https://www.newcastlede.gov/DocumentCenter/View/59019/Tyler-Mass-Appraisal-Report-for-New-Castle-County_final
A subject matter expert at New Castle County uploaded the Tyler report in the link into NotebookLM and asked the AI, “What was the methodology for assessing residential properties?”
This is the result – a multiple regression analysis model. It is no wonder the values are all over the place:
What was the methodology for assessing residential properties?
For assessing residential properties, Tyler Technologies Inc. primarily utilized the Market Approach (also known as the sales comparison approach), while also considering the Cost Approach. The Income Approach was not specifically mentioned as being relied upon for residential properties; instead, it was typically applied to commercial properties.
Here's a breakdown of the methodology for assessing residential properties:
• Valuation Approaches:
◦ Market Approach (Sales Comparison Approach):
▪ This method estimates a property's value by examining recently sold properties (comparables) that are similar in size and features and are located within a close geographic proximity.
▪ For residential properties, verified, settled transactions were heavily relied upon, especially for single-family dwellings.
▪ A Multiple Regression Analysis (MRA) model was used to establish the relationship between selling price and observable property characteristics, thereby estimating market value for each residential property. This model also provides a mechanism to adjust a sold property to estimate the value of a subject property.
▪ The MRA models for the market/sales approach were developed using 8,890 settled transactions from a sales study period of January 1, 2021, through July 1, 2024.
▪ Confirmed transactions were time-adjusted to the effective date of value (July 1, 2024) to account for market fluctuations within the study period. Sales not considered "arms-length transactions" were excluded from the analysis.
◦ Cost Approach:
▪ This method calculates the probable selling price by estimating the cost to provide a replacement building of similar condition, quality, and utility.
▪ It involves analyzing local construction costs and land sales to develop a "replacement cost".
▪ The premise is that adding land value to the replacement cost of the new building (less depreciation) provides a rational estimate of market value.
▪ For residential properties, cost and depreciation tables were calibrated based on empirical nationwide cost publications, adjusted for local market conditions.
▪ The cost approach formula is expressed as MV = LV + BV, where LV (land value) is based on parcel land price multiplied by land size (PL x LSize), and BV (building value) considers building price multiplied by building size minus depreciation ([(PB x BSIZE) - Depreciation %]).
• Property Characteristics Collected and Analyzed for Residential Properties:
◦ Lot Size
◦ Topographical Influences
◦ Site Specific Influences
◦ Building Style/Design
◦ Building Quality/Grade
◦ Building Condition
◦ Year Built
◦ Building Square Footage
◦ Total Livable Area
◦ Number of Dwelling Units
◦ Number of Total Rooms
◦ Number of Bedrooms
◦ Number of Bathrooms
◦ Total Fixtures
◦ Foundation
◦ Basement Type & Area
◦ Fuel Type
◦ Central or Unit A/C
◦ Attached Additions
◦ Detached Improvements
◦ Miscellaneous Features
◦ Percent Complete
◦ New Castle County's residential properties were analyzed with units of comparison such as Price per Square Foot of Total Living Area and Price per Square Foot (or Acre) of Land.
• Geographic Stratification and Neighborhood Delineation:
◦ Residential properties were divided into seven main zones based on market knowledge and geo-statistical testing.
◦ Within these zones, 383 unique locational variables (subareas or neighborhoods) were used in the valuation process for residential properties.
◦ This stratification is appropriate when property attribute values vary significantly among areas and when housing types are relatively uniform within areas.
◦ The statistical technique used for neighborhood delineation was K-means clustering, a machine learning algorithm that groups similar parcels into clusters by minimizing the sum of squared distances between parcels and their cluster centroids.
◦ Appraiser judgment and local market knowledge were also relied upon to manually confirm or edit the polygons produced by K-means clustering.
• Market Conditions for Residential Properties:
◦ The market conditions for residential properties in New Castle County were considered positive, with an upward, compounding influence on value throughout the study period (Q3 2021 through Q3 2024).
◦ Double-digit appreciation was observed in 2021 and 2022, slowing to single-digit appreciation in 2023 and 2024 due to increased cost of debt (30-Year Fixed Rate Mortgage Average).
◦ Median and average sales prices continued to rise due to a continued lack of housing stock supply.
• Appraisal Performance Evaluation:
◦ The performance of the mass appraisal for residential properties was primarily judged using ratio study statistics, which compare appraised values to market values (represented by sales prices).
◦ Eight residential models were specified and calibrated across the seven residential zones, with an additional model created due to the heterogeneity of housing stock in the City of Wilmington (Zone 3).
◦ The aggregate model performance aligned with IAAO's standards, though models for Zones 3 and 8 had Coefficients of Dispersion (CODs) slightly above acceptable limits. The elevated COD for Zone 3 was attributed to superior condition of sold properties compared to unsold ones and the difficulty in ascertaining interior condition from exterior inspections.
◦ The reassessment aimed for an appraisal level of one-to-one, meaning appraised values should typically be near 100% of market value, with high and low ratios balancing out.
◦ Appraisal uniformity, ensuring fair and equitable treatment of properties within and between groups, was measured using metrics like the Coefficient of Dispersion (COD) and Price-related Differential (PRD). The Coefficient of Price-related Bias (PRB) also quantified the relationship between assessment-sales ratios and value.
