Chapter: An appraiser is using the sales comparison approach to value a property in Maine. Which of the following adjustments would be made if the comparable property has a feature that the subject property lacks? (EN)

Chapter: Adjustment for Superior Features in Comparables (Sales Comparison Approach)

The Sales Comparison Approach: Principles and Methodology

The Sales Comparison Approach (SCA) estimates the value of a subject property by comparing it to similar properties (“comparables”) that have recently sold. The underlying principle is substitution: a rational buyer will pay no more for a property than the cost of acquiring an equally desirable substitute. SCA relies on market data, specifically closed sales of comparable properties. Adjustments are made to the sale prices of the comparables to account for differences between them and the subject property. This process strives to isolate the factors influencing market value.

• Principle of Contribution: The value of a component (feature) of a property is measured by its contribution to the overall value, not its cost. This guides adjustment amounts.
• Data Sources: Reliable data is crucial. Sources include MLS databases, county records, appraisers’ files, and interviews with market participants (buyers, sellers, brokers).
• Element of Comparison: Key characteristics requiring analysis and potential adjustment including:
  1. Property Rights Conveyed
  2. Financing Terms
  3. Conditions of Sale (Motivation)
  4. Market Conditions
  5. Location
  6. Physical Characteristics

Adjustment Process for Superior Features in Comparables

When a comparable property possesses a feature that the subject property lacks, the comparable’s sale price must be adjusted downward. This adjustment reflects the amount a typical buyer would likely pay less for the comparable due to the presence of this feature, relative to the subject property. The adjustment aims to simulate what the comparable would have sold for if it lacked that feature.

• Direction of Adjustment: If the comparable has a superior feature, the adjustment is negative (subtracted) from the comparable’s sale price. This is because we are trying to estimate what the comparable would have sold for without that feature.

• Quantifying the Adjustment: Determining the amount of the adjustment is a critical and often challenging aspect of the SCA. Several methods are used:

  1. Matched Pair Analysis: This is the most reliable method. It involves finding two or more pairs of comparable sales where one property in each pair has the feature in question and the other does not. The difference in their sale prices indicates the market value of the feature.

     • Formula: Let S₁ be the sale price of comparable 1 (with the feature) and S₂ be the sale price of comparable 2 (without the feature), everything else being equal. The adjustment amount A is:

       • A = S₂ - S₁ (Note that A will be a negative number).

       Example: Two identical houses in the same neighborhood sold recently. House 1 has a finished basement and sold for \$350,000. House 2 does not have a finished basement and sold for \$325,000. The adjustment for a finished basement is -\$25,000.
       2. Cost Approach Analysis (Depreciated Cost): The cost to add the feature new, less any accrued depreciation, can provide an indication of its value. This method is most appropriate for newer improvements where depreciation is minimal.
       * Formula: Value = Cost_new - Depreciation
       * Depreciation Types: Physical deterioration (wear and tear), functional obsolescence (design flaws), and external obsolescence (economic factors outside the property).
       3. Income Capitalization (Rental Income): If the feature generates income (e.g., a rental apartment in a single-family home), the income can be capitalized to estimate its contribution to value.
       * Formula: Value = Net Operating Income / Capitalization Rate or V = NOI / R
       * The Capitalization Rate (R) represents the rate of return an investor expects on their investment.
       4. Market Participant Interviews: Talking to buyers, sellers, brokers, and builders can provide valuable insights into the market’s perception of the feature’s value.
       5. Statistical Analysis (Regression): Regression analysis can be used to quantify the relationship between various property characteristics and sale prices. This requires a large dataset of comparable sales. It provides a more sophisticated estimate of adjustment size but requires specific statistical knowledge.

• Percentage vs. Dollar Adjustments: Adjustments can be expressed as a dollar amount or as a percentage of the comparable’s sale price. In general, dollar adjustments are preferred because they directly reflect the value of the feature. Percentage adjustments are more appropriate for broad market condition adjustments.

Examples and Practical Applications in Maine

• Waterfront Property: In Maine, waterfront property commands a premium. A comparable with significantly more desirable waterfront frontage than the subject would require a substantial downward adjustment. Matched pair analysis using similar waterfront properties is essential. The adjustment would not be based on the price of the waterfront lot alone, but rather the market’s perception of the difference in value between the subject’s waterfront and the comparable’s.
• Finished Basement: A finished basement adds usable square footage and can increase a home’s value. If a comparable has a finished basement and the subject does not, a downward adjustment is necessary. Local market data, showing sales of houses with and without finished basements, provides data for matched-pair analysis.
• Garage: In Maine’s climate, a garage is a valuable asset. A comparable with a two-car garage when the subject has none requires a downward adjustment. The adjustment would consider the size and condition of the garage.
• Heating System: Differences in heating systems require adjustments. For example, a comparable with a modern, efficient propane furnace might require a downward adjustment if the subject has an older oil furnace. Fuel prices, efficiency ratings, and buyer preferences are considered.
• Solar Panels: If a comparable has a functioning solar panel system that is owned outright (not leased), this can increase its market value. If the subject property does not, a negative adjustment will be needed. This should be valued based on the energy savings generated by the solar panels.

Potential Errors and Mitigation Strategies

• Over-Adjustment: Making adjustments that are too large can result in an inaccurate value estimate.
• Under-Adjustment: Conversely, failing to make sufficient adjustments can also lead to an inaccurate estimate.
• Double-Counting: Avoid adjusting for the same feature twice. For example, adjusting for a superior view and also adjusting for the location, when the view is directly attributable to the location, leads to over-adjustment.
• Subjectivity: All adjustments involve some degree of judgment. Strive for objectivity by relying on market data and sound reasoning. Document the rationale for each adjustment clearly in the appraisal report.
• Data Limitations: The availability of comparable sales data can be limited, especially in rural areas. Expand the search area or time frame with caution, carefully considering any differences.

Impact of Scientific Advancements

• Advanced Statistical Modeling: Regression analysis, geographical information systems (GIS), and artificial intelligence (AI) are being used to analyze market data more effectively and improve the accuracy of adjustments. These tools can identify subtle patterns and relationships that might be missed by traditional methods.
• Data Analytics: Increased availability of real estate data (e.g., from online portals, public records, and private databases) provides more opportunities for comparative analysis.
• Automated Valuation Models (AVMs): While AVMs can provide a preliminary estimate of value, they should be used with caution and validated by a human appraiser. AVMs may not adequately capture the nuances of a particular property or market. The complexity of these AVMs often use algorithms such as the gradient boosting method (GBM) or Random Forest (RF).

Important Discoveries and Breakthroughs

• Early Development of the Sales Comparison Approach: Grounded in the core economics of substitution, SCA was initially qualitative and evolved into a more quantitative approach through experience and research.
• Development of Statistical Techniques: The implementation of regression analysis and similar methods enabled a more rigorous and scientific approach to quantifying adjustments.
• Availability of Data: The rise of MLS databases and other comprehensive data sources has drastically improved the accessibility and quality of market information, contributing to more accurate appraisals.