Clustering Methods for Real Estate Portfolios

Abstract

A clustering algorithm is applied to effective rents for twenty‐one metropolitan U.S. office markets, and to twenty‐two metropolitan markets using vacancy data. It provides support for the conjecture that there exists a few major “families” of cities: including an oil and gas group and an industrial Northeast group. Unlike other clustering studies, we find strong evidence of bicoastal city associations among cities such as Boston and Los Angeles. We present a bootstrapping methodology for investigating the robustness of the clustering algorithm, and develop a means for testing the significance of city associations. While the analysis is limited to aggregate rent and vacancy data, the results provide a guideline for the further application of cluster analysis to other types of real estate and economic information.

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