Real Estate Appraisal: Foundational Data Analysis

Chapter 5: Real Estate Appraisal: Foundational Data Analysis

I. Introduction: The Cornerstone of Appraisal - Data Analysis

Real estate appraisal relies heavily on the thorough and scientific analysis of various types of data. This chapter lays the foundation for understanding the fundamental principles and practices of data analysis within the appraisal context. We will explore the different categories of data that inform the appraisal process, and discuss how this data is collected, organized, and analyzed to arrive at a credible value opinion. Proper data analysis is not merely a procedural step but the very core of reliable appraisal practice.

II. Data Classification and Relevance

The raw data available to an appraiser can be vast and varied. It is crucial to classify this data and determine its relevance to the specific appraisal assignment. Data can be categorized in several ways, but a common approach is by its scope and focus:

• Market Trend Data (General Data): Broad economic, social, governmental, and environmental factors influencing real estate values. These are not specific to a single property but affect the overall market.
• Competitive Supply and Demand Data: Data specific to the local market, indicating the balance between available properties and the demand for them.
• Subject Property Data: Information directly pertaining to the physical and legal characteristics of the property being appraised.
• Comparable Property Data: Information about similar properties that have recently sold or are currently available in the market.

An important consideration is the relevance of data. Not all data is pertinent to every appraisal. The appraiser must exercise professional judgment to identify and focus on the information that truly impacts the subject property’s value.

Example: While government statistics might show a trend towards smaller households, this data may be less relevant than income levels when appraising larger, more expensive homes. The demand for these homes may be more closely tied to household income and interest rates than household size.

III. Market Trend Data: Understanding the Macro Environment

Market trend data, also known as general data, provides a broad overview of the forces shaping the real estate market. It helps the appraiser understand the overall economic climate and its potential impact on property values. Key areas of focus include:

1. Economic Factors:
   • Gross Domestic Product (GDP): A measure of the total value of goods and services produced in an economy.
     • Formula: GDP = C + I + G + (X – M), where C = Consumption, I = Investment, G = Government Spending, X = Exports, and M = Imports.
     • A growing GDP typically indicates a healthy economy, which can lead to increased demand for real estate.
   • Inflation Rate: The rate at which the general level of prices for goods and services is rising, and subsequently, purchasing power is falling.
     • High inflation can erode purchasing power and increase interest rates, potentially dampening real estate demand.
   • Interest Rates: The cost of borrowing money.
     • Lower interest rates make mortgages more affordable, potentially boosting demand.
   • Unemployment Rate: The percentage of the labor force that is unemployed.
     • High unemployment can negatively impact consumer confidence and reduce demand for housing.
   • Wage Growth: The rate at which wages are increasing.
     • Strong wage growth supports consumer spending and can drive demand for real estate.
2. Social Factors:
   • Population Growth: Changes in the number of people living in an area.
     • Population growth typically increases demand for housing.
   • Demographic Shifts: Changes in the age, ethnicity, and household composition of the population.
     • These shifts can influence the types of housing demanded (e.g., smaller homes for retirees, larger homes for families).
   • Lifestyle Trends: Changes in how people choose to live and spend their time.
     • For example, an increased desire for walkable neighborhoods or urban living can impact property values in those areas.
3. Governmental Factors:
   • Zoning Regulations: Rules that govern how land can be used.
     • Changes in zoning can affect the supply of land available for development and impact property values.
   • Tax Policies: Government policies related to taxes on real estate.
     • Property taxes, capital gains taxes, and mortgage interest deductions can all influence real estate investment decisions.
   • Infrastructure Development: Government investment in roads, schools, and other public services.
     • Improved infrastructure can increase the desirability and value of nearby properties.
4. Environmental (Physical) Factors:
   • Climate: Weather patterns and seasonal variations.
     • Climate can significantly impact property values, particularly in areas prone to extreme weather events.
   • Natural Resources: Availability of water, minerals, and other natural resources.
     • Access to resources can impact land values and development potential.
   • Environmental Regulations: Laws and regulations designed to protect the environment.
     • Environmental regulations can restrict development and impact property values.

Practical Application: An appraiser analyzing a coastal property needs to consider factors such as sea-level rise projections, flood zone designations, and the availability of flood insurance, all of which can impact the property’s marketability and value.

IV. Competitive Supply and Demand Data: Focusing on the Local Market

Competitive supply and demand data is a specialized form of market trend data that focuses on the specific local market relevant to the subject property. This data provides insights into the balance between the number of properties available for sale or rent (supply) and the number of potential buyers or renters (demand).

1. Supply Data:
   • Existing Inventory: The number of currently listed properties in the market.
   • New Construction: The number of new properties being built or planned for development.
   • Vacancy Rates: The percentage of properties that are unoccupied.
   • Absorption Rates: The rate at which new properties are being sold or rented.
   • Land Availability: The amount of vacant land suitable for development.
   • Potential Conversions: Properties that could be converted to residential use (e.g., office buildings).
2. Demand Data:
   • Employment Levels: The number of people employed in the area.
   • Wage Levels: The average wages earned by workers in the area.
   • Population Growth: Changes in the number of people living in the local market.
   • Household Formation: The rate at which new households are being formed.
   • Consumer Confidence: A measure of how optimistic consumers are about the economy.
   • Migration Patterns: The movement of people into or out of the area.

Analysis: Analyzing supply and demand data helps the appraiser determine whether the market is a buyer’s market (more supply than demand), a seller’s market (more demand than supply), or a balanced market. This understanding informs the appraiser’s valuation process and helps explain market trends to the client.

Example: A large influx of new apartment buildings in a specific neighborhood might increase the supply of rental units, leading to lower rents and higher vacancy rates, potentially affecting the value of existing rental properties.

V. Subject Property Data: Understanding the Unique Characteristics

Subject property data refers to all information that is specific to the property being appraised. This includes:

1. Physical Characteristics:
   • Size: Square footage, lot size, number of rooms, etc.
   • Condition: Overall state of repair and maintenance.
   • Floor Plan: Layout and functionality of the interior spaces.
   • Architectural Style: Design and appearance of the building.
   • Amenities: Features such as pools, garages, fireplaces, etc.
   • Landscaping: Appearance and maintenance of the grounds.
2. Legal Characteristics:
   • Ownership: Type of ownership (e.g., fee simple, leasehold).
   • Zoning: Permitted uses for the property.
   • Easements: Rights granted to others to use the property.
   • Restrictions: Limitations on the use of the property (e.g., covenants, conditions, and restrictions - CC&Rs).
3. Economic Characteristics:
   • Terms of Sale: Financing arrangements, concessions, or other conditions of the sale.
   • Rental Income: If the property is income-producing.
   • Operating Expenses: Costs associated with owning and operating the property.

Relevance: The appraiser must determine which characteristics are most relevant to the property’s value in the specific market. Some characteristics, such as size, location, and condition, are virtually always relevant. Others, such as a swimming pool, may be desirable in one market but undesirable or irrelevant in another.

Experiment: An appraiser might conduct a paired-data analysis, comparing the sales prices of similar properties with and without a swimming pool, to determine the pool’s contribution to value in a particular market.

VI. Comparable Property Data: Finding the Best Matches

Comparable property data is information about properties that are similar to the subject property and have recently sold or are currently listed for sale. These properties, often called “comps,” are used to estimate the value of the subject property through the sales comparison approach. To be considered a true comparable, a property should ideally:

1. Have Similar Physical Characteristics: Similar size, age, style, condition, and features.
2. Be Competitive: Appeal to the same types of buyers or renters as the subject property.
3. Be Located in the Same Market Area: Be subject to the same market forces and neighborhood influences.
4. Have Sold Within a Limited Time: Typically within the past six months, but this can vary depending on market conditions.

Data Sources: Common sources of comparable property data include:

• Multiple Listing Service (MLS): A database of properties listed for sale by real estate agents.
• Public Records: County assessor’s offices, recorder’s offices, and other government agencies.
• Real Estate Professionals: Brokers, agents, and other appraisers.
• Online Databases: Commercial real estate data providers.

Data Elements: The appraiser typically gathers the following data elements for each comparable property:

• Sales Price: The price at which the property was sold.
• Date of Sale: The date on which the transaction closed.
• Property Address: The location of the property.
• Physical Characteristics: As described above for subject property data.
• Financing Terms: Information about the mortgage and other financing arrangements.
• Conditions of Sale: Any unusual circumstances surrounding the sale (e.g., foreclosure, short sale).
• Photos: Images of the property.

Formula (Simplified Adjustment Model):

Adjusted Sale Price (Comparable) = Sale Price (Comparable) ± Dollar Adjustment for Differences

The appraiser adjusts the sale price of each comparable property to account for differences between the comparable and the subject property. These adjustments are typically based on market data and the appraiser’s professional judgment.

Example: If a comparable property has a larger lot than the subject property, the appraiser might deduct an amount from the comparable’s sale price to reflect the value of the larger lot.

VII. Regional and Community Data

Regional and community data reflects the effects of local social, economic, governmental and physical forces on value. The interaction of these forces influence real estate values, either for better or for worse.

A. USE OF REGIONAL AND COMMUNITY DATA

The collection and analysis of regional and community data is essential to the appraisal process for several reasons. First, it helps the appraiser identify the particular characteristics of properties that increase or decrease value.

B. REGIONAL AND COMMUNITY VALUE