Location

RM/FIN 460: Real Estate Financial Analysis

Instructor

  • Jiro Yoshida

Defining a Market

  1. Property Types

    • Apartments

    • Hotels

    • Retail Spaces

    • Office Buildings

    • Industrial Properties

  2. Geography

    • Metropolitan Statistical Areas (MSAs)

    • Submarkets

  3. Additional Dimensions

    • Classes (e.g. Class A, Class B)

    • Configurations

  4. What is Traded

    • Assets (e.g. properties)

    • Space Usage (e.g. leased or owned spaces)

Metropolitan Statistical Areas (MSAs)

  • Metropolitan and Micropolitan Statistical Areas of the United States and Puerto Rico, delineated by the Office of Management and Budget.

  • Definition: A Core-Based Statistical Area (CBSA) includes a core area with substantial population and adjacent communities with high economic and social integration.

    • Metropolitan Statistical Areas: Must have at least one urbanized area with a population of 50,000 or more.

    • Micropolitan Statistical Areas: Must have at least one urban cluster of 10,000 but less than 50,000 population.

  • Criteria: CBSAs are composed of entire counties.

    • Current numbers (as of September 2018): 392 metropolitan statistical areas, 11 of which are further subdivided into metropolitan divisions, plus 546 micropolitan statistical areas.

Submarkets: The Philadelphia Office Market

  • A detailed overview of submarkets in the Philadelphia area, including major cities and regions surrounding Philadelphia.

  • Examples of Submarkets:

    • West Philadelphia

    • South Philadelphia

    • Norristown/Valley Forge

    • Upper Main Line

    • King of Prussia/Wayne

  • The list continues to cover various areas, highlighting specific subregions and their characteristics.

Submarkets: Definitions and Complexity

  • Importance of submarket definitions in real estate analytics: analytical breakdown of properties and market behavior.

  • The documents show a multitude of properties, analytics, leases, and search capabilities discussed.

Office Market Rents

  1. Pittsburgh Office Market

    • Average asking rents categorized into price brackets.

    • Notable that office rents are typically higher in Central Business Districts (CBD) than in suburban areas (as reflected from various reports).

  2. Comparison of Housing Rents

    • Housing rents in cities like Dallas-Fort Worth confirm that central locations command higher rents than suburbs.

Hedonic Pricing Model

  • Hedonic Price Function Formula: p = eta0 + f1 z1 + … + fn z_n + eg Where:

    • p = purchase or rental prices

    • z = property characteristics (e.g., size, structure)

    • eta = constant or coefficients for the price function

  • Example application of the model: distance significantly impacts price, particularly in heterogeneous markets like real estate.

Urban Rent Premium Considerations

  1. Concept of Urban Rent Premium

    • People are willing to pay for living closer to the CBD due to convenience-related factors:

      • Reduced commuting time costs

      • Proximity to shopping and entertainment

      • Convenience perceived in urban living.

  2. Calculating Urban Rent Premium

    • rac{ riangle R}{ riangle s}_{year} imes s = C/mile/year imes riangle D Where:

      • C = convenience value per mile

      • D = distance metric between properties

  3. Rent Gradient

    • The differential rac{ riangle R}{ riangle D} is indicative of how proximity affects rent transaction.

Changes in Real Estate Value Due to External Factors

  1. User Cost and Rent

    • Comparison of rent versus user cost in context of proximity.

  2. Residential Sorting

    • People sort into neighborhoods based on their transportation cost structure, influencing their choice of dwelling places.

  3. Economic Implications

    • Discussion around what influences consumer choice in terms of commuting costs, and how that reflects on housing prices.

Implications of Urban Mobility and Work-from-Home Trends

  1. Work-from-Home Trends

    • Analysis of how WFH arrangements influence office occupancy rates and rental strategies.

  2. COVID-19 Impact

    • A detailed overview of how different metropolitan areas are recovering post-pandemic in terms of employment and office space usage.

    • Usage of analytics from Kastle’s Barometer to show occupancy over time.

Historical Urban Development

  1. City Growth Patterns

    • Examination of how urban growth and its attractiveness is paramount to the value of real estate in various cities over time, stressing the influence of entertainment, employment, and overall livability.

  2. Historical Examples

    • Changes in key cities (e.g., Detroit, New York) over specific time frames to highlight shifts in urban centers due to economic factors.

  3. Urbanization Trends and Economic Factors

    • Exploration of agglomeration economies and types of forces (centripetal/centrifugal) leading to changes in urban structures over time.