Data Sources: Macro & Micro Analysis

Chapter: Data Sources: Macro & Micro Analysis

Introduction

Real estate appraisal relies heavily on comprehensive data collection and analysis. Understanding the distinction between macro-level (economic and demographic trends) and micro-level (property-specific and local market details) data is crucial for accurate valuation. This chapter explores various sources of both types of data, emphasizing their relevance, limitations, and application in appraisal practice.

1. Macro-Level Data Analysis

Macro-level analysis considers broader economic, demographic, and governmental factors influencing real estate values. It seeks to understand the overall market conditions and their impact on specific properties.

1.1 Economic Indicators

Economic indicators provide insights into the overall health and direction of the economy. They include:

• Gross Domestic Product (GDP): The total value of goods and services produced within a country’s borders in a specific period. It indicates overall economic activity.

  • Formula: GDP = C + I + G + (X – M), where C = Consumption, I = Investment, G = Government Spending, X = Exports, and M = Imports.

  • Application: A rising GDP typically indicates economic growth, potentially increasing demand for real estate. A declining GDP may signal recessionary pressures, potentially reducing demand.

• Inflation Rate: The rate at which the general level of prices for goods and services is rising, and subsequently, purchasing power is falling.

  • Formula: Inflation Rate = ((CPI Current Year – CPI Previous Year) / CPI Previous Year) ) * 100, where CPI is the Consumer Price Index.

  • Application: High inflation erodes purchasing power and can lead to higher interest rates, potentially dampening real estate investment.

• Unemployment Rate: The percentage of the labor force that is unemployed and actively seeking employment.

  • Application: A low unemployment rate generally indicates a strong economy, potentially boosting demand for housing. High unemployment can lead to foreclosures and decreased property values.

• Interest Rates: The cost of borrowing money, typically expressed as an annual percentage.

  • Application: Lower interest rates make mortgages more affordable, increasing demand for real estate. Higher interest rates can reduce affordability and cool the market.
  • Example: The Federal Reserve’s decisions on the federal funds rate significantly impact mortgage rates and, consequently, the real estate market.

• Consumer Confidence Index (CCI): A measure of consumers’ optimism regarding the state of the economy and their personal financial situations.

  • Application: High consumer confidence indicates greater willingness to spend and invest, potentially driving demand for real estate.

1.2 Demographic Trends

Demographic trends examine population characteristics and their changes over time, impacting housing demand and preferences.

• Population Growth: The rate at which the population is increasing or decreasing in a specific area.

  • Formula: Population Growth Rate = ((Population End Year – Population Start Year) / Population Start Year) * 100

  • Application: Rapid population growth often leads to increased demand for housing and infrastructure.

• Household Formation: The rate at which new households are being formed.

  • Application: A high household formation rate signifies increased demand for housing units.

• Age Distribution: The distribution of the population across different age groups.

  • Application: An aging population may lead to increased demand for retirement communities and healthcare facilities. A younger population may drive demand for starter homes and schools.

• Migration Patterns: The movement of people from one area to another.

  • Application: In-migration to a region can boost housing demand and property values.

• Education Levels: The educational attainment of the population.

  • Application: Higher education levels often correlate with higher incomes and greater demand for quality housing.

1.3 Governmental and Regulatory Factors

Government policies and regulations can significantly influence real estate markets.

• Tax Policies: Tax incentives or disincentives related to homeownership or real estate investment.

  • Application: Mortgage interest tax deductions can stimulate homeownership. Property taxes affect the overall cost of owning real estate.

• Zoning Regulations: Rules governing land use and development.

  • Application: Zoning ordinances can restrict the type and density of development in certain areas, influencing property values.

• Environmental Regulations: Laws protecting the environment that may affect land use and development.

  • Application: Restrictions on development in environmentally sensitive areas can limit the supply of developable land, potentially increasing property values in other areas.

• Building Codes: Standards for construction and safety.

  • Application: Stricter building codes can increase construction costs but also improve the quality and durability of buildings.

• Fiscal and Monetary Policies: Government spending, taxation, and interest rate policies.

  • Application: Expansionary fiscal policy (increased government spending) can stimulate economic growth and boost real estate demand. Contractionary monetary policy (higher interest rates) can slow down the economy and cool the real estate market.

1.4 Sources of Macro-Level Data (Examples)

• Government Agencies:

  • U.S. Bureau of Economic Analysis (BEA) (https://apps.bea.gov/scb/index.htm): Provides data on GDP, inflation, and other economic indicators.
  • U.S. Department of Housing and Urban Development (HUD) (www.hud.gov): Offers reports on housing starts, financing, and vacancy surveys.
  • U.S. Bureau of Labor Statistics (BLS) (http://stats.bls.gov/opub/mlr/mlrhome.htm): Publishes data on employment, unemployment, and wage rates.
  • U.S. Census Bureau (www.census.gov): Provides detailed demographic data, including population, household characteristics, and housing statistics.

• State and Local Agencies:

  • Departments of development, planning agencies, state demographers, and transportation authorities.

• Real Estate Associations:

  • National Association of Realtors (NAR) (www.nar.realtor & www.houselogic.com).
  • Appraisal Institute (www.appraisers.org).
  • American Real Estate Society (ARES) (www.aresnet.org).

• Private Sources:

  • Banks, utility companies, university research centers (e.g., https://robinson.gsu.edu/research/, www.lincolninst.edu/research-data/data-toolkits, https://wsb.wisc.edu/faculty-research/academic-departments/real-estate/featured), and private advisory firms.

2. Micro-Level Data Analysis

Micro-level analysis focuses on specific properties, neighborhoods, and local market conditions. It involves gathering detailed information about the subject property and comparable properties to determine value.

2.1 Property Characteristics

Gathering detailed information about the subject property is the first step in micro-level data analysis.

• Physical Attributes: Size, age, condition, design, materials, amenities, and unique features.
• Legal Attributes: Ownership rights, deed restrictions, easements, and zoning compliance.
• Location Attributes: Neighborhood characteristics, accessibility, proximity to amenities, schools, and transportation.

2.2 Market Data

Analyzing comparable sales and listings is crucial for determining market value.

• Comparable Sales: Properties similar to the subject property that have recently sold in the same market area.

  • Analysis: Adjustments are made to the sale prices of comparable properties to account for differences in features, location, and market conditions relative to the subject property.
    • Formula: Adjusted Sale Price = Sale Price ± Adjustments for Differences
    • Example: If a comparable property sold for $300,000 but has a superior view (worth $10,000), the adjusted sale price would be $300,000 - $10,000 = $290,000, assuming the subject property does not have this amenity.

• Listing Data: Properties currently offered for sale that are similar to the subject property.

  • Analysis: Listing prices indicate the upper limit of value and provide insights into market sentiment.
• Rent Data: For income-producing properties, analyzing comparable rental rates is essential.
  • Analysis: Gross Rent Multiplier (GRM) is used to estimate value based on gross rental income.
    • Formula: GRM = Sale Price / Gross Annual Rent
    • Application: If comparable properties are selling at a GRM of 10, and the subject property has a gross annual rent of $30,000, the estimated value would be $30,000 * 10 = $300,000.

2.3 Neighborhood Analysis

Understanding the characteristics of the neighborhood is vital for assessing property values.

• Neighborhood Boundaries and Characteristics: Defining the boundaries of the neighborhood and identifying its unique features, such as housing styles, demographics, and amenities.
• Property Values and Trends: Analyzing property values and trends within the neighborhood to determine whether values are increasing, decreasing, or stable.
• Amenities and Services: Assessing the availability and quality of amenities and services, such as schools, parks, shopping centers, and transportation options.
• Quality of Life Factors: Evaluating factors that affect the quality of life in the neighborhood, such as crime rates, traffic congestion, and environmental conditions.

2.4 Sources of Micro-Level Data (Examples)

• Public Records:

  • County recorder’s office: Property deeds, mortgages, and other legal documents.
  • Tax assessor’s office: Property tax records, including assessed value, land and building sketches, and sales information.

• Multiple Listing Service (MLS):

  • Comprehensive database of properties listed for sale, including descriptions, prices, and photographs.

• Commercial Real Estate Services Sites:

  • CoStar (www.costar.com): Database of researched information including properties for sale, properties for lease, verified comparable sales transactions, and tenant information (subscription basis).
  • LoopNet (www.loopnet.com): Site with listing and sales information.
  • Reis, Inc. (Real Estate Solutions by Moody’s Analytics) (www.reis.com): Commercial real estate performance information and analysis (subscription basis).
  • CBRE (www.cbre.us), Colliers International (www2.colliers.com/en), Cushman & Wakefield (www.cushmanwakefield.com), Jones Lang LaSalle (JLL) (www.us,jll.com/en), Marcus & Millichap Real Estate Investment Services (www.marcusmillichap.com), NAI Global (www.naiglobal.com), Transwestern (www.transwestern.net): Corporate real estate services sites with listing information.
  • RealtyRates.com (www.realtyrates.com): Commercial real estate investment, financial and market rates and returns for properties across the United States (subscription only).
  • Site to Do Business (www.stdb.com): Demographic data with reporting and analytical tools.

• Real Estate Professionals:

  • Brokers, appraisers, property managers, and developers.

• Published News and Market Reports:

  • Local newspapers, business journals, and real estate publications.

3. Integrating Macro and Micro Analysis

Effective appraisal requires integrating macro and micro data to develop a comprehensive understanding of market conditions and property value.

• Top-Down Approach: Starting with macro-level analysis to understand the overall economic and demographic trends, then drilling down to micro-level analysis to assess the specific property and its market.

• Bottom-Up Approach: Beginning with micro-level analysis to gather detailed information about the property and its local market, then integrating macro-level data to understand broader economic and demographic influences.

• Iterative Process: Continuously refining the analysis by incorporating new data and insights from both macro and micro sources.

4. Emerging Trends in Data Sources

• Big Data and Analytics: The increasing availability of large datasets and advanced analytical tools is transforming real estate appraisal. Appraisers can use big data to identify patterns, trends, and relationships that would be difficult or impossible to detect using traditional methods.

• Artificial Intelligence (AI) and Automated Valuation Models (AVMs): AI and AVMs are automating certain aspects of the appraisal process, such as data collection and analysis. However, appraisers still play a crucial role in reviewing and validating the results of AI and AVMs.

• Blockchain Technology: Blockchain technology has the potential to revolutionize real estate transactions by providing a secure and transparent platform for recording and verifying property ownership.

• Increased Data Accessibility: The trend towards increased data accessibility is empowering consumers and appraisers alike. Online platforms and databases are making it easier to access a wide range of real estate data.

5. Data Verification and Validation

• Importance of Verification: It is critical to verify and validate all data sources to ensure accuracy and reliability.
• Cross-Referencing Data: Comparing data from multiple sources to identify discrepancies and inconsistencies.
• Field Inspections: Conducting physical inspections of the property and comparable properties to verify the accuracy of the data.
• Due Diligence: Investigating the credibility and reputation of data providers.

Conclusion

Data collection and analysis are fundamental to the real estate appraisal process. Appraisers must have a thorough understanding of the various sources of macro and micro data, as well as the analytical techniques needed to interpret and apply this data effectively. By integrating macro and micro analysis, appraisers can develop credible opinions of value that are supported by market evidence and sound reasoning. The field continues to evolve with new technologies and data sources, requiring ongoing education and adaptation from appraisal professionals.