08/09/2026
(This won't likely be the post that gets the most "likes" from the real estate community)
Errors in commercial property valuations are highly correlated by brokerage. Unmeasured local market factors, shared proprietary data models, and uniform appraiser training within the same firm create systematic valuation biases. Properties handled by the same brokerage often share similar appraisal errors.
๐๐ฒ๐ ๐๐ฎ๐ฐ๐๐ผ๐ฟ๐ ๐๐ฟ๐ถ๐๐ถ๐ป๐ด ๐๐ผ๐ฟ๐ฟ๐ฒ๐น๐ฎ๐๐ถ๐ผ๐ป
๐ฆ๐ต๐ฎ๐ฟ๐ฒ๐ฑ ๐๐ฎ๐๐ฎ ๐ฎ๐ป๐ฑ ๐ ๐ผ๐ฑ๐ฒ๐น๐
โข Brokerages use internal comparable sales databases.
โข Firms apply uniform capitalization rate assumptions.
โข Analysts use standard financial modeling templates.
๐ข๐ฟ๐ด๐ฎ๐ป๐ถ๐๐ฎ๐๐ถ๐ผ๐ป๐ฎ๐น ๐๐๐น๐๐๐ฟ๐ฒ ๐ฎ๐ป๐ฑ ๐๐ป๐ฐ๐ฒ๐ป๐๐ถ๐๐ฒ๐
โข Brokers share local market opinions and biases.
โข Firms face pressure to meet client pricing expectations.
โข Internal review processes reinforce groupthink.
๐จ๐ป๐บ๐ฒ๐ฎ๐๐๐ฟ๐ฒ๐ฑ ๐๐ผ๐ฐ๐ฎ๐น ๐๐ฎ๐ฐ๐๐ผ๐ฟ๐
โข Local market nuances are interpreted the same way.
โข Neighborhood trends are viewed through a single lens.
โข Off-market deal knowledge stays trapped inside the firm.
Lenders already know this. They don't take brokerage valuations at face value โ they underwrite around the bias by applying strict risk management overlays to reduce exposure to inflated property valuations. Because lenders risk capital based on these loan-to-value ratios, they actively discount or verify brokerage-provided data.
If lenders are pricing in a broker's bias, shouldn't you know what it is before they tell you?
This is exactly the kind of question hierarchical modeling, clustered standard errors, and residual variance decomposition we're built to answer โ and it's the lens I bring to every valuation I sign off on.
This is also the kind of econometric testing I build into every engagement โ for investors or brokers that want a second, independent set of eyes on valuation risk before a lender finds the bias for you, or if that's a gap on your team, let's talk.
