New Valuation and Trading Model for Commercial Real Estate Ecosystems

Researchers at Columbia Business School have developed a new valuation and trading model designed to analyze the commercial real estate (CRE) ecosystem. The research, conducted by Stijn Van Nieuwerburgh, Ralph Koijen, and Neel Shah, examines the joint dynamics of trading volume and transaction prices within the market.

The central finding of the study is that the identity of the buyers and sellers involved in a transaction has a first-order effect on both the valuation of the property and the likelihood that a trade will occur.

The Micro-Founded Model

The researchers utilized a micro-founded model to understand how different market participants interact. This approach allows for an analysis of how buyers and sellers differ in their private valuations of specific building characteristics.

According to the research, these valuations are based on several key property characteristics, including:

• The size of the building
• The location of the property
• The quality of the asset

The model suggests that these characteristics do not function as fixed attributes. Instead, the research identifies the presence of interaction effects, meaning the importance of a specific property characteristic can vary depending on the attributes of the investor.

Market Dynamics and Valuation

By focusing on the ecosystem of participants, the model seeks to explain the relationship between the price at which properties are transacted and the overall volume of trades in the commercial sector. This deviates from models that may view property characteristics in isolation from the specific identities of the trading parties.

The findings were detailed in an abstract published on February 1, 2025, and further insights were provided by the Columbia Business School Milstein Center on February 3, 2026.