Levels of Market Analysis: From Inferred to Fundamental Demand

This chapter explores the spectrum of market analysis techniques, ranging from simple inferred demand analysis to comprehensive fundamental demand analysis. Understanding these levels is crucial for determining the appropriate scope of work for real estate appraisal assignments. The intensity of research and analysis must align with the complexity of the property, prevailing market conditions, and the specific objectives of the appraisal.

1. Introduction to Demand Analysis in Real Estate

Market analysis fundamentally revolves around understanding and predicting demand for real estate. This demand stems from users needing space for various purposes, including residential, commercial, and industrial activities. Demand is influenced by both long-term trends and short-term fluctuations. Long-term trends are rooted in changes in:
* Employment characteristics.
* Population demographics.
* Income levels.
* Consumer preferences.

Short-term fluctuations are more closely linked to:
* Credit availability.
* Overall economic conditions.

The core distinction between different levels of market analysis lies in how demand is analyzed and estimated.

2. Inferred Demand Analysis (Trend Analysis)

2.1. Definition and Characteristics

Inferred demand analysis, sometimes called trend analysis, relies heavily on historical data and observed trends to project future demand. It infers demand without directly quantifying the specific demand for a particular property. The underlying assumption is that past trends will likely continue, or at least provide a reasonable basis for projecting future behavior. Inferred analysis is primarily descriptive.

2.2. Application

• General Market Analysis: Uses broad market data and selected comparable properties to represent the larger market.
• Specific Marketability Analysis: Focuses on area-wide market data and draws subject-specific conclusions.

2.3. Limitations

• The reliability and relevance of market data decrease as the geographic area broadens. For instance, state-level employment data is less relevant than employment data for the property’s immediate surrounding area.
• Data from dissimilar property types is unreliable. The occupancy rates of regional malls provide little insight into the demand for space in neighborhood shopping centers.
• Ignores the underlying economic forces that generate demand.

2.4. Mathematical Representation (Simplified Example)

While inferred analysis often relies on qualitative judgment, a simple example of its quantitative aspects could involve linear regression. If V represents vacancy rate and t represents time (in years), a simple linear model could be:

V = a + bt

Where a is the intercept (initial vacancy rate) and b is the slope (annual change in vacancy rate). This projects future vacancy based on historical trends.

2.5. Practical Applications and Experiments

• Example: Analyzing historical apartment occupancy rates in a city to predict future occupancy rates for a new apartment complex.
• Experiment: Collecting historical sales data for single-family homes in a specific neighborhood. Plotting the data to visually identify trends in sales prices and volume. Extrapolating these trends to forecast future sales activity.

3. Fundamental Demand Analysis

3.1. Definition and Characteristics

Fundamental demand analysis goes beyond simple trend extrapolation. It aims to quantify current and forecast future demand by analyzing the underlying economic forces that drive demand. It involves a segmentation of broad demographic and economic data to understand the specific market relevant to the subject property.

3.2. Key Components

• Economic Drivers: Examines the relationships between employment, population, and income as primary drivers of demand.
• Market Segmentation: Identifies specific segments of the market that would be potential users of the subject property.
• Supply Analysis: Quantifies existing supply and forecasts future supply, considering planned and potential competition.

3.3. Assessing Current Demand

• Occupancy Rates: Existing property occupancy serves as an indicator of total current demand.
• Property Performance: The performance of the appraised property can be a reliable indicator of current demand, assuming it has been properly managed.
• Pent-Up Demand: Addresses instances where current occupancy does not reflect actual demand due to inadequate supply or the lack of desired features in existing properties. Pent-up demand can be defined as the demand exceeding the occupied space within the market.

3.4. Forecasting Future Demand

Fundamental demand analysis involves projecting future levels of employment, population, income, and other key economic variables. These projections are then used to estimate future demand for specific types of real estate.

3.5. Mathematical Models

• Population Growth Model: A simple exponential growth model can be used to project population:
  P(t) = P₀ * e^(rt)
  Where:

  • P(t) is the population at time t.
  • P₀ is the initial population.
  • r is the population growth rate.
  • e is the base of the natural logarithm.

• Demand Elasticity: Measures the responsiveness of demand to changes in other factors. For example, income elasticity of demand (Eᵢ) is calculated as:

  Eᵢ = (% Change in Quantity Demanded) / (% Change in Income)

  A positive income elasticity indicates that demand for a property type increases as income rises.

3.6. Practical Applications and Related Experiments

• Example: Forecasting demand for office space in a city by analyzing employment growth in key industries, projected population growth, and trends in office occupancy rates.
• Experiment: Conducting a survey of potential tenants to determine their preferences for different types of office space (e.g., location, amenities, lease terms). Using the survey data to refine the demand forecast.

4. Indicators of Demand

Both inferred and fundamental analyses utilize indicators of demand. The level of detail differs.

4.1. Area Examined and Indicators of Demand:

• Competitive Properties:
  • Inferred: Current and historical vacancy rates; trends in rental rates.
  • Fundamental: Detailed analysis of amenities, lease terms, and competitive advantages.
• Market Area:
  • Inferred: Vacancy rates, rental rate trends, construction activity.
  • Fundamental: Pre-leasing activity, underlying economic drivers, demographic trends.
• Macroeconomic Area:
  • Inferred: Vacancy rates, rental rate trends, construction activity for the property type.
  • Fundamental: Employment levels, foreclosure rates, residential occupancy, income levels, consumer spending.

5. Levels of Market Analysis: A Spectrum of Complexity

Market analysis is commonly segmented into four levels of increasing depth and complexity: Level A, Level B, Level C, and Level D. Levels A and B typically involve inferred demand analysis, while Levels C and D utilize fundamental demand analysis.

• Level A: Simple inferred analysis, suitable for stable markets and simple properties.
• Level B: More detailed inferred analysis, incorporating subject-specific considerations.
• Level C: Fundamental analysis focusing on economic drivers and market segmentation.
• Level D: Comprehensive fundamental analysis, including primary research and detailed marketability studies.

The choice of level depends on market conditions, the complexity of the property, and the objectives of the appraisal.

6. Table Summary of Levels of Market Analysis

7. Economic Base Analysis

Economic base analysis is a critical component of fundamental demand analysis, particularly in Level C and Level D studies. It involves examining the industries and businesses that generate employment and income in a community, driving demand for real estate.

7.1. Steps in Economic Base Analysis:

1. Identify the geographic extent of the local economy.
2. Identify the basic industries in the local economy (industries that export goods or services, bringing income into the community).
3. Estimate total basic employment.
4. Calculate the economic base multiplier (ratio of total employment to basic employment) and other relevant ratios.
5. Forecast future basic employment.
6. Forecast future total employment and related economic factors.

7.2. Techniques for Identifying Basic Industries:

• Judgment Approach: Based on expert opinion and knowledge of the local economy.
• Direct Survey Approach: Involves surveying businesses to determine the destination of their products or services (local vs. export).
• Location Quotient (LQ) Approach: Compares the concentration of an industry in the local economy to its concentration in the national economy. An LQ greater than 1 indicates a basic industry.
• Minimum Requirements Approach: Identifies industries that exceed the minimum employment levels necessary to support the local population.

7.3. Formula for Location Quotient (LQ)

LQᵢ = (Eᵢ,local / Etotal,local) / (Eᵢ,national / Etotal,national)

Where:

• LQᵢ is the location quotient for industry i.
• Eᵢ,local is employment in industry i in the local economy.
• Etotal,local is total employment in the local economy.
• Eᵢ,national is employment in industry i in the national economy.
• Etotal,national is total employment in the national economy.

8. Conclusion

Choosing the right level of market analysis depends on the specific appraisal assignment. Inferred analysis is suitable for simple properties and stable markets, while fundamental analysis is necessary for complex properties and volatile markets. Understanding the underlying economic forces that drive demand is crucial for accurate real estate appraisals and investment decisions. By carefully considering the factors discussed in this chapter, appraisers can select the appropriate level of analysis to provide reliable and relevant insights.