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Key Takeaways
- Product implementations for market rent estimation include market stats widgets, heat maps for geographic comparisons, and direct API integration² for seamless data access and analytics
- Market rent estimation provides critical insights for commercial real estate valuation and lease pricing through statistical modeling and data analysis
- CompStak’s market rent index uses crowdsourced lease comparables to track quarterly changes since 2005 across major gateway markets¹
- A hedonic price index model incorporating property attributes and financial information enables accurate market rent estimation
Market Rent Estimation
- Commercial real estate transactions are often limited, presenting challenges for comprehensive market analysis. The limitation restricts the available data, making it difficult to capture accurate market trends. Market rent estimation, which aligns closely with the Mark-to-Market concept, addresses this challenge by adjusting historical rents to reflect current market conditions. For landlords, market rent estimation provides insight into the potential leasing price of their properties in today’s market, offering a more dynamic and comprehensive view of market conditions.
- By isolating time as the primary variable influencing price changes, market rent estimation broadens the data pool. This adjustment is crucial, as relying solely on recent transactions would result in smaller sample size, reducing the effectiveness of historical data in machine learning models and predictive analysis.
- Differences in building class, age, low-rise versus high-rise characteristics, and other factors can lead to significant variations in historical data, causing deviations that a simple average or weighted average approach cannot adequately address. These methods fail to capture the nuanced dynamics of the commercial real estate (CRE) market. To overcome these complexities, a comprehensive market rent index is necessary. This approach assumes that, all other factors being equal, macro market momentum is the primary force influencing rent levels. By treating variations in property and lease-level characteristics as independent variables and isolating the effect of time, the market rent index effectively captures rent changes driven by overall market trends, offering a robust tool for understanding and predicting market dynamics.
Building Market Rent Index
The market rent index is constructed using CompStak’s crowdsourced lease comparables. It’s a quarterly updated index that CompStak uses to create market rent estimates for properties and space analytics offerings. Currently, indices for office and industrial properties are constructed at the national level (gateway markets¹ ) and for individual markets where data is available.
National Indices
The index begins in 2005, with separate indices for office and industrial properties, each based on different sets of lease comparable attributes. The index values are interpreted as the percentage growth compared to the base year, Q3 2008. For example, if the index value for Q2 2023 is 125, it indicates that rents have increased 25% since Q3 2008.
Market and Mid Market Indices
To provide more accurate market rent estimations, each market utilizes its own regression models. The chart below illustrates the rent growth differences in each office market over the past 15 years. For instance, San Francisco experienced the highest growth since 2010, attributable to the booming tech industry. However, it also faced the steepest decline as the tech industry adopted the work-from-home trend following the COVID-19 pandemic.
Methodology
To construct the indices, CompStak employs a time dummy variable approach to develop a hedonic price index. This semi-logarithmic regression model defines the transaction quarter, property attributes, and financial information as independent variables, while the starting rent serves as the dependent variable to represent market trends.
In this semi-logarithmic model, the coefficients of the time dummy variables represent proportional impacts on rental price. The base year is defined as the third quarter of 2008, marking the market peak prior to the Great Recession and the subprime mortgage crisis.
*Industrial attributes, such as ceiling height, number of loading docs, and number of drive-ins, are specific to industrial properties and are only included in the industrial index model.
Experiment and Results
The underlying assumption in current market rent estimation is that, all else being equal, time is the sole factor influencing price differences. To evaluate the effectiveness of the hedonic price index outlined above, CompStak used renewal lease comparables for backtesting. For clarity, let the renewal timestamp represent the moment a lease is renewed, and the initial timestamp represent the comparable lease from the previous period. Under these conditions, the following relationship should hold true:
The market rent index should be interpreted as a Laspeyres-like index. In the equation above, the index reflects the market rent index value at the respective timestamps. To provide greater granularity, the mid-market rent index was used, depending on its availability.
The Mean Absolute Percentage Error (MAPE) was calculated to assess the accuracy of the market rent estimation by comparing the predicted market rent values to the actual rents observed in the market. MAPE is determined by taking the average of the absolute percentage differences between predicted and actual rents, providing a measure of prediction accuracy that accounts for both over- and under-estimation. Focusing the experiment on office space, the histogram of percentage errors shows symmetry around the 0% mark, suggesting that the errors are approximately normally distributed. The mean absolute percentage error was found to be around 11%.
To stacked bar chart above highlights differences in how errors are distributed for each market. The interquartile range (IQR) of percentage errors also differs, with some markets exhibiting a wider spread than others.
Product Impact
Market Stats
Market rent estimation is integrated into various analytical features on CompStak’s Property page. A new widget highlights property lease snapshots and market statistics, providing additional insights. Below is a snapshot showcasing the implementation of the market rent estimation feature on the platform.
Heat Map
Market rents used for analytics are adjusted to reflect current market trends. This adjustment allows for a more accurate comparison of starting rent trends across different geographic regions, highlighting regional variations and providing deeper insights into market dynamics.
API Integration
A direct API integration² is available, leveraging the methodology described above. This integration provides seamless access to the adjusted market rent data through a data feed, enabling users to incorporate real-time, trend-adjusted market insights into their analytics.
Footnotes
¹ Gateway markets refer to major metropolitan areas that serve as critical hubs for commercial real estate investment and economic activity due to their size, economic importance, and high transaction volumes.
- The office gateway market index is built using data collected in New York City, San Francisco, the Bay Area, Los Angeles, Washington, DC, Chicago Metro, Boston, Dallas, Houston, Philadelphia, Phoenix and Denver.
- The industrial gateway market index is built using data collected in Atlanta, Chicago, Dallas, Los Angeles, Miami, New Jersey North & Central and Philadelphia.
² API link: https://compstak-api.readme.io/reference/post_api-v2-market-averagerent
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