Starting the new year off right by sharing the news that the Heybrook West team has published another paper! In partnership with NAIOP, download and read our free report by clicking here: A Two-Dimensional Approach to Evaluating Commercial Real Estate Markets. This paper is the second in our series exploring the current Market Tier and Ranking Systems. Preview – https://www.naiop.org/research-and-publications/research-reports/reports/a-two-dimensional-approach-to-evaluating-commercial-real-estate-markets/ By: Maria Sicola, Charles Warren, Ph.D., and Megan Weiner Original Release Date: August 2021
Note: This white paper was originally published under a previously used company name
In 2020, the NAIOP Research Foundation published A New Look at Market Tier and Ranking Systems, which identified the limitations of one-dimensional tier and ranking systems that are commonly used to evaluate metropolitan commercial real estate markets. When tailored to the needs of a specific type of investor, these models can help prioritize markets for consideration. However, tier and ranking reports designed for a more general audience tend to be of only limited use to most end-users since they do not account for differences in investment strategy, risk tolerance or specialization. Further, all tier and ranking models condense complex market characteristics into a single score, providing only limited information that investors can use to evaluate and compare different markets.
The NAIOP Research Foundation asked the authors of the 2020 report to develop an alternative model for evaluating commercial real estate markets that uses a two-dimensional analysis to simultaneously evaluate multiple market characteristics such as size and risk. The authors consulted with industry practitioners and analyzed 15 years of market data to develop and test multiple two-dimensional models for evaluating the 50 largest commercial real estate markets in the United States. This report:
Evaluates four models for comparing industrial and office markets using different variables along the axes of a two-dimensional grid.
Reveals how investors and developers can use a two-dimensional analysis to identify markets that align with their strategy and risk tolerance.
Demonstrates that market size and average transaction prices do not reliably predict risk.
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