Introducing Strategic Advisory - Integrate, automate, and accelerate decision-making with expert CRE insights. Click to learn more! Learn about CompStak Strategic Advisory
Help us direct you to the right place to sign up

At CompStak, we’re thrilled to see our data contributing to valuable research in commercial real estate.

“Filtering in Commercial Real Estate” by Nathaniel Baum-Snow, Stephan Heblich, and Stuart S. Rosenthal, explores the phenomenon of “filtering” in CRE, which refers to the process by which buildings degrade over time, impacting their market performance and value.

The full abstract of the paper can be found below, offering a glimpse into the depth of research that leverages the precision and accuracy of CompStak data to assess market changes.

“While considerable evidence exists that residential properties host increasingly lower income tenants as they age, little analogous evidence exists for commercial properties. Using comprehensive data on commercial leasing and occupancy, this paper shows evidence ofltering in commercial real estate. Each year, the typical oce property early n its life cycle depreciates by about 0.9 percent. Since leased space per user declines by about 2 percent per year while employment declines by 1.5 percent per year, buildings become more intensively used as they age. These changes are due entirely to shifts in the mix of tenants as buildings age. Tenants in older buildings are less productive and have higher labor shares. Only about one-fifth of these shifts are accounted for by changes in building industrial composition with age.”

Download the full paper here.

Related Posts

Commercial Mortgage Debt Overhang and Intent to Default: Insights from Daniel Broxterman, Mariya Letdin, Chongyu Wang, and Tingyu Zhou Using CompStak Data

Commercial Mortgage Debt Overhang and Intent to Default: Insights from Daniel Broxterman, Mariya Letdin, Chongyu Wang, and Tingyu Zhou Using CompStak Data

The Disruption of Generative AI in Real Asset Markets: Insights from Chongyu Wang, Jingfang Wang, and Tingyu Zhou Using CompStak Data

The Disruption of Generative AI in Real Asset Markets: Insights from Chongyu Wang, Jingfang Wang, and Tingyu Zhou Using CompStak Data

Dynamic Urban Economics: Insights from Brian Greaney, Andrii Parkhomenko, and Stijn Van Nieuwerburgh Using CompStak Data

Dynamic Urban Economics: Insights from Brian Greaney, Andrii Parkhomenko, and Stijn Van Nieuwerburgh Using CompStak Data