In Buncombe County, NC, Billions of Dollars of Home Value Go Untaxed

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…But Also Just Wrong Enough to Overlook Billions

First, this approach to performance evaluation does not conform to industry standards. The International Association of Assessing Officers (IAAO) adopted their most recent Standards on Ratio Studies nearly a decade ago. These standards unambiguously define the purpose and approach to sales ratio studies. The process of selectively updating property characteristics of sold properties (as described above), without updating the characteristics of unsold properties is referred to as “sales chasing” and is explicitly recognized as unsound practice. 

Second, this approach to performance evaluation does not represent the vast majority of the housing stock. The IAAO’s standards emphasize the importance of ensuring that the sample of sold properties is representative of the broader housing stock. “Sales chasing,” as defined by the IAAO, increases the accuracy of property characteristics only for sold properties and therefore compromises the representativeness of the sample. Therefore, the findings from a ratio study in which sold property characteristics have been differentially updated are not representative of the 95% of unsold homes that do not have their characteristics updated (see above: “Sales Ratio Version 2”).

Third, this approach to performance evaluation overlooks the impact of incomplete or inaccurate property characteristic data. In 2021, roughly 40% of sold homes were identified to have missing or incomplete property characteristic data. In total, $96 million dollars of previously untaxed value was discovered from the less than 5% of homes that sold that year. If this rate of incomplete or inaccurate property characteristic data is present across the broader housing stock, there could be between $1 and $3 billion dollars of untaxed value missing from the county’s calculations. 

There are two important trends to note when understanding the implications of incomplete property characteristic data. First, the likelihood of a property having inaccurate or incomplete data is higher among more expensive properties. Second, in general, incomplete or inaccurate data produces assessed values significantly lower than market value. Taken together, this means that owners of higher-valued properties are more likely to receive a tax break, simply because of bad data.

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