Mastering the Sales Comparison Approach in Real Estate Appraisal: Units of Comparison & Adjustments

Chapter 3: Units of Comparison & Adjustments

This chapter delves into the core of the Sales Comparison Approach: identifying relevant units of comparison and making scientifically sound adjustments to comparable sales data to arrive at a credible value indication for the subject property. We will explore the theoretical underpinnings of this process, emphasizing the importance of market-derived data and statistically valid methods.

3.1 Understanding Units of Comparison

A unit of comparison is a standardized element used to analyze and compare properties. It allows appraisers to extract meaningful data from market transactions and identify patterns related to value. Selecting the appropriate unit of comparison is crucial for accurate analysis.

• Definition: A consistent metric used to compare properties, allowing for the identification and quantification of differences.

• Purpose:

  • Standardize data for comparison.
  • Isolate key value-influencing characteristics.
  • Quantify the contribution of each characteristic to the overall value.

• Common Units of Comparison:

  1. Price per Square Foot (PSF): Calculated by dividing the sale price by the gross building area (GBA) or gross living area (GLA). Equation: PSF = Sale Price / GBA (or GLA)

     • Application: Useful for properties where size is a primary driver of value, such as residential homes, office buildings, and retail spaces.
     • Experiment: Collect data on recent home sales in a neighborhood. Calculate the PSF for each sale. Graph the PSF against house size. Observe the correlation – is it linear? Does PSF decrease with increasing size (economies of scale)?

  2. Price per Acre (PPA): Calculated by dividing the sale price by the land area in acres. Equation: PPA = Sale Price / Land Area (acres)

     • Application: Suitable for vacant land, agricultural properties, and large residential lots.
     • Experiment: Research vacant land sales. Analyze if PPA decreases as parcel size increases (bulk discount principle❓).

  3. Price per Unit (PPU): Calculated by dividing the sale price by the number of units in the property (e.g., apartments in an apartment building). Equation: PPU = Sale Price / Number of Units

     • Application: Used for income-producing properties like apartments, duplexes, and mobile home parks.
     • Experiment: Analyze recent apartment building sales. Investigate the correlation between PPU and factors like the number of bedrooms per unit, occupancy rate, or average rent.

  4. Price per Room: Calculated by dividing the sale price by the number of rooms.

     • Application: Rarely used because the meaning of the term ‘room’ is not standardised enough.

  5. Other Units: The choice of unit depends on the specific property type and market characteristics. Examples include:

     • Price per Front Foot (commercial land)
     • Price per Parking Space (parking garages)
     • Gross Income Multiplier (GIM) or Net Income Multiplier (NIM) (income-producing properties; these are technically ratios, but serve a similar comparison purpose).

• Selecting the Appropriate Unit:

  • Market Analysis: Identify which characteristics are most influential on value in the subject property’s market.
  • Data Availability: Choose a unit for which reliable data is readily available from comparable sales.
  • Homogeneity: Select a unit that minimizes the need for excessive adjustments.

3.2 The Adjustment Process: Bridging the Gap

The adjustment process is the core of the Sales Comparison Approach. It involves analyzing the differences between comparable properties and the subject property, and then quantifying and applying these differences to the comparable sale prices.

• Definition: The process of analyzing and quantifying differences between comparable properties and the subject property to arrive at an adjusted indication of value.

• Fundamental Principle: The principle of contribution – the value of a component is measured by the amount it adds to the overall value of the property. This is rooted in microeconomic theory regarding marginal utility.

• Types of Adjustments:

  1. Quantitative Adjustments: Based on numerical data and statistical analysis.

     • Paired Sales Analysis: Identifies two comparable sales that are virtually identical except for one specific characteristic. The price difference between the two sales isolates the value of that characteristic.
       • Example: Two identical houses sold within the same time frame. One has a garage; the other does not. The difference in sale price is attributed to the value of the garage.
       • Formula: Adjustment = Sale Price (with characteristic) - Sale Price (without characteristic)
     • Statistical Analysis: Uses regression analysis or other statistical methods to quantify the relationship between property characteristics and sale prices.
       • Regression Analysis: A statistical technique used to model the relationship between a dependent variable (e.g., sale price) and one or more independent variables (e.g., GLA, lot size, age). The regression equation provides coefficients that represent the estimated impact of each independent variable on the sale price.
         • Simple Linear Regression: Y = a + bX
           • Y = Dependent variable (e.g., sale price)
           • X = Independent variable (e.g., GLA)
           • a = Y-intercept (constant)
           • b = Slope (coefficient representing the change in Y for each unit change in X)
         • Multiple Linear Regression: Y = a + b1X1 + b2X2 + ... + bnXn
           • Y = Dependent variable (e.g., sale price)
           • X1, X2, ..., Xn = Independent variables (e.g., GLA, lot size, age)
           • a = Y-intercept (constant)
           • b1, b2, ..., bn = Coefficients representing the change in Y for each unit change in X, holding other variables constant.
       • Caution: Statistical analyses rely on sufficient data and should be interpreted with caution, considering the R-squared value (indicating the proportion of variance explained by the model) and the significance of the coefficients.
     • Cost-Related Adjustments: Uses the cost to cure or cost to replace as a basis for adjustment.
       • Example: A comparable property lacks central air conditioning, while the subject property has it. The adjustment could be based on the cost of installing central air conditioning in the comparable property.
       • Formula: Adjustment = Cost to Cure (or Replace)
     • Capitalization of Rent Difference: Calculates the appropriate adjustment by capitalizing the rent different of two comparable properties.
       • Formula: Adjustment = Rent Difference / Capitalization Rate

  2. Qualitative Adjustments: Based on subjective judgment and market knowledge when quantitative data is insufficient or unreliable.

     • Relative Comparison Analysis: Compares the subject and comparable properties based on various characteristics (e.g., location, condition, amenities) and assigns a rating of “superior,” “inferior,” or “equal” for each characteristic. The overall adjustment is then made based on a holistic assessment of the relative strengths and weaknesses.
     • Ranking: Assigns ranks to the comparable sales based on their overall similarity to the subject property. The sales with higher ranks are given more weight in the final reconciliation.
     • Scenario Analysis: Considers multiple potential scenarios and their potential impact on value.

• Order of Adjustments: While there is no universally agreed-upon rigid order, a common and logical sequence is:

  1. Financing Terms: Adjust for any atypical or creative financing arrangements that affected the sale price. (The example review exercises 2 on page 222 of the Student Handbook addresses a typical financing adjustment.
  2. Conditions of Sale: Adjust for any unusual circumstances surrounding the sale (e.g., duress, related-party transaction).
  3. Market Conditions (time adjustment❓❓): Adjust for changes in market conditions between the date of sale of the comparable and the date of value of the subject property. (The example review exercises 6 on page 223 of the Student Handbook addresses a typical market/time adjustment).
     • Formula: Adjusted Price = Sale Price * (1 + Appreciation Rate)^Time Difference (Assuming straight-line appreciation).
  4. Location: Adjust for differences in location that affect value (e.g., proximity to amenities, schools, noise levels).
  5. Physical Characteristics: Adjust for differences in physical attributes (e.g., size, age, condition, features).
  6. Legal Characteristics: Adjust for any differences in title, restrictions or property rights transferred.

• Applying Adjustments:

  • If the comparable is INFERIOR to the subject, ADD to the comparable’s sale price.
  • If the comparable is SUPERIOR to the subject, SUBTRACT from the comparable’s sale price.

• Percentage vs. Dollar Adjustments:

  • Dollar Adjustments: Generally preferred for items where the value impact is relatively stable and independent of the overall sale price (e.g., a garage, a swimming pool).
  • Percentage Adjustments: May be appropriate for items where the value impact is proportional to the sale price (e.g., location, overall condition).
  • Best Practice: Justify the choice of dollar or percentage adjustments based on market evidence.

3.3 Reconciliation and Value Conclusion

After making all necessary adjustments to the comparable sales, the appraiser must reconcile the adjusted sale prices to arrive at a final value indication for the subject property.

• Definition: The process of weighing the adjusted sale prices of the comparable properties and arriving at a single value indication for the subject property.

• Reconciliation is NOT averaging: The appraiser should not simply average the adjusted sale prices. Instead, the appraiser should consider the following factors:

  1. Number of Adjustments: Sales requiring fewer adjustments are generally more reliable indicators of value.
  2. Magnitude of Adjustments: Sales with smaller adjustments are generally more reliable.
  3. Data Source Reliability: Give greater weight to sales where the data is verified and from reliable sources.
  4. Similarity to Subject: Give greater weight to sales that are most similar to the subject property in terms of key characteristics.

• Range of Value: The adjusted sale prices of the comparable properties will typically fall within a range. The appraiser must select a single point estimate within that range that represents the most probable market value of the subject property.

• Supporting the Conclusion: The final value conclusion must be supported by a clear and well-reasoned analysis of the market data and the adjustment process. The appraisal report should clearly document the rationale for each adjustment and the factors considered in the reconciliation process.

3.4 Practical Applications and Experiments

The following practical applications and experiments are designed to solidify your understanding of units of comparison and adjustments.

1. Paired Sales Analysis Experiment:

   • Objective: Determine the market value of a swimming pool.
   • Procedure: Identify two comparable house sales in the same neighborhood that are identical except that one has a swimming pool and the other does not.
   • Data Collection: Gather detailed information on the two sales, including sale price, date of sale, and property characteristics.
   • Analysis: Calculate the price difference between the two sales. This difference represents the market value of the swimming pool.
   • Report: Document the findings, including the sales data, the calculated adjustment, and a discussion of any limitations.

2. Time Adjustment Exercise:

   • Objective: Determine the appropriate time adjustment for a specific market area.
   • Procedure: Research sales and resales of comparable properties in the target market area over a specified period.
   • Data Collection: Record the sale price and date of each sale and resale.
   • Analysis: Calculate the annual appreciation rate for each property by dividing the price difference between the sale and resale by the original sale price and the time between sales.
   • Reconciliation: Reconcile the individual appreciation rates to arrive at a market-supported appreciation rate.
   • Report: Document the data, calculations, and the concluded appreciation rate. This rate can then be used to make time adjustments to comparable sales.

3. Gross Building Area Adjustment Exercise:

   • Objective: Determine the appropriate GBA adjustment in an urban market.
   • Procedure: Choose a city and research a type of property (e.g. one-bedroom condos).
   • Data Collection: Record the sale price and GBA of comparable one-bedroom condos.
   • Analysis: Calculate the price per square foot for each comparable.
   • Reconciliation: Use regression analysis to determine the linear relationship between price per square foot and GBA.
   • Report: Document the data, calculations, and the concluded GBA adjustments.

3.5 Conclusion

Mastering the application of units of comparison and adjustments is essential for performing credible real estate appraisals using the Sales Comparison Approach. By understanding the theoretical principles and applying scientifically sound methods, appraisers can provide reliable value indications that are well-supported by market data.

Remember, this is a simplified overview. Further study and practical experience are necessary to fully master this critical aspect of real estate appraisal.