Why Most CAMA Models Are Built on a House of Cards (And How to Fix It)

 In standard Computer-Assisted Mass Appraisal (CAMA)—especially in valuations delivered by third-party consultants—diagnostic testing rarely goes beyond a basic R-squared check and a high-level ratio study.

Assessors and junior analysts often receive opaque, black-box models with no visibility into whether they meet classical econometric assumptions. When a high-stakes Value Adjustment Board (VAB) hearing or courtroom challenge rolls around, that lack of proof leaves jurisdictions dangerously exposed.

True model defensibility requires looking under the hood.

This Wednesday, Session 7 of our Mass Appraisal Masterclass drops on Substack. We are cutting through the academic noise to show new analysts and practitioners how to run a practical, transparent diagnostic battery using a single representative town model.

Here is a sneak peek at what we cover:

·        Linearity & Zero Conditional Mean: Verifying absolute residual symmetry without getting lost in matrix math.

·        Homoscedasticity via RCV: Tracking relative error dispersion across value deciles using the Residual Coefficient of Variation.

·        Normality: Swapping out sensitive statistical tests for intuitive sales ratio skewness and kurtosis.

·        Multicollinearity: Running targeted auxiliary regressions to keep VIFs well below standard safety thresholds.

·        Catching OVB: Spotting Omitted Variable Bias in auxiliary outputs and knowing when to deploy hybrid Regression Comps.

Stop relying on unverified black-box models. Master the four foundational OLS tests and build valuation rolls that stand up to any challenge.

Catch Session 7 on Substack this Wednesday!