Foundations of the Sales Comparison Approach: Data & Adjustments

Chapter 4: Foundations of the Sales Comparison Approach: Data & Adjustments

4.1 Introduction

The Sales Comparison Approach (SCA) is a cornerstone of real estate valuation. It hinges on the principle of substitution: a rational buyer will pay no more for a property than they would for an equally desirable substitute. This chapter lays the foundation for mastering the SCA, focusing on the crucial aspects of data acquisition, analysis, and adjustment. The accuracy and reliability of these elements directly impact the validity of the value conclusion.

4.2 Data Acquisition and Verification

4.2.1 Types of Data

The SCA relies on collecting comprehensive data on comparable properties (also termed “comparables”) and the subject property itself. This includes, but is not limited to:

• Sale Prices: Verified transaction amounts from recent sales.
• Property Characteristics: Detailed descriptions of physical attributes (size, age, condition, features, construction quality), location, and legal rights.
• Market Conditions: Information on prevailing interest rates, economic indicators, supply and demand, and real estate market trends.
• Conditions of Sale: Details of the transaction, including financing terms, motivations of buyer and seller (e.g., foreclosure sale), and any atypical circumstances that might influence the price.
• Legal Rights Conveyed: Information on easements, leases, mineral rights, or other encumbrances affecting the property.

4.2.2 Sources of Data

• Public Records: County recorder’s offices, tax assessor’s offices, and other government agencies provide information on property ownership, sales history, and tax assessments.
• Multiple Listing Services (MLS): Databases of properties listed for sale, containing detailed property descriptions, sale prices (for closed transactions), and listing histories.
• Commercial Data Providers: Companies that compile and sell real estate data, including sales information, property characteristics, and market analytics.
• Real Estate Professionals: Brokers, agents, and other industry experts can provide insights into market conditions and specific property transactions.
• Direct Inquiry: Contacting buyers, sellers, or real estate agents involved in comparable sales to obtain additional information about the transaction.

4.2.3 Data Verification

Reliable data is the bedrock of a credible appraisal. Appraisers must independently verify the accuracy of information obtained from various sources. This includes:

• Confirming Sale Prices: Cross-referencing sale prices reported in the MLS with official records from the county recorder’s office.
• Inspecting Comparable Properties: Conducting physical inspections of comparable properties to verify property characteristics and condition.
• Interviewing Parties Involved: Speaking with buyers, sellers, or real estate agents to confirm the circumstances of the sale and any unusual factors that might have influenced the price.
• Reviewing Legal Documents: Examining deeds, leases, and other legal documents to confirm property rights and encumbrances.

4.2.4 Data Reliability

• Unreliable data renders the SCA meaningless. An appraiser is responsible for using only reliable data.
• Knowing only the reported price but not the terms of a comparable sale can make a very large difference in the conclusions presented.

4.3 The Adjustment Process: Principles and Techniques

4.3.1 The Need for Adjustments

Seldom do comparable properties mirror the subject property perfectly. The adjustment process bridges the gap between comparables and the subject by quantifying the differences in their characteristics. This ensures a fair comparison and a reliable value indication.

4.3.2 Underlying Principles

• Paired Data Analysis: Extracting adjustments by analyzing paired sales that are identical except for one differing characteristic.
• Market Extraction: Deriving adjustments based on market data that reflects how buyers and sellers react to differences in property characteristics.
• Cost-Related Adjustments: Estimating adjustments based on the depreciated cost of the differing feature or amenity.
• Income Capitalization: Estimating adjustments based on the capitalized value of income differences.

4.3.3 Order of Adjustments

A generally accepted order of adjustments is:

1. Property Rights Conveyed: Adjustments for differences in the legal rights conveyed (e.g., leasehold vs. fee simple).
2. Financing Terms: Adjustments for differences in financing terms (e.g., below-market interest rates).
3. Conditions of Sale: Adjustments for atypical conditions of sale (e.g., forced sale, sale to a related party).
4. Market Conditions: Adjustments for changes in market conditions between the date of sale of the comparable and the date of valuation (also called time adjustments).
5. Location: Adjustments for locational differences between the comparable and the subject property.
6. Physical Characteristics: Adjustments for differences in physical attributes (e.g., size, age, condition, features).

4.3.4 Types of Adjustments

• Dollar Adjustments: Adding or subtracting a fixed dollar amount to the sale price of the comparable. Dollar adjustments are the most common adjustment type.
• Percentage Adjustments: Adjusting the sale price of the comparable by a percentage. Percentage adjustments are used in many nonresidential appraisal assignments to maintain ratios.

4.3.5 Adjustment Techniques

• Paired Data Analysis (Matched Pairs Analysis)
  • This technique isolates the effect of a single difference between comparable sales.
  • Equation: Adjustment = Sale Price of Property with Feature - Sale Price of Property without Feature
  • Example: Two houses are identical except one has a garage and sold for $250,000, while the other, without a garage, sold for $235,000. The adjustment for a garage would be $15,000.
  • Limitations: Difficult to find truly matched pairs in real estate markets.
• Statistical Analysis
  • Using statistical techniques, such as regression analysis, to quantify the relationship between property characteristics and sale prices.
  • Linear Regression Model: Sale Price = β0 + β1X1 + β2X2 + ... + ε
    • Where:
      • Sale Price is the dependent variable.
      • β0 is the intercept.
      • β1, β2,... are the regression coefficients for each independent variable.
      • X1, X2,... are the independent variables (e.g., square footage, number of bedrooms).
      • ε is the error term.
  • Example: A regression analysis indicates that for every additional square foot, the sale price increases by $150. This $150 would be the adjustment rate for size differences.
  • Limitations: Requires a large dataset of comparable sales. Results can be sensitive to data quality and model specification.
• Cost Analysis (Cost-Related Adjustments)
  • Using the depreciated cost of a feature to estimate the adjustment.
  • Equation: Adjustment = Replacement Cost New - Accrued Depreciation
  • Example: A comparable property has a swimming pool. The cost of a new pool is $50,000, and its accrued depreciation is $10,000. The adjustment would be $40,000.
  • Assumes no functional or external obsolescence.
  • Depreciation from all causes = physical, functional, and external forms.
• Capitalization of Income Differences
  • Used for income-producing properties. Capitalizes the difference in rental income attributable to a specific feature.
  • Equation: Adjustment = Difference in Net Operating Income (NOI) / Capitalization Rate (Cap Rate)
  • Example: A comparable property has higher rents of $5,000 annually, and the cap rate is 8%. The adjustment would be $5,000 / 0.08 = $62,500.
  • Example using units of comparison: Farm appraisers commonly divide the sale price by the number of acres to calculate the ratio sale price per acre.

4.3.6 Qualitative Analysis

Qualitative analysis is used for differences that cannot be easily quantified or when data is limited. Techniques include:

• Relative Comparison Analysis: Ranking comparables based on their overall similarity to the subject property.
• Ranking Analysis: Ranking comparables by specific characteristics.
• Scenario Analysis: Developing different value scenarios based on varying assumptions about market conditions or property characteristics.

4.4 Reconciliation

Reconciliation is the final step in the SCA, where the appraiser weighs the indications of value derived from the adjusted comparable sales to arrive at a single value conclusion or a narrow range of values.

4.4.1 Factors to Consider During Reconciliation

• Number and Reliability of Comparable Sales: Greater weight is given to sales that are more similar to the subject property and have reliable data.
• Extent of Adjustments: Sales requiring smaller adjustments are generally considered more reliable indicators of value.
• Market Relevance: Sales that are recent and located in the subject property’s market area are given greater weight.

4.4.2 Questions to Ask During Reconciliation

• How much evidence of value is available and how much is included?
• Should comparable listings, pending sales, or even expired listings be considered?
• Should a history of market exposure of the subject property be considered?
• How many of the available comparable sales are truly comparable?
• Do the adjustments to the sales or listings represent the market’s reactions?
• Are the comparable properties used legitimate alternatives to the subject property?

4.5 Common Pitfalls to Avoid

• Over-Reliance on Quantity Over Quality: A few well-analyzed comparables are better than many poorly analyzed ones.
• Excessive Adjustments: Large adjustments can introduce significant uncertainty into the value conclusion. Logically, the more adjustments made to the sale price of a comparable, the less reliable the final indication of value will be.
• Circular Reasoning: Using the subject property’s characteristics to select comparable sales, leading to a biased value conclusion.
• Ignoring Market Trends: Failing to account for changes in market conditions can result in an inaccurate appraisal.

4.6 Conclusion

Mastering the Sales Comparison Approach requires a deep understanding of data acquisition, analysis, and adjustment techniques. By following sound appraisal principles, verifying data, and carefully considering market conditions, appraisers can develop credible and defensible value conclusions.

Review Questions

1. Explain the principle of substitution as it relates to the Sales Comparison Approach.
2. Describe three sources of data for the Sales Comparison Approach.
3. Explain the importance of data verification.
4. List the generally accepted order of adjustments.
5. Describe the Paired Data Analysis technique and its limitations.
6. Explain the limitations of excessive reliance on percentage adjustments.
7. Define reconciliation and list three factors to consider during the reconciliation process.
8. Discuss the problems of using the common statistical techniques of calculating the mean and median sale prices as support for value conclusions.