Estimating the value, ownership structure and turnover rate for investible commercial real estate from transaction datasetsDevaney, S. ORCID: https://orcid.org/0000-0002-1916-2558 and Scofield, D. (2021) Estimating the value, ownership structure and turnover rate for investible commercial real estate from transaction datasets. Journal of Property Investment & Finance, 39 (4). pp. 336-382. ISSN 1463-578X
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1108/JPIF-05-2020-0052 Abstract/SummaryPurpose: Commercial real estate (CRE) is a major investment asset. Yet detailed information on the value of investible CRE in different cities is lacking. We propose an innovative method to measure the value of investible CRE using transaction datasets. Design/methodology/approach: We take transaction prices and index them to produce a time series of values for each asset. The sum of the values at each point represents the value of investible CRE at that date. Our method is applied to transaction data for New York, London and Toronto. Findings: London had the highest proportions of institutional and foreign ownership, and its turnover was more resilient to the downturn in global CRE following the GFC. The results illustrate the potential of our method to shed light on the characteristics of investible CRE markets. Originality: Our modification of the perpetual inventory technique is simple, novel and practical. We propose this approach given the absence of a building-by-building inventory of investible CRE in many markets. Research limitations: We use data from Real Capital Analytics (RCA). This provides good coverage of transactions for investible CRE in the cities that we examine, but data from other sources might lead to different estimates. Practical implications: Measuring the value and turnover of investible CRE is important for portfolio strategies that account for the size and liquidity of investment markets. Knowledge of these features, and of ownership patterns, provides a better understanding of market operation.
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