An adjustment grid that shows the same dollar figure for every difference regardless of magnitude suggests:
Correct Answer
D) The adjustments were assumed rather than derived
Why this is correct: Identical dollar adjustments for different features (e.g., same amount for a bathroom as for a garage) suggest the adjustments were not derived from specific market data but were assumed or guessed. Why the other choices are wrong: A properly supported market analysis would yield varying adjustment amounts. The market does not value all features identically. Unusually well-matched comparables would require few or no adjustments, not identical ones. Exam tip: Round, repeated adjustments across unrelated items are a red flag for unsupported analysis.
Why This Is the Correct Answer
Option D is correct because identical figures across dissimilar and unequally sized differences indicate the adjustments were assumed rather than derived. Genuine market extraction produces varied amounts, since different features and different magnitudes command different prices. The uniformity is a symptom of a filled-in grid rather than an analyzed one. A reviewer encountering this pattern will ask for the support, and the appraiser must be able to produce it.
Why the Other Options Are Wrong
Option A: A properly supported market analysis was actually performed
A properly supported analysis produces amounts that differ by element and scale with magnitude, because that is what market evidence looks like. Uniform figures are the opposite of what derivation yields. The option asserts the conclusion the evidence contradicts.
Option B: The market values all features identically
A market valuing every feature identically, regardless of type or size, is not something observed in practice; buyers pay different amounts for baths, garages, and square footage. Even if two features happened to contribute similar amounts, the coincidence would not extend across all differences and all magnitudes. The uniformity is an artifact of the appraiser's process, not of buyer behavior.
Option C: The comparables were unusually well matched
Well-matched comparables produce small or absent adjustments, not identical ones, and a truly close comparable would need few adjustments at all. Uniform figures appear precisely where differences do exist but have not been individually measured. Comparability quality and adjustment support are separate issues, and this pattern speaks to the second.
Real data is lumpy
Market-derived numbers come out uneven: $3,150 here, $11,400 there. Identical round figures across every line are the fingerprint of a filled-in grid rather than an analyzed one.
How to use: When a stem describes a pattern in a grid, ask what process would produce it. Uniformity and round numbers point to assumption; variation scaled to magnitude points to derivation.
Exam Tip
If the data will not support a dollar adjustment, use qualitative ranking instead of guessing an amount. An honest superior-or-inferior comparison beats an invented number.
Common Mistakes to Avoid
- -Using habitual round figures instead of derived amounts
- -Failing to scale an adjustment to the magnitude of the difference
- -Omitting documentation of how adjustments were derived
- -Inventing dollar amounts where qualitative analysis is the honest choice
Concept Deep Dive
Analysis
This tests the diagnostic reading of a grid's internal pattern. Adjustments are supposed to be individually derived, each answering how much the market pays for one specific difference, so a well-supported grid produces amounts that vary by element and by magnitude. A garage differs from a bathroom, a 400 square foot size difference differs from a 100 square foot one, and market evidence would rarely price them identically. When every difference carries the same round figure, the pattern is telling you the numbers came from habit or convenience rather than from paired sales, statistical analysis, or any other extraction technique. Reviewers look for exactly this signature, because uniform round adjustments are among the easiest indicators of unsupported work to spot. The remedy is to derive each adjustment from data and to document the derivation, and where the data will not support a dollar amount, to use qualitative analysis rather than inventing one.
Background Knowledge
You need to know the recognized methods for deriving adjustments, including paired sales analysis, grouped data analysis, statistical techniques, depreciated cost, and capitalization of rent differences, and that adjustments must be supported and explained. You should also know that qualitative analysis is the appropriate alternative when data will not support dollar amounts, and that reviewers scrutinize adjustment support closely.
Real-World Application
Reviewing a colleague's grid, you notice every difference carries a $5,000 adjustment, from a half bath to a 500 square foot size gap. You ask for the derivations, find none exist, and rebuild the adjustments from paired sales, which produces amounts ranging from $2,800 to $19,000 and materially changes the reconciled conclusion.
More Sales Comparison Questions
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