VALUED INSIGHTS

Invaluable Valuation Knowledge for the Real Estate Stakeholder

SERIES:
Opportunities And Challenges
In The U.S. Multifamily Market
CHAPTER
  1. Supply And Demand In The Rental Market
    (Published: July 22, 2024)

  2. Understanding Multi-Family Housing Metrics (Available: July 29, 2024)

  3. Key Supply and Demand Indicators for Apartment Investors
    (Available: August 5, 2024)

  4. The Economics of Build-to-Rent Projects
    (Available:August 12, 2024)

  5. Analyzing Regional Apartment Market Trends (Available: August 19, 2024)

  6. Forecasting Demand for Multi-Family Units (Available: August 26, 2024)
SERIES:
Opportunities And Challenges
In The U.S. Multifamily Market
CHAPTER:

Forecasting Demand for Multi-Family Units

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Author: Jason D. Beakley, Certified General Appraiser
Published: August 26, 2024

Accurately forecasting demand for multi-family housing units is crucial for developers, investors, and property managers in the commercial real estate industry. As the multifamily sector continues to evolve, understanding the factors that drive demand and utilizing effective forecasting methods can provide a competitive edge in this dynamic market. This article will explore the key components of multifamily demand forecasting, the various methodologies employed, and the challenges and opportunities that lie ahead.

Factors Influencing Multifamily Demand

To effectively forecast demand for multi-family units, it’s essential to consider a wide range of factors that influence housing choices and market dynamics:

Jason D. Beakley
CERTIFIED GENERAL APPRAISER
Director
+1-480-440-2842 EXT 09
  1. Demographic Trends.

Demographic shifts play a significant role in shaping multifamily housing demand. Key factors include:

    • Population growth: Areas experiencing rapid population growth typically see increased demand for housing, including multifamily units.
    • Age distribution: Different age groups have varying housing preferences. For example, millennials and young professionals often prefer renting apartments in urban areas, while baby boomers may seek age-restricted communities.
    • Household formation: The rate of new household creation, including trends in marriage, divorce, and single-person households, impacts housing demand.

  1. Economic Conditions

The overall economic landscape significantly influences multifamily demand:

    • Employment growth: Job creation and employment opportunities attract residents to an area, driving housing demand.
    • Income levels: Changes in income levels affect affordability and housing choices.
    • Economic diversification: Areas with diverse economies tend to have more stable housing markets.

  1. Housing Affordability

The relationship between housing costs and income levels impacts the demand for multifamily units:

    • Home prices: High single-family home prices can drive demand for more affordable multifamily rentals.
    • Mortgage rates: Rising mortgage rates can make homeownership less attainable, increasing demand for rental units.
    • Rent-to-income ratios: Areas with favorable rent-to-income ratios may see increased demand for multifamily housing.

  1. Supply Dynamics

The existing and planned supply of housing units affects demand forecasts:

    • Current inventory: The number and quality of existing multifamily units in a market.
    • Pipeline projects: Planned and under-construction developments that will add to future supply.
    • Obsolescence: The rate at which older properties are being removed from the market.

  1. Location and Amenities

The desirability of specific locations and property features influences demand:

    • Proximity to employment centers: Areas with strong job markets and easy commutes often see higher demand.
    • Access to transportation: Properties near public transit or major highways may be more desirable.
    • Community amenities: Features such as shopping, dining, and entertainment options can drive demand in certain areas.
    • Property amenities: In-unit and community amenities can differentiate properties and attract specific tenant segments.

  1. Regulatory Environment

Government policies and regulations can impact multifamily demand:

    • Zoning laws: Restrictions or incentives for multifamily development can affect supply and demand dynamics.
    • Rent control: Regulations on rent increases can influence investor interest and property management strategies.
    • Tax incentives: Programs that encourage multifamily development or renovation can impact supply and demand.

  1. Technological Advancements

Emerging technologies are shaping housing preferences and demand:

    • Remote work trends: The rise of remote work may influence where people choose to live and the types of housing they prefer.
    • Smart home features: Increasing demand for tech-enabled apartments may drive interest in newer or renovated properties.
    • Virtual leasing: The ability to tour and lease apartments remotely may expand the pool of potential renters in a market.

Forecasting Methodologies

Accurately predicting multifamily demand requires a combination of quantitative analysis and qualitative insights. Here are some common forecasting methodologies used in the industry:

  1. Trend Analysis

This method involves examining historical data to identify patterns and project future demand. Key steps include:

    • Collecting historical data on population growth, household formation, and multifamily absorption rates.
    • Analyzing trends in these metrics over time.
    • Projecting future demand based on historical patterns, adjusted for expected changes in market conditions.

  1. Econometric Modeling

Econometric models use statistical techniques to estimate the relationships between various economic factors and multifamily demand. These models typically involve:

    • Identifying key variables that influence demand (e.g., employment growth, income levels, housing prices).
    • Developing regression models to quantify the relationships between these variables and multifamily absorption.
    • Using the model to forecast future demand based on projected changes in the independent variables.

  1. Cohort Analysis

This approach focuses on tracking specific demographic groups over time to predict their housing needs:

    • Identifying key age cohorts and their historical housing preferences.
    • Projecting how these cohorts will move through different life stages and how their housing needs may change.
    • Estimating future demand based on the size and preferences of each cohort.

  1. Survey-Based Forecasting

Surveys can provide valuable insights into consumer preferences and intentions:

  • Conducting surveys of current renters, potential renters, and homeowners to gauge their future housing plans.
  • Analyzing survey results to identify trends in preferences for different housing types and locations.
  • Incorporating survey findings into demand projections.

  1. Machine Learning and AI

Advanced analytics techniques are increasingly being used to forecast multifamily demand:

    • Utilizing large datasets and machine learning algorithms to identify complex patterns and relationships.
    • Developing predictive models that can account for a wide range of variables and their interactions.
    • Continuously refining models based on new data and market developments.

Challenges in Forecasting Multifamily Demand

While forecasting methodologies have become increasingly sophisticated, several challenges remain:

  1. Data Limitations

Accurate and timely data can be difficult to obtain, particularly at the local level. Forecasters must often rely on estimates or proxy measures, which can introduce uncertainty into projections.

  1. Changing Consumer Preferences

Housing preferences can shift rapidly, influenced by factors such as technological advancements, cultural trends, and economic conditions. Forecasting models must be flexible enough to account for these changes.

  1. External Shocks

Unexpected events, such as economic recessions, natural disasters, or public health crises, can dramatically impact housing demand. Incorporating these low-probability, high-impact events into forecasts is challenging but necessary.

  1. Local Market Variations

National or regional trends may not accurately reflect conditions in specific local markets. Forecasters must account for unique local factors that can influence demand.

  1. Long-Term vs. Short-Term Forecasts

Balancing the need for long-term strategic planning with the desire for short-term accuracy can be challenging. Different forecasting horizons may require different methodologies and assumptions.

Opportunities for Improving Forecasting Accuracy

Despite these challenges, several opportunities exist to enhance the accuracy and usefulness of multifamily demand forecasts:

  1. Integrating Alternative Data Sources

Incorporating non-traditional data sources, such as social media sentiment, mobile phone location data, or online search trends, can provide additional insights into consumer behavior and preferences.

  1. Scenario Planning

Developing multiple demand scenarios based on different assumptions can help stakeholders prepare for a range of potential outcomes and identify key drivers of demand.

  1. Collaborative Forecasting

Combining insights from various stakeholders, including developers, property managers, economists, and local market experts, can lead to more comprehensive and accurate forecasts.

  1. Real-Time Monitoring and Adjustment

Implementing systems to continuously monitor key demand indicators and adjust forecasts in real-time can improve responsiveness to changing market conditions.

  1. Granular Market Analysis

Developing more detailed, submarket-level forecasts can provide valuable insights for targeted investment and development decisions.

Conclusion

Forecasting demand for multi-family units is a complex but essential task for success in the multifamily real estate sector. By understanding the key factors that drive demand, utilizing a combination of forecasting methodologies, and addressing the challenges inherent in predicting future housing needs, industry professionals can make more informed decisions and better position themselves for success in this dynamic market.

As the multifamily landscape continues to evolve, driven by demographic shifts, economic changes, and technological advancements, the importance of accurate demand forecasting will only increase. Those who can effectively leverage data, analytics, and market insights to predict future housing needs will be well-positioned to capitalize on opportunities and navigate challenges in the years ahead.

Ultimately, successful multifamily demand forecasting requires a combination of rigorous analysis, market expertise, and adaptability. By continually refining forecasting methods and incorporating new data sources and analytical techniques, industry professionals can enhance their ability to anticipate market trends and make sound investment and development decisions in the ever-changing world of multifamily real estate.

Citations:

[1] https://multifamily.fanniemae.com/news-insights/multifamily-market-commentary/2024-multifamily-market-outlook-instability-expected

[2] https://mf.freddiemac.com/research/outlook/20231219-2024-multifamily-outlook

[3] https://propertymetrics.com/blog/how-to-analyze-supply-and-demand-for-apartment-buildings/

[4] https://www.northmarq.com/insights/research/2024-national-multifamily-outlook-report-supply-demand-imbalance-likely-2024

[5] https://www.naahq.org/future-apartment-demand

[6] https://www.cbre.com/insights/books/us-real-estate-market-outlook-2024/multifamily

[7] https://www.youtube.com/watch?v=96rBssL4ak0

[8] https://www.teacherspayteachers.com/browse?search=envision+topic+6+kindergarten