latest changes in the balance between supply and demand. For example, absorption at a new office building was brisk for the first year and slower thereafter (Figure 11). This pattern may be a normal absorption pattern for this market or it may indicate a softening market over the last year.

Some property types, such as retirement centers, boarding schools, and detoxification facilities can be compared with absorption comparables based on average daily census (Figure 12).

Broad market absorption trends for office space can be placed beside proposed construction (see Figure 13). Actual market absorption is shown in black and scheduled construction is shown in white. This juxtaposition is helpful for predicting whether new office construction will be excessive and cause detrimental changes to market vacancy rates and the pace of absorption at new speculative offices.

Conclusion

The use of visual display is a powerful means of developing and reporting a reliable income forecast. Computer graphic analysis is almost universally available due to significant advances in spreadsheet technology. Income graphics can increase the utility of an appraisal for a variety of appraisal users.

Visual display is not impervious to errors or distortion; it neither replaces sound judgment nor eliminates the need for careful review. The shapes, slopes, and intercepts of trendlines must be reasonable, logical, and representative of collective market attitudes and behavior. [4]

A chart is useless if it merely reiterates the obvious. Data displays should reveal valuable insight and be straightforward and uncluttered. In some cases, multiple charts are necessary to tell the complex story about the income characteristics of an investment property.

Bryan L. Goddard, MAI, is a senior appraiser for AEGON USA Realty Advisers. He earned his MBA from Brigham Young University. Mr. Goddard is an active member of various Appraisal Institute committees and is a frequent contributor to The Appraisal Journal.

(1.) W. S. Cleveland, editor, The Collected Works of John W. Tukey, Graphics: 1965-1985, v. 5 (Belmont, California: Wadsworth, Inc., 1998): 421.

(2.) Bryan L. Goddard, "The Power of Computer Graphics for Comparative Analysis," The Appraisal Journal (April 2000): 134-141.

(3.) Bryan L. Goddard, "The Role of Graphic Analysis in Appraisals," The Appraisal Journal (October 1999): 429-435.

(4.) Edward R. Tufte, The Visual display of Quantitative Information (Cheshire, Connecticut, Graphics Press, 1992)" 53.

References

Carey, Patrick. Data Analysis with Microsoft Excel (Pacific Grove, California: International Thompson Publishing Company, 1997).

Tufte, Edward R. Visual Explanations: Images and Quantities, Evidence and Narrative (Cheshire, Connecticut: Graphics Press, 1992).
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Author:Goddard, Bryan L.
Publication:Appraisal Journal
Geographic Code:1USA
Date:Oct 1, 2000
Words:1876
Previous Article:August 2000.
Next Article:National Survey of Residential Appraisers Shows SRAs Have More Earning Power.
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