Appraisal Data: Sources and Analysis

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Chapter 4: Appraisal Data: Sources and Analysis

I. Introduction: The Foundation of Sound Valuation

Appraisal is not merely an art; it’s a discipline built on a rigorous foundation of data. The accuracy and reliability of an appraisal hinge directly on the data gathered and the methods employed to analyze it. This chapter delves into the crucial aspects of appraisal data, exploring its various sources, the methods for analyzing it, and the scientific principles that underpin these processes. A robust understanding of appraisal data ensures well-supported and defensible valuations.

II. Categorizing Appraisal Data: A Multifaceted Approach

Data can be classified based on its scope and source:

• A. Scope-Based Classification:
  • 1. General Data: Broad economic, social, governmental, and environmental forces that influence real estate values. This type of data helps understand market trends.
    • Example: Interest rates, unemployment rates, population growth, inflation, zoning regulations, climate change patterns.
  • 2. Specific Data: Pertains directly to the subject property and comparable properties.
    • Example: Property size, age, condition, amenities, recent sales prices, rental rates.
• B. Source-Based Classification:
  • 1. Primary Data: Information collected directly by the appraiser through observation, inspection, surveys, and interviews.
    • Example: Measuring the subject property’s dimensions, noting the condition of building materials, interviewing neighborhood❓ residents, inspecting comparable properties.
  • 2. Secondary Data: Information obtained from existing sources such as public records, industry publications, and online databases.
    • Example: County property records, MLS data, government economic reports, appraisal databases, CoStar (for commercial properties).

III. The Appraisal Process & Data Application

The data gathering and analysis effort is focused on different objectives in the appraisal process, with the most common reasons being:
* Identifying market trends that may affect real estate values
* Identifying the probable future supply and demand of competitive properties
* Determining the characteristics of the subject property that will affect its value
* Determining characteristics of comparable properties that will affect their values

IV. Key Data Categories and Sources

The following sections detail the primary categories of data that appraisers need, along with typical sources and analytical techniques used for each:

• A. Regional and Community Data: Macroeconomic Influences

  • 1. Description: Broad economic, social, governmental, and environmental forces impacting the entire region or community. This data provides the context for understanding local market dynamics.
  • 2. Key Elements:
    • Economic Base: Industries that drive the local economy (e.g., manufacturing, tourism, technology). Understand industry growth or decline trends.
    • Infrastructure: Transportation networks (roads, airports, public transit), utilities (water, electricity, internet), and public services (schools, hospitals, emergency services).
    • Demographics: Population size, age distribution, income levels, household size, education levels. Analyze population growth or decline trends.
    • Governmental Factors: Zoning regulations, building codes, property taxes, environmental regulations, economic development incentives.
    • Natural Environmental Factors: Climate, topography, natural resources, susceptibility to natural disasters.
  • 3. Data Sources:
    • U.S. Census Bureau (demographic data).
    • Bureau of Labor Statistics (employment data).
    • Local economic development agencies.
    • Chambers of Commerce.
    • City and county planning departments (zoning, infrastructure).
    • State government agencies.
    • Universities and research institutions.
    • Real estate publications.

• B. Neighborhood Data: Microeconomic Influences

  • 1. Description: Focuses on specific areas within a community, exploring local market forces and property characteristics. This data helps assess the desirability and stability of the subject property’s immediate surroundings.
  • 2. Key Elements:
    • Boundaries: Physical (rivers, roads), zoning changes, or other distinct features that delineate the neighborhood.
    • Land Use: Mix of residential, commercial, and industrial properties. Percentage of each land use type and potential for land use change.
    • Property Values: Trends in sales prices, rents, vacancy rates.
    • Property Ages: A range and predominant age that gives an indication of overall physical condition.
    • Supply and Demand: Number of properties listed for sale/rent, average marketing time, absorption rates (how quickly properties are sold/rented).
    • Demographics: Social attitudes, income, and quality of schools.
    • Negative and Positive Factors: Influences such as noise, traffic, environmental concerns, aesthetic qualities, access to amenities, the quantity, age, and condition of the various types of properties, the traffic patterns, the presence of negative value influences, and overall neighborhood quality and appeal.
  • 3. Data Sources:
    • Multiple Listing Service (MLS) data (sales prices, listings).
    • Local real estate agents and brokers.
    • Neighborhood associations.
    • City and county planning departments.
    • Property tax assessor records.
    • Field inspections (driving around the neighborhood).
    • Interviews with residents.

• C. Site Data: Physical Characteristics and Legal Considerations

  • 1. Description: Information specific to the land on which the subject property is located. This data helps assess the site’s suitability for its current and potential uses.
  • 2. Key Elements:
    • Legal Description: Metes and bounds, lot and block, or rectangular survey descriptions. Ensures the accurate identification of the property’s boundaries.
    • Size and Dimensions: Lot area, frontage, depth.
    • Topography: Slope, drainage, and soil composition for construction or suitability.
    • Utilities: Availability and type of water, sewer, electricity, gas, and internet services.
    • Zoning: Permitted uses, setback requirements, building height restrictions.
    • Easements and Restrictions: Rights of way, utility easements, deed restrictions.
    • FEMA Flood Zone: Determining flood risks that might require insurance.
    • Site Improvements: Landscaping, fencing, driveways, retaining walls.
  • 3. Data Sources:
    • County recorder’s office (deeds, plats, easements).
    • City and county planning departments (zoning maps).
    • Utility companies.
    • Soil survey maps.
    • Surveyors.
    • FEMA flood maps (available online).
    • Visual inspection of the site.

• D. Building Data: Characteristics of the Improvements

  • 1. Description: Details of the physical structure on the site, including its size, condition, and features. This data is critical for determining the cost to reproduce the property, the amount of depreciation, and overall quality.
  • 2. Key Elements:
    • Size: Gross Living Area (GLA), number of rooms, number of stories.
    • Age and Condition: Effective age, overall condition rating (e.g., excellent, good, fair, poor).
    • Construction Quality: Materials used, workmanship, architectural style.
    • Foundation: Type (slab, crawl space, basement), materials (concrete, block), condition.
    • Exterior: Siding, roofing, windows, doors. Materials and condition.
    • Interior: Wall finishes (drywall, plaster), flooring (carpet, hardwood, tile), cabinetry, fixtures, appliances.
    • Heating, Ventilation, and Air Conditioning (HVAC): Type of system (central air, heat pump, forced air), fuel source, age, and efficiency rating.
    • Special Features: Fireplaces, swimming pools, decks, patios, garages.
    • Energy Efficiency: Insulation, high-efficiency windows, solar panels, tankless water heaters, other green features.
  • 3. Data Sources:
    • Visual inspection of the property (measuring dimensions, noting materials and condition).
    • Building permits.
    • Architectural plans (if available).
    • Contractors and building experts (for cost estimates).

• E. Specific Market Data: Comparable Property Information

  • 1. Description: Information on similar properties that have recently sold or rented in the same market area. This data forms the basis for the Sales Comparison❓❓ approach❓❓ and the Income Approach to valuation.
  • 2. Key Elements:
    • Sales Price: The actual price paid for the property.
    • Date of Sale: Critical for making adjustments for market conditions.
    • Financing Terms: Type of mortgage, interest rate, points, seller concessions.
    • Conditions of Sale: Arm’s length transaction, motivations of buyer and seller.
    • Location and Physical Characteristics: As described in Site Data and Building Data sections above. Pay close attention to similarities and differences between the comparable properties and the subject property.
    • Income and Expenses (for income-producing properties): Gross income, operating expenses, vacancy rates, net operating income (NOI).
    • Rental rates, vacancies.
  • 3. Data Sources:
    • Multiple Listing Service (MLS).
    • County recorder’s office (deeds).
    • Commercial real estate databases (CoStar, LoopNet).
    • Real estate appraisers.
    • Real estate agents and brokers.
    • Property owners.
    • FNC, Inc. and Corelogic

V. Data Analysis: Extracting Meaning from Information

Gathering data is only half the battle. Appraisers must employ analytical techniques to transform raw data into meaningful value indicators.

• A. Highest and Best Use Analysis:

  • 1. Principles: As previously outlined, a property’s Highest and Best Use (HBU) is the most probable use of a property that is physically possible, legally permissible, financially feasible, and results in the maximum value. Analysis must be conducted for both the land as if vacant and the property as improved.
  • 2. Analytical Methods:
    • Market analysis: To assess the demand for different potential land uses.
    • Feasibility studies: To determine the economic viability of different development scenarios.
    • Comparative analysis: Evaluating potential uses relative to other similar properties.

  • B. Sales Comparison Analysis:

  • 1. Principles: The Sales Comparison Approach, also known as the market data approach, estimates value by comparing the subject property to similar properties that have recently sold.

  • 2. Analytical Methods:
    • Identifying comparable sales: Selecting properties with similar characteristics to the subject.
    • Making adjustments: Quantifying and applying adjustments to the comparable sales prices to account for differences in location, size, condition, features, and financing terms.
    • Quantitative Adjustments: adjustments for physical characteristics or market conditions (ex: $5,000 for additional bedroom)
    • Qualitative Adjustments: comparative analysis (ex: property is rated “superior” for quality of construction)
  • 3. Formula: Subject Value = Comparable Sales Price +/- Adjustments
  • C. Cost Approach Analysis:
  • 1. Principles: The Cost Approach estimates value by summing the value of the land and the depreciated cost of the improvements.
  • 2. Analytical Methods:
    • Estimating land value: Using one of the methods described below.
    • Estimating reproduction or replacement cost: Using cost manuals or consulting with contractors.
    • Estimating depreciation: Identifying and quantifying physical deterioration, functional obsolescence, and external obsolescence.
  • 3. Formula: Property Value = Land Value + (Cost New - Depreciation)
  • D. Income Capitalization Analysis:
  • 1. Principles: The Income Approach estimates value based on the income the property is expected to generate.
  • 2. Analytical Methods:
    • Estimating potential gross income: Based on market rental rates and occupancy rates.
    • Estimating operating expenses: Projecting all expenses associated with owning and operating the property.
    • Calculating net operating income (NOI): Subtracting operating expenses from potential gross income.
    • Capitalizing NOI: Dividing NOI by a capitalization rate to arrive at an estimate of value.
  • 3. Formula: Value = NOI / Capitalization Rate

• E. Site Valuation Methods:

  • 1. Sales Comparison: (Most reliable) Compare sales of similar vacant parcels to determine the value of the subject land or site, making adjustments for differences in location, size, zoning, and other factors.
  • 2. Allocation Method: Assume a certain percentage of a property’s value is attributable to the land. This method is generally considered less reliable.
  • 3. Extraction Method: Estimate the land value for an improved property by subtracting the depreciated cost of the improvements from the total sale price. This method is most effective when improvements represent a small portion of the total value.
  • 4. Development Method: (Subdivision analysis) Project the revenues and expenses from developing a vacant parcel and discount future cash flows to arrive at a present value for the land. This requires detailed market research and accurate projections.
  • 5. Land Residual Method: If the rent can be clearly divided into land and the improvements, it should be estimated based on what the land is responsible for bringing into the value of the total rent.
  • 6. Ground Rent Capitalization: Use the ground rent to determine the proper percentage to bring land value to the total property value.

VI. The Role of Technology in Data Collection and Analysis

Technology has revolutionized the appraisal process, providing appraisers with access to vast amounts of data and sophisticated analytical tools.

• A. Online Databases: MLS, CoStar, and other databases provide detailed property information, sales histories, and market trends.
• B. Geographic Information Systems (GIS): GIS software allows appraisers to visualize and analyze spatial data, such as zoning maps, flood zones, and demographic information.
• C. Statistical Software: Software packages like SPSS and R can be used to perform statistical analysis on large datasets.
• D. Mobile Apps: Mobile devices and specialized appraisal apps streamline data collection in the field and provide access to information on the go.
  Inspection data entered onsite.
  Sketches are more accurate, with precise measurements available through laser measuring devices.
  Nearly unlimited number of photos can be downloaded as they are saved in the cloud and not in a physical file.
  Numerous comps can be accessed and stored for use on other appraisals.
  Directions, maps, and voice notes are easily accessible from a mobile device.
  Dozens of the most commonly used forms are available through these online apps and can be filled out immediately in the field, synced with other devices, and information transferred from one form to another without having to re-enter the information on each separate form.

VII. Conclusion: The Importance of Data Integrity and Sound Analysis

The foundation of a reliable appraisal rests upon accurate and comprehensive data, coupled with sound analytical techniques. Appraisers must be diligent in gathering and verifying data from reputable sources, understanding the strengths and limitations of each data source, and applying appropriate analytical methods to extract meaningful value indicators.

VIII. Review Questions:

1. Discuss the differences between general and specific appraisal data.
2. How do you classify data as primary versus secondary, and what are some examples of each?
3. What is ‘competitive supply and demand data’ and why is this data important to collect?
4. In what order do comparable sales price adjustments usually occur and why?

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