Why CAMA Mass Appraisal Over-Assesses Commercial Property, and How to Show It

How a CAMA model values a commercial parcel

Most CAMA systems carry three engines. A cost model starts with replacement cost new from cost manuals, subtracts depreciation by age and condition, and adds land value. A market model uses multiple regression or comparable sales selection to relate sale prices to property characteristics. An income model applies market rent, vacancy, expense and cap rate tables by property class and neighborhood to the building area on record.

Each engine works from the parcel record: building area, year built, class, quality grade, condition, land area, and use code. None of them reads the rent roll. The income model does not know the building is 70% leased, that the anchor tenant is leaving, or that the roof needs replacing next year. It applies a standard rent and vacancy for the class and capitalizes the result. When the actual property tracks the class average, the value is close. When it does not, the error is entirely on the parcel.

Four ways the model drifts from market value

The over-assessment pattern in commercial property is not random. It comes from a handful of predictable sources, and each one points to the evidence that corrects it.

• Calibration lag: models are calibrated on sales that occurred before the valuation date, often over a period of two or more years. In a falling market, the model carries yesterday's prices into today's value.
• Thin sales: a county with three suburban office sales in two years cannot calibrate a reliable office model, so it borrows coefficients from other classes or areas.
• Class-wide income tables: one rent, vacancy and cap rate for a whole class ignores building-level vacancy, concessions, rollover risk and capital needs.
• Stale characteristics: wrong building area, outdated condition ratings, demolished or vacant space still graded as finished, and missing functional or external obsolescence.

What assessors measure: IAAO ratio study standards

Assessors test their own models with sales ratio studies: the ratio of the appraised (market) value on the roll to the sale price of each property that sold, adjusted for time where needed. The IAAO Standard on Ratio Studies (2013) sets the benchmarks most jurisdictions use. The level of appraisal, measured by the median ratio, should fall between 0.90 and 1.10. Uniformity is measured by the coefficient of dispersion (COD), the average percentage deviation of ratios from the median. For income-producing property the standard's guideline is a COD of 5.0 to 15.0 in larger areas with large samples and 5.0 to 20.0 in smaller areas with smaller samples. Vertical equity is measured by the price-related differential (PRD), which should fall between 0.98 and 1.03.

Two more points from the standard matter for owners. A PRD above 1.03 suggests regressivity: lower-value properties appraised at higher ratios than higher-value ones. A COD below 5.0 may indicate sales chasing, the practice of reappraising a property at or near its sale price, which makes sold properties look accurate while unsold properties are not reviewed the same way.

COD = 100 x (average of |ratio - median ratio|) / median ratio;  PRD = mean ratio / weighted mean ratio

Running your own ratio check

The same arithmetic works for a consultant. Pull the arms-length sales of the subject's property type in the assessor's neighborhood or market area, match each one to its appraised value for the lien date after the sale, and compute the statistics. The table below shows eight suburban office sales in a subject's market area.

The median ratio of 1.177 is above the 0.90 to 1.10 range, which suggests the stratum as a whole is appraised above market. The COD of 7.8 shows the model is consistently high, not erratic. The PRD of 1.029 sits inside the standard but near its ceiling, and the pattern is visible in the rows: four of the five smallest buildings show ratios of 1.235 to 1.276, while the three largest run 1.017 to 1.119. A small office building in this market area has a strong case that it shares the stratum's over-appraisal.

Turning model error into appeal evidence

A ratio study rarely wins an appeal on its own, because most boards decide the value of the subject, not the quality of the model. Its job is to explain why the assessor's number is high and to make the board receptive to the property-specific evidence that follows. Use it as the opening exhibit, then show the parcel-level reasons.

Start with the parcel record. Correct building area, class and condition before arguing value, because a record error is the easiest reduction to obtain and often the one the assessor will fix informally. Then present the income approach from the actual rent roll and stabilized market inputs, a sales comparison grid, and, in states that allow it, an equity comparison. Texas is the clearest example: Tax Code §41.43(b) and §42.26(a) include ratio-based unequal appraisal grounds, and the adjusted comparables ground lets an owner show the subject is appraised above the median of comparable properties without any sales at all.

Where the jurisdiction publishes its own ratio studies, cite them. Several large assessors, including the Cook County Assessor's Office, post IAAO-style ratio studies for their reassessments, and a published median ratio above 1.10 for a commercial class is a hard number for that assessor to argue against.

Where software fits

ATALI ELECTRIC's Assessment Audit module ingests county notices, pulls the parcel characteristics the CAMA model relied on, and benchmarks the assessed value against sales and peer assessments to produce an over-assessment score for each parcel. Across ATALI ELECTRIC customers, the average assessment reduction has been 14.2%, and the parcels with the largest reductions are usually the ones where the model's class-wide assumptions diverge most from the building's actual income. The consultant decides which parcels to appeal and which evidence to lead with.