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Appellants and Clay County dispute valuation of Amazon-leased distribution centers in Liberty

August 25, 2025 | Clay County, Missouri


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Appellants and Clay County dispute valuation of Amazon-leased distribution centers in Liberty
Representatives for two large distribution centers leased by Amazon asked a Clay County appeals panel to lower the county’s assessed values, arguing market rent and local sales comparables support a requested value of about $78,000,000 for one property.
Appellant representative Michael, an Amazon employee, told the panel the subject warehouse was “recently built in 02/2022, sitting on about 69 acres of land,” and that the company’s calculation, using actual rent of $6.28 per square foot and an 8 percent capitalization rate, produced a requested value of $78,000,000.
The county’s representative, Grant Knopf of the Clay County assessor’s office, urged the panel to “completely disregard the equity argument as we don't look at equity” at this stage and said the assessor’s office used broader market data and lower cap rates in their valuation. Knopf cited sales and cap‑rate data showing a range of cap rates and prices per square foot and said the county used a 7 percent cap rate for mass appraisal purposes.
Appellants presented three sales comparables in the local market with per‑square‑foot sales ranging from about $64 to $82 and argued a $75 average per square foot (and the property’s actual rent) supports reducing the assessment. Appellants also provided a pro forma income analysis showing net operating income they capitalized at 8 percent to derive their figure.
Knopf and county staff countered with a larger packet of evidence that included 14–15 sales and cap‑rate observations, national data sources and TREP/portfolio appraisal allocations the county said indicate lower cap rates (the county cited an average cap rate near 5.5–6.3 percent in some comparables) and higher market value. Knopf also emphasized that in Clay County “Amazon is the tenant, not the owner,” and noted the county relied on income‑approach analyses and available appraisal/reporting data required by lending institutions.
The hearing also included discussion about a portfolio appraisal appearing in the county’s TREP data; county staff said they do not have the full appraisal document before the panel and cautioned the board about treating allocated portfolio prices as direct market evidence for a single building. An appellant representative said the appraisal numbers were included in the lender’s reporting package but acknowledged the physical appraisal was not provided to the panel.
No formal vote or change was announced at the hearing. The board told participants it would review the submitted evidence and “notify you in the next few days,” and asked county staff to follow up with appellants.

Discussion (what was debated)
- Appellant argument: income approach using actual rent ($6.28/sf), 33.5% market vacancy allowance (matching assessor’s vacancy assumption), 3.5% expenses, and an 8% capitalization rate; sales comparables in Liberty averaging about $75/sf; requested assessment approximately $78,000,000.
- County argument: mass appraisal uses a 7% cap rate and a larger set of sales and cap‑rate evidence (some cap‑rate observations in the county’s packet were as low as ~3.7% and averaged 5.5–6.3% for similar, larger sales), TREP/portfolio appraisal allocations and lender‑ordered appraisals suggest higher market value; Amazon is tenant not owner.
- Evidence dispute: appellant provided lease and local sales; county provided broader sales, TREP data and references to lender appraisals that were not in the hearing record in full.

Direction / next steps
- The panel indicated it will consider the submitted evidence and notify appellants of its decision in the coming days; no formal action was taken at the hearing.

Ending
- The board did not issue an immediate ruling. County staff and appellants were told they would receive written notice of the panel’s decision after members review the evidence.

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Scribe from Workplace AI
Scribe from Workplace AI